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Autoimmune Polyglandular Syndromes

ABSTRACT

 

The autoimmune polyglandular syndromes (APS) are clusters of endocrine abnormalities that occur in discreet patterns in subjects with immune dysregulation and that permit treatment and anticipation of associated systemic or other hormonal deficiencies. Three major entities are recognized, APS1, APS2 and APS3; the rare X-linked syndrome of immune-dysregulation, poly-endocrinopathy, and enteropathy due to mutations in the FOXP3 gene also qualifies as an APS. An additional increasingly described category occurs in patients treated with immunoregulatory agents such as checkpoint inhibitors for cancer, so that tumor antigens that have evaded recognition can now be targeted, but at the expense of activating autoimmunity with adverse effects on various endocrine tissues. APS1 is a syndrome characterized by chronic muco-cutaneous candidiasis, hypoparathyroidism, primary adrenal insufficiency, as well as ectodermal dystrophy and a host of other endocrine and non-endocrine tissue involvement in autoimmune destructive processes. The underlying cause is a homozygous inactivating mutation in the autoimmune regulator gene AIRE whichpermits the intra-thymic expression of ectopic antigens normally expressed only in specific peripheral tissues (e.g. insulin), so that T-cells as they mature within the thymus and acquire a receptor for the self- antigen are eliminated (negative selection), thereby avoiding autoimmunity. Studies demonstrate that in addition to the classical homozygous mutations, single gene dominant mutations in AIRE also play an important role in autoimmune regulation and its disorders. Recent studies demonstrate that tissue damage in APS1 due to AIRE mutations is mediated via the JAK-STAT signaling cascade and involves interferon gamma. Inhibiting the JAK-STAT signaling cascade via the monoclonalantibody, ruxolitinib, improves clinical and biochemical manifestations in both a murine model and human patients, offering promise for dramatic improvement in prognosis and clinical outcomes for affected patients. Larger studies in affected patients are awaited with interest.

APS2 and APS3 are both due to mutations in the HLA DQ/DR regions which regulate antigen presentation to T-cell receptors; however their genetic profile is more complex. APS2 is characterized by type 1 diabetes mellitus (T1DM), Addison Disease, and hypothyroidism, whereas APS3 is similar but without Addison disease. In keeping with other autoimmune disorders, these entities are more frequent in females, whereas APS1 has no sexual predominance. The recent emergence of autoimmune endocrinopathies in patients treated with checkpoint immunoregulatory agents for cancer add a new dimension to considerations of autoimmune polyendocrinopathy syndromes. Rapid progress in the immunology and genetics of these entities offers the promise of potential amelioration and eventual reversal via genetic manipulation before organ damage is established.

 

AUTOIMMUNE POLYGLANDULAR SYNDROMES

 

The autoimmune polyglandular syndromes are clusters of endocrine abnormalities that occur in discreet patterns in subjects with immune dysregulation and that permit treatment and anticipation of associated systemic or other hormonal deficiencies (1-8). Three major entities are recognized, APS1, APS2 and APS3 as well as the extremely rare X-linked syndrome of immunodysregulation, polyendocrinopathy, and enteropathy (IPEX) syndrome. An additional but increasing category occurs in patients treated with checkpoint immunoregulatory agents for cancer, by which the tumor’s blockade of immune regulatory checkpoints is inhibited, so that tumor antigens that had evaded recognition can now be targeted, but at the expense of activating autoimmunity against endocrine organs.

 

APS1 results from a failure to eliminate T-cells that have acquired receptors with high affinity to auto-antigens, as these T-cells mature and traverse the thymic epithelium during their development. Normally, such T-cells are prevented from entering the periphery because of the ectopic expression of multiple antigens within the thymus that usually are expressed only in discrete tissues, e.g. insulin in pancreatic β-cells. A developing T-cell that acquires and expresses a high affinity receptor for insulin will be bound to the ectopically expressed insulin antigen within the thymus, undergo apoptosis and be excluded from entering the periphery to initiate auto-immunity (Fig1). This ectopic expression of antigens within the thymus is mediated by the Auto-Immune REgulator gene (AIRE) located on chromosome 21. Discovered in 1997 as the gene whose variable inactivation is responsible for the clinical entity APS1 (1, 2, 4, 6), this gene is now known to be an essential component of the adaptive immune response cascade, and the spectrum of disorders ascribed to mutations in this gene extend beyond the APS1 syndrome (2, 4). Moreover, although APS1 is a rare entity with predilection for particular populations, the increased incidence of autoimmunity in persons with trisomy 21, a relatively common genetic abnormality, may be due to abnormal function of the AIRE gene (9). In addition, it is becoming apparent that mutations in AIRE can have autosomal dominant effects and become manifest as autoimmune disorders later in life in patterns that differ from the classical APS1 (2, 4). Since the incidence of such autosomal mutations may be as high as 1:1000, whereas the incidence of APS1 is much rarer (1:9000 in Iranian Jews; 1:14,500 in Sardinia; 1:25,000 in Finland), the influence of the AIRE gene on autoimmune processes and diseases may be far wider than hitherto appreciated, especially since Treg cells (regulatory T cells) also are now implicated in the abnormalities induced by AIRE deficiency (2, 4). Both T-cell and B-cell abnormalities are observed in APS1, so that circulating antibodies to various hormonal, connective tissues, and protein antigens such as enzymes in the steroidogenic or thyroid synthesis cascades are evident in the serum of affected patients with APS1, and indeed in all forms of the autoimmune polyglandular syndromes. Figure 1 summarizes these concepts.

 

Several recent case series indicate that the phenotypic variation and age of symptom onset vary greatly, even within the same family (10, 11), implying that other genes such as major histocompatibility complex genes, or environmental exposures, influence the phenotype and natural course (11, 12). This wide variation in presentation and symptomatology may make the diagnosis of APS-1 challenging.

 

Figure1. Left panel: Modified from Autoimmune Polyglandular Syndromes in Pediatric Endocrinology 4th Edition, Ed. Sperling MA. (with permission of the authors Drs. Michael Haller, William Winter, Desmond Schatz). A developing T-cell migrates from its origins in the bone marrow to the thymus where it matures and acquires its repertoire of receptors. The expression of self-antigens, including ectopic expression of antigens mediated via the AIRE gene, results in apoptosis of the T-cell possessing the complementary receptor, and prevention of the T-cell entering the periphery, a fate of almost all T-cells. A small fraction of T-cells enter the periphery where they remain anergic to self-antigens, but can mount an immune response to non-self-antigens. Right panel: Failure of self-tolerance, due to non-expression of self-antigens as would occur with inactivating mutations of the AIRE gene, results in failure of central tolerance as well as failure of recognition of self-antigens that leads to an auto-immune response.

 

APS2 is characterized by the triad of T1DM, adrenocortical insufficiency, and hypothyroidism as a result of autoimmunity to components of the pancreatic β-cell, adrenal cortex, and thyroid synthesizing machinery. APS3 is essentially identical to APS2 except that adrenocortical insufficiency is absent. This similarity has led some investigators to label the former as APS2a and the latter as APS2b. Whereas APS2a is rare, APS2b is relatively common, as approximately 20% of patients with T1DM harbor circulating antibodies to thyroid synthesis components, namely thyroid peroxidase (TPO) and thyroglobulin (TGB), markers associated with Hashimoto thyroiditis. Note however that the presence of autoantibodies is not necessarily predictive of glandular failure and its clinical manifestations. The genes responsible for the disordered immunity in APS2 and APS3 are in the DQ and DR regions of the HLA complex on the short arm of chromosome 6; specific alleles or mutations facilitate the presentation of antigens co-expressed with the particular HLA complex by antigen presenting cells such as dendritic cells and macrophages. This facilitated presentation of self-antigens, along with other regulatory factors such as lower expression of T-regulatory cells, initiate auto- immunity. Consistent with the generally heightened immune responses in females, these forms of autoimmune endocrine disorders are significantly more prevalent in women, whereas in APS1 the sex distribution is equal.

 

AUTOIMMUNE POLYGLANDULAR SYNDROME 1 (APS1-APECED)

 

APS1 is characterized by 3 classical features; muco-cutaneous candidiasis, hypoparathyroidism with hypocalcemia, hyperphosphatemia, and low PTH concentrations, as well as Addison disease with cortisol deficiency, occasional aldosterone deficiency, and marked elevations in adrenocorticotropic hormone (ACTH). Clinical manifestations of primary adrenal insufficiency include hyperpigmentation (increased MSH in conjunction with increased ACTH), abdominal pain, vomiting, weight loss and electrolyte disturbances, as well as hypoglycemia with fasting. Two of the 3 classical features are required to make a diagnosis of APS1. Other manifestations include periodic rash with fever, kerato-conjunctivitis,chronic diarrhea, primary gonadal failure occurring pre-or post-puberty, Hashimoto thyroiditis with hypothyroidism, Vitamin B12 deficiency, chronic active hepatitis, T1DM, and ectodermal dystrophy-hence the term APECED (Autoimmune Poly Endocrinopathy, Candidiasis, Ectodermal Dystrophy).The features of ectodermal dystrophy include enamel hypoplasia affecting only the permanent teeth, pitted nail dystrophy unrelated to candidiasis of the nails, and visible alterations in the tympanic membranes characterized by calcium deposits. Iritis, optic atrophy and skin changes termed keratopathy, as well as alopecia and vitiligo also are reported (1). Most affected patients manifest their problem(s) by 5 years of age; non-endocrine manifestations precede the endocrine manifestations in about 75% of cases, with mucocutaneous, including oral, candidiasis as the first manifestation in about 60% and malabsorption in about 10%, and vitiligo, alopecia, hepatitis and keratopathy in about 5% of affected subjects (see table 1). Mucocutaneous candidiasis, the most common nonendocrine manifestation, occurs due to defective receptor- mediated internalization of Candida by monocytes as well as decreased kinase activation (13). In these subjects, the median interval to an endocrine manifestation is about 4 years with a range from 0.1-33 years.

 

When an endocrine disorder is the first manifestation it is almost invariably hypoparathyroidism; overall about 70%-80% develop hypoparathyroidism, and in those who develop hypoparathyroidism first, about 60% develop Addison disease. If Addison disease is the first manifestation, about a third also develop hypoparathyroidism. The manifestations vary in sequence and age at onset; the description of all known Finnish cases in 2006 by Peerhentupa (1) remains one of the most detailed series description, and indicates the remarkable heterogenous pattern with the 3 most common being muco-cutaneous candidiasis (~80%), followed by hypoparathyroidism (~80%), and Addison disease(~70%). Ovarian failure occurs in about 60% of affected females but testicular failure only occurs in about 15% of males; parietal cell atrophy with atrophic gastritis and B12 deficiency, and T1DM occur in only about 12% of patients, with diabetes a late complication in comparison to the early manifestations of parathyroid and adrenal deficiency; although anti-thyroid antibodies are common, hypothyroidism only develops in about 5% of affected patients. Rare manifestations include diabetes insipidus, growth hormone deficiency secondary to hypophysitis, and infertility due to sperm antibodies in males and ovarian failure in females. In most patients with APS1, disease manifestations develop earlier than in APS2, as noted above, and are usually more severe than in APS-2. Typically, a given APS-1 patient develops an average of 4–5 manifestations of the syndrome, but may have as few as one or as many as twenty. Due to chronic mucocutaneous candidiasis, patients are also susceptible to squamous carcinoma of the oral mucosa and esophagus over time. In general, patients with APS-1 have an increased mortality risk , due to cancer, adrenal and hypocalcemic crises, and certain conditions induced by aberrant autoimmune responses, particularly hepatitis, nephritis and pneumonitis (14).

 

Circulating antibodies against components of the parathyroid, adrenal, and thyroid glands as well as those of the pancreatic islets are hallmarks of this disease which affects T-cell as well as B- cell function. Although lymphocytic infiltration of the parathyroid glands is frequent, the protein NALP5 that serves as the antigen for the immune response was not discovered until 2008 (5). Antibodies to NALP5 (NACHT leucine-rich-repeat protein 5) were found to be highlyspecific and present only in those with hypoparathyroidism as part of APS1, but absent in other forms of autoimmune syndromes (5) or patients with APS1 but without hypoparathyroidism. Antibodies against adrenal cytochrome P450 enzymes such as Cyp21, Cyp17 and Cyp11A1 are present in many patients but wane with glucocorticoid treatment. Circulating antibodies to GAD 65 and IA2 may be present but are not strong predictors for the development of T1DM. Thyroid peroxidase and anti-thyroglobulin antibodies also are common but not predictive for development of hypothyroidism. Antibodies against liver microsomal proteins, against parietal cells (α & β subunits of H+/K+ ATPase), and against intrinsic factor also are reported. Other less common autoantibodies observed in APS-1 include BPI Fold Containing Family B Member 1 (BPIFB1), the potassium channel regulator KCNRG, expressed in the lung, and transglutaminase-4, expressed solely in the prostate gland (15-17).  

 

A unique feature is the presence of autoantibodies that neutralize type1 interferon, mostly interferon1α and 1ω; these antibodies appear to be specific for this entity and therefore have clinical diagnostic utility (18). Since over 95% of patients with APS-1 have autoantibodies to type 1 interferons, it has been proposed that evaluating the presence of these interferon antibodies should be part of the diagnostic evaluation of patients suspected of harboring APS1. In addition, patients with AIRE mutations possess high-affinity disease-ameliorating autoantibodies, which may explain the low incidence and late appearance of T1DM in patients with APS1 (19). In contrast to the autoantibodies mentioned above, systemic autoantibodies to certain cytokines are highly prevalent in many, if not most, APS-1 patients. Autoantibodies to the interleukin (IL) 17 family of cytokines, especially IL-22 are also prevalent in APS-1, exceeding 90% in some series (20).

 

The cause of this autoimmunity are inactivating mutations in the autoimmune regulator gene (AIRE) on chromosome 21q22.3, which normally acts to permit ectopic expression in the thymus of numerous tissue restricted hormonal and other peripheral antigens, so that developing T-cells that acquire high affinity receptors for these antigens as the developing T-cell traverses the thymic epithelium are eliminated and do not enter the periphery to cause auto-immunity (2, 4, 6, 7). For the classic case, this is an autosomal recessive inherited disorder; however, point mutations resulting in an autosomal dominant form have been reported, albeit this autosomal dominant form seems less severe than the classic autosomal recessive disease, suggesting that this genetic disorder may be more prevalent in various immune disorders hitherto not considered to be due to AIRE mutations (2, 4, 11, 21).

 

The structure of the AIRE gene, the sites of autosomal dominant and autosomal recessive mutations, their influence on the expression and function of the gene and its consequences, are elegantly discussed in recent reviews (2, 4, 11, 21). To date, over 100 different disease-causing mutations have been reported. The most common is the so-called Finnish major mutation p.R257X, located in the SAND-domain (named after a range of proteins in the protein family: Sp100,AIRE-1, NucP41/75, DEAF-1). The Finnish major mutation is especially prevalent in people in Finland, Russia, and Eastern Europe (22).  Another common mutation is the so-called 13 base pair deletion (p.C322del13) in the histone protein reading region called plant homeodomain 1 (PHD1), prevalent in persons in Norway, the British Isles, France, and North-America (10, 23). Additionally, patients with unique dominant negative mutations in AIRE with autosomal dominant inheritance have recently been identified. These dominant negative mutations are associated with milder disease, often with accompanying pernicious anemia, vitiligo, autoimmune thyroid disease, and T1DM, and can be confused with the much more common condition, APS-2, which has a complex inheritance. The dominant gene variants are located both in the PHD1 and SAND domain (24, 25). Recent findings indicate that AIRE controls immune tolerance by an additional mechanism—the induction of a unique population of FOXP3-positive T regulatory cells (Tregs) in the thymus that have the ability to suppress autoreactive cells (11, 25, 26). Thus, not only do more autoreactive cells escape deletion, but those Tregs normally in place to limit their activities are either not developed or are dysfunctional.

 

The peri-post pubertal period is a common time for presentation of some manifestations, although initial presentation may occur as early as the first year of life (3). The classic disorder is rare, and altogether it is estimated that there were only several hundred cases worldwide. However, the syndrome is more common in certain populations; 1: 25,000 in Finns, 1:14,500 Sardinians, 1:9000 Iranian Jews, all examples of past “isolated” populations that demonstrate a founder effect. Surprisingly, however, diabetes mellitus is uncommon and generally appears as a late manifestation in the thirdand fourth decades of life (1-3, 20). Unusual features include chronic kidney disease, apparent mineralocorticoid excess, asplenia and oral or esophageal malignancy. The frequency, patterns and long-term outcomes of this syndrome vary in different populations that harbor different mutations; recent reviews of the patterns and outcomes in cohorts from Sardinia (27), Norway (10) and India (28) highlight these unique patterns. The classic features based on the Finnish cohort are summarized in Table1.

 

Table 1. Clinical Features of APS1

Symptom

Percentage of patients

Mucocutaneous candidiasis

80%

Hypoparathyroidism

70-80%

Adrenal Insufficiency

60%

Type 1 Diabetes Mellitus

12%

Hypothyroidism

4%

Ovarian Failure in Affected Females

60%

Testicular Failure in Affected Males

14%

Gastric Parietal Cell Failure

15%

Hepatitis

13%

Ectodermal Dysplasia

33%

Keratopathy

22%

Alopecia

27%

Vitiligo

13%

Based on references (1-4)

 

Treatment of APS1

 

Treatment guidelines for this condition have been proposed (29); they are based on immune suppression and modulation with agents including glucocorticoids such as prednisone, cyclosporin, the calcineurin inhibitors tacrolimus and sirolimus, methotrexate, mycophenolate mofetil, and rituximab, a CD20 inhibitor; these are especially used for auto-immune hepatitis, enteropathy, tubulo-interstitial nephritis, interstitial lung disease, and keratoconjunctivitis, and are detailed by Kisand et al (20). In general, management of autoimmune polyendocrine syndromes includes hormonal replacement therapy as needed, and treatment of complications (11).

 

An interesting development is the discovery that the damage to various tissues in patients affected by APS 1 mutations  is mediated via the JAK-.STAT signaling cascade and involves interferon gamma (30, 31). Note that we previously stated above that antibodies to interferon1 were diagnostic for the entity APS1; damage to organs is mediated via the JAK-STAT signaling cascade. Hence, blockade of JAK-STAT signaling might reduce tissue damage. Indeed, inhibiting the JAK-STAT signaling cascade via the monoclonal Ab Ruxolitinib, improves clinical and biochemical manifestations in both a murine model and human patients (11, 32), offering promise for dramatic improvement in prognosis and clinical outcomes for affected patients. Larger studies in affected patients are awaited with interest.

 

Current standard treatment requires that hormonal and vitamin (Vitamin D, B12) replacement should be implemented for the known hormonal deficiencies, and other deficiencies should be anticipated and screened for periodically, especially in those with circulating antibodies for components of adrenal steroidogenesis (21-hydroxyase,17-hydroxylase), thyroid (TPO, TG antibodies) and calcium, phosphate, and/or parathyroid hormone levels as indicated. Periodic assessment ofHbA1c, fasting glucose, liver function via ALT and AST should complement careful clinical assessment at 6 month-1year intervals in affected patients. When hypoparathyroidism and chronic mucocutaneous candidiasis are the initial manifestations, screening for primary adrenal insufficiency via an afternoon ACTH concentration is suggested to be performed every 6 months and at least annually. A level of ACTH greater than 80pg/ml is highly suggestive and a level exceeding 100pg/ml is virtually diagnostic. Whereas some recommend performing an ACTH- stimulation test to document adrenal reserve, others recommend starting cortisol replacement therapy and ongoing monitoring of sodium and potassium levels to exclude evolving aldosterone deficiency, as well as checking supine and standing blood pressure. Anti-candida drugs such as ketoconazole when used to treat the candidiasis should alert the treating physicians to exclude possibility of adrenal insufficiency since these agents are known to interfere with cortisol synthesis and hence may accelerate the appearance of adrenal insufficiency or worsen manifestations of existing adrenal deficiency. Cortisol should initially be given in stress dosage, commonly 2-3 times the daily maintenance of ~10mg/m2/d for several days once initial diagnosis is established; thereafter, normal replacement doses of ~8- 10mg/M2/day may be given in 3 divided oral doses daily. When initial diagnosis is established during an inpatient admission, or at a subsequent hospital stay, consideration should be given to administer the hydrocortisone via parenteral means, intravenously or via intramuscular injection. This precaution is advised as oral medication may be less absorbed due to the concomitant presence of candidiasis of the esophagus and lower GI tract which might impair absorption. Patients should also be advised to wear a Medic-Alert bracelet, necklace or key chain, so that cortisol treatment is not delayed should a patient be involved in a motor vehicle accident or be in coma due to adrenal crisis or hypoglycemia. There is evidence that the predilection for autoimmunity in persons with trisomy 21 (Downs syndrome) may also be due to abnormality in the AIRE gene (9). Absent the classic triad of hypoparathyroidism, chronic mucocutaneous candidiasis, and primary adrenal insufficiency, or 2 of these three manifestations, it is likely that many cases are missed; the wide spectrum of potential presentations suggest that genetic testing via AIRE mutational analysis be considered in patients with hepatitis, chronic diarrhea, and periodic rash with fever (1). Recent reviews also raise the possibility of genetic manipulation of certain mutations to restore thymic surveillance at some future date (2). Patients with APS-1 are best followed by a multi-disciplinary team led by a pediatric or adult endocrinologist at an academic medical center. Patients should have a minimum of two follow-up visits per year due to the complexity of the entity, and asymptomatic mutations carriers should be followed at least annually. It is mandatory to check all siblings of APS-1 patients even if they are adult and seemingly well. Screening for 21-hydroxylase and NALP5 antibodies is useful in assessing the risk of development of adrenal insufficiency and hypoparathyroidism, respectively.

 

AUTOIMMUNE POLYGLANDULAR SYNDROME 2 (APS2a; SCHMIDT SYNDROME)

 

APS2 is characterized by the triad of T1DM, Addison disease, and thyroid autoimmunity with hypothyroidism, hyperthyroidism, or Hashimoto thyroiditis; T1DM and Addison disease are obligatory components, but thyroid autoimmunity is not and a host of other autoimmune entities can also be associated. These entities include celiac disease, vitiligo, alopecia, myasthenia gravis, pernicious anemia, IgA deficiency, hepatitis and hypogonadism. Peak prevalence is in the range of 20-40 years of age. In keeping with an autoimmune basis, the syndrome is more prevalent in females and associated with specific HLA DR3 and DR4 haplotypes and with the class II HLA alleles DQ2 and DQ8, also strongly linked to celiac disease. Autoantibodies to islet cell components (GAD65, IA2, ZnT8), thyroid (anti-thyroglobulin TG, anti-thyroid peroxidase TPO), adrenal leading to Addison disease (anti-21-hydroxylase or anti 17-hydroxylase), and celiac disease (tissue transglutaminase and gliadin) are commonly present and should be periodically sought in those with two autoimmune endocrinopathies such as Addison disease and T1DM. Specific treatment for each entity should be continued in the hospital, with cortisol dosage adjusted for stress (8). A mechanism by which viral disease may trigger autoimmunity in the gut leading to celiac disease has recently been proposed and may have relevance to the other auto-immune diseases that form this entity (32).

 

The onset of APS-2 typically appears later than APS-1, mostly in young adulthood. Currently, there are no unique tests to detect patients with APS-2, but testing for autoantibodies may be helpful in assessing disease risk, since the relevant autoantibodies are frequently detectable years before disease onset. Despite the major advancement in identification of disease genes, the heritability of APS-2 is complex. Some authors propose splitting this syndrome into further subtypes, but there is little evidence for distinct etiology in such subcategories, so the broader term APS-2 for all of these patients seems appropriate (11).

 

Illustrative Case

 

A 16-year old girl was admitted to the hospital in coma and found to have profound hypoglycemia. Her physical findings were striking for pigmented patches on her tongue, gums, and lips and her skin was deeply suntanned (see figure 2). The mother related that her daughter has T1DM since age 12 and had been experiencing numerous hypoglycemic episodes unrelated to food intake or exercise. Accordingly, the dose of insulin had been reduced to about 50% of what it had been 3 months previously. She responded to glucose infusion and recovered full consciousness. Laboratory tests documented a marked elevation of ACTH, low morning cortisol, elevated antibodies to 21OH, and markedly elevated TSH with a low T4. Thus, this patient fulfills all the criteria for APS2. The hypoglycemia was due to a combination of deficient hormonal counter-regulation (cortisol deficiency) as well as the delayed clearance of insulin as a result of hypothyroidism.

 

Figure 2. Patient with APS 2

 

AUTOIMMUNE POLYGLANDULAR SYNDROME 3 (APS2b)

 

APS-3 also known as APS2b, is sometimes referred to as Carpenter’s syndrome, and has the same array of endocrine tissue autoimmune abnormalities as APS2, but without Addison disease. Almost 20% of patients with T1DM have thyroglobulin (TG) and thyroid peroxidase (TPO) antibodies, but only a minority progress to clinical or biochemical hypothyroidism, so APS3 (APS2b) could be considered as a relatively common disorder (9).

 

Treatment of APS-2 should focus on replacement of missing hormones according to current guidelines for treating the main components of APS-2. Physicians should be particularly aware that a patient with APS-2 has an increased risk of developing another organ-specific autoimmune disease. Massive family accumulation of autoimmune diseases, especially with early debut could indicate a monogenic disease, possibly a “non-classical” APS-1 especially if vitiligo and pernicious anemia is prevalent (2).

 

Table 2. Clinical features of APS2 and APS3

APS2

APS3

Type 1 Diabetes Mellitus

Type 1 Diabetes Mellitus

Thyroid autoimmunity

Thyroid autoimmunity

Adrenal Insufficiency

 

 

ADRENAL INSUFFICIENCY

 

Since adrenal insufficiency is a hallmark feature of APS1 and 2a syndromes, and since it is the most life threatening, we briefly review the crucial role of the adrenal in metabolic homeostasis. During stress, cortisol produced by the zona fasciculata of the adrenal gland is required to maintain normoglycemia and hemodynamic stability. Cortisol regulates carbohydrate metabolism to maintain normoglycemia, decreases capillary permeability to maintain a normal blood pressure, and is required for activating enzymatic activity to convert norepinephrine to epinephrine. Cortisol production is under the regulation of the hypothalamus and pituitary. The hypothalamic-pituitary-adrenal (HPA) axis is mediated through the circulating level of plasma cortisol by negative feedback of cortisol on corticotropin releasing factor (CRF) and ACTH secretion. Aldosterone produced by the zona glomerulosa is predominantly regulated by the renin-angiotensin system. Aldosterone stimulates the kidneys to reabsorb sodium and water and excrete potassium. At high concentrations, cortisol can also act on the mineralocorticoid receptor to increase sodium and water retention as the activity of 11β-hydroxysteroid-dehydrogenase 2 which inactivates cortisol to cortisone is overwhelmed.

 

Presentation of adrenal insufficiency is often chronic, presenting with fatigue, anorexia, and weight loss; hyperpigmentation of the buccal mucosa and skin creases or generalized tanning of the skin occur with primary adrenal insufficiency from the excess of melanocyte stimulating hormone produced as a byproduct in the formation of excess ACTH.

 

Adrenal insufficiency can be caused by primary adrenal disease or dysfunction of the HPA axis (secondary adrenal insufficiency). The most common etiologies of primary adrenal disease in children, adolescents, and young adults include autoimmune disease, retroperitoneal trauma and rare genetic syndromes involving the formation of the adrenal gland, the biosynthetic formation of cortisol, and the ability of the adrenal gland to respond to ACTH. Severe defects may present in the neonatal period or may be unmasked later in life by the requirement for higher secretion during a physiological stress situation such as sepsis or trauma. Secondary adrenal insufficiency is most commonly caused by damage to the hypothalamus or pituitary gland by trauma or neurological surgery or impingement on these structures by a tumor or mass; congenital defects of isolated ACTH formation or action also may occur. More commonly, suppression of the HPA axis can occur in patients chronically treated with potent glucocorticoid steroids.

 

Patients with adrenal insufficiency can present acutely in a severe life-threatening event termed adrenal crisis, particularly if there is an inciting event such as a septic illness, surgical procedure, anesthesia, or trauma. These patients have symptoms of nausea, vomiting, abdominal pain, dehydration, altered mental status, hypotension, hypoglycemia, or shock (33). Hypotension may be unresponsive to fluid resuscitation alone due to deficiency of cortisol required to activate β-adrenergic receptors and vascular tone. Salt wasting (hyponatremia, hyperkalemia) results from aldosterone deficiency. A cardinal feature of primary adrenal insufficiency is hyperpigmentation owing to concurrent rise in melanocyte stimulating hormone (MSH) associated with elevated ACTH production. Darkening of the skin is most prominent at the axillae, palmer creases, areolae, genitalia, and pigmentary lines of the gums (see Fig 2 above). This hyperpigmentation does not occur in secondary adrenal insufficiency as there is no rise in ACTH. Secondary causes of adrenal insufficiency, and certain forms of primary adrenal insufficiency that do not affect aldosterone production, do not present with salt-wasting and Addisonian crisis.

 

Because of the circadian rhythm and diurnal variation in ACTH and cortisol production, early morning serum cortisol and ACTH concentrations provide the best assessment of endogenous adrenal function. An early morning serum cortisol of <10 mcg/dl is suspicious for adrenal insufficiency. The corresponding ACTH concentration is elevated in primary adrenal insufficiency; a low ACTH concentration is suspicious for secondary adrenal insufficiency. However, a randomly timed cortisol measurement of <15 mcg/dl, in the setting of an acute illness has been proposed as concerning for adrenal insufficiency in adults (33). In the absence of clinical clues suggesting primary adrenal insufficiency, such as hyperpigmentation, stimulation with ACTH is the best diagnostic test for identifying those with adrenal insufficiency. At baseline, ACTH and cortisol blood levels are obtained and 250 mcg of synthetic ACTH (cosyntropin) is administered either via the intravenous (IV) or intramuscular (IM) route. The test is considered diagnostic of adrenal insufficiency if the peak cortisol level is less than 18 mcg/dl, 60 minutes following cosyntropin administration (34). Such a supra- physiologic dose of ACTH may overcome a defect in the hypothalamic-pituitary-adrenal axis to produce the rise in serum cortisol. If there is a high suspicion for secondary adrenal insufficiency in the face of a normal cortisol response to high dose ACTH, early morning serum cortisol and ACTH concentrations may be more informative. The causes of adrenal insufficiency as well as that of thyroid dysfunction and their management are described elsewhere in Endotext (35, 36).

 

AUTO-IMMUNITY ASSOCIATED WITH CANCER IMMUNOTHERAPY

 

An increasingly important and frequent cause of endocrine-autoimmune syndromes is their appearance in association with the increasing use of immunotherapy as a front line or back-up therapy in various cancers (37). Indeed, the variety and severity of endocrine autoimmune syndromes associated with the use of inhibitors of CTLA4 (cytotoxic T-lymphocyte-associated protein 4) such as ipilimumab, and immune checkpoint blockade of programmed death 1(PD-1) and its ligands PDL1 and PDL2, has recently been termed “the Achilles heel of cancer immunotherapy” (38). The range of autoimmune endocrine manifestations includes hypophysitis with disturbances in anterior pituitary hormones, hypo-and hyperthyroidism, adrenal insufficiency, and T1DM (25, 39-43). Key checkpoints by which autoimmunity is regulated in normal individuals are also exploited by tumors to evade recognition and elimination via the immune system; employing immuno-regulatory agents that block these checkpoints facilitates the recognition of tumor antigens as foreignand activates their destruction, but at the same time stimulates autoimmune responses to self-antigens. Clinicians should be aware of these autoimmune manifestations and screen for involvement of endocrine tissues or their clinical manifestations. Notably, some of these endocrine autoimmune manifestations may appear months to years after initiation of immune therapy for cancer (40).

 

Thyroid disorders, typically associated with anti-PD-1 antibodies and hypophysitis commonly related to anti-CTLA-4 therapy, are the two most frequent endocrine organ pathologies (41). Notably, in a large cohort, it was shown that the incidence of any-grade immune-related adverse event (irAE) is higher with CTLA-4 (53.8%) than with PD-1 (26.5%) and PD-L1 (17.1%) Moreover, the incidence of any-grade irAE was highest in patients receiving CTLA-4 plus PD-1/PD-L1 combinations (61.1%) (44, 45). The incidence of endocrine adverse events reported with the use of immune checkpoint inhibitors (ICI) ranges from 5% to 20% (46, 47), with a recent systematic review and meta-analysis reporting an overall incidence of clinically significant endocrinopathies of approximately 10% (48). Hypophysitis appears most often in men older than 60 years and 2–5 times more frequent than in women. The incidence reported is 4%–20% with ipilimumab, 8% with the combination ipilimumab plus nivolumab, 0.6% with nivolumab, and 0.7% with pembrolizumab (47). The incidence of hypothyroidism ranges from 6% to 13% and for thyrotoxicosis varied from 3% to 16%. However, when subclinical hypothyroidism or hyperthyroidism is included, the incidence can reach 28% and 22%, respectively (49).These risks were reported to be dose dependent; in the case of anti-CTLA-4 treatment, the risk was observed only above a treatment threshold of 10 mg/kg.

 

Rarely, patients develop T1DM, or central diabetes insipidus, or hypoparathyroidism. Endocrinopathies less often reported include diabetes mellitus, as mentioned above, primary adrenal insufficiency, and hypercalcemia due to hyperparathyroidism. In the case of primary adrenal insufficiency, an incidence of less than 1% with monotherapy and 4%–8% with combined immunotherapy has been reported (48). For T1DM, overall incidence of 0.4% was reported in patients treated with anti-PD-1/PD-L1 but not those treated with anti-CTLA-4 (50, 51). However, a recent study reported a prevalence of 0.9% among 2,960 patients treated by ICI (52). In clinical practice, significant irAEs (grade 2 or higher) are managed with systemic immunosuppression mostly in the form of corticosteroids with methylprednisolone 0.5–1 mg/kg for grade 2 and 1–2 mg/kg for grade 2–3; for grade 4 irAEs, resuming treatment with the drug is contraindicated. More rarely, anti-tumor necrosis factor-α agents have been used if steroids are not effective or contraindicated (41).

 

X-LINKED IMMUNODYSREGULATION, POLYENDOCRINOPATHY, AND ENTEROPATHY (IPEX)

 

X-linked Immunodysregulation, Polyendocrinopathy and Enteropathy - or IPEX- is an extremely rare inherited syndrome characterized by early onset T1DM, (53) autoimmune enteropathy with intractable diarrhea and malabsorption, and dermatitis that may be eczematiform, ichthyosiform or psoriasiform. Eosinophilia and elevated IgE-levels are frequently present in IPEX. Some patients develop kidney disease, most often membranous glomerulonephritis or interstitial nephritis. Later manifestations may include autoimmune thyroiditis, alopecia, various autoimmune cytopenias, hepatitis and exocrine pancreatitis (54). Several of these features overlap with APS-1, but in IPEX they usually develop much earlier in life at 0.1-0.4 years (55). The disorder is frequently fatal in the first few years of life, unless patients are diagnosed and promptly treated with immunosuppressive agents or, if possible, receive an allogenic bone marrow transplant, which can be curative (54).

The defective gene was mapped to mutations in the FOXP3 (human) gene (56). To date, over 100 different mutations throughout the gene have been reported in patients. FOXP3 is currently recognized as a master transcription factor that is highly expressed in Tregs in association with other key Treg elements such as CD4, cytotoxic T Lymphocyte-associated protein 4 (CTLA4), and CD25, the high affinity IL-2 receptor (11, 57, 58).

 

Patients with IPEX, like those with APS-1, develop circulating autoantibodies that can be helpful in making the diagnosis. Despite the rarity of IPEX, studies of affected patients have revealed a key pathway for self-tolerance that has aided in the understanding of Tregs and has led to research aimed at the development of methods to enhance Treg function in transplantation and as a treatment for autoimmune disorders. (59)

 

NEW DIRECTIONS

 

Over the past decade, better diagnostic tools including genetic tests and autoantibody analyses have been developed for the detection and management of APS-related diseases. Early diagnosis in association with personalized genomics might possibly enable physicians to apply early immunomodulatory therapy to ameliorate the autoimmune process before irreversible organ damage has occurred. Restoration of thymic epithelium with intact immune regulatory function via stem cell engineering to reverse the defective immune system remains a long-term goal but is being pursued (60). Modulation of the JAK-STAT signalling cascade for improving and diminishing the harmful effects of APS-1 is in the early stages of development but appears highly promising for this and related syndromes (30, 31).

 

REFERENCES

 

  1. Perheentupa, J., Autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy. J Clin Endocrinol Metab, 2006. 91(8): p. 2843-50.
  2. Anderson, M.S. and M.A. Su, AIRE expands: new roles in immune tolerance and beyond. Nat Rev Immunol, 2016. 16(4): p. 247-58.
  3. Fierabracci, A., Type 1 Diabetes in Autoimmune Polyendocrinopathy-Candidiasis-Ectodermal Dystrophy Syndrome (APECED): A "Rare" Manifestation in a "Rare" Disease. Int J Mol Sci, 2016. 17(7).
  4. Kisand, K. and P. Peterson, Autoimmune polyendocrinopathy candidiasis ectodermal dystrophy. J Clin Immunol, 2015. 35(5): p. 463-78.
  5. Alimohammadi, M., et al., Autoimmune polyendocrine syndrome type 1 and NALP5, a parathyroid autoantigen. N Engl J Med, 2008. 358(10): p. 1018-28.
  6. Finnish-German, A.C., An autoimmune disease, APECED, caused by mutations in a novel gene featuring two PHD-type zinc-finger domains. Nat Genet, 1997. 17(4): p. 399-403.
  7. Anderson, M.S., et al., Projection of an immunological self shadow within the thymus by the aire protein. Science, 2002. 298(5597): p. 1395-401.
  8. Kakleas, K., et al., Associated autoimmune diseases in children and adolescents with type 1 diabetes mellitus (T1DM). Autoimmun Rev, 2015. 14(9): p. 781-97.
  9. Gimenez-Barcons, M., et al., Autoimmune predisposition in Down syndrome may result from a partial central tolerance failure due to insufficient intrathymic expression of AIRE and peripheral antigens. J Immunol, 2014. 193(8): p. 3872-9.
  10. Bruserud, O., et al., A Longitudinal Follow-up of Autoimmune Polyendocrine Syndrome Type 1. J Clin Endocrinol Metab, 2016. 101(8): p. 2975-83.
  11. Husebye, E.S., M.S. Anderson, and O. Kampe, Autoimmune Polyendocrine Syndromes. N Engl J Med, 2018. 378(26): p. 2543-2544.
  12. Halonen, M., et al., AIRE mutations and human leukocyte antigen genotypes as determinants of the autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy phenotype. J Clin Endocrinol Metab, 2002. 87(6): p. 2568-74.
  13. Brannstrom, J., et al., Defect internalization and tyrosine kinase activation in Aire deficient antigen presenting cells exposed to Candida albicans antigens. Clin Immunol, 2006. 121(3): p. 265-73.
  14. Bensing, S., et al., Increased death risk and altered cancer incidence pattern in patients with isolated or combined autoimmune primary adrenocortical insufficiency. Clin Endocrinol (Oxf), 2008. 69(5): p. 697-704.
  15. Shum, A.K., et al., BPIFB1 is a lung-specific autoantigen associated with interstitial lung disease. Sci Transl Med, 2013. 5(206): p. 206ra139.
  16. Alimohammadi, M., et al., Pulmonary autoimmunity as a feature of autoimmune polyendocrine syndrome type 1 and identification of KCNRG as a bronchial autoantigen. Proc Natl Acad Sci U S A, 2009. 106(11): p. 4396-401.
  17. Landegren, N., et al., Transglutaminase 4 as a prostate autoantigen in male subfertility. Sci Transl Med, 2015. 7(292): p. 292ra101.
  18. Meager, A., et al., Anti-interferon autoantibodies in autoimmune polyendocrinopathy syndrome type 1. PLoS Med, 2006. 3(7): p. e289.
  19. Meyer, S., et al., AIRE-Deficient Patients Harbor Unique High-Affinity Disease-Ameliorating Autoantibodies. Cell, 2016. 166(3): p. 582-595.
  20. Kisand, K., et al., Chronic mucocutaneous candidiasis in APECED or thymoma patients correlates with autoimmunity to Th17-associated cytokines. J Exp Med, 2010. 207(2): p. 299-308.
  21. Sahoo, S.K., et al., Identification of autoimmune polyendocrine syndrome type 1 in patients with isolated hypoparathyroidism. Clin Endocrinol (Oxf), 2016. 85(4): p. 544-50.
  22. Orlova, E.M., et al., Expanding the Phenotypic and Genotypic Landscape of Autoimmune Polyendocrine Syndrome Type 1. J Clin Endocrinol Metab, 2017. 102(9): p. 3546-3556.
  23. Proust-Lemoine, E., et al., Autoimmune polyendocrine syndrome type 1 in north-western France: AIRE gene mutation specificities and severe forms needing immunosuppressive therapies. Horm Res Paediatr, 2010. 74(4): p. 275-284.
  24. Cetani, F., et al., A novel mutation of the autoimmune regulator gene in an Italian kindred with autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy, acting in a dominant fashion and strongly cosegregating with hypothyroid autoimmune thyroiditis. J Clin Endocrinol Metab, 2001. 86(10): p. 4747-52.
  25. Abbott, J.K., et al., Dominant-negative loss of function arises from a second, more frequent variant within the SAND domain of autoimmune regulator (AIRE). J Autoimmun, 2018. 88: p. 114-120.
  26. Leonard, J.D., et al., Identification of Natural Regulatory T Cell Epitopes Reveals Convergence on a Dominant Autoantigen. Immunity, 2017. 47(1): p. 107-117 e8.
  27. Meloni, A., et al., Autoimmune polyendocrine syndrome type 1: an extensive longitudinal study in Sardinian patients. J Clin Endocrinol Metab, 2012. 97(4): p. 1114-24.
  28. Zaidi, G., et al., Autoimmune polyendocrine syndrome type 1 in an Indian cohort: a longitudinal study. Endocr Connect, 2017. 6(5): p. 289-296.
  29. Husebye, E.S., et al., Clinical manifestations and management of patients with autoimmune polyendocrine syndrome type I. J Intern Med, 2009. 265(5): p. 514-29.
  30. Oikonomou, V., et al., The Role of Interferon-gamma in Autoimmune Polyendocrine Syndrome Type 1. N Engl J Med, 2024. 390(20): p. 1873-1884.
  31. Su, M.A., JAK Inhibition Immunotherapy for APS-1. N Engl J Med, 2024. 390(20): p. 1918-1921.
  32. Verdu, E.F. and A. Caminero, How infection can incite sensitivity to food. Science, 2017. 356(6333): p. 29-30.
  33. Cooper, M.S. and P.M. Stewart, Corticosteroid insufficiency in acutely ill patients. N Engl J Med, 2003. 348(8): p. 727-34.
  34. Bornstein, S.R., et al., Diagnosis and Treatment of Primary Adrenal Insufficiency: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab, 2016. 101(2): p. 364-89.
  35. Weetman, A. and L.J. DeGroot, Autoimmunity to the Thyroid Gland, in Endotext, L.J. De Groot, et al., Editors. 2000: South Dartmouth (MA).
  36. Nicolaides, N.C., Chrousos, and E. Charmandari, Adrenal Insufficiency, in Endotext, L.J. De Groot, et al., Editors. 2000: South Dartmouth (MA).
  37. Vardarli, I., et al., Risk and Incidence of Endocrine Immune-Related Adverse Effects Under Checkpoint Inhibitor Mono- or Combination Therapy in Solid Tumors: A Meta-Analysis of Randomized Controlled Trials. J Clin Endocrinol Metab, 2024. 109(4): p. 1132-1144.
  38. June, C.H., J.T. Warshauer, and J.A. Bluestone, Is autoimmunity the Achilles' heel of cancer immunotherapy? Nat Med, 2017. 23(5): p. 540-547.
  39. Ryder, M., et al., Endocrine-related adverse events following ipilimumab in patients with advanced melanoma: a comprehensive retrospective review from a single institution. Endocr Relat Cancer, 2014. 21(2): p. 371-81.
  40. Pedoeem, A., et al., Programmed death-1 pathway in cancer and autoimmunity. Clin Immunol, 2014. 153(1): p. 145-52.
  41. Del Rivero, J., et al., Endocrine-Related Adverse Events Related to Immune Checkpoint Inhibitors: Proposed Algorithms for Management. Oncologist, 2020. 25(4): p. 290-300.
  42. Kotwal, A., et al., Endocrinopathies Associated With Immune Checkpoint Inhibitor Use. Endocr Pract, 2024. 30(6): p. 584-591.
  43. Shi, H., et al., Endocrine system-related adverse events associated with PD-1/PD-L1 inhibitors: data mining from the FDA adverse event reporting system. Front Med (Lausanne), 2024. 11: p. 1366691.
  44. Faje, A.T., et al., Ipilimumab-induced hypophysitis: a detailed longitudinal analysis in a large cohort of patients with metastatic melanoma. J Clin Endocrinol Metab, 2014. 99(11): p. 4078-85.
  45. Trevisani, V., et al., Endocrine immune-related adverse effects of immune-checkpoint inhibitors. Expert Rev Endocrinol Metab, 2023. 18(5): p. 441-451.
  46. Corsello, S.M., et al., Endocrine side effects induced by immune checkpoint inhibitors. J Clin Endocrinol Metab, 2013. 98(4): p. 1361-75.
  47. Torino, F., et al., Endocrine side-effects of anti-cancer drugs: mAbs and pituitary dysfunction: clinical evidence and pathogenic hypotheses. Eur J Endocrinol, 2013. 169(6): p. R153-64.
  48. Barroso-Sousa, R., et al., Incidence of Endocrine Dysfunction Following the Use of Different Immune Checkpoint Inhibitor Regimens: A Systematic Review and Meta-analysis. JAMA Oncol, 2018. 4(2): p. 173-182.
  49. Illouz, F., et al., Expert opinion on thyroid complications in immunotherapy. Ann Endocrinol (Paris), 2018. 79(5): p. 555-561.
  50. Byun, D.J., et al., Cancer immunotherapy - immune checkpoint blockade and associated endocrinopathies. Nat Rev Endocrinol, 2017. 13(4): p. 195-207.
  51. Sznol, M., et al., Endocrine-related adverse events associated with immune checkpoint blockade and expert insights on their management. Cancer Treat Rev, 2017. 58: p. 70-76.
  52. Stamatouli, A.M., et al., Collateral Damage: Insulin-Dependent Diabetes Induced With Checkpoint Inhibitors. Diabetes, 2018. 67(8): p. 1471-1480.
  53. Wildin, R.S., S. Smyk-Pearson, and A.H. Filipovich, Clinical and molecular features of the immunodysregulation, polyendocrinopathy, enteropathy, X linked (IPEX) syndrome. J Med Genet, 2002. 39(8): p. 537-45.
  54. Barzaghi, F., et al., Long-term follow-up of IPEX syndrome patients after different therapeutic strategies: An international multicenter retrospective study. J Allergy Clin Immunol, 2018. 141(3): p. 1036-1049 e5.
  55. Jamee, M., et al., Clinical, Immunological, and Genetic Features in Patients with Activated PI3Kdelta Syndrome (APDS): a Systematic Review. Clin Rev Allergy Immunol, 2020. 59(3): p. 323-333.
  56. Bennett, C.L., et al., The immune dysregulation, polyendocrinopathy, enteropathy, X-linked syndrome (IPEX) is caused by mutations of FOXP3. Nat Genet, 2001. 27(1): p. 20-1.
  57. Sakaguchi, S., et al., Regulatory T cells and immune tolerance. Cell, 2008. 133(5): p. 775-87.
  58. Caudy, A.A., et al., CD25 deficiency causes an immune dysregulation, polyendocrinopathy, enteropathy, X-linked-like syndrome, and defective IL-10 expression from CD4 lymphocytes. J Allergy Clin Immunol, 2007. 119(2): p. 482-7.
  59. Bluestone, J.A., et al., Type 1 diabetes immunotherapy using polyclonal regulatory T cells. Sci Transl Med, 2015. 7(315): p. 315ra189.
  60. Parent, A.V., et al., Generation of functional thymic epithelium from human embryonic stem cells that supports host T cell development. Cell Stem Cell, 2013. 13(2): p. 219-29.

Diabetic Striatopathy

ABSTRACT

 

Acute onset de novo movement disorders are increasingly being reported in the settings of hyperglycemia, particularly from Asian countries. Although hemichorea-hemiballism is the most common and classically described movement semiology in association with hyperglycemia, various other hyperkinetic (choreoathetosis, dystonia, tremors, akathisia, restless leg syndrome etc.) and hypokinetic (parkinsonism) movement disorders are recognized. Diabetic striatopathy (DS) is defined as the disease phenomenon characterized by either choreo-ballistic movement or suggestive signature changes in striatum on imaging or presence of both. DS is generally considered as the complication of long-standing, poorly controlled non-ketotic hyperglycemia with acute hyperglycemic surge, though it can also be the first presentation of previously undiagnosed diabetes. Thus, it is recommended to test for capillary blood glucose in every patient presenting with de novo acute onset movement disorders of any semiology irrespective of past history of diabetes. It is important to recognize that normal brain imaging does not exclude the diagnosis of DS (clinically isolated DS) because nearly 50% cases may not have any characteristic neuroradiological stigmata. There is also high prevalence of clinical-neuroradiological discordance in DS cases. Thus, while managing such patients’ priority should be imparted on bedside identification of the movement semiology accurately and aggressive treatment of hyperglycemia rather than ordering expensive neuroradiological investigation. Generally diabetic movement disorder carries excellent prognosis. The majority of cases rapidly resolves with insulin therapy alone with or without use of adjunctive neuroleptics.      

 

INTRODUCTION

 

Although a myriad of neurological complications resulting from chronic micro- and macroangiopathy and acute metabolic perturbations in diabetes mellitus (DM) had been well documented, structured studies on acute-onset movement disorders among patients with DM were surprisingly left out until recently (1,2). Movement disorders can manifest either as the first manifestation of undiagnosed DM or in later advanced stages of the disease (3-7). Genesis of these abnormal movements can directly be attributed to hyperglycemia or hypoglycemia, and may result from diabetic complications such as vasculopathy and neuropathy (2,8). Moreover, there are syndromes or conditions which can present as movement disorders alongside DM (8,9). Aggressive glycemic control is known to alleviate abnormal movements in most of the cases (1,2,8). Among all the movement semiologies discussed in literature, hemichorea-hemiballism is most frequently reported (1,2). Diabetic striatopathy (DS) is an umbrella term referring to a hyperglycemic condition associated with both or either one of the two following conditions: (1) acute onset chorea-ballism; (2) striatal hyperdensity on computed tomography (CT) or striatal hyperintensity on T1-weighted magnetic resonance imaging (MRI) (1,2,10). We herein briefly summarize the movement disorders in DM keeping DS at the center of discussion. Epidemiological and clinical spectrum, pathophysiology, neuroradiological conundrums, and available treatment are discussed. We also have tried to shed light upon the knowledge gaps in understanding of this particular disease that need to be addressed.

 

EPIDEMIOLOGY- MAGNITUDE OF THE PROBLEM

 

At present there is no prospective epidemiological study to assess the incidence or prevalence data available regarding movement disorders in diabetes. Few retrospective analyses with weak study methodology showed the prevalence of DS was in order of 1% or even less (11-13). On the other hand, a prospective study by Dubey et al revealed that 17.4% patients were diabetic among 552 patients presented with acute onset movement disorders and its mimics (including epilepsia partialis continua in a movement disorder clinic (1).

 

A systematic review of 176 patients observed that the lion share of DS cases was reported from Asian countries (2). Multiple factors like easy accessibility to healthcare, poor compliance to drugs, ethnicity, or genetic susceptibility might play roles, but it definitely requires more exploration. However, a study by Shafran et al revealed that DS was actually underdiagnosed in western populations leading to its underreporting (11).

 

Acute onset movement disorders in diabetes had been reported in a wide range of age groups ranging from first to ninth decade (2). The mean age of the patients was generally sixth to seventh decade observed in different case series or systematic reviews (2,14-19). Two studies from India reported a relatively younger mean age (fifth decade) of presentation (1,20). Chen et al analyzing only the cases of hemichorea-hemiballism with ketotic hyperglycemia also found a median age of 54 years (21).

 

Across different studies over the years, notably, a woman preponderance (nearly 2 times in most of the studies) of hyperglycemic hemichorea-hemiballism movements had been observed (2,14-21). The exact reason for this female predominance or the role of biological sex on hyperglycemia-induced acute movement disorders needs further study. Some have postulated that increased dopaminergic receptor sensitivity secondary to estrogen deficiency in the striatum among postmenopausal women might make them susceptible to hyperkinetic movement disorders (17,21). In contrast with this global scenario, the authors’ largest clinical series from India revealed a slight male predominance (52.5%) which needs further confirmation by replication in other independent studies (1).

 

CLINICAL PRESENTATION- SPECTRUM OF MOVEMENT DISORDERS IN DIABETES

 

Among different movement semiologies described among diabetics (table-1), hemichorea-hemiballism is the most common and classically described (1-8). See video 1-6 for different movement disorders associated with hyperglycemia.

 

VIDEOS

 

Table 1. Different Movement Semiologies Observed Among Patients with Diabetes

Choreic and ballistic movements

Non-choreoballistic movements

·       Choreoballism- hemi / mono / generalized

·       Pure chorea- hemi / mono / generalized

·       Pure ballism- hemi / mono / generalized

·       Choreoathetosis

 

·       Tremors

·       Hemifacial spasm

·       Parkinsonism

·       Myoclonus- focal, action, diaphragmatic, opsoclonus-myoclonus

·       Dystonia

·       Restless leg syndrome

·       Ataxia

·       Dyskinesia- Paroxysmal kinesigenic dyskinesia, paroxysmal non-kinesigenic dyskinesia, paroxysmal exertional dyskinesia

 

Dubey et al (1) in their largest clinical series showed that non-choreic, non-ballistic movements were present among 30.5% of 59 cases. Therefore, an immediate capillary blood glucose (CBG) measurement in all patients with any sort of acute onset movement disorders is of pivotal importance before ordering other costly and time-consuming investigations. Bilateral clinical involvement was identified in 37.2% of all patients and was significantly more common in non-choreoballistic movement disorders than choreoballism (1). In an analysis by Chua et al bilaterality was documented in 9.7% DS cases (2), whereas bilaterality was even more frequently (19.5%) observed in the series described by Dubey et al (1). The latter was the only study which systematically assessed both the hyperglycemia-associated choreoballism and non-choreoballistic movement disorders. It observed no statistically significant differences regarding demographic or clinical variables between these two types of movement disorders except bilaterality and delay in diagnosis (more frequent in non-choreoballism than choreoballism) (1).

 

Many a times seizures can mimic hyperkinetic movement disorders or sometimes both may coexist (3). Most commonly epilepsia partialis continua mimics a movement disorder. It is not conventionally categorized as a movement disorder; but is rather a type of simple focal motor status epilepticus with frequent repetitive muscle jerks, usually arrhythmic, that continues over prolonged periods. Moreover, the epilepsia partialis continua patients have electroencephalographic changes. The differentials to be considered are stroke, associated opposite hemispheric structural defect/s, and space-occupying lesions. Non-ketotic hyperglycemia is a well-known cause of reversible epilepsia partialis continua (22,23).

 

CORRELATION WITH MARKERS OF GLYCEMIA AND DIABETIC COMPLICATIONS

 

Movement disorders have been described in different types of DM, including type 1, type 2 and type 3c diabetes (1,2,5). DS is generally a complication of long-standing DM with poorly controlled glycemic status flared up by an acute hyperglycemic surge in a non-ketotic milieu. In the cohort of Dubey et al the mean duration of DM was 9.8 years and movement disorders were the presenting manifestation of previously undiagnosed DM in three cases (5.1%) (1). Patient-level meta-analysis of previously published cases has found a higher number (17%) of DS cases having previously undiagnosed DM (2). This discrepancy could be due to lack of screening or publication bias. Nonetheless, it is recommended to measure blood glucose levels at presentation among all patients with acute onset movement disorders irrespective of their past glycemic status. Importantly, the majority of the patients with DS bears the stigmata of other chronic microvascular diabetic complications (1).

 

PATHOPHYSIOLOGY- HOW METABOLIC MICROVASCULAR EFFECTS INFLUENCE MACRO-MOVEMENTS

 

From the various previously reported speculative pathophysiological basis of DS, Dubey et al (10) proposed "ominous octet" of pathogenesis of DS, which includes sequential occurrence of following factors: 1) gemistocytopathy, 2) petechial hemorrhage, 3) methemoglobin deposition, 4) mineral (calcium and magnesium) deposition, 5) cytotoxic edema, 6) myelinolysis, 7) gliosis, and 8) atrophy. The hyperglycemic state results in hyperosmolarity and hyperviscosity leading to reduced cerebral blood flow causing insult to the striatal astrocytes which are exquisitely sensitive to ischemia. These tumescent reactive astrocytes are known as gemistocytes, the most consistent finding gathered from limited number of biopsy studies (2).

 

Interestingly enough, genesis of majority of hyperglycemic movement disorders occurs in the background of non-ketotic milieu (1,2). In non-ketotic hyperglycemia brain metabolism is shifted towards the alternative anaerobic pathway in Krebs cycle causing depletion in gamma-aminobutyric acid (GABA), an inhibitory neurotransmitter. This leads to attenuated inhibition of the subthalamus by the medial globus pallidus resulting in hyperkinetic movements. Conversely, GABA can be readily re-synthesized from acetoacetate, which is in abundance in the ketotic milieu (8). Hence, in the latter state, hyperkinetic movements rarely occur unless some other sinister mechanisms (such as cerebrovascular insufficiency or ultrastructural changes in basal ganglia) are at play (1).

 

NEURORADIOLOGICAL AND CLINICAL CONUNDRUM OF DS

 

Although the sensitivity of MRI was observed to be higher than CT scan to detect DS (95.3% vs. 78.9%), the need for CT can’t be obviated in cases of negative MRI scans. There is plenty of cases where mismatch (defined as the complete absence of anomaly in basal ganglia on one imaging modality, but not the other) and incompatibility (defined as the difference in locations of striatal anomalies between CT and MRI) exist (2). Hyperdensity on CT or hyperintensity on T1-weighted MRI in contralateral (to the side of the abnormal movements) putamen surrounding edema or mass effect, along with hyperglycemia and hemichorea-hemiballism movements, is pathognomonic of DS (10). Putamen is the most commonly involved striatal structure, whereas isolated caudate or globus pallidus or subthalamic nucleus involvement seem to be less frequent (1,2). A significant portion of cases shows concomitant affliction of all three striatal components (putamen, caudate, and globus pallidus) (2). The reason behind putaminal vulnerability to hyperglycemia and how the same anatomical lesion causes such wide arrays of movement disorders remain elusive.

 

The pathological basis behind the striatal hyperintensity on T1-weighted MRI and hyperdensity on CT scan in these patients can be proved by histopathological evidence of petechial hemorrhages causing accumulation of methemoglobin (2). Unfortunately, this theory of microhemorrhages behind T1 hyperintensity can’t be substantiated well on corresponding gradient-echo images. In contrast, accumulation of gemistocytes due to ischemic events and neuronal dysfunction may partially explain the striatal hyperintensity on T1-weighted MRI, but not hyperdensity on CT (2,10). Few DS cases have documented restricted diffusion in diffusion-weighted imaging sequence (24). Advanced imaging modalities such as MR volumetry, spectroscopy, functional MRI, positron emission tomography (PET), single photon emission CT (SPECT), susceptibility weighted MR, perfusion imaging etc. although not routinely done in clinical practice for diagnosis of DS, might unveil its intricate pathophysiological basis (2,10).  

 

Previous studies showed that in different case series patients with choreo-ballistic movements did not have suggestive neuroimaging findings in 5-45% cases (clinically isolated DS) (2,14-17,25). Study focusing on both choreo-ballistic and non-choreo-ballistic movements revealed that only 44% cases had changes in brain MRI (1). This wide variability had been attributed to the varied use of MRI or CT and non-homogenous neuroradiological definition of DS applied among various studies (1,2,10). Moreover, neuroradiological changes lag behind the clinical manifestations. Nevertheless, it underscores the importance of initiating management by recognizing this disease phenomenon on the basis of clinical symptomatology (presence of acute onset movement disorders with concurrent hyperglycemia) without waiting for neuroimaging (1). On the contrary, 2% of patients may show radiological striatal lesions without any clinically manifested movement disorders (radiologically isolated DS) (2,26-28). There are also plenty of reports of clinical-radiological discordance or inconsistency in DS (1,2,14). Thus, striatopathy with clinically manifested movement disorders (symptomatic DS) can be subdivided into two groups, i.e., 1) concordant: bilateral involuntary movements with bilateral DS, or unilateral involuntary movements with contralateral DS (6); and 2) discordant: bilateral involuntary movements with unilateral DS or unilateral involuntary movements with bilateral or ipsilateral DS (10,29-31). This frequently observed clinical-radiological dissociation in DS is apparently contradictory with the classical concept of neurological localization of lesion-manifestation and requires further studies with newer neuroimaging modalities (1,10). Due to the controversial and ambiguous nature of the term "diabetic striatopathy" in literature (2), we had previously proposed a three-subset classification (10) (figure- 1).

 

Figure 1. Dubey’s classification schema of Diabetic Striatopathy (Adapted from: Dubey S, Biswas P, Ghosh R, Chatterjee S, Ray BK, Benito-León J. Neuroimaging of Diabetic Striatopathy: More Questions than Answers. Eur Neurol. 2022;85:371-6.)

Figure 2. Right striatal hyperintensity on T1 weighted MRI in a 56-yeald-old lady with previously undiagnosed diabetes presented with left hemichorea-hemiballism persisting for 1 week. Blood glucose was 453 mg/dl. Movement disorders abated with management of hyperglycemia with insulin therapy alone.

Figure 3. Left striatal hypodensity on non-contrast CT scan in a 68-year-old gentleman with diabetes presented with right hemichorea. Blood glucose was 356 mg/dl and HbA1c was 15.2%. Movement disorder was partially improved with glycemic control and needed haloperidol for complete recovery.

 

TREATMENT AND PROGNOSIS

 

Intensive management of hyperglycemia with insulin remains the pivotal measure to treat movement disorders associated with hyperglycemia (1,2). Some authors have speculated worsening of involuntary movements on aggressive lowering of blood glucose (analogous to diabetic retinopathy) (32-35), but this needs clarification by further reports. According to past studies, from one-fourth to almost half of the patients recover with insulin therapy alone (1,2,16,17) with a higher recovery rate in ketotic hyperglycemia cases (21). Additional therapies such as haloperidol, tetrabenazine, risperidone, tiapride (ballism and chorea), levodopa (parkinsonism), trihexyphenidyl, clonazepam (dystonia), pramipexole (restless leg syndrome), propranolol (tremor), carbamazepine (hemifacial spasm) etc. have been used with varying success rates (1,2). Whether the requirement of additional drugs may be attributed to late presentation or diagnostic delay needs further study (1,2,15,20). Surgical interventions such as pallidotomy, ventrolateral thalamotomy, transcranial magnetic stimulation, and globus pallidus internus deep brain stimulation had been tried for intractable symptoms (2,36-38).

 

In the study by Dubey et al (1), treatment of movement disorders was documented and followed up for at least three weeks. Patients who recovered fully from all involuntary movements within seven days were regarded as early responders, while the rest were taken as late responders. In that series the majority (47.5%) of the patients had early and complete resolution of symptoms, 28.8% responded late but had a complete reversal, while 23.7% cases recovered partially. Interestingly, in Chua et al’s analysis recovery was earlier among patients on glucose-therapy only (2 days) compared to those receiving additional anti-chorea medications (14 days), although median pre-treatment lag period was identical between those two groups (4 days) (2). Overall, the previous literature showed that recovery rate varied from 76.4% to 100% (2,14-21), which could be attributable to heterogeneity in the definition of recovery (clinical and/or neuroradiological) and duration of follow-up employed across different studies. During recovery, as expected, symptomatic improvement precedes abolition of neuroradiological stigmata. Minimum time period for radiological reversal noted in study by Chua et al were 10 days on CT and 60 days on MRI. On follow-up MRI scans progressive increase in striatal hyperintensity to reach its maximum limit was noted at around 90 days, whereas the mean periods of complete radiological reversal were around 60 and 180 days on CT and MRI, respectively. The median duration of discernible changes on CT and MRI were 24 and 120 days respectively (2). However, it is not at all uncommon to come across cases demonstrating persisting striatal anomalies on follow-up neuroimaging for months irrespective of symptomatic recovery (2,3,39). Currently there is paucity of studies which longitudinally evaluate the evolution of radiological changes over the course of disease process.

 

Despite having limited data regarding long-term follow-up, nearly 20% cases of DS clinically recurred even after initial resolution of striatal anomalies., which underscored the importance of periodic neuroradiological surveillance even after initial recovery. Recurrence rate did not differ across different treatment modalities (i.e., with or without additional use of anti-chorea medications) employed (2).

 

CONCLUSION

 

Acute onset or de novo movement disorder is one of the important neurological complications of DM, most prevalent but not limited to Asian population. Unfortunately, it is still less well-recognized among physicians, diabetologists, and endocrinologists leading to its diagnostic delay and probably poorer prognosis. Although DS and other movement disorders are generally complications of poorly controlled long-standing type 2 diabetes in the non-ketotic hyperglycemia state among elderly, it may be the first presentation of diabetes. Hence, clinicians must be aware of this entity so that crucial time is not wasted and readily available glucose measurement are ordered when dealing with such patients irrespective of their past glycemic status. Exact pathophysiological mechanisms, genetic basis, radiological correlates, and the explanation for the seemingly discordant clinical-radiological picture in hyperglycemia-induced movement disorders remain elusive. Much work needs to be done to determine the optimal management and prognostic indicators of this emerging disease entity.

 

ACKNOWLEDGMENTS

 

Informed consent was obtained from all patients whose videos are included in this chapter.

 

REFERENCES

 

  1. Dubey S, Chatterjee S, Ghosh R, Louis ED, Hazra A, Sengupta S, et al. Acute onset movement disorders in diabetes mellitus: A clinical series of 59 patients. Eur J Neurol. 2022;29:2241-8.
  2. Chua CB, Sun CK, Hsu CW, Tai YC, Liang CY, Tsai IT. "Diabetic striatopathy": clinical presentations, controversy, pathogenesis, treatments, and outcomes. Sci Rep. 2020;10:1594.
  3. Chatterjee S, Ghosh R, Ojha UK, Diksha, Biswas P, Benito-León J, et al. Recurrent facial focal seizure with chronic striatopathy and caudate atrophy- a double whammy in an elderly woman with diabetes mellitus. Neurohospitalist. 2022;12:147-50.
  4. Chatterjee S, Ghosh R, Kumari R, Ojha UK, Benito-León J, Dubey S. Faciobrachial myoclonus as the presenting manifestation of diabetic keto-acidosis. Tremor Other Hyperkinet Mov (N Y). 2021;11:9.
  5. Ghosh R, Roy D, Chatterjee S, Dubey S, Swaika BC, Mandal A, et al. Hemifacial spasm as the presenting manifestation of type 3c diabetes mellitus. Tremor Other Hyperkinet Mov (N Y). 2021;11:14.
  6. Ghosh R, Dubey S, Roy D, Ray A, Pandit A, Ray BK, et al. Choreo-ballistic movements heralding COVID-19 induced diabetic ketoacidosis. Diabetes Metab Syndr. 2021;15:913-7.
  7. Dubey S, Chatterjee S, Mukherjee D, Ghosh R, Sengupta S, Lahiri D, et al. “Dancing belly” in an old diabetic lady. J Family Med Prim Care. 2020;9:2580-2.
  8. Jagota P, Bhidayasiri R, Lang AE. Movement disorders in patients with diabetes mellitus. J Neurol Sci. 2012;314:5-11.
  9. Chakraborty PP, Ray S, Bhattacharjee R, Ghosh S, Mukhopadhyay P, Mukhopadhyay S, et al. First Presentation of Diabetes as Diabetic Ketoacidosis in a Case of Friedreich's Ataxia. Clin Diabetes. 2015;33:84-6.
  10. Dubey S, Biswas P, Ghosh R, Chatterjee S, Ray BK, Benito-León J. Neuroimaging of Diabetic Striatopathy: More Questions than Answers. Eur Neurol. 2022;85:371-6.
  11. Shafran I, Greenberg G, Grossman E, Leibowitz A. Diabetic striatopathy- Does it exist in non-Asian subjects? Eur J Intern Med. 2016;35:51-4.
  12. Ryan C, Ahlskog JE, Savica R. Hyperglycemic chorea/ballism ascertained over 15 years at a referral medical center. Parkinsonism Relat Disord. 2018;48:97-100.
  13. Ottaviani S, Arecco A, Boschetti M, Ottaviani E, Renzetti P, Marinelli L. Prevalence of diabetic striatopathy and predictive role of glycated hemoglobin level. Neurol Sci. 2022;43:6059-65.
  14. Gómez-Ochoa SA, Espín-Chico BB, Pinilla-Monsalve GD, Kaas BM, Téllez-Mosquera LE. Clinical and neuroimaging spectrum of hyperglycemia-associated chorea-ballism: systematic review and exploratory analysis of case reports. Funct Neurol. 2018;33:175-87.
  15. Cosentino C, Torres L, Núñez Y, Suárez R, Vélez M, Flores M. Hemichorea/hemiballism associated with hyperglycemia: report of 20 cases. Tremor other hyperkinet mov (N Y). 2016;6:402.
  16. Guo Y, Miao YW, Ji XF, Li M, Liu X, Sun XP. Hemichorea associated with nonketotic hyperglycemia: clinical and neuroimaging features in 12 patients. Eur Neurol. 2014;71:299-304.
  17. Lee SH, Shin JA, Kim JH. Chorea-ballism associated with nonketotic hyperglycaemia or diabetic ketoacidosis: characteristics of 25 patients in Korea. Diabetes Res Clin Pract. 2011;93:e80-3.
  18. Oh SH, Lee KY, Im JH, Lee MS. Chorea associated with nonketotic hyperglycemia and hyperintensity basal ganglia lesion on T1-weighted brain MRI study: a meta-analysis of 53 cases including four present cases. J Neurol Sci. 2002;200:57-62.
  19. Lee BC, Hwang SH, Chang GY. Hemiballismus-hemichorea in older diabetic women: a clinical syndrome with MRI correlation. Neurology. 1999;52:646-8.
  20. Prabhu S, Ramya N. Movement disorders and diabetes: a study of South India. Internet J Neurol. 2012;14:1-5.
  21. Chen C, Zheng H, Yang L, Hu Z. Chorea-ballism associated with ketotic hyperglycemia. Neurol Sci. 2014;35:1851-5.
  22. Paiboonpol S. Epilepsia partialis continua as a manifestation of hyperglycemia. J Med Assoc Thai. 2005;88:759-62.
  23. Shrivastava V, Burji NP, Basumatary LJ, Das M, Goswami M, Kayal AK. Etiological profile of epilepsia partialis continua among adults in a tertiary care hospital. Neurol India. 2013;61:156-60.
  24. Chu K, Kang DW, Kim DE, Park SH, Roh JK. Diffusion-weighted and gradient echo magnetic resonance findings of hemichoreahemiballismus associated with diabetic hyperglycemia: a hyperviscosity syndrome? Arch Neurol. 2002;59:448–52.
  25. Chen C, Zheng H, Yang L, Hu Z. Chorea-ballism associated with ketotic hyperglycemia. Neurol Sci. 2014;35:1851-5.
  26. Choi JY, Park JM, Kim KH, Park JS, Shin DW, Kim H. Radiographic basal ganglia abnormalities secondary to nonketotic hyperglycemia with unusual clinical features. Clin Exp Emerg Med. 2016;3:252-5.
  27. Hsu JL, Wang HC, Hsu WC. Hyperglycemia-induced unilateral basal ganglion lesions with and without hemichorea. A PET study. J Neurol. 2004;251:1486-90.
  28. Hansford BG, Albert D, Yang E. Classic neuroimaging findings of nonketotic hyperglycemia on computed tomography and magnetic resonance imaging with absence of typical movement disorder symptoms (hemichorea-hemiballism). J Radiol Case Rep. 2013;7:1-9.
  29. Danve A, Kulkarni S, Bhoite G. Non-ketotic hyperglycemia unmasks hemichorea. J Community Hosp Intern Med Perspect. 2015;5:27825.
  30. Lin JJ. Ipsilateral putamen hyperintensity on T1-weighted MRI in non-ketotic hyperglycemia with hemiballism-hemichorea: a case report. Parkinsonism Relat Disord. 2001;7:319-21.
  31. Fong SL, Tan AH, Lau KF, Ramli N, Lim SY. Hyperglycemia-associated hemichorea-hemiballismus with predominant ipsilateral putaminal abnormality on neuroimaging. J Mov Disord. 2019;12:187-9.
  32. Lim KX, Khaing Zin T, Yu Z, Peh WM. Delayed Presentation of Hemichorea in Diabetic Striatopathy. Cureus. 2022;14:e30219.
  33. Lizarraga KJ, Adams D, Post MJD, Skyler J, Singer C. Neurovascular uncoupling after rapid glycemic control as a trigger of the diabetic-uremic striatopallidal syndrome. Parkinsonism Relat Disord. 2017;39:89-90.
  34. Ando Y, Kadoya M, Kodera T. Involuntary Movements During Treatment for Hyperglycemia. AACE Clin Case Rep. 2022;9:21-2.
  35. Cho HS, Hong CT, Chan L. Hemichorea after hyperglycemia correction: A case report and a short review of hyperglycemia-related hemichorea at the euglycemic state. Medicine (Baltimore). 2018;97:e0076.
  36. Son BC, Choi JG, Ko HC. Globus Pallidus Internus Deep Brain Stimulation for Disabling Diabetic Hemiballism/Hemichorea. Case Rep Neurol Med. 2017;2017:2165905.
  37. De Vloo P, Breen DP, Milosevic L, Lee DJ, Dallapiazza RF, Hutchison WD, et al. Successful pallidotomy for post-hyperglycemic hemichorea-ballism. Parkinsonism Relat Disord. 2019;61:228-30.
  38. Kaseda Y, Yamawaki T, Ikeda J, Hayata M, Dohi E, Ohshita T, et al. Amelioration of persistent, non-ketotic hyperglycemia-induced hemichorea by repetitive transcranial magnetic stimulation. Case Rep Neurol. 2013;5:68-73.
  39. Lucassen EB, Delfyett WT, Stahl MC. Persistent Hemichorea and Caudate Atrophy in Untreated Diabetic Striatopathy: A Case Report. Case Rep Neurol. 2017;9:299-303.

 

Hypoglycemia During Therapy of Diabetes

ABSTRACT

 

The major cause of hypoglycemia is iatrogenic. Treatment with an insulin secretagogue, including sulfonylureas or glinides, or insulin, particularly when coupled with compromised defenses against the resulting falling plasma glucoseconcentrations, is the limiting factor in the glycemic management of diabetes. It causes recurrent morbidity in most peoplewith type 1 diabetes mellitus (T1DM) and many with advanced type 2 diabetes mellitus (T2DM) and is sometimes fatal. Low blood glucose also impairs physiological and behavioral defenses against subsequent hypoglycemia, further increasing the risk of hypoglycemia and its complications including adverse cardiovascular effects. Strategies to reduce hypoglycemia are based on the individual’s age, regimen, and comorbidities. A patient-centered approach, newer insulin analogues, novel insulin delivery devices, and continuous glucose monitoring help reduce the risk of hypoglycemia and optimize glycemia.

 

THE CLINICAL PROBLEM OF HYPOGLYCEMIA IN DIABETES 

 

The problem of iatrogenic hypoglycemia in diabetes has been reviewed in detail (1–6).

 

Glycemic Control

 

In the context of comprehensive treatment, including weight, blood pressure, and blood lipid control among other measures, normoglycemia makes a difference for people with diabetes. Improved glycemic control reduces microvascular complications (retinopathy, nephropathy, and neuropathy) in both type 1 diabetes mellitus (T1DM) (7) and type 2 diabetes mellitus (T2DM) (8,9). Follow-up of patients with T1DM (10) and T2DM (11) suggests that an improved earlier period of glycemic control may also reduce subsequent macrovascular complications. Thus, safe and long-term maintenance of physiologic normoglycemia is in the best interest of people with diabetes.

 

The Limiting Factor

 

Iatrogenic hypoglycemia, fundamentally but not exclusively usually results from treatment with an insulin secretagogue or insulin either alone or in combination with other glucose lowering medications, and is the major limitingfactor in the goal of near normoglycemia in the management of diabetes (1). Iatrogenic hypoglycemia causes recurrent morbidity in most people with T1DM and many with advanced T2DM and is sometimes fatal (4). It impairs defensesagainst subsequent falling plasma glucose concentrations and results in a vicious cycle of recurrent hypoglycemia. It generally precludes maintenance of euglycemia over a lifetime of diabetes and, thus, full realization of the benefits of glycemic control.

 

Type 1 and Type 2 Diabetes

 

Iatrogenic hypoglycemia commonly occurs in the overwhelming majority of people with T1DM who must, of course, be treated with insulin. Most have untold numbers of episodes of asymptomatic hypoglycemia. These are not benign sincethey impair defenses against subsequent hypoglycemia (1). Individuals with T1DM suffer an average of two episodes of symptomatic hypoglycemia per week – thousands of such episodes over a lifetime of diabetes – and about one episode of disabling severe (i.e., requiring assistance) hypoglycemia per year. Hypoglycemia causes brain fuel deprivation that, if unchecked, results in functional brain failure that is typically corrected after the plasma glucose concentration is raised (12). Rarely, if low blood glucose is profound and prolonged, it can result in brain death (12). Hypoglycemia may lead to cardiac arrhythmias, especially in patients with preexisting cardiac abnormalities (13,14). Additionally, hypoglycemia has been demonstrated to be pro-coagulant and pro-atherothrombotic (15,16). Furthermore, severe hypoglycemia has beenassociated with increased risk of death extending many months and up to one year after the sentinel episode (17). Of concern, roughly from 2 to 10 percent of deaths of people with diabetes were the result of hypoglycemia (4,5,14,18,19).Regardless of the actual rate, the fact that there is an iatrogenic hypoglycemia mortality rate is alarming.

 

Overall, for a given individual, iatrogenic hypoglycemia is less frequent in T2DM (1,20,21). However, due to the greatly increased numbers of individuals with T2DM, the prevalence of hypoglycemic episodes is actually greater than in T1DM. Drugs that can cause endogenous or exogenous (insulin) hyperinsulinemia unregulated by glucose can cause hypoglycemia. On the other hand, insulin sensitizers (metformin or a thiazolidinedione), α-glucosidase inhibitors, sodium glucose cotransporter 2 inhibitors, and drugs such as dipeptidyl peptidase-IV inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) that cause glucose-dependent hyperinsulinemia should not, and probably do not, causehypoglycemia. They do, however, increase the risk of hypoglycemia if used with an insulin secretagogue or with insulin. Even during treatment of T2DM with insulin, hypoglycemia event rates are about one-third of those in T1DM overall (20).However, for reasons discussed shortly (see Glucose Counterregulatory Physiology and its Pathophysiology inDiabetes), the incidence of iatrogenic hypoglycemia increases over time, approaching that in T1DM, as people approach the insulin deficient end of the spectrum of T2DM (21). Because T2DM is roughly 20-fold more prevalent than T1DM and many, perhaps most, people with T2DM ultimately require treatment with insulin, most episodes of hypoglycemia, including those of severe hypoglycemia, occur in individuals with T2DM. Insulin secretagogue and insulin induced hypoglycemia can be fatal in T2DM although precise hypoglycemic mortality rates are as yet known. As many as 10% of patients with severe sulfonylurea-induced hypoglycemia die (22).

 

DEFINITION AND CLASSIFICATION OF HYPOGLYCEMIA

 

The American Diabetes Association and the International Hypoglycemia Study Group (Table 1) define clinicallysignificant hypoglycemia as a blood glucose <54 mg/dl (3.0 mmol/L) which is detected by the individual’s self-monitoring blood glucose (SMBG) as well as by continuous glucose monitoring ((CGM), glucose values of <54 mg/dl(3.0 mmol/L) for at least 20 min), or laboratory measurement of plasma glucose which is sufficiently low to indicate clinically significant hypoglycemia (23,24). Blood glucose ≤70 mg/dl (3.9 mmol/L) is considered a hypoglycemia alert value, which represents an important lower glucose cutoff value for treatment with fast-acting carbohydrates and doseadjustments of antidiabetic medications. Severe hypoglycemia is defined as a low glucose value with severe cognitiveimpairment that requires assistance from another person in order to achieve recovery (25). Relative hypoglycemia or pseudohypoglycemia represents an event during which the person with diabetes reports any of the typical symptoms of hypoglycemia and interprets those as indicative of hypoglycemia with a measured plasma glucose concentration >70 mg/dL (>3.9 mmol/L).

 

Table 1. Classification of Hypoglycemia in Diabetes (23,24)

Level

Glycemic criteria

 

Hypoglycemia alert value

≤70 mg/dl (3.9 mmol/L)

Sufficiently low for treatment with fast

(level 1)

 

acting carbohydrate and dose adjustment

 

 

of glucose lowering therapy

Clinically significant

hypoglycemia (level 2)

<54 mg/dl (3.0 mmol/L)

Sufficiently low to indicate serious, clinically

important hypoglycemia

Severe hypoglycemia (level 3)

No specific glucose threshold

Hypoglycemia associated with severe cognitive impairment requiring external assistance for recovery

 

COMPLICATIONS OF HYPOGLYCEMIA

 

Increased mortality has been observed in randomized controlled trials during more aggressive compared with less aggressive glucose-lowering therapy in patients with T2DM (26) and in patients with hypoglycemia in intensive care units (27). In addition, intensive glycemic control has not been shown to improve cardiovascular outcomes in patients with T2DM (28). The associations between increased hypoglycemia and increased morbidity and mortality during aggressive glycemic therapy in these and other (18,29,30)  trials have been thought to be multifactorial (31). A possible explanation is that aggressive reduction of blood glucose increases the risk of hypoglycemia. The latter can trigger sympathoadrenal activation with the release of catecholamines, cause abnormal cardiac repolarization, and lead to myocardial ischemia. Hypoglycemia-induced ECG changes include ST-segment depression, atrial and ventricular ectopic beats, P- and T-wave abnormalities, and QT-interval prolongation (32). Low blood glucose creates procoagulant and prothrombotic states and induces inflammation and oxidative stress (33,34).

 

The association of hypoglycemia with cognitive function appears to be more complicated. Among older individuals with type 2 diabetes, a history of severe hypoglycemia was associated with a greater risk of dementia (37). The ACCORD study reported that cognitive impairment at baseline and a continuing decline in cognitive function among individuals were associated with a greater risk for dementia following hypoglycemia (35). It should be noted however that in DCCT/EDIC, which involved much younger participants, no association of severe hypoglycemia and cognitive decline was found (25, 39).

 

Hypoglycemic episodes can create fear of subsequent hypoglycemia and negatively affect the quality of life in T1DM as well as T2DM (36). Some of the consequences may include anxiety, shortness of breath, palpitations, tremors, symptoms of depression, and reduced ability to function.

 

GLUCOSE COUNTERREGULATORY PHYSIOLOGY AND ITS PATHOPHYSIOLOGY IN DIABETES

 

Physiology

 

In nondiabetic individuals, there are a number of physiological defenses against falling plasma glucose concentrations. These include reductions in insulin secretion, which occur as glucose levels decline within the physiological range. This allows for increased hepatic (and renal) glucose production, and increments in glucagon and epinephrine secretion, which occur as glucose levels fall just below the physiological range and stimulate hepatic glucose production (1,2,37)(Figure 1). Increased epinephrine levels also normally mobilize gluconeogenic precursors from muscle and fat, stimulate renal glucose production, limit glucose utilization by muscle and fat, and limit insulin secretion (2). The behavioral defense against falling plasma glucose concentrations is carbohydrate ingestion prompted largely by the perception ofneurogenic (autonomic) symptoms (e.g., palpitations, tremor, and anxiety/arousal which are catecholamine-mediated or adrenergic and sweating, hunger, and paresthesias which are sympatho-adrenal mediated or cholinergic) (38,39) (Figure 1). These are largely sympathetic neural, rather than adrenomedullary, in origin (39). The extent to which mild neuroglycopenic symptoms such as altered mentation or psychomotor changes contribute to the patient’s recognition of hypoglycemia is unclear; awareness of hypoglycemia is largely prevented by pharmacological antagonism of neurogenicsymptoms (38). Severe neuroglycopenic symptoms include frank confusion, acute focal or central neurologic deficits, seizure and/or loss of consciousness. All of these defenses can be compromised in T1DM and advanced T2DM (1,40,41).

 

Pathophysiology

 

Episodes of therapeutic hyperinsulinemia, the result of glucose unregulated delivery of endogenous (insulin secretagoguetherapy) or exogenous (insulin therapy) insulin into the circulation, initiate the sequence that may, or may not, culminate in an episode of hypoglycemia (1). Absolute therapeutic insulin excess of sufficient magnitude can cause isolated episodes of hypoglycemia despite intact glucose counterregulatory defenses against hypoglycemia (Figure 2). But that isan uncommon event. Iatrogenic hypoglycemia is typically the result of the interplay of mild-moderate absolute therapeutic insulin excess, reduced glucose intake, exercise, increased insulin sensitivity, sleep, and existing or induced compromised physiological and behavioral defenses against falling plasma glucose concentrations in T1DM (1,40) and T2DM (1,41). In T1DM, because of β-cell failure, insulin levels do not decrease as glucose levels fall; the first physiological defense is lost. Furthermore, glucagon levels do not increase as glucose levels fall (42); the second physiological defense is lost. That, too, is possibly attributable to a β-cell signaling failure since a decrease in β-cell secretion, coupled with a low α-cell glucose concentration, normally signals α-cell glucagon secretion (3,43,44). Finally, the increase in epinephrine levels as glucose levels fall is also attenuated ((1,41); and thus, the three major physiological defenses are compromised.

 

Figure 1. Physiological and Behavioral Defenses Against Hypoglycemia in Humans. ACH, acetylcholine; NE, norepinephrine; PNS, parasympathetic nervous system; SNS, sympathetic nervous system. From reference (45).

 

Although it is often caused by recent antecedent hypoglycemia (40,46) or by prior exercise (47) or sleep (48–50), the mechanism of the attenuated sympathoadrenal response to falling glucose levels is unknown (3). Nonetheless, theattenuated epinephrine response is a marker of an attenuated sympathetic neural response (39) and the latter largely results in the reduction of the symptoms of hypoglycemia causing hypoglycemia unawareness (or impaired awareness of hypoglycemia) and thus loss of the behavioral defense, i.e., carbohydrate ingestion. In the setting of therapeutichyperinsulinemia, falling plasma glucose concentrations, absent decrements in insulin, absent increments in glucagon, and attenuated increases in epinephrine cause the clinical syndrome of defective glucose counter-regulation (1,40), whichis associated with a 25-fold (51) or greater (52) increased risk of iatrogenic hypoglycemia. The attenuated sympathoadrenal, particularly the attenuated sympathetic neural response, causes the clinical syndrome of hypoglycemiaunawareness (1) which is associated with a 6-fold increased risk of iatrogenic hypoglycemia (53).

 

The pathophysiology of glucose counter-regulation is the same in T1DM and T2DM albeit with different time courses. β-cell failure, and therefore loss of the insulin and glucagon responses to falling plasma glucose concentrations, develops early in T1DM but more gradually in T2DM. Thus, iatrogenic hypoglycemia, becomes a common problem early in T1DMand later in T2DM.

 

The concept of hypoglycemia-associated autonomic failure (HAAF) in diabetes (1,3,5,40,41) (Figure 2) posits that recentantecedent hypoglycemia, as well as prior moderate exercise or sleep, causes both defective glucose counter-regulation(by reducing increments in epinephrine in the setting of absent decrements in insulin and absent increments in glucagon during subsequent hypoglycemia) and hypoglycemia unawareness (by reducing sympathoadrenal and resulting neurogenic symptom responses during subsequent hypoglycemia) and, therefore, a vicious cycle of recurrent hypoglycemia. Supporting this concept is the finding, that as little as 2-3 weeks of scrupulous avoidance of hypoglycemia reverses hypoglycemia unawareness and improves the attenuated epinephrine component of defective glucose counter-regulation in most affected patients. (54–57).

 

The mechanism(s) of the attenuated sympathoadrenal response to falling glucose levels, the key feature of HAAF, is not known (3). It must involve the central nervous system or the afferent or efferent components of the sympathoadrenal system. Theories include increased blood-to-brain transport of a metabolic fuel, effects of a systemic mediator such as cortisol on the brain, altered hypothalamic mechanisms, and activation of an inhibitory cerebral network mediated through the thalamus (3).

 

Figure 2. Schematic Diagram of HAAF in Diabetes. From reference (45).

 

RISK FACTORS FOR HYPOGLYCEMIA IN DIABETES

 

Conventional Risk Factors

 

The conventional risk factors are based on the premise that relative to low rates of glucose delivery into the circulation, high rates of glucose efflux out of the circulation, or both, or absolute therapeutic hyperinsulinemia is the soledeterminant of risk (1). They include (but are not limited to):

 

  1. Insulin (or insulin secretagogue) doses are excessive, ill-timed, or of the wrong type.
  2. Exogenous glucose delivery is decreased (as following missed meals and during the overnight fast, with gastroparesis or celiac disease).
  3. Glucose utilization and sensitivity to insulin are increased (as during and shortly after exercise, in the middle of the night, following weight loss, or improved glycemic control).
  4. Endogenous glucose production is decreased (as following alcohol ingestion or in liver failure).
  5. Insulin clearance is decreased (as in renal failure).
  6. Classical diabetic autonomic

 

Patients with diabetes and their caregivers must consider each of these risk factors carefully whenever hypoglycemia is a problem (58).

 

Risk Factors Indicative of Hypoglycemia-Associated Autonomic Failure (HAAF)

 

These risk factors stem directly from the pathophysiology of glucose counter-regulation and the concept of HAAF in diabetes (1,40,41). They include:

 

  1. The degree of absolute endogenous insulin deficiency. This determines the extent to which insulin levels will notdecrease and glucagon levels will not increase as plasma glucose concentrations fall in response to therapeutic It is in part a function of the duration of diabetes.
  2. A history of severe hypoglycemia, hypoglycemia unawareness, or both as well as recent antecedent hypoglycemia, prior exercise or sleep.
  3. Aggressive glycemic therapy per se (lower A1C levels, lower glycemic goals). Studies with a control group treated to higher mean glycemia consistently document higher rates of hypoglycemia in individuals treated to lower mean glycemia (e.g. (4)). Mean glycemia is a risk factor for hypoglycemia. However, severe hypoglycemia can occur in individuals with any A1C level, and the fact that mean glycemia is a risk factor does not mean that one cannot both lower mean glycemia and reduce the risk of hypoglycemia in individual patients (6).

 

PREVENTION OF HYPOGLYCEMIA IN DIABETES

 

The prevention of hypoglycemia can be viewed as a process with four steps (1,6). The first step is acknowledging the problem; the second - considering the conventional risk factors in diabetes; the third – considering the risk factors indicative of HAAF in diabetes; and the fourth - application of the relevant principles of intensive glycemic therapy of diabetes.

 

Acknowledge the Problem

 

The issue of hypoglycemia should be addressed at every contact with a patient treated with an insulin secretagogue or with insulin (6). In addition to the patient’s comments and review of the individual’s SMBG data (as well as any CGM data) we find it especially helpful to inquire what is the glucose level when each patient can detect hypoglycemia andwhat are the symptoms and signs at various hypoglycemic levels. It is also often helpful to question close associates of the patient since they may have observed clues to episodes of hypoglycemia. Patient concerns about the reality, or even the possibility, of hypoglycemia can be a barrier to glycemic control (59,60). Their concerns need to be discussed and addressed if hypoglycemia is a real or perceived problem.

 

Consider the Conventional Risk Factors for Hypoglycemia in Diabetes

 

Each of the risk factors that result in relative or absolute therapeutic hyperinsulinemia, as just discussed, should be considered carefully in any patient with iatrogenic hypoglycemia. Those include the dose, timing, and type of the insulinsecretagogue or insulin preparations(s) used, and conditions in which exogenous glucose delivery or endogenous glucose production is decreased, glucose utilization or insulin sensitivity is increased or insulin clearance is decreased.

 

Consider the Risk Factors Indicative of HAAF in Diabetes

 

As detailed earlier, the risk factors indicative of HAAF include the degree of absolute endogenous insulin deficiency, ahistory of severe hypoglycemia, impaired awareness of hypoglycemia, or both as well as any relationship between iatrogenic hypoglycemia and recent antecedent hypoglycemia, prior exercise or sleep, and lower glycemic goals. A history of severe hypoglycemia is a clinical red flag. Without a fundamental adjustment of the treatment regimen, the likelihood of another episode is high (7,61).

 

Apply the Relevant Principles of Intensive Glycemic Therapy

 

The principles of intensive glycemic therapy relevant to minimizing the risk of iatrogenic hypoglycemia in diabetes include drug selection, selective application of diabetes treatment technologies, individualized glycemic goals, structured patient education, and short-term scrupulous avoidance of hypoglycemia (6). Based on the premise that the risk of hypoglycemia is modifiable, the International Hypoglycemia Study Group recommended that people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat self- monitored plasma glucose (SMPG) <70 mg/dL (<3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia, and should regularly be queried about hypoglycemia, including the glucose level at which symptoms develop (6).

 

Drug selection relevant to minimizing the risk of hypoglycemia includes avoidance, if possible, of sulfonylureas or glinides, the use of more physiological insulin regimens (62), and the use of long-acting or even ultra-long-acting daily basal insulin analogues and rapid-acting prandial insulin analogues in lieu of human insulins (63–66). Insulin analogues reduce the frequency of at least nocturnal hypoglycemia (63–65) including severe nocturnal hypoglycemia (65) compared to human insulins. In insulin-requiring T2DM, basal insulins are associated with less hypoglycemia than prandial insulin regimens. Furthermore, the combination of a long-acting basal insulin with a glucose-lowering drug with low hypoglycemic potential (e.g., a GLP-1 receptor agonist) may result in less hypoglycemia than with the use of basal-bolus insulin therapy (67).

 

Relevant diabetes treatment technologies include continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), and combinations of CSII and CGM. Although earlier meta-analyses disclosed little (68) or no (69)advantage of CSII, recent evidence suggest that CSII treatment is superior in achieving glucose control compared to multiple daily injections (70,71). CGM devices alone have been shown to improve glycemic control and decrease duration of hypoglycemia in patients with diabetes mellitus (72,73). As their accuracy is continuously improving, several CGM systems have been approved by the FDA, and other regulatory authorities to even replace point of care blood glucose testing (74,75). Real-time CGM systems have also been found to improve hypoglycemia awareness, without achange in A1C, in a small group of patients with T1DM (76). A favorable experience with CSII has also been reported (77,78). The combination of CSII and real-time CGM – sensor augmented pump therapy, particularly that including an insulin pump programmed to stop insulin infusion for up to two hours when CGM values fall to a selected glucose level (“low glucose suspend”) – has been reported to reduce the frequency of severe hypoglycemia in T1DM (79–81). Recentinnovations have included cessation of insulin delivery during hypoglycemia. Several promising studies have investigated approaches for leading closed-loop insulin (or insulin and glucagon) replacement. The development of automated closed-loop insulin pumps represents an area of ongoing research and fully closed-loop insulin (82) or insulin and glucagon replacement (83) and pancreatic islet transplantation (84) will undoubtedly eliminate hypoglycemia andimprove overall glycemic control. A hybrid-not fully automated -system (as only basal insulin is automatically adjusted) has received approval by the FDA (85).

 

Special circumstances relevant to drug selection and treatment technologies in the prevention of hypoglycemia in diabetes include exercise, the overnight period, the elderly, drivers, and pregnancy. Especially in insulin-treated patients’ hypoglycemia can occur during or shortly after exercise (86) or late after exercise (87,88). Measures to avoid early-onset exercise hypoglycemia include interspersing episodes of intense exercise (which tends to raise plasma glucose concentrations), adding carbohydrate ingestion, and reducing insulin doses (89). A consistent observation since the DCCT (7) is that more than half of episodes of hypoglycemia, including severe hypoglycemia, occur during the night. That is typically the longest interval between meals and between SMPG and includes the time of maximal sensitivity to insulin. In addition to the use of insulin analogues, sensor augmented pump therapy or closed-loop insulin or insulin and glucagon replacement, all discussed earlier, approaches to the prevention of nocturnal hypoglycemia include attempts to produce sustained delivery of exogenous carbohydrate or sustained endogenous glucose production (90). With respect to the former approach, a conventional bedtime snack or bedtime administration of uncooked cornstarch have not been found to be consistently effective (90). With respect to the latter approach an experimental treatment is bedtime administration of a β2-adrenergic agonist such as terbutaline (90–92). In addition to HAAF, comorbidities including renal insufficiency, polypharmacy, and impaired cognition are more relevant to the development of hypoglycemia in older individuals (93). Drivers with diabetes and a history of recurrent hypoglycemia-related driving mishaps have been found to have greater driving simulator impairments (94). Finally, up to 45% of pregnant women with type 1 diabetes experience severe hypoglycemia especially in the first trimester (95).

 

Individualized Glycemic Goal

 

Glycemic goals should be individualized in patients with diabetes (4,96). The selection of a glycemic goal in a person with diabetes is a trade-off between the benefits of glycemic control – partial prevention or delay of microvascularcomplications – and the risk of recurrent morbidity, and potential mortality, of hypoglycemia (4). A reasonable individualized glycemic goal is the lowest A1C that does not cause severe hypoglycemia and preserves awareness of hypoglycemia, preferably with little or no symptomatic or even asymptomatic hypoglycemia, at a given stage in the evolution of the individual’s diabetes (4). Thus, the glycemic goal should be linked not only to the level of glycemic control (i.e., the A1C) but also to the risk of hypoglycemia, specifically the drugs used (a sulfonylurea, a glinide, or insulin), the degree of endogenous insulin deficiency, and the anticipated benefit of the targeted level of glycemic control. A nondiabetic A1C would be reasonable in a patient with early T2DM treated effectively with lifestyle changes and/or drugsthat do not cause hypoglycemia. For the majority of non-pregnant adults, a reasonable goal for an A1C is <7% (53 mmol/mol). For selected individuals with long life expectancy, without significant comorbidities (especially cardiovascular disease), stringent A1c goals (<6.5% (48 mmol/mol)) should be targeted, if this can be achieved without significant hypoglycemia (23). For children and adolescents, an A1C of <7.5% (58 mmol/mol) should be the goal, although a lower target (<7% (53 mmol/mol)) should be reasonable if it can be achieved without excessive hypoglycemia (97). Howevermuch higher levels of A1C (7.5%-8.0% (58-64 mmol/mol)) may be appropriate in elderly patients where hypoglycemia may be harmful. Even higher targets (A1C<8.5% (69 mmol/mol)) may be appropriate in individuals with very limited life expectancy (93).

 

Of note, it needs to be underscored that severe hypoglycemia can and does occur at A1C levels between 8-10% (64-86 mmol/mol) or higher in either T1DM or T2DM. Thus, severe hypoglycemia is not just a consequence of “low or near normal” A1C values. Of concern are recent data that severe hypoglycemia occurring in T2DM individuals >60 years withelevated A1C may have greater serious adverse events and increased mortality compared to individuals with improved glycemic control and lower A1C values.

 

Thus, attempts to improve glycemic control with insulin in T2DM individuals that have been resistant or proven challenging to strategies to lower glucose levels may be at greater risk for severe hypoglycemia and associated serious adverse events (18,26,29,30).

 

Structured Patient Education

 

The core approach, applicable to virtually all patients with diabetes treated with a sulfonylurea, a glinide, or insulin in whom hypoglycemia becomes a problem, is thorough, structured patient education (often re- education) that teaches the patient how and when their drugs can cause hypoglycemia, how to adjust their medications, meal plans, and exercise to optimize glycemic control and minimize hypoglycemia, and how to recognize and treat hypoglycemia (6). Based conceptually on earlier inpatient education programs (98), there is increasing evidence that outpatient structured education programs decrease hypoglycemia, often with a decrease in A1C (99–103). For example, a structured patient education program in flexible insulin therapy led to a reduction of impaired awareness of hypoglycemia (45% of those with impaired awareness initially were aware at one year) and a reduction in severe hypoglycemia (from 1.9 to 0.6 episodes per patient-year and a small but significant decrease in A1C in patients with type 1 diabetes (101). Patient education needs to cover a broad range of information and skill training and often include a motivational element (6).

 

Short-Term Scrupulous Avoidance of Hypoglycemia

 

In patients with impaired awareness of hypoglycemia structured patient education should be combined with 2- to 3-weeks of scrupulous avoidance of hypoglycemia – which may require acceptance of somewhat higher glycemic goals in the short-term – since that can be expected to restore awareness of hypoglycemia in most affected patients (54–57).

 

In summary, people with diabetes treated with a sulfonylurea, a glinide, or insulin should be educated about hypoglycemia, should treat SMPG (or CGM) glucose levels <70 mg/dL (<3.9 mmol/L) to avoid progression to clinical iatrogenic hypoglycemia, and should regularly be queried about hypoglycemia, including the SMPG (or CGM) level at which symptoms develop (6).

 

TREATMENT OF HYPOGLYCEMIA IN DIABETES

 

Most episodes of asymptomatic hypoglycemia, detected by routine SMBG or CGM, or of mild- moderate symptomatic hypoglycemia are effectively self-treated by ingestion of glucose tablets or carbohydrate containing juice, soft drinks, candy, other snacks, or a meal (1,104). A reasonable dose is 20 g of carbohydrate (104). The dose can be repeated in 15 to 20 minutes, if necessary. Since the glycemic response to oral glucose is transient – roughly two hours in the setting of ongoing hyperinsulinemia (104) – the ingestion of a more substantial snack or meal shortly after the plasma glucose level is raised is generally advisable.

 

When a hypoglycemic patient is unwilling (because of neuroglycopenia) or unable to take carbohydrate orally, parenteral therapy is required. That is often glucagon injected subcutaneously or intramuscularly by an associate of the patient whohas been trained to recognize and treat severe hypoglycemia. The usual glucagon dose is 1.0 mg; that can be life-saving although it causes substantial, albeit transient, hyperglycemia (104) and can cause nausea, and even vomiting. Smaller doses (e.g., 150 mcg), repeated, if necessary, have been found to be effective without side effects in adolescents (105). Recent advances include 1) approval of nasal glucagon and of a device to deliver glucagon intranasally (106), that would obviate the need for parenteral injection and 2) a glucagon that is stable in solution (107), that would obviate the need to reconstitute the drug prior to administration. Because it also stimulates insulin secretion, glucagon might be less effectivein patients with early T2DM. In a medical setting intravenous glucose, 25 g initially, is the standard parenteral therapy(1). The glycemic response to intravenous glucose is, of course, transient. A subsequent glucose infusion is generally needed, and food should be provided as soon as the patient is able to ingest it safely.

 

The duration of a hypoglycemic episode is a function of its cause. While that caused by a short-acting insulin secretagogue or a rapid-acting insulin can be measured in hours, that caused by a long-acting insulin secretagogue or insulin can last for days requiring hospitalization for prolonged therapy. The duration of secretagogue-induced hypoglycemia can be shortened by administration of octreotide (108,109).

 

In the UK, the Joint British Diabetes Societies for Inpatient Care have produced guidance on the management of hypoglycemia for hospital inpatients, although these can be used in the community setting as necessary (110).

 

ACKNOWLEDGMENTS AND DISCLOSURES

 

Hugh A. Davis has no disclosures to report.

 

Elias K. Spanakis has received research support (CGM supplies) from DEXCOM (San Diego, CA) for the conduction of inpatient CGM clinical studies.

 

Maka Siamashvili has no disclosures to report.

 

Stephen N. Davis- This work has received support from the NIH, NHLBI, NIDDK, JDRF and VA.

 

 

REFERENCES

 

  1. Cryer PE. The barrier of hypoglycemia in diabetes. Vol. 57, Diabetes. 2008.
  2. Cryer PE. The Prevention and Correction of Hypoglycemia. In: Comprehensive Physiology. 2001.
  3. Cryer PE. Mechanisms of Hypoglycemia-Associated Autonomic Failure in Diabetes. New England Journal of Medicine. 2013;369(4).
  4. Cryer PE. Glycemic goals in diabetes: Trade-off between glycemic control and iatrogenic hypoglycemia. Vol. 63, Diabetes. 2014.
  5. Cryer PE. Hypoglycemia-associated autonomic failure in diabetes: Maladaptive, adaptive, or both? Vol. 64, Diabetes. 2015.
  6. Cryer PE. Minimizing hypoglycemia in diabetes. Diabetes Care. 2015;38(8).
  7. Shamoon H, others. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. The Diabetes Control and Complications Trial Research Group. N Engl J Med. 1993;329.
  8. Turner R. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352(9131).
  9. Turner R. Effect of intensive blood-glucose control with metformin on complications in overweight patients with type 2 diabetes (UKPDS 34). Lancet. 1998;352(9131).
  10. Intensive Diabetes Treatment and Cardiovascular Disease in Patients with Type 1 Diabetes. New England Journal of Medicine. 2005;353(25).
  11. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HAW. 10-Year Follow-up of Intensive Glucose Control in Type 2 Diabetes. New England Journal of Medicine. 2008;359(15).
  12. Cryer PE. Hypoglycemia, functional brain failure, and brain death. Vol. 117, Journal of Clinical Investigation. 2007.
  13. Stahn A, Pistrosch F, Ganz X, Teige M, Koehler C, Bornstein S, et al. Relationship between hypoglycemic episodes and ventricular arrhythmias in patients with type 2 diabetes and cardiovascular diseases: Silent hypoglycemias and silent arrhythmias. Diabetes Care. 2014;37(2).
  14. Chow E, Bernjak A, Williams S, Fawdry RA, Hibbert S, Freeman J, et al. Risk of cardiac arrhythmias during hypoglycemia in patients with type 2 diabetes and cardiovascular risk. Diabetes. 2014;63(5).
  15. Frier BM, Schernthaner G, Heller SR. Hypoglycemia and cardiovascular risks. Vol. 34, Diabetes Care. 2011.
  16. Jialal I, Dhindsa S. Hypoglycemia and the predisposition to cardiovascular disease: Is the pro-inflammatory-pro-coagulant diathesis a plausible explanation? Vol. 251, Atherosclerosis. 2016.
  17. Lee AK, Warren B, Lee CJ, McEvoy JW, Matsushita K, Huang ES, et al. The association of severe hypoglycemia with incident cardiovascular events and mortality in adults with type 2 diabetes. Diabetes Care. 2018;41(1).
  18. Mellbin LG. Does hypoglycaemia increase the risk of cardiovascular events? A report from the ORIGIN trial. Eur Heart J. 2013;34(40).
  19. Reno CM, Daphna-Iken D, Chen YS, VanderWeele J, Jethi K, Fisher SJ. Severe hypoglycemia-induced lethal cardiac arrhythmias are mediated by sympathoadrenal activation. Diabetes. 2013;62(10).
  20. Donnelly LA, Morris AD, Frier BM, Ellis JD, Donnan PT, Durran R, et al. Frequency and predictors of hypoglycaemia in Type 1 and insulin-treated Type 2 diabetes: A population-based study. Diabetic Medicine. 2005;22(6).
  21. Heller SR, Choudhary P, Davies C, Emery C, Campbell MJ, Freeman J, et al. Risk of hypoglycaemia in types 1 and 2 diabetes: Effects of treatment modalities and their duration. Diabetologia. 2007;50(6).
  22. Holstein A, Egberts EH. Risk of Hypoglycaemia with Oral Antidiabetic Agents in Patients with Type 2 Diabetes. Vol. 111, Experimental and Clinical Endocrinology and Diabetes. 2003.
  23. 6. Glycemic Targets: Standards of Medical Care in Diabetes—2022. Diabetes Care. 2022;45.
  24. Heller SR. Glucose concentrations of less than 3.0 mmol/L (54 mg/dL) should be reported in clinical trials: A joint position statement of the American diabetes association and the European association for the study of diabetes. Diabetes Care. 2017;40(1).
  25. Seaquist ER, Anderson J, Childs B, Cryer P, Dagogo-Jack S, Fish L, et al. Hypoglycemia and diabetes: A report of a workgroup of the american diabetes association and the endocrine society. Journal of Clinical Endocrinology and Metabolism. 2013;98(5).
  26. Effects of Intensive Glucose Lowering in Type 2 Diabetes. New England Journal of Medicine. 2008;358(24).
  27. Intensive versus Conventional Glucose Control in Critically Ill Patients. New England Journal of Medicine. 2009;360(13).
  28. Giorgino F, Leonardini A, Laviola L. Cardiovascular disease and glycemic control in type 2 diabetes: Now that the dust is settling from large clinical trials. Ann N Y Acad Sci. 2013;1281(1).
  29. Zoungas S, Patel A, Chalmers J, de Galan BE, Li Q, Billot L, et al. Severe Hypoglycemia and Risks of Vascular Events and Death. New England Journal of Medicine. 2010;363(15).
  30. Duckworth W, Abraira C, Moritz T, Reda D, Emanuele N, Reaven PD, et al. Glucose Control and Vascular Complications in Veterans with Type 2 Diabetes. New England Journal of Medicine. 2009;360(2).
  31. Davis IC, Ahmadizadeh I, Randell J, Younk L, Davis SN. Understanding the impact of hypoglycemia on the cardiovascular system. Vol. 12, Expert Review of Endocrinology and Metabolism. 2017.
  32. Robinson RTCE, Harris ND, Ireland RH, Lee S, Newman C, Heller SR. Mechanisms of abnormal cardiac repolarization during insulin-induced hypoglycemia. Diabetes. 2003;52(6).
  33. Joy NG, Hedrington MS, Briscoe VJ, Tate DB, Ertl AC, Davis SN. Effects of acute hypoglycemia on inflammatory and pro-atherothrombotic biomarkers in individuals with type 1 diabetes and healthy individuals. Diabetes Care. 2010;33(7).
  34. Joy NG, Tate DB, Younk LM, Davis SN. Effects of acute and antecedent hypoglycemia on endothelial function and markers of atherothrombotic balance in healthy humans. Diabetes. 2015;64(7).
  35. Punthakee Z, Miller ME, Launer LJ, Williamson JD, Lazar RM, Cukierman-Yaffee T, et al. Poor cognitive function and risk of severe hypoglycemia in type 2 diabetes: Post hoc epidemiologic analysis of the ACCORD trial. Diabetes Care. 2012;35(4).
  36. Przezak A, Bielka W, Molęda P. Fear of hypoglycemia—An underestimated problem. Vol. 12, Brain and Behavior. 2022.
  37. Briscoe VJ, Davis SN. Hypoglycemia in type 1 and type 2 diabetes: Physiology, pathophysiology, and management. Vol. 24, Clinical Diabetes. 2006.
  38. Towler DA, Havlin CE, Craft S, Cryer P. Mechanism of awareness of hypoglycemia: Perception of neurogenic (predominantly cholinergic) rather than neuroglycopenic symptoms. Diabetes. 1993;42(12).
  39. DeRosa MA, Cryer PE. Hypoglycemia and the sympathoadrenal system: Neurogenic symptoms are largely the result of sympathetic neural, rather than adrenomedullary, activation. Am J Physiol Endocrinol Metab. 2004;287(1 50-1).
  40. Dagogo-Jack SE, Craft S, Cryer PE. Hypoglycemia-associated autonomic failure in insulin-dependent diabetes mellitus: Recent antecedent hypoglycemia reduces autonomic responses to, symptoms of, and defense against subsequent hypoglycemia. Journal of Clinical Investigation. 1993;91(3).
  41. Segel SA, Paramore DS, Cryer PE. Hypoglycemia-associated autonomic failure in advanced type 2 diabetes. Diabetes. 2002;51(3).
  42. Gerich JE, Langlois M, Noacco C, Karam JH, Forsham PH. Lack of glucagon response to hypoglycemia in diabetes: Evidence for an intrinsic pancreatic alpha cell defect. Science (1979). 1973;182(4108).
  43. Raju B, Cryer PE. Loss of the decrement in intraislet insulin plausibly explains loss of the glucagon response to hypoglycemia in insulin-deficient diabetes: Documentation of the intraislet insulin hypothesis in humans. Diabetes. 2005;54(3).
  44. Cooperberg BA, Cryer PE. β-cell-mediated signaling predominates over direct α-cell signaling in the regulation of glucagon secretion in humans. Diabetes Care. 2009;32(12).
  45. Cryer PE. Mechanisms of sympathoadrenal failure and hypoglycemia in diabetes. Vol. 116, Journal of Clinical Investigation. 2006.
  46. Heller SR, Cryer PE. Reduced neuroendocrine and symptomatic responses to subsequent hypoglycemia after 1 episode of hypoglycemia in nondiabetic humans. Diabetes. 1991;40(2).
  47. Ertl AC, Davis SN. Evidence for a vicious cycle of exercise and hypoglycemia in type 1 diabetes mellitus. Vol. 20, Diabetes/Metabolism Research and Reviews. 2004.
  48. Jones TW, Porter P, Sherwin RS, Davis EA, O’Leary P, Frazer F, et al. Decreased Epinephrine Responses to Hypoglycemia during Sleep. New England Journal of Medicine. 1998;338(23).
  49. Banarer S, Cryer PE. Sleep-related hypoglycemia-associated autonomic failure in type 1 diabetes: Reduced awakening from sleep during hypoglycemia. Diabetes. 2003;52(5).
  50. Schultes B, Jauch-Chara K, Gais S, Hallschmid M, Reiprich E, Kern W, et al. Defective awakening response to nocturnal hypoglycemia in patients with type 1 diabetes mellitus. PLoS Med. 2007;4(2).
  51. White NH, Skor DA, Cryer PE, Levandoski LA, Bier DM, Santiago J V. Identification of Type I Diabetic Patients at Increased Risk for Hypoglycemia during Intensive Therapy. New England Journal of Medicine. 1983;308(9).
  52. Bolli GB, de Feo P, de Cosmo S, Perriello G, Ventura MM, Benedetti MM, et al. A reliable and reproducible test for adequate glucose counterregulation in type I diabetes mellitus. Diabetes. 1984;33(8).
  53. Geddes J, Schopman JE, Zammitt NN, Frier BM. Prevalence of impaired awareness of hypoglycaemia in adults with type 1 diabetes. Diabetic Medicine. 2008;25(4).
  54. Fanelli CG, Epifano L, Rambotti AM, Pampanelli S, Di Vincenzo A, Modarelli F, et al. Meticulous prevention of hypoglycemia normalizes the glycemic thresholds and magnitude of most of neuroendocrine responses to, symptoms of, and cognitive function during hypoglycemia in intensively treated patients with short-term IDDM. Diabetes. 1993;42(11).
  55. Fanelli C, Pampanelli S, Epifano L, Rambotti AM, Di Vincenzo A, Modarelli F, et al. Long-term recovery from unawareness, deficient counterregulation and lack of cognitive dysfunction during hypoglycaemia, following institution of rational, intensive insulin therapy in IDDM. Diabetologia. 1994;37(12).
  56. Cranston I, Lomas J, Amiel SA, Maran A, Macdonald I. Restoration of hypoglycaemia awareness in patients with long-duration insulin-dependent diabetes. The Lancet. 1994;344(8918).
  57. Dagogo-Jack S, Rattarasarn C, Cryer PE. Reversal of hypoglycemia unawareness, but not defective glucose counterregulation, in IDDM. Diabetes. 1994;43(12).
  58. Epidemiology of severe hypoglycemia in the diabetes control and complications trial. Am J Med. 1991;90(1).
  59. Gonder-frederick LA, Fisher CD, Ritterband LM, Cox DJ, Hou L, Dasgupta AA, et al. Predictors of fear of hypoglycemia in adolescents with type 1 diabetes and their parents. Pediatr Diabetes. 2006;7(4).
  60. Nordfeldt S, Ludvigsson J. Fear and other disturbances of severe hypoglycaemia in children and adolescents with type 1 diabetes mellitus. Journal of Pediatric Endocrinology and Metabolism. 2005;18(1).
  61. Cox DJ, Gonder-Frederick L, Ritterband L, Clarke W, Kovatchev BP. Prediction of severe hypoglycemia. Diabetes Care. 2007;30(6).
  62. Rossetti P, Porcellati F, Bolli GB, Fanelli CG. Prevention of hypoglycemia while achieving good glycemic control in type 1 diabetes: the role of insulin analogs. Vol. 31 Suppl 2, Diabetes care. 2008.
  63. Siebenhofer A, Plank J, Berghold A, Jeitler K, Horvath K, Narath M, et al. Short acting insulin analogues versus regular human insulin in patients with diabetes mellitus. Cochrane Database of Systematic Reviews. 2006.
  64. Horvath K, Jeitler K, Berghold A, Ebrahim SH, Gratzer TW, Plank J, et al. Long-acting insulin analogues versus NPH insulin (human isophane insulin) for type 2 diabetes mellitus. Cochrane Database of Systematic Reviews. 2007.
  65. Pedersen-Bjergaard U, Kristensen PL, Beck-Nielsen H, Nørgaard K, Perrild H, Christiansen JS, et al. Effect of insulin analogues on risk of severe hypoglycaemia in patients with type 1 diabetes prone to recurrent severe hypoglycaemia (HypoAna trial): A prospective, randomised, open-label, blinded-endpoint crossover trial. Lancet Diabetes Endocrinol. 2014;2(7).
  66. Garber AJ, King AB, Del Prato S, Sreenan S, Balci MK, Muñoz-Torres M, et al. Insulin degludec, an ultra-longacting basal insulin, versus insulin glargine in basal-bolus treatment with mealtime insulin aspart in type 2 diabetes (BEGIN Basal-Bolus Type 2): A phase 3, randomised, open-label, treat-to-target non-inferiority trial. The Lancet. 2012;379(9825).
  67. Eng C, Kramer CK, Zinman B, Retnakaran R. Glucagon-like peptide-1 receptor agonist and basal insulin combination treatment for the management of type 2 diabetes: A systematic review and meta-analysis. The Lancet. 2014;384(9961).
  68. Fatourechi MM, Kudva YC, Murad MH, Elamin MB, Tabini CC, Montori VM. Hypoglycemia with intensive insulin therapy: A systematic review and meta-analyses of randomized trials of continuous subcutaneous insulin infusion versus multiple daily injections. Vol. 94, Journal of Clinical Endocrinology and Metabolism. 2009.
  69. Yeh HC, Brown TT, Maruthur N, Ranasinghe P, Berger Z, Suh YD, et al. Comparative effectiveness and safety of methods of insulin delivery and glucose monitoring for diabetes mellitus: A systematic review and meta-analysis. Vol. 157, Annals of Internal Medicine. 2012.
  70. Pickup JC, Reznik Y, Sutton AJ. Glycemic control during continuous subcutaneous insulin infusion versus multiple daily insulin injections in type 2 diabetes: Individual patient Data meta-analysis and meta-regression of randomized controlled trials. Diabetes Care. 2017;40(5).
  71. Benkhadra K, Alahdab F, Tamhane SU, McCoy RG, Prokop LJ, Murad MH. Continuous subcutaneous insulin infusion versus multiple daily injections in individuals with type 1 diabetes: a systematic review and meta-analysis. Endocrine. 2017;55(1).
  72. Beck RW, Riddlesworth T, Ruedy K, Ahmann A, Bergenstal R, Haller S, et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections the diamond randomized clinical trial. In: JAMA - Journal of the American Medical Association. 2017.
  73. Beck RW, Riddlesworth TD, Ruedy K, Ahmann A, Haller S, Kruger D, et al. Continuous glucose monitoring versus usual care in patients with type 2 diabetes receiving multiple daily insulin injections. Ann Intern Med. 2017;167(6).
  74. US Food and Drug Administration. Press Announcements - FDA expands indication for continuous glucose monitoring system, first to replace fingerstick testing for diabetes treatment decisions. FDA News Release. 2016.
  75. News Release F. FDA Approves First Continuous Glucose Monitoring System for Adults Not Requiring Blood Sample Calibration. Vol. 9, Molecular and Cellular Pharmacology. 2017.
  76. Rickels MR, Peleckis AJ, Dalton-Bakes C, Naji JR, Ran NA, Nguyen HL, et al. Continuous glucose monitoring for hypoglycemia avoidance and glucose counterregulation in long-standing type 1 diabetes. Journal of Clinical Endocrinology and Metabolism. 2018;103(1).
  77. Cooper MN, O’Connell SM, Davis EA, Jones TW. A population-based study of risk factors for severe hypoglycaemia in a contemporary cohort of childhood-onset type 1 diabetes. Diabetologia. 2013;56(10).
  78. Johnson SR, Cooper MN, Jones TW, Davis EA. Long-term outcome of insulin pump therapy in children with type 1 diabetes assessed in a large population-based case-control study. Diabetologia. 2013;56(11).
  79. Bergenstal RM, Klonoff DC, Garg SK, Bode BW, Meredith M, Slover RH, et al. Threshold-Based Insulin-Pump Interruption for Reduction of Hypoglycemia. New England Journal of Medicine. 2013;369(3).
  80. Ly TT, Nicholas JA, Retterath A, Lim EM, Davis EA, Jones TW. Effect of sensor-augmented insulin pump therapy and automated insulin suspension vs standard insulin pump therapy on hypoglycemia in patients with type 1 diabetes: A randomized clinical trial. JAMA. 2013;310(12).
  81. Maahs DM, Calhoun P, Buckingham BA, Chase HP, Hramiak I, Lum J, et al. A randomized trial of a home system to reduce nocturnal hypoglycemia in type 1 diabetes. Diabetes Care. 2014;37(7).
  82. Leelarathna L, Dellweg S, Mader JK, Allen JM, Benesch C, Doll W, et al. Day and night home closed-loop insulin delivery in adults with type 1 diabetes: Three-center randomized crossover study. Diabetes Care. 2014;37(7).
  83. Russell SJ, El-Khatib FH, Sinha M, Magyar KL, McKeon K, Goergen LG, et al. Outpatient Glycemic Control with a Bionic Pancreas in Type 1 Diabetes. New England Journal of Medicine. 2014;371(4).
  84. Ang M, Meyer C, Brendel MD, Bretzel RG, Linn T. Magnitude and mechanisms of glucose counterregulation following islet transplantation in patients with type 1 diabetes suffering from severe hypoglycaemic episodes. Diabetologia. 2014;57(3).
  85. FDA. FDA. 2020. FDA Approves First-of-its-Kind Automated Insulin Delivery and Monitoring System for Use in Young Pediatric Patients.
  86. Tansey MJ, Tsalikian E, Beck RW, Mauras N, Buckingham BA, Weinzimer SA, et al. The effects of aerobic exercise on glucose and counterregulatory hormone concentrations in children with type 1 diabetes. Diabetes Care. 2006;29(1).
  87. MacDonald MJ. Postexercise late-onset hypoglycemia in insulin-dependent diabetic patients. Diabetes Care. 1987;10(5).
  88. Tsalikian E. Impact of exercise on overnight glycemic control in children with type 1 diabetes mellitus. Journal of Pediatrics. 2005;147(4).
  89. Gallen IW. Hypoglycemia associated with exercise in people with type 1 diabetes. Vol. 7, Diabetic Hypoglycemia. 2014.
  90. Raju B, Arbelaez AM, Breckenridge SM, Cryer PE. Nocturnal hypoglycemia in type 1 diabetes: An assessment of preventive bedtime treatments. Journal of Clinical Endocrinology and Metabolism. 2006;91(6).
  91. Cooperberg BA, Breckenridge SM, Arbelaez AM, Cryer PE. Terbutaline and the prevention of nocturnal hypoglycemia in type 1 diabetes. Diabetes Care. 2008;31(12).
  92. Taplin CE, Cobry E, Messer L, McFann K, Chase HP, Fiallo-Scharer R. Preventing post-exercise nocturnal hypoglycemia in children with type 1 diabetes. Journal of Pediatrics. 2010;157(5).
  93. Elsayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. 13. Older Adults: Standards of Care in Diabetes—2023. Diabetes Care. 2023;46.
  94. Cox DJ, Singh H, Lorber D. Diabetes and driving safety: Science, ethics, legality and practice. In: American Journal of the Medical Sciences. 2013.
  95. Nielsen LR, Pedersen-Bjergaard U, Thorsteinsson B, Johansen M, Damm P, Mathiesen ER. Hypoglycemia in pregnant women with type 1 diabetes: Predictors and role of metabolic control. Diabetes Care. 2008;31(1).
  96. Inzucchi SE, Bergenstal RM, Buse JB, Diamant M, Ferrannini E, Nauck M, et al. Management of Hyperglycemia in Type 2 Diabetes, 2015: A Patient-Centered Approach: Update to a position statement of the american diabetes association and the european association for the study of diabetes. Diabetes Care. 2015;38(1).
  97. Children and adolescents: Standards of medical care in diabetes- 2020. Diabetes Care. 2020;43.
  98. Sämann A, Mühlhauser I, Bender R, Kloos C, Müller UA. Glycaemic control and severe hypoglycaemia following training in flexible, intensive insulin therapy to enable dietary freedom in people with type 1 diabetes: A prospective implementation study. Diabetologia. 2005;48(10).
  99. Little SA, Leelarathna L, Walkinshaw E, Tan HK, Chapple O, Lubina-Solomon A, et al. Recovery of hypoglycemia awareness in long-standing type 1 diabetes: A multicenter 2 × 2 factorial randomized controlled trial comparing insulin pump with multiple daily injections and continuous with conventional glucose self-monitoring (HypoCOMPaSS). Diabetes Care. 2014;37(8).
  100. Leelarathna L, Little SA, Walkinshaw E, Tan HK, Lubina-Solomon A, Kumareswaran K, et al. Restoration of self-awareness of hypoglycemia in adultswith long-standing type 1 diabetes: Hyperinsulinemic-hypoglycemic clamp substudy results from the HypoCOMPaSS trial. Diabetes Care. 2013;36(12).
  101. Hopkins D, Lawrence IAN, Mansell P, Thompson G, Amiel S, Campbell M, et al. Improved biomedical and psychological outcomes 1 year after structured education in flexible insulin therapy for people with type 1 diabetes the U.K. DAFNE experience. Diabetes Care. 2012;35(8).
  102. De Zoysa N, Rogers H, Stadler M, Gianfrancesco C, Beveridge S, Britneff E, et al. A psychoeducational program to restore hypoglycemia awareness: The DAFNE-HART pilot study. Diabetes Care. 2014;37(3).
  103. Elliott J, Jacques RM, Kruger J, Campbell MJ, Amiel SA, Mansell P, et al. Substantial reductions in the number of diabetic ketoacidosis and severe hypoglycaemia episodes requiring emergency treatment lead to reduced costs after structured education in adults with Type 1 diabetes. Diabetic Medicine. 2014;31(7).
  104. Wiethop B V., Cryer PE. Alanine and terbutaline in treatment of hypoglycemia in IDDM. Diabetes Care. 1993;16(8).
  105. Haymond MW, Schreiner B. Mini-dose glucagon rescue for hypoglycemia in children with type 1 diabetes. Diabetes Care. 2001;24(4).
  106. Pontiroli AE. Intranasal glucagon: A promising approach for treatment of severe hypoglycemia. J Diabetes Sci Technol. 2015;9(1).
  107. Chabenne J, Chabenne MDM, Zhao Y, Levy J, Smiley D, Gelfanov V, et al. A glucagon analog chemically stabilized for immediate treatment of life-threatening hypoglycemia. Mol Metab. 2014;3(3).
  108. Boyle PJ, Justice K, Krentz AJ, Nagy RJ, Schade DS. Octreotide reverses hyperinsulinemia and prevents hypoglycemia induced by sulfonylurea overdoses. Journal of Clinical Endocrinology and Metabolism. 1993;76(3).
  109. McLaughlin SA, Crandall CS, McKinney PE. Octreotide: An antidote for sulfonylurea-induced hypoglycemia. Ann Emerg Med. 2000;36(2).
  110. Graveling A, Walden E, Flanagan D. The Hospital Management of Hypoglycaemia in Adults with Diabetes Mellitus. Joint British Diabetes Societies for Inpatient Care. 2022.

Non-Pharmaceutical Intervention Options for Type 2 Diabetes: Complementary Health Approaches and Integrative Health (Including Natural Products and Mind/Body Practices)

ABSTRACT

 

Complementary and Integrative Health (CIH) approaches, otherwise known as non-mainstream practices or Complementary and Alternative Medicine (CAM), are commonly used by patients with diabetes. Natural products, including dietary supplements, are the most frequently used complementary approach by patients with diabetes. While popular, there are regulatory, safety, and efficacy concerns regarding natural products. Commonly used dietary supplements for diabetes can be categorized as hypoglycemic agents, carbohydrate absorption inhibitors, and insulin sensitizers. Hypoglycemic agents of interest include banaba, bitter melon, fenugreek, and gymnema. American ginseng, banaba, berberine, chromium, cinnamon, gymnema, milk thistle, prickly pear cactus, soy, and vanadium are insulin sensitizers that have been studied in patients with diabetes. The carbohydrate absorption inhibitors aloe vera gel, fenugreek, flaxseed, prickly pear cactus, soy, and turmeric may be used in patients with diabetes. Mind body therapies including yoga, massage, and Tai Chi have preliminary evidence to support use in patients with diabetes. Deceptive marketing tactics may be employed by sellers of natural products. Consumers and clinicians must be aware of potential risks and make informed choices. Resources such as the Food and Drug Administration’s (FDA’s) MedWatch may be helpful. The FDA’s online health fraud website informs consumers on various types of fraud and how to avoid them.

 

COMPLEMEMTARY AND INTEGRATIVE HEALTH APPROACHES BACKGROUND        

 

This chapter reviews information regarding Complementary and Integrative Health (CIH) approaches used to treat diabetes. First, background information on complementary health approaches (sometimes referred to as Complementary and Alternative Medicine or CAM) will be presented. This will be followed by a description of non-mainstream practices used by patients with diabetes. An evidence-based description of specific natural products used to treat diabetes will be next. Mind body practices will be addressed. The chapter will conclude with specific ways clinicians can assist patients in choosing safe natural products. Please note information regarding therapies to treat comorbidities of diabetes are covered elsewhere in this text.

 

To help clarify the contents of this chapter, nomenclature definitions relevant to CIH will be provided as defined by the National Institute of Health (NIH) National Center for Complementary and Integrative Health (NCCIH). Table 1 provides definitions of commonly used terms. Complementary medicine is defined as non-mainstream practices that are used together with conventional medicine. In contrast, alternative medicine describes non-mainstream practices used instead of conventional medicine. Complementary health approaches are non-mainstream practices. The term integrative medicine refers to medicine that brings complementary and conventional health approaches together in a coordinated manner. Integrative health describes complementary approaches that are incorporated into mainstream healthcare. Lastly, the term natural products refer to herbs, vitamins, minerals, and probiotics (1).

 

Table 1. Definitions of Terms Relevant to Complementary and Alternative Medicine (1)

Term

Definition

Alternative Medicine

Non-mainstream practice used instead of conventional medicine

Complementary Health Approaches

Non-mainstream practices

Complementary Medicine

Non-mainstream practice used together with conventional medicine

Integrative Health

Complementary approaches being incorporated into mainstream healthcare

Integrative Medicine

Medicine that brings complementary and conventional health approaches together in a coordinated fashion

Natural Products

Herbs, vitamins, minerals, and probiotics

 

“Complementary health approaches” is an umbrella term for non-mainstream practices. Complementary health approaches can be classified by their primary therapeutic input, or method of delivery (Table 2). A graphic representation of the examples of complementary health approaches and their categorization is provided in Figure 1 (1).

 

Table 2. Classification of Complementary Health Approaches (1)

Primary Therapeutic Input

Examples

Nutritional

Special diets, dietary supplements, herbs, and probiotics

Psychological

Mindfulness

Physical

Osteopathic manipulative therapy, chiropractic spinal manipulation, massage therapy, physical therapy

Combinations

Psychological and physical, e.g., yoga, Tai Chi, acupuncture, dance or art therapies, or psychological and nutritional, e.g., mindful eating

 

FIGURE 1. COMPLEMENTARY HEALTH APPROACH. IMAGE SOURCE: https://files.nccih.nih.gov/nutritional-psychological-physical-venn-diagram-08-01-crop.png.

The complementary health approach classification system has its limitations and, therefore, a five-domain system has been proposed to organize CIH. The domains include: (1) biologically based therapies; (2) mind-body interventions; (3) manipulative and body-based therapies; (4) alternative or whole medical systems; and (5) energy therapies. Examples of each domain are provided in Table 3 (1, 2).

 

Table 3. Domains to Classify Complementary and Integrative Health

Domain

Examples

Biologically based therapies

Dietary interventions, vitamins, minerals, supplements, herbal/botanical medicines

Mind–body interventions

Meditation, relaxation and breathing techniques, guided imagery, hypnosis, biofeedback, yoga, Tai Chi, qigong, expressive arts therapies, spiritual practices, and other forms of “directed” attention

Manipulative and body-based methods

Osteopathic manipulative therapy, chiropractic spinal manipulation, massage therapy, physical therapy

Alternative or whole medical systems

Traditional Chinese medicine, ayurveda, naturopathic medicine, homeopathy, Polynesian medicine, Unani-Tibb medicine, traditional African medicine, traditional Mayan medicine

Energy therapies

Acupuncture, Tai Chi, qigong, reiki, therapeutic or healing touch, bioenergetic therapy, and other methods that affect the body’s “bioelectric” field

 

REGULATIONS OF DIETARY SUPPLEMENTS AND NATURAL PRODUCTS

 

Background Information

 

The Dietary Supplement Health and Education Act (DSHEA) was passed in 1994. This legislation created the category of dietary supplements. Prior to DSHEA, natural products (herbs, vitamins, minerals, probiotics) were classified as either food or drug. Even though natural products are biologically active, they are considered food products and are exempt from the same approval process as drugs (3).

 

Under DSHEA, natural product manufacturers are not allowed to sell any adulterated or misbranded product. Manufacturers are expected to ensure natural products are effective and safe. However, manufacturers are not required to provide proof of efficacy or safety before marketing and selling a particular product (3).

 

When DSHEA was passed, it required that good manufacturing practices (GMPs) be established. Several years later the Food and Drug Administration (FDA) provided these standards. The standards say products must be labeled correctly and be free of impurities or adulterants (4).

 

Labeling requirements for dietary supplements exist. Products sold as dietary supplements must contain certain informational pieces on their labels. Items such as the product name, the word “supplement”, the net content quantity, the name and place of business of the manufacturer/packer/distributor, directions for use, a “Supplement Facts” panel, and a listing of all nondietary ingredients must be included. Table 4 reviews labeling requirements and Figure 2 is an example “Supplement Facts” panel (5).

 

Table 4. Information Required to Appear on Dietary Supplement Labels (5)

Dietary Supplement Labeling Requirements

Product Name

The word “supplement” or a statement the product is a supplement

Net content quantity

Manufacturer’s, packer’s, or distributor’s name

Manufacturer’s, packer’s, or distributor’s place of business

Directions for use

“Supplement Facts” panel listing serving size, dietary ingredients, amount per serving size, and percent daily value (if established)

Nondietary ingredients such as fillers, artificial colors, sweeteners, binders,

Figure 2. Example Supplement Facts Label. IMAGE SOURCE: https://www.fda.gov/food/guidanceregulation/guidancedocumentsregulatoryinformation/dietarysupplements/ucm070597.htm#4-59.

 

Dietary supplement products are allowed to make claims about maintaining structure or function of the body.  However, products are not allowed to make claims about diagnosis, treatment, cure, or prevention of a disease. For example, a product may claim to “maintain a healthy pancreas.” Conversely, a product may not claim to “treat diabetes.” If a product does make a health maintenance claim, the label must include the following statement: “This statement has not been evaluated by the Food and Drug Administration (FDA). This product is not intended to diagnose, treat, cure, or prevent any disease” (5).

 

Reporting of Adverse Events

 

The Dietary Supplement and Nonprescription Drug Consumer Protection Act was signed into law in 2006. This act required manufacturers to report adverse events for dietary supplements and nonprescription drugs. In addition, individuals are encouraged to report supplement and nonprescription drug adverse events to the FDA (6). Despite the Dietary Supplement and Nonprescription Drug Consumer Protection Act, there is concern of underreporting of adverse events.

 

Safety Concerns

 

Safety surrounding dietary supplements and natural products is a concern for clinicians and consumers alike. Despite DSHEA and the Dietary Supplement and Nonprescription Drug Consumer Protection Act, adverse events and safety issues regarding natural products abound. In fact, an article published in 2015 in The New England Journal of Medicineestimated 23,005 emergency room visits annually were a result of adverse effects related to dietary supplements (7).

 

The FDA publishes recalls for prescription drugs, nonprescription drugs, and dietary supplements. The most serious recalls are classified as Class I. A Class I drug recall is one where the product in question has “reasonable probability that the use of or exposure to . . . will cause serious adverse health consequences or death” (8). From 2008 to 2012, half of all Class I drug recalls were from dietary supplements (9).

 

INTEGRATIVE HEALTH USE IN THE UNITED STATES

 

According to the Council for Responsible Nutrition (CRN), Americans spend an estimated $35 billion on dietary supplements each year. The market appears to be growing each year. CRN estimates 74% of adults in the United States use supplements (10).

 

Most users of natural products take a multivitamin. Other commonly used supplements include specific vitamins (D, C, and B), calcium, omega-3 fatty acids/fish oil, probiotics, green tea, protein bars, whey protein powders, and energy drinks. Mass merchandizers and pharmacies are the most common places where dietary supplements are purchased (10,11).

 

Reasons for dietary supplement use vary. The most popular was to support overall health and wellness. Other popular reasons include filling nutrient gaps, heart health, healthy aging, immune health, energy, bone health, preventing illness, and joint health (11).

 

Integrative Health Use Amongst Patients with Diabetes

 

According to a meta-analysis published in 2021, 51% of patients with diabetes globally use some form of CAM. Use prevalence was highest in Europe, where 76% of patients with diabetes in France use CAM; prevalence was lowest in North America, where 45% of patients used CAM (12). Reasons for CAM use specific to the United States (US) include overall wellness (28% of users), treatment of diabetes (15%), or a combination of the two (57%) (13). Figure 3 illustrates the reasons for CAM use in patients with diabetes.

 

Figure 3. Reasons for CAM Use in Patients with Diabetes in the United States. Data Source (13).

 

Overall, the most common forms of CAM used in US patients with diabetes were herbal therapies (56.7% of users), chiropractic (25.3%), and massage (20.2%). See Figure 4 for an illustration. For those citing treatment alone as their reason for complementary health approach use, the most common types were chiropractic, herbal therapies, and massage. Those that cited wellness alone as their reason, the most common types of CAM utilized were herbal therapies, massage, and chiropractic (13).

 

 

Figure 4. Most Common Types of CAM Used in Patients with Diabetes. Data Source (13).

 

Sociodemographically, there are several differences in US CAM users with diabetes. The racial/ethnic group most likely to utilize complementary health approaches were non-Hispanic Whites. Those employed and with higher education attainment were also more likely to use CAM (13).

 

Due to the high usage, clinicians should gather comprehensive complementary health approach use histories from patients. This may prevent dangerous CAM-herb and CAM-disease interactions.

 

Older Adults

 

In particular, older adults with diabetes that utilize CAM can present unique challenges. Older adults tend to have more chronic medical conditions and diabetes complications. Additionally, older adults tend to use more medications compared to the general population.

 

One-quarter of older adults with diabetes utilize complementary, alternative, or integrative medicine (14). Of these older adults, 62.8% utilize herbal therapies specifically. Chiropractic (23.9%), massage (14.7%), acupuncture (10.2%), and yoga (5.2%) were the other most popular therapies used (14).

 

Clinicians should query older adult patients with diabetes on active CAM use. This may prevent dangerous CAM-herb and CAM-disease interactions.

 

NATURAL PRODUCTS  

 

Natural products have been used for thousands of years. Natural products were depicted on clay tablets in ancient Mesopotamia (2600 BC). An ancient Egyptian pharmaceutical record, the Ebers Papyrus, dates to 2900 BC and documents hundreds of natural therapies. Documented records of natural product use have also been found in China (the Chinese Materia Medica) and Greece (from the physician Dioscorides) (15).

 

This section will discuss natural products that are commonly used in patients with type 2 diabetes mellitus (T2DM) for glycemic control. A brief description of each product will be followed by an overview of proposed mechanisms of action. Next, currently available evidence for the product will be reviewed. A brief discussion of adverse effects and drug interactions will also be included.

 

While botanical products are often hypothesized to work by multiple mechanisms, each product is categorized below by the major mechanism thought to exert its effect. For your convenience, an alphabetized table of botanical products is also presented.

 

Hypoglycemic Agents

 

The natural products covered in this section are all agents that theoretically lower blood glucose. Each individual product may have additional mechanisms of action, which are also covered.

 

BANABA (LAGERSTROEMIA SPECIOSA)

 

Banaba is a crepe myrtle species indigenous to Southeast Asia. The first published report of banaba use is from 1940. Banaba is used for diabetes and weight loss. See Figure 5 for an illustration of the banaba plant. The banaba leaf is the portion thought to exert beneficial effects. It is thought the active constituents of the banaba leaf are corosolic acid and ellagitannins (lagerstroemin, flosin B, and reginin A) (16-18).

 

Figure 5. Banaba Plant Image Source: https://commons.wikimedia.org/wiki/File:Inflorescence_of_Lagerstroemia_speciosa.JPG.

 

Mechanism of Action

 

It is hypothesized that banaba lowers blood glucose by increasing insulin secretion and stimulating glucose uptake of cells (insulin-like effect). Additional proposed mechanisms include alpha-glucosidase inhibition and subsequent reduction in nutrient load; increasing insulin sensitivity via increased expression of liver peroxisome proliferator‐activated receptor‐α (PPAR‐α) mRNA and adipose tissue peroxisome proliferator‐activated receptor‐γ (PPAR‐γ) mRNA; decreased gluconeogenesis; and increased glycolysis by increasing glucokinase activity (17-21).

 

Evidence

 

A randomized controlled trial studied the activity of 1% corosolic acid (an active constituent of banaba) on glucose control in patients with type 2 diabetes. This was a dose-response study of 10 subjects aged 55-70 years. Subjects did not use any oral hypoglycemic medications for 45 days prior to the clinical trial. Five subjects in each group received either a hard or soft gelatin capsule containing 1% corosolic acid of 16, 32, and 48 mg doses (equivalent to 0.16 mg, 0.32 mg, and 0.48 mg of corosolic acid). Doses were given sequentially with a 10-day wash-out period between dose escalation.  Blood glucose levels were measured via finger-prick sample. Compared to control blood glucose levels, 1% corosolic acid from a soft gelatin capsule resulted in a statistically significant percent reduction in blood glucose levels at the 32 mg (10.7% ± 1.4) and 48 mg (30.0% ± 3.4) doses (p <0.05). The hard gel formulation resulted in a significant (p <0.05) percentage reduction in blood glucose for only the 48 mg dose (20.2% ± 1.29). Results are summarized in Table 5 (18).

 

Table 5. Percent Reduction in Basal Blood Glucose Levels in Patients with Type 2 Diabetes After 15 Days of Treatment with Different Doses of 1% Corosolic Acid (18)

Dosage Form

Dose of 1% Corosolic Acid (Equivalent Corosolic Acid Dose)

Percent Reduction in Blood Glucose Levels (± SD)

p-value

 

32 mg (0.32 mg)

10.7 ± 1.4

≤0.01

48 mg (0.48 mg)

30.0 ± 3.4

≤0.002

32 mg (0.32 mg)

6.5 ± 1.13

≤0.09

48 mg (0.48 mg)

20.2 ± 1.29

≤0.001

 

Fukushima and colleagues performed a double-blind cross-over design trial in 31 subjects with type 2 diabetes. In this study, subjects were not randomized. Subjects received oral supplementation with a 10 mg corosolic acid (an active constituent of banaba) capsule or placebo five minutes prior to a 75-g oral glucose tolerance test. The majority of the subjects had type 2 diabetes (n=19) while seven had impaired glucose tolerance, one had impaired fasting glucose, and four had normal glucose according to 1998 WHO criteria. Subjects with diagnosed hypertension, hepatic, or renal disease; engaged in heavy exercise; or took any medication were excluded. Thirty minutes after the oral glucose tolerance test, there were no differences in plasma glucose levels. The corosolic acid treatment group showed lower glucose levels from 60 minutes until 120 minutes after glucose administration. Statistical significance was reached at 90 minutes (p<0.05) (22).

 

Adverse Effects and Warnings

 

Banaba extract appears to be well tolerated when used orally. Dizziness, headache, tremor, weakness, diaphoresis, and nausea have been reported (23).

 

Interactions

 

As banaba lowers blood glucose, it should be used with caution in those using other hypoglycemic agents. Banaba may also lower blood pressure and may have an additive effect with other antihypertensives (18, 23).

 

Summary

 

Banaba is possibly effective for the treatment of type 2 diabetes. Data from human studies investigating banaba demonstrate corosolic acid’s potential to lower blood glucose. Small sample size and short study duration limit applicability of results.

 

BITTER MELON (MOMORDICA CHARANTIA)

 

Bitter melon is a plant cultivated in India, Asia, South America, and the Caribbean. Local nomenclature for Bitter melon varies – in India it is known as karela, bitter melon, and bitter gourd. It can also be known as wild cucumber, ampalaya, and cundeamor (24, 25). A member of the melon family, bitter melon is consumed in Asian cuisine and used both orally and topically. Uses for bitter melon include diabetes, cancer, and HIV (26). See Figure 6 for an image of the bitter melon plant.

 

Figure 6. Bitter Melon Plant Image Source: https://commons.wikimedia.org/wiki/File:Momordica_charantia_(Bitter_melon)_leaves_and_a_flower.jpg.

 

Mechanism of Action

 

It is thought bitter melon has insulin-like properties. More specifically, it is hypothesized bitter melon: 1) inhibits mitogen-activated protein kinases (MAPKs) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) in pancreatic cells; 2) promotes glucose and fatty acid catabolism; 3) stimulates fatty acid absorption; 4) induces insulin production; 5) improves insulin resistance; 6) stimulates activated protein kinases (AMPK); and 6) inhibits fructose-1,6-bisphosphate and glucose-6-phosphatase (27, 28).

 

Evidence

 

In 2024, a meta-analysis was published that aimed to examine the impact of bitter melon on glycemic control and lipid profiles in individuals with T2DM. Eight randomized controlled trials were included (n=423). The authors found bitter melon was associated with significant reductions in fasting blood glucose (weighted mean distribution [WMD] of -15.3 mg/dL; 95% CI: -25.9 to -4.7; p = 0.005; I2= 73.4 %); postprandial glucose (WMD: -41.0 mg/dL; 95% CI: -60.3 to -21.8; p = 0.000; I2 = 66.9 %); and glycosylated hemoglobin A1c (HbA1c) (WMD: -0.38%; 95% CI: -0.53 to -0.23; p = 0.000; I2= 37.6 %). Total cholesterol was also significantly reduced (WMD: -6.8 mg/dL; 95% CI: -12.6 to -1.3; p = 0.017; I2 = 63.6 %). No significant differences were observed in terms for triglycerides (TG), high-density lipoproteins (HDL), and low-density lipoprotein (LDL) (29).

 

A 2019 meta-analysis was conducted to evaluate the efficacy of bitter melon in lowering elevated plasma glucose levels in patients with prediabetes and T2DM. Ten studies were included in the meta-analysis and ranged from 4 to 16 weeks in follow up. Overall, bitter melon lowered fasting plasma glucose by 13 mg/dL (95% CI: -23.9 to -2.2). Postprandial glucose decreased by 25.7 mg/dL (95% CI: -39.2 to -12.1) and HbA1c decreased by 0.26% (95% CI, -0.49 to 0.03). Of note, the studies had overall bias risk of moderate to high. The study authors rated the evidence quality low due to risk of bias and inadequate sample size (30).

 

A 2012 Cochrane Review of four randomized controlled trials found no statistically significant difference in glycemic control with bitter melon compared to placebo. Additionally, there was no significant change in glycemic control compared to metformin and sulfonylureas. Of note, no significant interactions were noted (31).

 

Adverse Effects and Warnings

 

Adverse effects reported include abdominal discomfort, pain, and diarrhea (32).

 

Bitter melon has been used as an abortifacient agent. Animal research confirms two proteins isolated from the plant possess abortifacient properties and may decrease fertility (33).

 

Interactions

 

As bitter melon may lower blood glucose, it should be used with caution in those using other hypoglycemic agents.

 

Bitter melon may increase levels of drugs that are P-glycoprotein substrates. For example, levels of apixaban, cimetidine, corticosteroids, diltiazem, erythromycin, fexofenadine, linagliptin, rivaroxaban, and verapamil may be increased with concurrent bitter melon use.

 

Those with G6PD deficiency should avoid use due to risk of developing favism (27).

 

Summary

 

Bitter melon is commonly used medicinally and in cuisine. There is mixed regarding bitter melon’s blood glucose lowering efficacy in patients with type 2 diabetes. Bitter melon has abortifacient properties and should be avoided in pregnancy.

 

FENUGREEK (TRIGONELLA FOENUM-GRAECUM)

 

Fenugreek, a member of the Fabaceae family, is an aromatic herb native to the Mediterranean region, northern Africa, southern Europe, and western Asia. The plant appears clover-like and its leaves are used in southeast Asian cuisine (see Figure 7 for an illustration). The seed is considered to be the pharmaceutically active portion of Trigonella foenum-graecum. If consuming fenugreek seeds, one must crush them to release the viscous gel fiber to increase efficacy. The flavor and fragrance of the seed is similar to maple syrup. Fenugreek seeds are approximately 50% fiber (30% soluble and 20% insoluble fiber) (21, 34).

 

Figure 7. Fenugreek Plant Image Source: https://en.wikipedia.org/wiki/Fenugreek.

 

Mechanism of Action

 

Fenugreek is thought to lower blood glucose via multiple mechanisms. As fenugreek seeds are fiber rich, it is thought this may slow postprandial glucose absorption (34, 35). Bioactive compounds in fenugreek include 4-hydroxyisoleucine (which accounts for the majority), saponins, alkaloids, and coumarins (36). 4-hydroxyisoleucine increases glucose-dependent insulin secretion in human beta-islet cells (21, 37). Fenugreek may play a role in regulating glucagon-like peptide-1 (GLP-1) through the action of an active compound N55, which is thought to bind to GLP-1 and enhance its potency in stimulating GLP-1 receptor signaling (35). Fenugreek, along with other herbal products used for the treatment of type 2 diabetes, contains biguanide-related compounds. In fact, the history of metformin can be traced back to the use of French lilac as herbal medicine in medieval Europe (38).

Evidence

 

A systematic review and meta-analysis published in 2023 evaluated fourteen trials (n=894) on the effect of fenugreek on hyperglycemia. Twelve of the trials included patients with T2DM; the two remaining trials included patients with pre-diabetes and that were classified as overweight, respectively. The meta-analysis demonstrated a non-significant reduction in fasting blood glucose levels (WMD -3.70 mg/dL; 95% CI: −27.02 to 19.62; p = 0.76) and postprandial blood glucose (WMD of −10.61 mg/dL; 95% CI: −68.48 to 47.26; p = 0.72). A significant reduction in HbA1c was seen (WMD of −0.88%; 95% CI: −1.49 to −0.27; p < 0.05) with fenugreek consumption. See Table 6 for a summary of the results of the meta-analysis (39).

 

Table 6. Fenugreek Meta-Analysis Results (39)

Parameter

Weighted Mean Difference

(95% CI)

p-value

Weighted Mean Difference

Heterogeneity

(I2)

p-value Heterogeneity

HbA1c

-0.88% (-1.49 to -0.27)

<0.05

74.9%

< 0.01

Fasting blood glucose

-3.70 mg/dL (−27.02 to 19.62)

0.76

99.4%

< 0.01

Postprandial glucose

−10.61 mg/dL (−68.48 to 47.26)

0.72

99.1%

< 0.01

 

An earlier meta-analysis evaluated ten trials of fenugreek found both fasting blood glucose and HbA1c significantly decreased with fenugreek compared to placebo. The weighted mean difference in HbA1c was -0.58% (95% CI: -0.99 to -0.17; p<0.05). The same analysis found a difference in fasting blood glucose of – 12.94 mg/dL (95% CI: -21.39 to -4.49; p<0.05) (40).

 

A study evaluating the effect of fenugreek on glycemic control enrolled 25 patients with T2DM. Baseline fasting glucose was less than 200 mg/dL in all study participants. Half of patients received 1 g of hydroalcoholic extract of fenugreek seeds while the other half received placebo. At the end of two months, the fenugreek group’s fasting and two hour post prandial glucose levels were not different from placebo. There was, however, a difference favoring fenugreek in area under the curve of blood glucose (2375 +/- 574 vs 27597 +/- 274) as well as insulin (2492 +/- 2536 vs. 5631 +/- 2428) (p < 0.001). Homeostatic model assessment for insulin resistance (HOMA-IR) was lower in the fenugreek group (86.3 +/- 32 vs. 70.1 +/- 52) and insulin sensitivity increased (112.9 +/- 67 vs 92.2 +/- 57) (p < 0.05) (41).

 

Adverse Effects and Warnings

 

Adverse effects of fenugreek include diarrhea, heartburn, and flatulence (34).

 

Fenugreek is aromatic and smells similar to maple syrup. Consumption prior to delivery may cause the neonate to have this odor, which may lead to confusion with maple syrup urine disease (42).

 

Patients with chickpea allergies should use fenugreek with caution as there is potential for cross-reactivity. Furthermore, fenugreek may cause uterine contractions and should be avoided in pregnancy (34).

 

Interactions

 

Fenugreek preparations may contain coumarin and increase the risk of bleeding with anticoagulants. Theophylline levels may be decreased with concomitant use. As fenugreek may lower blood glucose levels, it should be used cautiously with other agents that decrease glucose (34).

 

Summary

 

Fenugreek is a commonly used herb that is possibly effective for the treatment of hyperglycemia in patients with type 2 diabetes. Due to the risk of uterine contractions, fenugreek should not be used in pregnancy. Fenugreek may contain coumarin and should be used cautiously with anticoagulants.

 

GYMNEMA (GYMNEMA SYLVESTRE)

 

Gymnema is a plant native to tropical and subtropical regions of Asia, Africa, and Australia. Ayurvedic medicine has long utilized gymnema and its Hindi name is gurmar, which means “destroyer of sugar” (43). The pharmaceutically active parts of the gymnema plant are the leaves and roots. See Figure 8 for an image of the gymnema plant (44).

 

FIGURE 8. GYMNEMA PLANT IMAGE SOURCE: https://commons.wikimedia.org/wiki/File:Gymnema_sylvestre_R.Br_-_Flickr_-_lalithamba.jpg.

 

Mechanism of Action

 

The active constituents of gymnema appear to be gymnemosides, saponins, stigmasterol, and various amino acid derivatives. In terms of glucose lowering, it appears gymnema reduces intestinal absorption of glucose. It may also increase enzymes that promote cellular glucose update. It is hypothesized gymnema impacts beta cells – particularly by increasing cell quantity and by stimulation of insulin release (45-47).

 

Evidence

 

In 2023, a systematic review and meta-analysis of six studies sought to determine the impact of gymnema on various cardiometabolic risk factors, including glycemic control. Participants had T2DM, metabolic syndrome, and/or impaired glucose tolerance. Fasting blood glucose significantly changed by -4.96 mg/dL (CI 95%: -7.65 to -2.27, p<0.001). HbA1c had a non-significant change of -1.78% (95% CI: -4.09 to 0.53, p=0.131). Results are shown in Table 7 (48).

 

Table 7. 2023 Gymnema Systematic Review and Meta-Analysis Results (48)

Parameter

Weighted Mean Difference

(95% CI)

p-value

Weighted Mean Difference

Heterogeneity

(I2)

p-value Heterogeneity

HbA1c

-1.78% (-4.09 to 0.53

0.131

98.9%

< 0.01

Fasting blood glucose

-4.96 mg/dL (-7.65 to -2.27)

<0.001

97.0%

< 0.01

 

An earlier systematic review and meta-analysis of ten studies (n=419) aimed to determine the effect of gymnema on glycemic control in individuals with T2DM. The study found that gymnema significantly reduced fasting blood glucose by 1.57 mg/dl (CI 95%: -2.22 to -0.93, p < .0001) and postprandial blood glucose by 1.04 mg/dl (CI 95%: -1.53 to -0.54, p < .0001). HbA1c was reduced by 3.91% (CI 95%: -7.35 to -0.16%, p < .0001), however heterogeneity did not show significance (see Table 8) (49). 

 

Table 8. 2021 Gymnema Systematic Review and Meta-Analysis Results (49)

Parameter

Weighted Mean Difference

(95% CI)

Heterogeneity

(I2)

p-value Heterogeneity

HbA1c

-3.91% (-7.35 to -0.16%,)

99%

>0.05

Fasting blood glucose

-1.57 mg/dl (-2.22 to -0.93

90%

< 0.01

Postprandial glucose

−1.04 mg/dl (-1.53 to -0.54)

80%

< 0.01

 

Gymnema was studied in 64 patients with type 1 diabetes in an open-label, non-randomized, controlled trial. The study group received 200 mg twice daily of a water-soluble extract of gymnema by mouth for 6 to 60 months. All participants remained on insulin throughout the duration of the study. Insulin requirements were reduced by 50% in those in the gymnema group. Additionally, blood glucose and HbA1c levels were reduced (50).

 

An open-label and non-randomized trial studied gymnema in 47 patients with T2DM. In addition to conventional oral hypoglycemic agents, 400 mg of a water-soluble extract of gymnema was administered for 18 to 20 months to 22 of the participants.  At the conclusion of the study, the gymnema group had significantly lower fasting glucose (29% reduction, p<0.001). HbA1c levels were also significantly (p<0.001) lower in the gymnema group (baseline 11.9% to 8.48%). Results are summarized in Table 9 (51).

 

Table 9. Effect of Gymnema on Patients with Type 2 Diabetes Mellitus (51)

 

Gymnema Group

Control Group

 

Baseline

18-20 months

p-value

Baseline

18-20 months

p-value

Fasting blood glucose (mg/dL)

 174 ± 7

 124 ± 5

<0.001

 150 ± 4

157 ± 4

>0.05

HbA1c (%)

11.91 ± 0.30

 8.48 ± 0.13

<0.001

 10.24 ± 0.15

 

 10.47 ± 0.14

>0.05

 

Adverse Effects and Warnings

 

A case of acute hepatitis secondary to gymnema use has been reported (43).

 

Interactions

 

Gymnema may potentiate the effects of other agents that lower glucose. There is evidence to suggest gymnema can inhibit and induce certain liver enzymes. For example, gymnema may inhibit cytochrome P450 (CYP) 1A2 and increase circulating levels of medications such as clozapine, cyclobenzaprine, mexiletine, olanzapine, propranolol, theophylline, and zolmitriptan. Gymnema may induce CYP 2C9 and decrease levels of concurrently used medications such as nonsteroidal anti-inflammatory drugs, glipizide, losartan, and warfarin (51).

 

Summary

 

Gymnema has been long used in Ayurvedic medicine. It is thought to lower blood glucose via multiple mechanisms. There are minimal human studies evaluating gymnema’s efficacy, but preliminary evidence shows promise.

 

Insulin Sensitizers

 

The natural products contained in this section are known to be insulin sensitizers. This means they improve the sensitivity of cells to the effects of insulin. Products may also employ other mechanisms of action, which are addressed.

 

AMERICAN GINSENG (PANAX QUINQUEFOLIUS)

 

American ginseng is from the Panax genus. While named similarly, American ginseng (Panax quinquefolius) is different from Asian ginseng (Panax ginseng). American ginseng, as its name suggests, is found mostly in North America and is considered endangered in some areas (53). Currently in the United States, only eighteen states allow for the harvesting of American ginseng. See Figure 9 for an image of the American ginseng plant (54).

 

FIGURE 9. AMERICAN GINSENG PLANT IMAGE SOURCE: https://commons.wikimedia.org/wiki/File:American-ginseng-with-fruit.jpg.

 

Mechanism of Action

 

The root of the American ginseng plant is the portion that exerts a pharmaceutical effect. Saponins, specifically ginsenosides, are hypothesized to reduce glucose levels 55-57). The primary mechanism is thought to be insulin sensitization, but increased insulin secretion and prevention of beta-cell loss may also play a role (56, 57).

 

Evidence

 

Vuksan and colleagues performed a randomized, double-blind, cross-over trial to evaluate the efficacy and safety of American ginseng as complementary therapy in patients with T2DM using conventional therapy. Participants (n=24) received either 1 g of American ginseng extract or placebo for 8-weeks while continuing their original conventional therapies. After a 4-week washout period, participants were crossed over to the opposite 8-week treatment arm. American ginseng reduced HbA1c by 0.29% (p = 0.041) and plasma blood glucose by 12.8 mg/mL (p=0.008). The safety parameters studied, liver and kidney function, were not affected (58). 

 

Vuksan and colleagues performed a randomized, single-blind, controlled study in ten patients to evaluate the efficacy of various doses of American ginseng. Participants received either placebo or 3, 6, or 9 g of American ginseng prior to a 25-g oral glucose challenge. Capillary glucose was measured during the study duration. Compared to placebo, American ginseng significantly decreased glucose (p<0.05) for the 3, 6, and 9 g doses. Glucose area under the curve was also reduced (19.7% for the 3 g dose, 15.3% for the 6 g dose, and 15.9% for the 9 g dose). There was no difference between the various American ginseng doses (56).

 

Due to concern over varying ginsenoside concentrations in different products, a follow up study was completed. The objective of this study was to determine the efficacy of American ginseng with a different ginsenoside profile. Twelve participants received 6 g of American ginseng or placebo after a 75-g oral glucose load. There was no significant difference in venous blood glucose levels at -40, 0, 15, 30, 45, 60, 90, and 120 minutes between the groups. There was also no difference in plasma insulin levels. The American ginseng used in this study contained 1.66% total ginsenosides with the breakdown being 0.90% protopanaxodiol ginsenosides (PPD) and 0.75% protopanaxatriol ginsenosides (PPT) (59).

 

Adverse Effects and Warnings

 

Headache is the most common side effect reported with American ginseng use (60).

 

American ginseng should not be confused for Asian ginseng (Panax ginseng), Siberian ginseng (Eleutherococcus senticosus) (53).

 

Interactions

 

American ginseng may stimulate immune function and may theoretically decrease the effect of immunosuppressants (61).

 

American ginseng can decrease the efficacy of warfarin. Concomitant use is not advised (62).

 

As American ginseng can lower glucose, it should be used cautiously with other glucose lowering agents (56). 

 

Summary

 

Limited trials suggest American ginseng (Panax quinquefolius) may lower blood glucose. However, variability of product ginsenoside profile can impact efficacy. Concomitant warfarin use is not recommended due to decreased warfarin effectiveness. American ginseng is often confused with Asian (Panax ginseng) or Siberian ginseng (Eleutherococcus senticosus).

 

BANABA (LAGERSTROEMIA SPECIOSA)

 

Banaba is a natural product with multiple mechanisms. It was previously covered in the “Hypoglycemia Agents” section.

 

BERBERINE

 

Berberine is a bitter tasting plant alkaloid extracted from various plants. Goldenseal, goldthread, Oregon grape, European barberry, phellodendron, and tree turmeric are all sources. See Figure 10 for an image of European barberry, a source of berberine. Berberine is used for glucose lowering, dyslipidemia, hypertension, and infections (63, 64).

 

FIGURE 10. EUROPEAN BARBERRY (BERBERIS VULGARIS) – BERBERINE IMAGE SOURCE: https://commons.wikimedia.org/wiki/File:Berberis_vulgaris_%27Atropurpurea%27_003.JPG.

 

Mechanism of Action

 

Berberine’s glucose lowering properties are thought to be from increased insulin secretion, increased glycolysis, increased levels of GLUT-4 and GLP-1, activation of PPAR gamma receptors, and alpha-glucosidase inhibition (65-68).

 

Evidence

 

The effect of berberine on metabolic profiles in patients with T2DM was studied in a systematic review and meta-analysis. Thirty-seven randomized controlled trials with 3,048 patients were included.  with at least 60 participants over the age of 18 were included. Compared to the control group, berberine was associated with a significant reduction in fasting plasma glucose (-14.8 mg/dL; 95% CI: -17.1 to -0.12.6; p<0.05), HbA1c (-0.63%; 95% CI: -0.72 to -0.53; p<0.05), and two-hour post prandial blood glucose (-20.9 mg/dL; 95% CI: -24.5 to -17.3; p<0.05). There was significant heterogeneity with each of the three outcomes. Adverse effects were included in 14 of the included studies. Analysis revealed incidence of adverse effects was lower with berberine compared to the control groups. Hypoglycemia was reported in nine studies with no significant difference between the berberine and control groups (fixed effects model; RR = 0.48; 95% CI: 0.21 to 1.08; p = 0.08). Results are presented in Table 10 (69).

 

Table 9. Berberine Systematic Review and Meta-Analysis Results (69)

Parameter

Weighted Mean Difference

(95% CI)

Heterogeneity

(I2)

p-value Heterogeneity

HbA1c

-0.63% (-0.72 to -0.53)

52%

< 0.001

Fasting blood glucose

14.8 mg/dL (-17.1 to -0.12.6)

60%

< 0.00001

Postprandial glucose

-20.9 mg/dL (-24.5 to -17.3)

68%

< 0.001

 

The analysis also concluded that berberine alone or in combination with oral hypoglycemic agents did not significantly increase the incidence of total adverse events (RR = 0.73; 95% CI: 0.55 to 0.97; p = 0.03) and the risk of hypoglycemia (RR = 0.48, 95% CI 0.21 to 1.08; p = 0.08).

 

Berberine has also been studied in a randomized controlled trial compared to metformin, a medication in the biguanide class. In this study, 36 patients that were recently diagnosed with T2DM were randomized to either berberine 500 mg three times daily or metformin 500 mg three times daily for three months. In the berberine group, HbA1c decreased from 9.5 ± 0.5% to 7.5 ± 0.4% (p<0.01). Fasting blood glucose changed from 191 ± 16 mg/dL to 124 ± 9 mg/dL (p<0.01). Postprandial glucose also decreased from 357 ± 31 mg/dL to 214 ± 16 mg/dL (p<0.01). These differences were similar to metformin. At the end of the trial, the HbA1c lowering effect of berberine was similar to metformin (70).

 

Adverse Effects and Warnings

 

Gastrointestinal side effects are most common with berberine (diarrhea, constipation, flatulence, abdominal pain, and vomiting).

 

Uterine contractions are an adverse effect of berberine. Berberine is also thought to cross the placenta and neonatal kernicterus may result when ingested during pregnancy. Use in pregnancy is not recommended. Berberine can be transferred through breastmilk (71, 72).

 

Interactions

 

Berberine may inhibit cytochrome P450 3A4, 2D6, and 2C9 and should be used cautiously with other agents that are substrates, inhibitors, or inducers of these hepatic enzymes. Of note, cyclosporine levels can be increased and concomitant use is not advised.

 

As berberine lowers glucose, caution should be exercised when used with other agents that lower glucose. Berberine may increase the risk of bleeding when used with anticoagulants (64).

 

Summary

 

Berberine is an alkaloid extract derived from various plants. There is evidence to suggest berberine lowers fasting glucose, postprandial glucose, and HbA1c. Berberine may cause uterine contractions and kernicterus so should be avoided during pregnancy. There is concern that berberine inhibits several CYP enzymes and may contribute to multiple drug interactions.

 

CHROMIUM

 

Chromium is a mineral essential to humans. It is found naturally in brewer’s yeast (where it was first discovered), oysters, mushrooms, liver, potatoes, beef, cheese, and fresh vegetables. Chromium exists in two valences – trivalent and hexavalent. Trivalent chromium (Cr+3 or Cr III) is the biologically active form found in food and supplements. Hexavalent chromium (Cr+6 of Cr VI) is a toxic manufacturing byproduct and may cause lung cancer, dermatologic issues, and perforated nasal septum with chronic exposure (73, 74). Chromium in this section will refer to the commercially available trivalent chromium.

 

Chromium may be referred to as glucose tolerance factor (74, 75). However, glucose tolerance factor is a complex that contains, amongst other molecules, chromium. There is an apparent association between low chromium levels and impaired glycemic control (76).

 

The Food and Nutrition Board of the Institute of Medicine determined there was not sufficient evidence to set an Estimated Average Requirement for chromium consumption. However, they did suggest Adequate Intake (AI) levels. For adults, the AI is 35 mcg per day for men and 25 mcg per day for women. Due to the fact few serious adverse effects are associated with excess chromium from food, there is no designated Tolerable Upper Intake Level (74).

 

Chromium is typically found in the chloride, nicotinate, and picolinate salt forms. It is thought the picolinate salt is absorbed by humans best (73, 77).

 

Mechanism of Action

 

The exact mechanism of chromium has not been elucidated. Chromium has an insulin sensitizing effect by reducing the content and activity of the tyrosine phosphatase PTP-1B (78). Alternatively, chromium might act directly on the insulin receptor (79, 80).

 

Evidence

 

Despite plausible mechanisms of action, there is mixed evidence surrounding chromium for the treatment of diabetes (75, 81).

 

A systematic review and meta-analysis of ten studies (n=509) was published in 2021 to determine the effect of chromium supplementation on blood glucose and lipid levels in patients with T2DM. The weighted mean difference in HbA1c indicated a significant reduction in HbA1c (-0.54%; 95% CI: -0.98 to -0.09; p = 0.02). No difference in fasting plasma glucose was found (-29.65 mg/dL; 95% CI: -68.62 to 9.31; p=0.14). There was no difference found in triglycerides, total cholesterol, low-density lipoproteins, and high-density lipoproteins. Results are summarized in Table 10 (82).

 

Table 10. 2021 Meta-Analysis Results of the Effect of Chromium on Glycemic Control in Patients with Diabetes (82)

Parameter

Weighted Mean Difference

(95% CI)

Heterogeneity

(I2)

p-value Heterogeneity

HbA1c

-0.54% (-0.98 to -0.09)

84%

< 0.01

Fasting blood glucose

-29.65 mg/dL (-68.62 to 9.31)

97%

< 0.00001

 

A meta-analysis of 28 randomized controlled studies aimed to investigate the effect of chromium on glycemic control in patients with T2DM was published in 2020. The revealed significant reductions in HbA1c (-0.71%; p = 0.004) and fasting blood glucose (-19.0 mg/dL; p = 0.030) with chromium use. Insulin levels (-12.35 pmol/L, p <0.001) and homeostatic model assessment for insulin resistance (HOMA-IR) were also significantly lower with chromium. HOMA-IR levels decreased by 1.53 (p <0.001). There was significant heterogeneity between studies for HbA1c, fasting blood glucose, insulin, and HOMA-IR. Results are shown in Table 11 (83).

 

Table 11. 2020 Meta-Analysis Results of the Effect of Chromium on Glycemic Control in Patients with Diabetes (83)

Parameter

Weighted Mean Distribution

(95% CI)

p-value Weighted Mean Distribution

Heterogeneity

(I2)

p-value Heterogeneity

p-value Begg’s test

HbA1c (%)

-0.71

(-1.19 to -0.23)

0.004

99.2%

<0.001

0.143

 

Fasting blood glucose (mg/dL)

-19.0

(-36.15 to -1.85)

0.030

99.8%

<0.001

0.086

 

Insulin level (pmol/L)

-12.35

(-17.86 to -6.83)

<0.001

98.1%

<0.001

0.363

 

HOMA-IR

-1.53

(-2.35 to -0.72)

<0.001

89.9%

<0.001

0.466

 

 

Another meta-analysis of 25 randomized controlled trials evaluating the efficacy of chromium supplementation was published in 2014. Of these trials, 22 studied chromium monosupplementation, while two trials studied chromium in combination with biotin and one trial studied chromium with vitamins C and E. Trial duration varied from four to 24 weeks. In the 14 included trials that assessed HbA1c, there was a statistically significant change of -0.55% (95% CI: -0.88 to -0.22). Twenty-four studies evaluated fasting glucose and the pooled mean change was -20.7 mg/dL (95% CI: -33.1 to -8.5). Monosupplementation with chromium significantly decreased triglycerides (-26.6 mg/dL; p=0.002) and increased high density lipoprotein concentration (4.6 mg/dL; p=0.01). There was no change in total cholesterol or low-density lipoprotein concentrations. The meta-analysis authors concluded chromium supplementation had favorable effects on HbA1c and fasting glucose in patients with diabetes (75). Results from this meta-analysis are presented in Table 12.

 

Table 12. Meta-Analysis Results of the Effect of Chromium on Glycemic Control in Patients with Diabetes (75)

Parameter

Pooled Mean Difference (95% CI)

Heterogeneity P-Value

HbA1c (%)

-0.55% (-0.88 to -0.22)

<0.00001

Fasting glucose (mg/dL)

-20.7 mg/dL (-33.1 to -8.5)

<0.00001

 

A meta-analysis from 2002 of 15 randomized controlled trials was conducted to determine the efficacy of chromium on glycemic control. Doses in the included trials ranged from 10 to 1,000 micrograms of chromium daily and varied in terms of source (brewer’s yeast, chromium chloride, chromium nicotinate, chromium picolinate, or chromium-niacin). Study duration ranged from one to 16 months. In terms of fasting glucose, 14 studies and 463 patients were included (n=38 with diabetes and n=425 without diabetes). For all included patients, the fasting glucose pooled mean difference was 0.5 mg/dL (95% CI: -1.6 to 2.7) with no evidence of heterogeneity (p=0.97).  The effect of chromium supplementation on two-hour OGTT results were included in five of the 14 trials. The majority of patients did not have a diabetes diagnosis (n=133 versus 8 with a diabetes diagnosis). The pooled mean difference was 4.7 mg/dL (95% CI, -4.3 to 13.7) with no evidence of heterogeneity (p=0.98). Fasting insulin levels were recorded in 10 of the studies (8 patients with diabetes and 326 without diabetes). The pooled mean difference in fasting insulin with chromium use was 0.28 pmol/L (95% CI, -7.0 to 7.5, heterogeneity p=0.097). Three of the trials assessed HbA1c (33 healthy subjects, 24 with glucose intolerance, and 155 with diabetes). There was no association between chromium supplementation and HbA1c in the study of healthy subjects. The single study that included subjects with glucose intolerance showed chromium supplementation was associated with a nonsignificant reduction in HbA1c (mean difference -0.30%; 95% CI: -0.86 to 0.25). The study that included subjects with diabetes showed a reduction in HbA1c for different chromium doses (mean difference for 1000 micrograms: -1.90%; 95% CI: -2.34 to -1.46; mean difference for 200 micrograms: -1.00%; 95% CI: -1.55 to -0.45). Data from the meta-analysis is presented in the following table. The authors of the meta-analysis concluded there was no effect of chromium on glucose or insulin concentrations in subjects without diabetes. The data for those with diabetes was inconclusive. Table 13 summarizes these results (81).

 

Table 13. Meta-Analysis Results of the Impact of Chromium on Glycemic Control (81)

Parameter

Number of Studies

N Patients with Diabetes

N Patients without Diabetes

Chromium Supplementation Pooled Mean Difference (95% CI)

Heterogeneity p Value

Fasting glucose (mg/dL)

14

38

425

0.5 (-1.6 to 2.7)

0.97

2-hour glucose tolerance test (mg/dL)

5

8

133

4.7 (-4.3 to 13.7)

0.98

Fasting insulin (pmol/L)

10

8

326

0.28 (-7.0 to 7.5)

0.097

 

Adverse Effects and Warnings

 

Trivalent chromium has demonstrated safety in large doses (74, 75). The picolinate form may cause cognitive, perceptual, and moto dysfunction (84).

 

Hexavalent chromium is toxic and is listed as a known carcinogen (74).

           

Interactions

 

There is a theoretical interaction between chromium and iron (74).

 

Summary

 

Chromium is a mineral essential to humans and may be referred to as glucose tolerance factor. There is conflicting evidence in terms of efficacy. Meta-analyses published in 2020 and 2014 suggested chromium decreased HbA1c and fasting glucose in patients with diabetes. Another meta-analysis published in 2002 found chromium to have no impact on glycemic control in those without diabetes. 

 

CINNAMON (CINNAMOMUM AROMATICUM, CINNAMOMUM CASSIA)

 

Cinnamon is a natural product derived from the dried inner bark of the evergreen tree. It is commonly used in many cuisines. Cinnamon commonly found in grocery stores for culinary purposes is usually Cinnamomum cassia, but may be Ceylon cinnamon (85, 86).

 

Mechanism of Action

 

Procyanidin polymers appear to be responsible for cinnamon’s insulin sensitizing actions. It is hypothesized that these compounds increase phosphorylation of the insulin receptor, therefore, increasing sensitivity to insulin. Cinnamon may also stimulate insulin release and increase GLP-1 and GLUT-4 levels. Evidence also suggests cinnamon increases cellular glucose uptake (87-90).

 

Evidence

 

Cinnamon has shown mixed results in various trials in patients with diabetes (91-94).

 

In 2012, a Cochrane Review was published evaluating the effectiveness of cinnamon in patients with T2DM. The primary outcomes included fasting glucose, postprandial glucose, and adverse effects. Change in HbA1c was a secondary outcome. There was no change in fasting glucose (-1.4 mg/dL; 95% CI: -6.1 to 3.2), post-prandial glucose (-7.0; 95% CI: -14.9 to 0.9), or HbA1c (-0.06%; 95% CI: -0.29 to 0.18]. There was no difference in adverse effects between users and non-users of cinnamon (OR 0.83; 95% CI: 0.22 to 3.07), p = 0.77; n = 264; 4 trials). Table 14 presents the results from this review (95).

 

Table 14. Cochrane Review Results of the Effect of Cinnamon on Glycemic Control in Patients with Diabetes (95)

Parameter

Weighted Mean Distribution

(95% CI)

p-value Weighted Mean Distribution

Heterogeneity

(I2)

Number of Trials

HbA1c (%)

-0.06%

(-0.29 to 0.18)

0.63

0%

6

Fasting blood glucose (mg/dL)

-1.4

(-6.1 to 3.2)

0.06

0%

8

 

Postprandial glucose (mg/dL)

-7.0

(-14.9 to 0.9)

0.08

n/a

1

 

 

More recently, a systematic review and meta-analysis by Moridpour and colleagues was published in 2024 that aimed to assess the effects of cinnamon supplementation in managing glycemic control in patients with T2DM. Twenty-four randomized controlled trials were included. The pooled results indicated cinnamon had a statistically significant (p<0.05) reduction in fasting blood glucose (-1.32 mg/dL; 95 % CI: -1.77 to -0.87; p<0.001), HbA1c (-0.67%; 95 % CI: -1.18 to -0.15; p=0.011), and HOMA-IR (-0.44; 95 % CI: -0.77 to -0.10; p<0.001). Results are summarized in Table 15 (94).

 

Table 15. Systematic Review and Meta-Analysis of the Effect of Cinnamon on Glycemic Control in Patients with Diabetes (94)

Parameter

Weighted Mean Distribution

(95% CI)

p-value Weighted Mean Distribution

Heterogeneity

(I2)

p-value

Heterogeneity

Number of Trials

Fasting blood glucose (mg/dL)

-1.32

(-1.77 to -0.87)

<0.001

94.0%

<0.001

 

23

 

HbA1c (%)

-0.67%

(-1.18 to -0.15)

0.011

94.7%

<0.001

18

HOMA-IR

-0.44

(-0.77 to -0.10)

<0.001

79.1%

<0.001

 

8

 

A systematic review and meta-analysis by Deyno and colleagues was published to evaluate the efficacy of cinnamon in patients with type 2 diabetes mellitus and pre-diabetes. Sixteen randomized controlled studies were included in the meta-analysis. There was no significant change in weighted mean difference of HbA1c and lipid profiles. There was, however, a statistically significant difference in fasting blood glucose and HOMA-IR. High heterogeneity was observed in the included studies and cinnamon doses ranged from 1 g to 14.4 g a day. Results can be found in Table 16 (96).

 

Table 16. Meta-Analysis Results for the Effect of Cinnamon on Glycemia and Lipoprotein Levels (96)

Parameter

Weighted Mean Difference (95% CI)

Heterogeneity

(I2)

Glycemic

 

Fasting plasma glucose (mg/dL)

-9.8 (-16.4 to -3.2)

83.6%

HbA1c (%)

-0.104 (-0.138 to 0.110)

69.6%

HOMA-IR

-0.714 (-1.388 to -0.04)

84.4%

Lipoprotein

 

Total Cholesterol (mg/dL)

-3.6 (-7.3 to 0.2)

86.4%,

Low density lipoprotein concentration (mg/dL)

-2.1 (-4.9 to 0.7)

86.0%

High density lipoprotein concentration (mg/dL)

-0.1 (-1.1 to 0.9)

81.0%

Triglycerides (mg/dL)

-1.8 (-4.0 to 0.4)

69.0%

 

A randomized, double-blind, placebo-controlled trial evaluated the effect of cinnamon on 66 Chinese patients with type 2 diabetes (HbA1c greater than 7% and fasting glucose greater than 144 mg/dL). Patients were not receiving insulin or other glucose-lowering agents aside from glicazide, a sulfonylurea, of which all participants were taking 30 mg daily. Patients were randomized to 120 mg daily of cinnamon, 360 mg daily of cinnamon, or placebo for 12 weeks. Both the 120 mg and 360 mg cinnamon groups experienced significantly lower HbA1c and fasting plasma glucose measurements. There was no significant change in either parameter for the placebo group. Results are provided in Table 17 (97).

 

Table 17. Effect of Various Cinnamon Doses on Glycemic Parameters (97)

 

Cinnamon 120 mg Daily Group

Cinnamon 360 mg Daily Group

Placebo Group

Change in HbA1c (%) (95% CI)

-0.67 (-1.1 to -0.25)

-0.93 (-1.38 to -0.47)

0.00 (-0.61 to 0.61)

Change in fasting plasma glucose (mg/dL) (95% CI)

-18.4 (-29.0 to -7.57)

-29.2 (-41.8 to -16.8)

-3.96 (-24 to 16)

 

Adverse Effects and Warnings

 

Cinnamon is typically tolerated well (98-100).

 

Cinnamon is a natural source of coumarin and use therefore presents a theoretical risk of hepatic injury (101).

 

Interactions

 

Due to concerns of hepatic injury when large doses of cinnamon are used, use cautiously with other hepatotoxic agents.

 

Cinnamon may decrease glucose levels and should be used cautiously with other agents that lower glucose.

 

Summary

 

Cinnamon is derived from the dried inner bark of evergreen trees and is commonly used as a spice in cuisine. In terms of glycemic lowering, cinnamon studies have shown varying results. A 2012 Cochrane review found cinnamon to be no more effective than placebo; a 2024 meta-analysis found cinnamon to have statistically significant improvements on fasting plasma glucose and HbA1c. Cinnamon is typically well tolerated.

 

GYMNEMA (GYMNEMA SYLVESTRE)

 

Gymnema has multiple mechanisms of action is addressed under the “Hypoglycemic Agents” section.

 

MILK THISTLE (SILYBUM MARIANUM)

 

Milk thistle (Silybum marianum) is a member of the aster family which also includes daisies and thistles (102). The plant itself is edible and was native to Europe before introduction to North America. Currently, milk thistle is found in Europe, North America, India, China, South America, Africa, and Australia (103).

 

Milk thistle has a long history of medicinal use. Use dates back to the time of ancient Greece. Milk thistle is used for diabetes, liver support, and menstrual support. An image of the milk thistle plant can be found in Figure 11 (103, 104).

 

FIGURE 11. MILK THISTLE PLANT IMAGE SOURCE: https://commons.wikimedia.org/wiki/File:(1)_Milk_thistle.jpg.

 

Mechanism of Action

 

The mechanism of action of milk thistle for glycemic control is not fully understood. The pharmaceutically active portions of the plant are the seeds and the above ground portions. Milk thistle seed extract is comprised primarily (up to 80%) of silymarin. Silymarin contains various flavonolignans, the most active being silybin or silibinin (102, 103, 105, 106).

 

Silymarin decreases insulin resistance and may have a protective pancreatic effect through a mechanism thought to involve antioxidant properties (107, 108). Some studies suggest that silymarin may also regenerate pancreatic beta cells and enhance insulin sensitivity of liver and muscle cells (106). Carbohydrate-induced glycolysis is decreased by silibinin through pyruvate kinase inhibition (103, 109).

 

Evidence

 

Milk thistle has been studied in randomized controlled trials. Soleymani and colleagues published a meta-analysis of 30 studies to determine the effects of milk thistle on cardiometabolic syndrome. Adults (with and without diabetes) were included. The study demonstrated that milk thistle significantly reduced the levels of fasting plasma glucose (WMD: -17.96 mg/dL; 95% CI: -32.91 to -3.02); HbA1c (WMD: -1.25%; 95% CI: -2.34 to -0.16); total cholesterol (WMD: -17.46 mg/dL; 95% CI: -30.98 to -3.95); triglycerides (WMD: -25.70 mg/dL; 95% CI: -47.23 to -4.17); low-density lipoproteins (WMD: -10.53 mg/dL; 95% CI: -19.12 to -1.94). High-density lipoprotein levels increased (WMD: 3.36 mg/dL; 95% CI: 0.88 to 5.84). There was no difference in BMI. The majority of patients included in the meta-analysis had type 2 diabetes mellitus. Results are summarized in Table 18 (106).

 

Table 18. Effect of Various Cinnamon Doses on Glycemic Parameters (106)

Parameter

Weighted Mean Difference (95% CI)

p-value

Weighted Mean Difference

Heterogeneity

(I2)

p-value

Heterogeneity

Glycemic

Fasting plasma glucose (mg/dL)

-17.96

(-32.91 to -3.02)

<0.05

82.4%

<0.001

HbA1c (%)

-1.25% (-2.34 to -0.16)

<0.05

92.9%

<0.001

Lipoprotein

Total Cholesterol (mg/dL)

-17.46 (-30.98 to -3.95)

<0.05

62.9%

0.006

Low density lipoprotein concentration (mg/dL)

-10.53 (-19.12 to -1.94)

<0.05

37.5%

0.119

High density lipoprotein concentration (mg/dL)

3.36 (0.88 to 5.84)

<0.05

81.0%

 

Triglycerides (mg/dL)

-25.70 (-47.23 to -4.17)

<0.05

54.3%

0.025

Body Mass Index (kg/m2)

0.07 kg (-0.7, 0.83)

>0.05

0%

0.94

 

In 2020, a meta-analysis was published to evaluate the efficacy and safety of milk thistle in patients with glucose or lipid metabolic dysfunction. Sixteen studies (n=1358) were included in the analysis. Fasting blood glucose levels and HbA1c were reduced significantly in milk thistle users compared to placebo. There was no difference between the groups in liver enzymes, creatinine phosphokinase, or creatinine. Results are shown in Table 19 (110).

 

Table 19. Effect of Silymarin on Glucose and Lipid Parameters (110)

Parameter

Weighted Mean Difference (95% CI)

p-value

Glycemic

Fasting plasma glucose (mg/dL)

-22.9 mg/dL (-32 to -13.7)

<0.001

HbA1c (%)

-1.88 (-2.57 to -1.20)

<0.001

 

A meta-analysis of trials was published in 2011 that evaluated the impact of milk thistle on glycemic control in patients with type 2 diabetes. Two studies (n=89) were identified that met analysis criteria. The mean pooled difference in fasting glucose was -38.1 mg/dL (95% CI: -66.6 to -9.5). The mean pooled difference in HbA1c was -1.92% (95% CI: -3.32 to -0.51). Heterogeneity for both had p-values of less than 0.05. The authors concluded milk thistle may improve glycemic control in patients with type 2 diabetes.

 

The two studies included in the aforementioned meta-analysis each individually showed statistically significant change in fasting glucose as well as HbA1c (107, 111). Results are shown in the Tables 20 and 21.

 

Table 20. The Effect of Milk Thistle on Glycemic Control (107)

Parameter

Milk Thistle Treatment (SD)

Control (SD)

P-Value

Fasting glucose (mg/dL)

133 (39)

188 (48)

0.001

HbA1c (%)

6.8 (1.1)

9.5 (2.2)

0.001

 

Table 21. The Effect of Milk Thistle on Fasting Glucose and HbA1c (111)

Parameter

Milk Thistle Treatment (SD)

Control (SD)

P-Value

Fasting glucose (mg/dL)

167.58 (9.9)

193.14 (16.1)

<0.01

HbA1c (%)

7.45 (0.8)

8.71 (0.63)

<0.05

 

Milk thistle has also been studied in combination with berberine. The combination of the two was more effective than berberine alone in reducing HbA1c in type 2 diabetes patients (112).

 

Adverse Effects and Warnings

 

Milk thistle is typically well tolerated. Side effects include nausea, diarrhea, and abdominal bloating (113).

 

As milk thistle is a member of the aster family, cross reactivity may exist with other plants. Those with a daisy or ragweed allergy may experience a cross reaction with milk thistle use (102).

 

Interactions

 

Milk thistle may inhibit certain cytochrome P450 isoenzymes. The isoenzymes 2C8, 2C9, 2D6, 3A4, and 3A5 may all be inhibited with concomitant use (114, 115).

 

As milk thistle may lower glucose levels, it should be used cautiously with other hypoglycemia agents. Increased warfarin levels may occur with concomitant use (116).

 

Summary

 

Milk thistle is a member of the aster family and is used for lowering glucose, liver support, and menstrual support. There is modest evidence to suggest milk thistle may lower glucose in patients with diabetes.

 

PRICKLY PEAR CACTUS (OPUNTIA FICUS-INDICA AND OTHER OPUNTIA SPECIES), NOPAL

 

Prickly pear cactus is native to Mexico and found widely in the southwestern United States, Africa, Australia, and the Mediterranean. The berries of the cactus are oval, edible, and may vary in color (117, 118). Prickly pear cactus has been used historically in Mexican cultures as a treatment for type 2 diabetes. Figure 12 illustrates the prickly pear cactus plant (119).

 

FIGURE 12. PRICKLY PEAR CACTUS PLANT IMAGE SOURCE: https://commons.wikimedia.org/wiki/File:Prickly_pear_cactus_in_Texas.jpg.

 

Mechanism of Action

 

Much of the prickly pear cactus plant is pharmaceutically active – the leaves, flowers, stems, and fruit are all thought to exert an effect. The plant contains carbohydrate, protein, fat, and fiber (120). It is thought prickly pear cactus lowers glucose by acting as an insulin sensitizer and by slowing carbohydrate absorption (117, 120, 121).

 

Evidence

 

A systematic review that included 20 articles investigated the effects of various parts of the prickly pear cactus plant on glucose and insulin. Studies that used prickly pear cactus fruit generally did not impact serum glucose or insulin. Studies that used the cladode portion of the plant (flat, leaf-like stem) predominantly demonstrated reductions in glucose and insulin (122).

 

A randomized, double-blind, placebo-controlled study was conducted to evaluate and effect of prickly pear cactus in obese patients with pre-diabetes. Patients received either 200 mg of a proprietary prickly pear product (n=15) or placebo (n=14). Patients underwent two different oral glucose tolerance tests – one without prickly pear cactus to determine baseline values and one half an hour after prickly pear cactus ingestion. There was a significant difference (p<0.05) in plasma glucose concentrations at 60, 90, and 120 minutes following the glucose tolerance test for the prickly pear cactus group. There was no difference in HbA1c, insulin levels, high sensitivity C-Reactive Protein, body weight, or fat mass. There was also no difference in comprehensive metabolic profile parameters (123).

 

Most prickly pear cactus trials were published in Spanish only with abstracts available in English. Two trials showed a decrease in postprandial glucose from prickly pear administration (124, 125). Another trial showed when added to a high-carbohydrate or high-soy-protein breakfast, prickly pear cactus decreased glucose area under the curve (126).

 

Adverse Effects and Warnings

 

Prickly pear cactus is generally tolerated well when used orally. Side effects include nausea, diarrhea, and headache (120).

 

Interactions

 

Prickly pear cactus may lower glucose levels and should be used cautiously with other agents that impact glycemic control (123, 126).

 

Summary

 

Prickly pear cactus was used historically in Mexican cultures and is gaining popularity. There is preliminary data to suggest prickly pear cactus may be effective in lowering glucose. Some parts of the plant, i.e., the cladode, may be more efficacious than others, i.e., fruit. However, more studies are needed to determine efficacy. Prickly pear cactus is usually well tolerated.

 

SOY (GLYCINE MAX)

 

Soy comes from the soybean, a legume originating from Asia. In fact, prior to the 1950s soybean was seldom grown outside of the region. Now soybeans are grown in other regions such as North and South America. Soybeans are used in various food preparations such as edamame, tofu, and soymilk. An image of a soybean plant can be found in Figure 13 (127.

 

FIGURE 13. SOYBEAN PLANT IMAGE SOURCE: https://pixabay.com/en/soy-soybean-nature-green-998566/.

 

Mechanism of Action

 

The portion of soy that is pharmaceutically active is the bean. Soybeans are protein-rich and contain calcium, iron, potassium, amino acids, vitamins, and fiber (128). Soybeans contain phytoestrogens (isoflavones and lignans) and phytosterols, which are biologically active (129. 130).

 

Soy works via various mechanisms. Soy has insulin sensitizing properties and may slow carbohydrate absorption due to its fiber content. It is hypothesized that the fiber content of soy helps reduce glucose levels (128, 131).

 

Evidence

 

Results on the efficacy of soy in type 2 diabetes are conflicting. A systematic review and meta-analysis summarizing the association of soy intake and the risk of type 2 diabetes was published in 2020. Fifteen studies were included (n = 565,810) and multivariable-adjusted relative risks were determined. The relative risk of incidence of type 2 diabetes was 0.83 (95% CI: 0.68 to 1.01; p>0.05) for total soy. The relative risk for soy milk was 0.89 (95% CI: 0.71 to 1.11; p>0.05); tofu was 0.92 (95% CI: 0.84 to 0.99; p<0.05); soy protein was 0.84 (95% CI: 0.75 to 0.95; p<0.05); and soy isoflavones was 0.88 (95% CI: 0.81 to 0.96; p<0.05). High heterogeneity was observed in the total soy (I2 = 90.8%) and soy milk (I2= 91.7%) categories. Inverse linear associations were observed for the tofu, soy protein, and soy isoflavone groups. The quality of evidence was rated as low for the total soy, soy milk, tofu, soy protein, and soy isoflavone groups. The study authors suggested dietary intake of tofu, soy protein, and soy isoflavones are inversely associated with type 2 diabetes incidence. They found no association between total soy intake and incidence of type 2 diabetes. The authors cautioned that the overall quality of evidence was low (132).

 

In 2020, Zuo and colleagues conducted a systematic review and meta-analysis regarding the intake of soy and the association with type 2 diabetes mellitus and cardiovascular disease events. The review included 29 studies with 16,521 individuals with T2DM and 54,213 individuals with cardiovascular disease events. The follow up duration of the studies ranged from 2.5 to 24 years. In groups with the highest soy consumption compared to the lowest soy consumption, there was a significant reduction in the risk of T2DM (17%; total relative risk [TRR] = 0.83; 95% CI: 0.74 to 0.93); cardiovascular disease events (13%; TRR = 0.87; 95% CI: 0.81 to 0.94); coronary heart disease (21%; TRR = 0.79; 95% CI: 0.71 to 0.88); and stroke (12%; TRR = 0.88; 95% CI: 0.79 to 0.99). Daily tofu intake of 26.7 g of reduced cardiovascular disease event risk by 18% (TRR = 0.82; 95% CI: 0.74 to 0.92) and daily intake of 11.1 g of natto lowered cardiovascular disease event risk by 17% (TRR = 0.83; 95% CI: 0.78 to 0.89). The authors concluded that soy consumption was negatively associated with the risk of developing T2DM and cardiovascular disease events (133).

 

In 2018, a meta-analysis was published that aimed to evaluate the efficacy of soy in preventing diabetes. Eight studies were included in the meta-analysis. Soy intake decreased the risk of type 2 diabetes with an overall risk reduction of 0.77 (95% CI: 0.66 to 0.97). Soy protein and isoflavone intake lowered the risk of diabetes with risk reduction of 0.77 (95% CI: 0.80 to 0.97). A subgroup analysis looked at the relationship of soy intake in women and Asian populations. Women had a risk reduction of 0.65 (95% CI: 0.49 to 0.87) and Asian populations had a risk reduction of 0.73 (95% CI: 0.61 to 0.88). The study authors concluded soy intake may be associated with a decreased risk of type 2 diabetes (134).

 

Yang and colleagues performed a meta-analysis evaluating the impact of soy on glycemic control and lipoproteins in patients with type 2 diabetes. Eight studies were included and found there was no association between soy consumption and fasting glucose and HbA1c. There was, however, a significant reduction in serum cholesterol, triacylglycerol, and LDL-C, associated with soy use (p<0.001 for all). The authors concluded there was no significant effect of soy on fasting glucose, insulin, or HbA1c, but there was a favorable effect on serum lipids (135).

 

Another meta-analysis was published in 2011 examining the impact of soy intake on glycemic control. Twenty-four trials were included (n=1,518). The pooled mean change in fasting glucose was -0.69 mg/dL (95% CI, -1.65 to 0.27). Fasting insulin concentrations decreased by 0.18 mg/dL (95% CI, -0.70 to 0.34). The authors concluded there was no significant overall effect of soy on fasting glucose and insulin, but there was a favorable change in studies that used whole soy foods or soy diet (136).

 

Adverse Effects and Warnings

 

Soy is generally well tolerated with side effects being nausea, diarrhea, and bloating. There is concern that soy may alter thyroid function, but this appears to occur in those with iodine deficiency (137-139).

 

Interactions

 

Fermented soy products such as tofu may contain small amounts of tyramine. Tyramine should be avoided in those using monoamine oxidase inhibitors (140). 

 

Summary

 

Soy comes from the soybean plant and contains phytoestrogens and phytosterols. There is some data to suggest soy consumption may decrease the risk of type 2 diabetes. Two meta-analyses showed soy did not significantly decrease fasting glucose of HbA1c in patients with type 2 diabetes. 

 

VANADIUM

 

Vanadium is a mineral found in food sources such as mushrooms, shellfish, black pepper, parsley, dill seed, and certain prepared foods. Beer and wine are also sources. Grains account for 13 to 30 percent of vanadium in adult diets (74).

 

Mechanism of Action

 

Vanadium increases sensitivity to insulin and may mimic insulin’s actions. It may stimulate glucose oxidation and transport, stimulate hepatic glycogen synthesis, inhibit hepatic gluconeogenesis, and increase glucose uptake. Vanadium inhibits phosphotyrosine phosphatase enzymes which impact the insulin receptor (141, 142).

 

Evidence

 

A systematic review of five trials (n=48) evaluated vanadium’s impact in glycemic control. Doses varied from 50 mg to 300 mg of vanadium over three to six weeks. All trials reported reductions in fasting glucose values. However, none of the trials included controls (85).

 

A study of vanadium’s role in glycemic control enrolled 11 patients with type 2 diabetes. Patients were treated with 150 mg of vanadyl sulfate (a salt form of vanadium) for 6 weeks. Treatment with vanadyl sulfate decreased fasting glucose from 194 mg/dL ± 16 to 155 mg/dL ± 15. There was no change in body weight. Patients had an increased rate of hepatic glucose production (HGP) compared with controls (4.1 ± 0.2 vs. 2.7 ± 0.2 mg/kg lean body mass/min; p< 0.001), which was closely correlated with fasting glucose (r = 0.56; p< 0.006). Vanadyl sulfate reduced HGP by about 20% (P < 0.01), and the decline in HGP was correlated with the reduction in FPG (r = 0.60; p<0.05). Vanadyl sulfate also caused a modest increase in insulin-mediated glucose disposal (from 4.3 ± 0.4 to 5.1 ± 0.6 mg/kg lean body mass/min; p< 0.03), although the improvement in insulin sensitivity did not correlate with the decline in fasting glucose after treatment (r = -0.16; p>0.05). Thus, vanadyl sulfate at a dose of 150 mg/day for 6 weeks improves hepatic and muscle insulin sensitivity in patients with type 2 diabetes. The glucose-lowering effect of vanadyl sulfate correlated well with the reduction in HGP, but not with insulin-mediated glucose disposal, suggesting that liver, rather than muscle, is the primary target of vanadyl sulfate action at therapeutic doses (143).

 

Li and colleagues conducted a case-control study to explore the association of plasma vanadium with gestational diabetes mellitus. They included 252 newly diagnosed gestational diabetes mellitus cases with 252 controls matched by age, parity, and gestational age. Plasma concentrations of vanadium were significantly lower in the gestational diabetes mellitus group compared to the control group (p<0.001). The authors concluded there was an inverse association between plasma vanadium and gestational diabetes mellitus (144).  

 

Adverse Effects and Warnings

 

Acute vanadium toxicity does not appear to be a common concern. Mild gastrointestinal effects such as abdominal cramps and loose stools may occur. Animal studies suggest vanadium may cause anemia. However, this has not been shown in humans (74).

 

Interactions

 

There is theoretical concern that vanadium may increase the risk of bleeding in anticoagulant agents (145).

 

Summary

 

Vanadium is a mineral that may increase sensitivity to insulin. There is a lack of human data to support the use of vanadium as a glucose lowering agent, but there is promise. 

 

Carbohydrate Absorption Inhibitors

 

The natural products contained in this section are known to be carbohydrate absorption inhibitors. This means they theoretically lower plasma glucose by preventing the absorption of ingested carbohydrate. Products may also employ other mechanisms of action, which are addressed.

 

ALOE VERA GEL

 

Aloe is a desert plant that appears similar to a cactus and typically grows in hot and dry climates. See Figure 14 for an image of the aloe plant. Aloe byproducts are commonly used in cosmetics and medicine. The byproducts aloe vera gel and aloe latex are common (146).

 

FIGURE 14. ALOE VERA PLANT IMAGE SOURCE: https://en.wikipedia.org/wiki/File:Aloe_aristata.jpg.

 

Mechanism of Action

 

The portion of the aloe extract that is thought to be pharmaceutically active is the leaf. Aloe gel is clear and can be extracted from the leaf (147, 148). Monosaccharides, polysaccharides, tannins, sterols, enzymes, amino acids, salicylic acid, arachidonic acid, lipids, vitamins, and minerals are all found in aloe vera gel (148). Studies in mice suggest aloe gel may stimulate beta-cells, while human studies show conflicting evidence. Aloe latex contains anthraquinones and may be toxic. Aloe latex should not be confused with aloe gel (149, 150).

 

Evidence

 

In 2021, an analysis of four systematic reviews analyzing the metabolic effects of aloe vera in individuals with type 2 diabetes and pre-diabetes was published. Fasting blood glucose was significantly lower in the aloe vera group compared to placebo (-5.61 mg/dL; 95% CI: -7.94 to -3.28; p<0.001); HbA1c was also lower in the aloe vera group (-0.95%; 95% CI: -1.76 to -0.14; p=0.02). There was no significant change in total cholesterol, low-density lipoproteins, triglycerides, or high-density lipoproteins. Results are summarized in Table 22 (151).

 

Table 22. Effect of Aloe Vera on Metabolic Parameters (151)

Parameter

Pooled Mean Difference (95% CI)

p-value

Pooled Mean Difference

Heterogeneity

(I2)

p-value

Heterogeneity

Glycemic

Fasting plasma glucose (mg/dL)

-5.61 (-7.94 to -3.28)

<0.001

98%

<0.001

HbA1c (%)

-0.95% (-1.76 to -0.14)

0.02

78%

0.004

Lipoprotein

Total Cholesterol (mg/dL)

-6.79 (-44.07 to 30.48)

0.72

96%

<0.001

Low density lipoprotein concentration (mg/dL)

24.49 (-13.70 to 62.67)

0.21

99%

<0.00001

High density lipoprotein concentration (mg/dL)

4.44 (-4.24 to 13.12)

0.32

98%

<0.00001

Triglycerides (mg/dL)

28.04 (-41.90 to 97.98)

0.43

100

<0.001

 

A meta-analysis was published in 2016 evaluating the impact of aloe vera on fasting glucose and HbA1c in patients with type 2 diabetes. Nine studies were included in the fasting glucose analysis. Aloe vera use decreased fasting glucose by 26.6 mg/dL (p<0.001). Five studies were included in the HbA1c analysis. HbA1c decreased by 1.05% in aloe vera treated individuals (p<0.004). Results suggested patients with higher fasting glucose levels may benefit more from aloe vera use (these patients demonstrated a decrease of 109.9 mg/dL; p<0.01). The authors concluded their results support the use of aloe vera for decreasing fasting glucose and HbA1c in patients with diabetes (152).

 

Aloe vera has also been studied in pre-diabetes. Alinejad-Mofrad and colleagues compared aloe vera to placebo in patients with prediabetes (n=72). Patients were randomized to three groups: aloe vera 300 mg daily, aloe vera 500 mg daily, and placebo for eight weeks. Treatment with aloe vera (both 300 mg and 500 mg daily) decreased fasting glucose and HbA1c compared to placebo. Results are presented in Table 23 (153).

 

Table 23. Comparison Fasting Glucose and HbA1c with use of Aloe Vera in Patients with Prediabetes (153)

Parameter

Time

Placebo

Within Group p-Value

Aloe Vera 300 mg Group

Within Group p-Value

Aloe Vera 500 mg Group

Within Group p-Value

Between Group p-value

Fasting glucose (mg/dL)

Baseline

110 ± 3.91

n/a

112 ± 2.5

n/a

111 ± 4.1

n/a

0.69

8 weeks

110 ± 4.22

0.19

108 ± 2.78*

0.001

104 ± 4.2*

<0.001

0.001*

HbA1c (%)

Baseline

6.01 ± 0.16

n/a

6 ± 0.24

n/a

6 ± 0.23

n/a

0.37

8 weeks

6.03 ± 0.14

0.059

5.8 ± 0.21*

0.042

5.6 ± 0.33*

0.011

0.04*

* indicates statistical significance compared to placebo (p<0.05)

 

A meta-analysis and systematic review of randomized controlled trials evaluated aloe vera in patients with type 2 diabetes and prediabetes. Eight trials were included (five enrolled patients with diabetes and three enrolled patients with prediabetes). In patients with diabetes, both fasting glucose (-21 mg/dL; p<0.05) and HbA1c (-1%; p=0.01) decreased significantly. In patients with prediabetes, fasting glucose decreased statistically significantly, but in a very small amount (-4 mg/dL; p<0.0001). There was no change in HbA1c in the prediabetes patients (154).

 

Adverse Effects and Warnings

 

Aloe vera gel, when used orally, is well tolerated. Aloe latex, however, can cause abdominal pain and cramps. Unlike aloe vera gel, aloe latex contains anthraquinones which may be toxic (148).

 

Interactions

 

Aloe vera gel may decrease glucose and should be used cautiously with other products with the same effect. It may also increase the risk of bleeding when used with anticoagulant or antiplatelet drugs (148).

 

Summary

 

Aloe vera gel is derived from the leaf of the aloe plant. There is preliminary evidence to suggest it lowers glucose in those with diabetes and prediabetes. Aloe vera gel is typically well tolerated.

 

FENUGREEK (TRIGONELLA FOENUM-GRAECUM)

 

Fenugreek has multiple mechanisms of action is addressed under the “Hypoglycemic Agents” section.

 

FLAXSEED (LINUM USITATISSIMUM)

 

Flaxseed is a grain that is native to Europe, Asia, and the Mediterranean. Flax is a blue flowering crop and the seeds exist in brown, yellow, and green colors (see Figure 15). Whole flaxseeds primarily contain fat (41%), dietary fiber (28%), and protein (21%). The oil contained in flaxseeds is particularly rich in polyunsaturated fat (73%) and lower in monounsaturated (18%) and saturated (9%) fats. Flaxseed oil is a rich source of the omega-3 fatty acid alpha linolenic acid (ALA) (155).

 

FIGURE 15. BROWN FLAXSEEDS IMAGE SOURCE: https://en.wikipedia.org/wiki/Flax#/media/File:Brown_Flax_Seeds.jpg.

 

Mechanism of Action

 

The pharmaceutically active portion of flaxseed is the seed and the oil. The high soluble fiber content is thought to decrease carbohydrate absorption. The high omega-3 fatty acid content (ALA) is also thought to play a crucial role as these acids have been shown improve insulin sensitivity and glycemic control. ALA has been shown to increase plasma GLP-1 levels (156). Flaxseeds contain lignans, which have been proven to have antioxidant effects (157-159).

 

Evidence

 

A systematic review and meta-analysis of randomized controlled trials aimed at determining the impact of flaxseed supplementation in patients with type 2 diabetes mellitus was published in 2023. Thirteen studies were included in the analysis. HbA1c was significantly reduced in the flaxseed supplementation group (-0.19%; 95% CI: -0.38 to 0.00; p=0.045). The authors found no significant change in fasting plasma glucose, insulin, HOMA-IR, lipid parameters, body weight, BMI, or blood pressure (160).

 

A single-blinded, randomized, controlled trial evaluated the impact of flaxseed in 53 patients with type 2 diabetes that also had constipation. Patients either received cookies with flaxseed twice a day or cookies free of flaxseed twice daily for 12 weeks. Constipation scores, weight (-3.8 kg), and fasting plasma glucose (-26.7 mg/dL) all decreased from baseline in the flaxseed group (p<0.05). Constipation scores, weight (-3.8 versus 0 kg), fasting plasma glucose (-26.7 versus 1.9 mg/dL), and HbA1c (-0.8% versus 1.0%) were significantly different in the flaxseed group compared to placebo (p<0.05) (161).

 

A placebo-controlled, crossover study evaluated the impact of flaxseed on diabetes. Seventy-three patients with type 2 diabetes took either placebo or 360 mg daily of flaxseed for 12 weeks. After an eight-week washout period, patients crossed over to the other group. HbA1c decreased a small, but statistically significant, amount (0.1%; p=0.01). There was no significant change in fasting plasma glucose or lipoprotein levels (162).

 

An open-label study evaluated the effect of flaxseed in patients with type 2 diabetes (n=29). Patients received 10 g of flaxseed daily (n=18) or placebo (n=11). Fasting glucose decreased 28.9 mg/dL in the flaxseed group (p=0.02) and slightly increased in the placebo group. HbA1c decreased 0.59% (from 8.75% to 8.16%) in the flaxseed group (p=0.009) and increased 0.1% in the placebo group. Triglycerides and LDL-C also decreased significantly in the flaxseed group (1630.

 

Flaxseed has also been studied in patients with prediabetes. Hutchins and colleagues randomized 25 patients with prediabetes to take 26 g of flaxseed, 13 g of flaxseed, or placebo for 12 weeks. After a 2-week washout period, patients were crossed over to another group. Fasting glucose levels did not decrease significantly in the 26 g group compared to placebo. However, fasting glucose decreased significantly in the 13 g group compared to placebo (-2 mg/dL, p=0.036). Insulin levels also decreased significantly in the 13 g group (p=0.021) (164).

 

Adverse Effects and Warnings

 

Few adverse effects are reported with flaxseed use.161 Gastrointestinal side effects are the most commonly reported (155).

 

Interactions

 

Oil from flaxseeds is shown to decrease platelet aggregation and may, therefore, increase the risk of bleeding in users of anticoagulants and antiplatelets (165).

 

Theoretically, flaxseed may decrease the absorption of acetaminophen and ketoprofen. However, this interaction has not been shown in human studies (166).

 

Summary

 

Flaxseed is rich in fat (primarily omega-3 fatty acids) and fiber. There are conflicting results regarding flaxseed’s efficacy in glycemic control. Most individuals tolerate flaxseed well.

 

PRICKLY PEAR CACTUS (OPUNTIA FICUS-INDICA), NOPAL

 

Prickly pear cactus has multiple mechanisms of action is addressed under the “Insulin Sensitizers” section.

 

SOY (GLYCINE MAX)

 

Soy has multiple mechanisms of action is addressed under the “Insulin Sensitizers” section.

 

TURMERIC (CURCUMA LONGA, CURCUMA DOMESTICA, CURCUMA AROMATIC) 

 

Turmeric is a member if the Zingiberaceae (ginger) family (167). Turmeric has a long history of use in Ayurvedic and Chinese medicine (see Figure 16). Curcumin is considered the active constituent of turmeric and is yellow-colored and fragrant. Curcumin is typically what is used as a flavoring and coloring agent in turmeric-containing products (168).

 

FIGURE 16. TURMERIC IMAGE SOURCE: https://en.wikipedia.org/wiki/Wikipedia:Featured_picture_candidates/Turmeric.

 

Mechanism of Action

 

Turmeric has multiple proposed mechanisms of action relating to glycemia. Turmeric can induce peroxisome proliferator-activated receptor-gamma activation. It may also activate hepatic enzymes associated with glycolysis and gluconeogenesis. Turmeric may also enhance tumor necrosis factor alpha (168).

 

Evidence

 

In 2023, a systematic review and network meta-analysis of randomized controlled trials was published that compared the effectiveness of different herbs in the management of T2DM. Turmeric (curcumin) was one of the herbs studied. Forty-four trials were included in the review. Compared to controls, turmeric use was correlated with a statistically significant reduction in fasting plasma glucose (-13.15 mg/dL; 95% CI: -23.64 to -2.66; p<0.05). The authors found no change in HbA1c associated with turmeric use (169).

 

A systematic review and meta-analysis published in 2021 was conducted to evaluate the effect of curcumin on glycemic and lipid profiles in patients with type 2 diabetes. There was a statistically significant difference in HbA1c in turmeric users (-0.42%, 95% CI -0.72 to -0.11; p< 0.05). There was non-significant (p = 0.107) moderate heterogeneity (I2 = 42.42) (170).

 

The effect of turmeric in delaying the development of type 2 diabetes was studied in patients with prediabetes in a randomized, double-blinded, placebo-controlled trial. Subjects (n=240) were randomly assigned to curcumin capsules or placebo for nine months. After nine months, 16.4% of subjects in the placebo group were diagnosed with type 2 diabetes. No subjects in the curcumin group were diagnosed in this timeframe (p<0.05). Markers of insulin sensitivity also showed favor for the curcumin group (higher HOMA-beta and lower HOMA-IR; p<0.05) (171).

 

Adverse Effects and Warnings

 

Turmeric is usually well tolerated. Itching, constipation, and vertigo have been reported with use (171).

 

Interactions

 

There is a risk of increased bleeding when turmeric is combined with anticoagulants (172).

 

Summary

 

Turmeric and its active constituent, curcumin, have been long used medicinally. There is limited evidence in humans to suggest curcumin use may delay the onset of type 2 diabetes in patients with prediabetes. Turmeric is typically well tolerated.

 

Summary of Natural Products

 

A summary of the natural products is presented alphabetically in Table 24.

 

Table 24. Summary of Natural Products Used for Diabetes Listed Alphabetically

Natural Product

Adverse Effects

Interactions

Aloe Vera Gel

 

 

Aloe vera gel is typically well tolerated

Aloe latex (which contains anthraquinones) can cause abdominal pain and cramps

May decrease glucose and should be used cautiously with other products with the same effect

 

Banaba (Lagerstroemia speciosa)

Dizziness, headache, tremor, weakness, diaphoresis, nausea

Additive effect with antihypertensives

Use with caution in those using hypoglycemic agents

Berberine

Diarrhea, constipation, flatulence, abdominal pain, and vomiting

Uterine contractions

May cross the placenta and result in neonatal kernicterus when ingested during pregnancy

 

May inhibit cytochrome P450 3A4 and should be used cautiously with other agents that are substrates, inhibitors, or inducers of this hepatic enzyme

As berberine lowers glucose, caution should be exercised when used with other agents that lower glucose

 

Bitter melon

 

 

Abdominal discomfort, pain, and diarrhea

May contain abortifacient proteins

 

Use with caution in those using other hypoglycemic agents

Those with G6PD deficiency should avoid use due to risk of developing favism

Chromium

 

Chromium picolinate may cause cognitive, perceptual, and motor dysfunction

There is a theoretical interaction between chromium and iron

Cinnamon

 

Cinnamon is typically tolerated well

Cinnamon is a natural source of coumarin and use, therefore, presents a theoretical risk of hepatic injury

 

May contain coumarin and increase the risk of bleeding with anticoagulants

Use cautiously with other hepatotoxic agents due to concerns of hepatic injury when large doses are used

May decrease glucose levels and should be used cautiously with other agents that lower glucose

Fenugreek (Trigonellafoenum-graecum)

 

 

Diarrhea, heartburn, and flatulence

Fenugreek smells similar to maple syrup; consumption prior to delivery may cause the neonate to have this odor, which may lead to confusion with maple syrup urine disease

Patients with chickpea allergies should use fenugreek with caution as there is potential for cross-reactivity

Fenugreek may cause uterine contractions and should be avoided in pregnancy

May contain coumarin and increase the risk of bleeding with anticoagulants

Theophylline levels may be decreased with concomitant use

Use cautiously with other agents that decrease glucose

 

 

Flaxseed (Linumusitatissimum)

 

Gastrointestinal side effects are the most commonly reported

 

Flaxseed may decrease the absorption of acetaminophen and ketoprofen

Flaxseed oil may increase the risk of bleeding with antiplatelets and anticoagulants

American Ginseng(Panax quinquefolius)

 

Headache

May stimulate immune function and theoretically decrease the effect of immunosuppressants

Can decrease the efficacy of warfarin; concomitant use is not advised

Use cautiously with other glucose lowering agents

Gymnema (Gymnemasylvestre)

 

 

A case of acute hepatitis secondary to gymnema use has been reported

May potentiate the effects of other agents that lower glucose

Milk thistle (Silybummarianum)

 

 

Nausea, diarrhea, and abdominal bloating may occur with use

Those with a daisy or ragweed allergy may experience a cross reaction with milk thistle use

May inhibit certain cytochrome P450 isoenzymes; the isoenzymes 2C8, 2C9, 2D6, 3A4, and 3A5 may all be inhibited with concomitant use

Increased warfarin levels may occur with concomitant use

May lower glucose levels and should be used cautiously with other hypoglycemia agents

 

Prickly Pear Cactus(Opuntia ficus-indica andother Opuntia species),Nopal

Prickly pear cactus is generally tolerated well when used orally

Side effects include nausea, diarrhea, and headache

 

Prickly pear cactus may lower glucose levels and should be used cautiously with other agents that impact glycemic control

 

Soy

Soy is generally well tolerated

May cause nausea, diarrhea, and bloating

Soy may alter thyroid function, but this appears to occur in those with iodine deficiency

Fermented soy products such as tofu may contain small amounts of tyramine; tyramine should be avoided in those using monoamine oxidase inhibitors

Turmeric (Curcuma longaCurcuma domesticaCurcuma aromatic)

 

 

Itching, constipation, and vertigo have been reported with use

There is a risk of increased bleeding when turmeric is combined with anticoagulants

Vanadium

Mild gastrointestinal effects such as abdominal cramps and loose stools may occur

Animal studies suggest vanadium may cause anemia

Theoretical concern that vanadium may increase the risk of bleeding in anticoagulant agents

 

 

MIND BODY PRACTICES FOR TYPE 2 DIABETES

 

According to the National Institute of Heath, mind body practices include, but are not limited to, yoga, chiropractic and osteopathic manipulation, meditation, massage, acupuncture, Tai Chi, healing touch, hypnotherapy, and movement manipulation (1). Mind body practices are used for overall health and to help with specific disease states. There is recent interest in studying the impact of mind body practices on type 2 diabetes.

 

Yoga has been studied in patients with type 2 diabetes. Preliminary studies indicate yoga may reduce BMI, improve glycemic control, improve lipid levels, and improve body composition. Yoga may also decrease blood pressure (173-177).

 

The impact of massage on glycemic control in patients with diabetes has been studied. One study showed parent-provided full body massage at bedtime improved serum glucose levels and decreased anxiety of both the massage giver and receiver (178). Another study compared changes in metabolic parameters of individuals with type 2 diabetes between a control group, a routine massage group, and an abdominal massage group. The control group had no significant change in fasting plasma glucose, postprandial plasma glucose, or HbA1c. The routine massage and abdominal massage groups had significant reductions in fasting plasma glucose, postprandial plasma glucose, and HbA1c (69).

 

A meta-analysis exploring the impact of Tai Chi on glucose and lipid metabolism in patients with T2DM was conducted and included 16 randomized controlled trials. Tai Chi significantly reduced fasting plasma glucose and HbA1c (179). Individual studies on Tai Chi have shown it may decrease fasting glucose values in patients with diabetes. However, Tai Chi does not appear to reduce glucose more than other types of gentle exercise (180-182).

 

RELIABLE RESOURCES FOR PROVIDERS AND PATIENTS

 

Clinicians need to be aware of the deceptive marketing tactics employed by natural product manufacturers. Patients and clinicians need reliable and dependable resources regarding integrative medicine.

 

MedWatch is a website developed and updated by the FDA. MedWatch provides timely safety information on dietary supplements as well as medications and cosmetics. MedWatch can be accessed at: https://www.fda.gov/Safety/MedWatch/.

 

The FDA also has a health fraud online resource. The website describes health fraud and provides actionable ways patients can protect themselves. The FDA’s health fraud website can be accessed at: https://www.fda.gov/consumers/health-fraud-scams

 

In terms of efficacy, primary literature is a reasonable resource. The US National Library of Medicine has an online database that can be searched free of change. The database can be accessed at: https://www.ncbi.nlm.nih.gov/pubmed.

 

Additional online resources are provided in Table 25.

 

Table 25. Complementary Health Approach Online Resources for Patients and Clinicians

Source

Description

Website Address

American Botanical Council

Non-profit, international member-based organization providing education using evidence-based and traditional information to promote the responsible use of herbal medicine

http://abc.herbalgram.org/site/PageServer

 

ConsumerLab.com

Independent testing site that reviews natural products and specific manufacturers

http://www.consumerlab.com

National Center for Complementary and Integrative Health (NCCIH)

National (US) center that supports and disseminates research results on complementary health approaches

https://www.nccih.nih.gov

 

 

 

National Institute of Health Office of Dietary Supplements (ODS) 

National (US) center that supports and disseminates research results on dietary supplements

http://ods.od.nih.gov/index.aspx

Natural Medicines

A scientifically-based and practical database on natural medicines (Subscription required)

https://naturalmedicines.therapeuticresearch.com

The Cochrane Library

An electronic database designed to provide high quality scientific evidence

https://www.cochranelibrary.com

United States Food and Drug Administration Health Fraud Website

The website describes health fraud and provides actionable ways patients can protect themselves.

https://www.fda.gov/consumers/health-fraud-scams

United States Food and Drug Administration MedWatch

MedWatch provides timely safety information on dietary supplements as well as medications and cosmetics.

https://www.fda.gov/Safety/MedWatch/

United States Food and Drug Administration Office of Nutritional Products, Labeling, and Dietary Supplements 

FDA office responsible for developing policy and regulations for dietary supplements, medical foods, and related areas, as well as for their scientific evaluation

http://www.fda.gov/Food/DietarySupplements/default.htm

WebMD Health 

WebMD provides comprehensive health information and tools for managing health care for health care professionals and their patients

http://diabetes.webmd.com/default.htm

 

IDENTIFYING POTENTIALLY HARMFUL PRODUCTS

 

According to the FDA’s health fraud website, there are certain red flags that can alert a consumer to potentially harmful natural products, including dietary supplements. Red flags to be wary of include: claims that a product is a cure-all for a wide variety of ailments; suggestions that a product can treat or cure diseases; promotions using words such as "scientific breakthrough" or "miraculous cure"; undocumented testimonies by consumers or doctors claiming amazing results; limited availability and advance payment requirements; promises of no-risk, money-back guarantees; promises of an "easy" fix; and claims that the product is "natural" or "non-toxic" (which doesn't necessarily mean safe) (183). These safety alerts are provided in Table 26. Additionally, the FDA fraud website warms to avoid websites that fail to list the company’s name, physical address, phone number, or other contact information.

 

Table 26. FDA Health Fraud Indicators a Natural Product May Be Ineffective or Unsafe (183)

Claims that a product is a quick, effective cure-all or a diagnostic tool for a wide variety of ailments

Suggests that a product can treat or cure diseases

Promotions using words such as "scientific breakthrough," "miraculous cure," "secret ingredient," and "ancient remedy"

Text with impressive-sounding terms such as: "hunger stimulation point" and "thermogenesis" for a weight loss product

Undocumented case histories by consumers or doctors claiming amazing results

Limited availability and advance payment requirements

Promises of no-risk, money-back guarantees

Promises of an "easy" fix

Claims that the product is "natural" or "non-toxic" (which doesn't necessarily mean safe)

 

REFERENCES

 

  1. Health NCfCaI. Complementary, Alternative, or Integrative Health: What’s In a Name? National Institute of Health. Accessed June 26, 2024. https://nccih.nih.gov/health/integrative-health
  2. Chan S, Hecht FM. Integrative Medicine. In: Feldman MD, Christensen JF, Satterfield JM, Laponis R, eds. Behavioral Medicine: A Guide for Clinical Practice, 5e. McGraw-Hill Education; 2019.
  3. Dietary Supplements (2024).
  4. Administration UFaD. Current Good Manufacturing Practices (CGMPs) for Dietary Supplements. 2024 June 11, Updated 2023 Dec 12. https://www.fda.gov/drugs/pharmaceutical-quality-resources/current-good-manufacturing-practice-cgmp-regulations
  5. National Institutes of Health OoDS. Dietary supplements: Background information. 2019 May 13, Updated 2020 March 11. Accessed 2024 June 11, https://ods.od.nih.gov/factsheets/DietarySupplements-Consumer/
  6. Dietary Supplement and Non-Prescription Drug Consumer Protection Act. Pub L. No. 109-462. (2006).
  7. Geller AI, Shehab N, Weidle NJ, et al. Emergency Department Visits for Adverse Events Related to Dietary Supplements. N Engl J Med. Oct 2015;373(16):1531-40. doi:10.1056/NEJMsa1504267
  8. Drug Recalls (2018).
  9. Harel Z HS, Waid R, Mamdani M, Bell CM. The frequency and characteristics of dietary supplement recalls in the United States. JAMA Intern med. 2013;173:926-8.
  10. Nutrition CfR. Consumer Survey on Dietary Supplements. 2023 Oct 5 2023;
  11. Nutrition CfR. Consumer Survey on Dietary Supplements. 30 Sept 2019;
  12. Alzahrani AS, Price MJ, Greenfield SM, Paudyal V. Global prevalence and types of complementary and alternative medicines use amongst adults with diabetes: systematic review and meta-analysis. Eur J Clin Pharmacol. Mar 8 2021;doi:10.1007/s00228-021-03097-x
  13. Rhee TG, Westberg SM, Harris IM. Complementary and alternative medicine in US adults with diabetes: Reasons for use and perceived benefits. J Diabetes. Apr 2018;10(4):310-319. doi:10.1111/1753-0407.12607
  14. Rhee TG, Westberg SM, Harris IM. Use of Complementary and Alternative Medicine in Older Adults With Diabetes. Diabetes Care. Apr 2018;doi:10.2337/dc17-0682
  15. Dias DA, Urban S, Roessner U. A historical overview of natural products in drug discovery. Metabolites. Apr 2012;2(2):303-36. doi:10.3390/metabo2020303
  16. Kakuda T, Sakane I, Takihara T, Ozaki Y, Takeuchi H, Kuroyanagi M. Hypoglycemic effect of extracts from Lagerstroemia speciosa L. leaves in genetically diabetic KK-AY mice. Biosci Biotechnol Biochem. Feb 1996;60(2):204-8.
  17. Hayashi T, Maruyama H, Kasai R, et al. Ellagitannins from Lagerstroemia speciosa as activators of glucose transport in fat cells. Planta Med. Feb 2002;68(2):173-5. doi:10.1055/s-2002-20251
  18. Judy WV, Hari SP, Stogsdill WW, Judy JS, Naguib YM, Passwater R. Antidiabetic activity of a standardized extract (Glucosol) from Lagerstroemia speciosa leaves in Type II diabetics. A dose-dependence study. J Ethnopharmacol. Jul 2003;87(1):115-7.
  19. Hattori K, Sukenobu N, Sasaki T, et al. Activation of insulin receptors by lagerstroemin. J Pharmacol Sci. Sep 2003;93(1):69-73.
  20. López-Murillo LD, González-Ortiz M, Martínez-Abundis E, Cortez-Navarrete M, Pérez-Rubio KG. Effect of Banaba (Lagerstroemia speciosa) on Metabolic Syndrome, Insulin Sensitivity, and Insulin Secretion. J Med Food. Feb 2022;25(2):177-182. doi:10.1089/jmf.2021.0039
  21. Derosa G, D'Angelo A, Maffioli P. The role of selected nutraceuticals in management of prediabetes and diabetes: An updated review of the literature. Phytother Res. Oct 2022;36(10):3709-3765. doi:10.1002/ptr.7564
  22. Fukushima M, Matsuyama F, Ueda N, et al. Effect of corosolic acid on postchallenge plasma glucose levels. Diabetes Res Clin Pract. Aug 2006;73(2):174-7. doi:10.1016/j.diabres.2006.01.010
  23. Center TR. Banaba. 2024 March 8. https://naturalmedicines.therapeuticresearch.com
  24. Grover JK, Yadav S, Vats V. Medicinal plants of India with anti-diabetic potential. J Ethnopharmacol. Jun 2002;81(1):81-100.
  25. Berman BM, Swyers JP, Kaczmarczyk J. Complementary and alternative medicine: herbal therapies for diabetes. J Assoc Acad Minor Phys. 1999;10(1):10-4.
  26. Center TR. Bitter melon. 2024 Feb 12. https://naturalmedicines.therapeuticresearch.com
  27. Basch E, Gabardi S, Ulbricht C. Bitter melon (Momordica charantia): a review of efficacy and safety. Am J Health Syst Pharm. Feb 2003;60(4):356-9.
  28. Oyelere SF, Ajayi OH, Ayoade TE, et al. A detailed review on the phytochemical profiles and anti-diabetic mechanisms of Momordica charantia. Heliyon. Apr 2022;8(4):e09253. doi:10.1016/j.heliyon.2022.e09253
  29. Zhang X, Zhao Y, Song Y, Miao M. Effects of Momordica charantia L. supplementation on glycemic control and lipid profile in type 2 diabetes mellitus patients: A systematic review and meta-analysis of randomized controlled trials. Heliyon. May 30 2024;10(10):e31126. doi:10.1016/j.heliyon.2024.e31126
  30. Peter EL, Kasali FM, Deyno S, et al. Momordica charantia L. lowers elevated glycaemia in type 2 diabetes mellitus patients: Systematic review and meta-analysis. J Ethnopharmacol. Mar 1 2019;231:311-324. doi:10.1016/j.jep.2018.10.033
  31. Ooi CP, Yassin Z, Hamid TA. Momordica charantia for type 2 diabetes mellitus. Cochrane Database Syst Rev. Aug 2012;(8):CD007845. doi:10.1002/14651858.CD007845.pub3
  32. Dans AM, Villarruz MV, Jimeno CA, et al. The effect of Momordica charantia capsule preparation on glycemic control in type 2 diabetes mellitus needs further studies. J Clin Epidemiol. Jun 2007;60(6):554-9. doi:10.1016/j.jclinepi.2006.07.009
  33. Leung SO, Yeung HW, Leung KN. The immunosuppressive activities of two abortifacient proteins isolated from the seeds of bitter melon (Momordica charantia). Immunopharmacology. Jun 1987;13(3):159-71.
  34. Basch E, Ulbricht C, Kuo G, Szapary P, Smith M. Therapeutic applications of fenugreek. Altern Med Rev. Feb 2003;8(1):20-7.
  35. Cortez-Navarrete M, Pérez-Rubio KG, Escobedo-Gutiérrez MJ. Role of Fenugreek, Cinnamon, Curcuma longa, Berberine and Momordica charantia in Type 2 Diabetes Mellitus Treatment: A Review. Pharmaceuticals (Basel). Mar 30 2023;16(4)doi:10.3390/ph16040515
  36. Marles RJ, Farnsworth NR. Antidiabetic plants and their active constituents. Phytomedicine. Oct 1995;2(2):137-89. doi:10.1016/S0944-7113(11)80059-0
  37. Sauvaire Y, Petit P, Broca C, et al. 4-Hydroxyisoleucine: a novel amino acid potentiator of insulin secretion. Diabetes. Feb 1998;47(2):206-10.
  38. Perla V, Jayanty SS. Biguanide related compounds in traditional antidiabetic functional foods. Food Chem. Jun 2013;138(2-3):1574-80. doi:10.1016/j.foodchem.2012.09.125
  39. Shabil M, Bushi G, Bodige PK, et al. Effect of Fenugreek on Hyperglycemia: A Systematic Review and Meta-Analysis. Medicina (Kaunas). Jan 27 2023;59(2)doi:10.3390/medicina59020248
  40. Khodamoradi K, Khosropanah MH, Ayati Z, et al. The Effects of Fenugreek on Cardiometabolic Risk Factors in Adults: A Systematic Review and Meta-analysis. Complement Ther Med. Aug 2020;52:102416. doi:10.1016/j.ctim.2020.102416
  41. Gupta A, Gupta R, Lal B. Effect of Trigonella foenum-graecum (fenugreek) seeds on glycaemic control and insulin resistance in type 2 diabetes mellitus: a double blind placebo controlled study. J Assoc Physicians India. Nov 2001;49:1057-61.
  42. Sewell AC, Mosandl A, Böhles H. False diagnosis of maple syrup urine disease owing to ingestion of herbal tea. N Engl J Med. Sep 1999;341(10):769. doi:10.1056/NEJM199909023411020
  43. Shiyovich A, Sztarkier I, Nesher L. Toxic hepatitis induced by Gymnema sylvestre, a natural remedy for type 2 diabetes mellitus. Am J Med Sci. Dec 2010;340(6):514-7. doi:10.1097/MAJ.0b013e3181f41168
  44. Tiwari P, Mishra BN, Sangwan NS. Phytochemical and pharmacological properties of Gymnema sylvestre: an important medicinal plant. Biomed Res Int. 2014;2014:830285. doi:10.1155/2014/830285
  45. Persaud SJ, Al-Majed H, Raman A, Jones PM. Gymnema sylvestre stimulates insulin release in vitro by increased membrane permeability. J Endocrinol. Nov 1999;163(2):207-12.
  46. Kanetkar P, Singhal R, Kamat M. Gymnema sylvestre: A Memoir. J Clin Biochem Nutr. Sep 2007;41(2):77-81. doi:10.3164/jcbn.2007010
  47. Gymnema sylvestre. Altern Med Rev. Feb 1999;4(1):46-7.
  48. Zamani M, Ashtary-Larky D, Nosratabadi S, et al. The effects of Gymnema Sylvestre supplementation on lipid profile, glycemic control, blood pressure, and anthropometric indices in adults: A systematic review and meta-analysis. Phytother Res. Mar 2023;37(3):949-964. doi:10.1002/ptr.7585
  49. Devangan S, Varghese B, Johny E, Gurram S, Adela R. The effect of Gymnema sylvestre supplementation on glycemic control in type 2 diabetes patients: A systematic review and meta-analysis. Phytother Res. Dec 2021;35(12):6802-6812. doi:10.1002/ptr.7265
  50. Shanmugasundaram ER, Rajeswari G, Baskaran K, Rajesh Kumar BR, Radha Shanmugasundaram K, Kizar Ahmath B. Use of Gymnema sylvestre leaf extract in the control of blood glucose in insulin-dependent diabetes mellitus. J Ethnopharmacol. Oct 1990;30(3):281-94.
  51. Baskaran K, Kizar Ahamath B, Radha Shanmugasundaram K, Shanmugasundaram ER. Antidiabetic effect of a leaf extract from Gymnema sylvestre in non-insulin-dependent diabetes mellitus patients. J Ethnopharmacol. Oct 1990;30(3):295-300.
  52. Fabio GD, Romanucci V, De Marco A, Zarrelli A. Triterpenoids from Gymnema sylvestre and their pharmacological activities. Molecules. Jul 2014;19(8):10956-81. doi:10.3390/molecules190810956
  53. Mucalo I, Jovanovski E, Rahelić D, Božikov V, Romić Z, Vuksan V. Effect of American ginseng (Panax quinquefolius L.) on arterial stiffness in subjects with type-2 diabetes and concomitant hypertension. J Ethnopharmacol. Oct 2013;150(1):148-53. doi:10.1016/j.jep.2013.08.015
  54. Services USFaW. Li st of States and Tribes with Approved Export Programs for Furbearers, Alligators, and Ginseng. 2017.
  55. Lim W, Mudge KW, Vermeylen F. Effects of population, age, and cultivation methods on ginsenoside content of wild American ginseng (Panax quinquefolium). J Agric Food Chem. Nov 2005;53(22):8498-505. doi:10.1021/jf051070y
  56. Vuksan V, Stavro MP, Sievenpiper JL, et al. Similar postprandial glycemic reductions with escalation of dose and administration time of American ginseng in type 2 diabetes. Diabetes Care. Sep 2000;23(9):1221-6.
  57. Liu T, Wang D, Zhou X, et al. Study on the mechanism of American ginseng extract for treating type 2 diabetes mellitus based on metabolomics. Front Pharmacol. 2022;13:960050. doi:10.3389/fphar.2022.960050
  58. Vuksan V, Xu ZZ, Jovanovski E, et al. Efficacy and safety of American ginseng (Panax quinquefolius L.) extract on glycemic control and cardiovascular risk factors in individuals with type 2 diabetes: a double-blind, randomized, cross-over clinical trial. Eur J Nutr. Apr 2019;58(3):1237-1245. doi:10.1007/s00394-018-1642-0
  59. Sievenpiper JL, Arnason JT, Leiter LA, Vuksan V. Variable effects of American ginseng: a batch of American ginseng (Panax quinquefolius L.) with a depressed ginsenoside profile does not affect postprandial glycemia. Eur J Clin Nutr. Feb 2003;57(2):243-8. doi:10.1038/sj.ejcn.1601550
  60. Stavro PM, Woo M, Leiter LA, Heim TF, Sievenpiper JL, Vuksan V. Long-term intake of North American ginseng has no effect on 24-hour blood pressure and renal function. Hypertension. Apr 2006;47(4):791-6. doi:10.1161/01.HYP.0000205150.43169.2c
  61. McElhaney JE, Gravenstein S, Cole SK, et al. A placebo-controlled trial of a proprietary extract of North American ginseng (CVT-E002) to prevent acute respiratory illness in institutionalized older adults. J Am Geriatr Soc. Jan 2004;52(1):13-9.
  62. Janetzky K, Morreale AP. Probable interaction between warfarin and ginseng. Am J Health Syst Pharm. Mar 1997;54(6):692-3.
  63. Berberine. Altern Med Rev. Apr 2000;5(2):175-7.
  64. Center TR. Berberine. 1 May 2024.
  65. Zhou JY, Zhou SW, Zhang KB, et al. Chronic effects of berberine on blood, liver glucolipid metabolism and liver PPARs expression in diabetic hyperlipidemic rats. Biol Pharm Bull. Jun 2008;31(6):1169-76.
  66. Zhang H, Wei J, Xue R, et al. Berberine lowers blood glucose in type 2 diabetes mellitus patients through increasing insulin receptor expression. Metabolism. Feb 2010;59(2):285-92. doi:10.1016/j.metabol.2009.07.029
  67. Lu SS, Yu YL, Zhu HJ, et al. Berberine promotes glucagon-like peptide-1 (7-36) amide secretion in streptozotocin-induced diabetic rats. J Endocrinol. Feb 2009;200(2):159-65. doi:10.1677/JOE-08-0419
  68. Yaribeygi H, Jamialahmadi T, Moallem SA, Sahebkar A. Boosting GLP-1 by Natural Products. Adv Exp Med Biol. 2021;1328:513-522. doi:10.1007/978-3-030-73234-9_36
  69. Xie W, Su F, Wang G, et al. Glucose-lowering effect of berberine on type 2 diabetes: A systematic review and meta-analysis. Front Pharmacol. 2022;13:1015045. doi:10.3389/fphar.2022.1015045
  70. Yin J, Xing H, Ye J. Efficacy of berberine in patients with type 2 diabetes mellitus. Metabolism. May 2008;57(5):712-7. doi:10.1016/j.metabol.2008.01.013
  71. Chan E. Displacement of bilirubin from albumin by berberine. Biol Neonate. 1993;63(4):201-8. doi:10.1159/000243932
  72. Abascal K YE. Recent clinical advances with berberine. Altern Complement Ther. 2010;16(5):281-7.
  73. Balk EM, Tatsioni A, Lichtenstein AH, Lau J, Pittas AG. Effect of chromium supplementation on glucose metabolism and lipids: a systematic review of randomized controlled trials. Diabetes Care. Aug 2007;30(8):2154-63. doi:10.2337/dc06-0996
  74. Trumbo P, Yates AA, Schlicker S, Poos M. Dietary reference intakes: vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc. J Am Diet Assoc. Mar 2001;101(3):294-301. doi:10.1016/S0002-8223(01)00078-5
  75. Suksomboon N, Poolsup N, Yuwanakorn A. Systematic review and meta-analysis of the efficacy and safety of chromium supplementation in diabetes. J Clin Pharm Ther. Jun 2014;39(3):292-306. doi:10.1111/jcpt.12147
  76. Cefalu WT, Hu FB. Role of chromium in human health and in diabetes. Diabetes Care. Nov 2004;27(11):2741-51.
  77. Evans GW, Pouchnik DJ. Composition and biological activity of chromium-pyridine carboxylate complexes. J Inorg Biochem. Feb 1993;49(3):177-87.
  78. Wang ZQ, Zhang XH, Russell JC, Hulver M, Cefalu WT. Chromium picolinate enhances skeletal muscle cellular insulin signaling in vivo in obese, insulin-resistant JCR:LA-cp rats. J Nutr. Feb 2006;136(2):415-20. doi:10.1093/jn/136.2.415
  79. Li M, Youngren JF, Dunaif A, et al. Decreased insulin receptor (IR) autophosphorylation in fibroblasts from patients with PCOS: effects of serine kinase inhibitors and IR activators. J Clin Endocrinol Metab. Sep 2002;87(9):4088-93. doi:10.1210/jc.2002-020363
  80. Pender C, Goldfine ID, Manchem VP, et al. Regulation of insulin receptor function by a small molecule insulin receptor activator. J Biol Chem. Nov 2002;277(46):43565-71. doi:10.1074/jbc.M202426200
  81. Althuis MD, Jordan NE, Ludington EA, Wittes JT. Glucose and insulin responses to dietary chromium supplements: a meta-analysis. Am J Clin Nutr. Jul 2002;76(1):148-55. doi:10.1093/ajcn/76.1.148
  82. Zhao F, Pan D, Wang N, et al. Effect of Chromium Supplementation on Blood Glucose and Lipid Levels in Patients with Type 2 Diabetes Mellitus: a Systematic Review and Meta-analysis. Biol Trace Elem Res. Feb 2022;200(2):516-525. doi:10.1007/s12011-021-02693-3
  83. Asbaghi O, Fatemeh N, Mahnaz RK, et al. Effects of chromium supplementation on glycemic control in patients with type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials. Pharmacol Res. Nov 2020;161:105098. doi:10.1016/j.phrs.2020.105098
  84. Fox GN, Sabovic Z. Chromium picolinate supplementation for diabetes mellitus. J Fam Pract. Jan 1998;46(1):83-6.
  85. Nahas R, Moher M. Complementary and alternative medicine for the treatment of type 2 diabetes. Can Fam Physician. Jun 2009;55(6):591-6.
  86. Suksomboon N, Poolsup N, Boonkaew S, Suthisisang CC. Meta-analysis of the effect of herbal supplement on glycemic control in type 2 diabetes. J Ethnopharmacol. Oct 2011;137(3):1328-33. doi:10.1016/j.jep.2011.07.059
  87. Anderson RA, Broadhurst CL, Polansky MM, et al. Isolation and characterization of polyphenol type-A polymers from cinnamon with insulin-like biological activity. J Agric Food Chem. Jan 2004;52(1):65-70. doi:10.1021/jf034916b
  88. Jarvill-Taylor KJ, Anderson RA, Graves DJ. A hydroxychalcone derived from cinnamon functions as a mimetic for insulin in 3T3-L1 adipocytes. J Am Coll Nutr. Aug 2001;20(4):327-36.
  89. Imparl-Radosevich J, Deas S, Polansky MM, et al. Regulation of PTP-1 and insulin receptor kinase by fractions from cinnamon: implications for cinnamon regulation of insulin signalling. Horm Res. Sep 1998;50(3):177-82. doi:10.1159/000023270
  90. Center TR. Cinnamon. 2024 March 25. https://naturalmedicines.therapeuticresearch.com
  91. Akilen R, Tsiami A, Robinson N. Efficacy and safety of 'true' cinnamon (Cinnamomum zeylanicum) as a pharmaceutical agent in diabetes: a systematic review and meta-analysis. Diabet Med. Apr 2013;30(4):505-6. doi:10.1111/dme.12068
  92. Allen RW, Schwartzman E, Baker WL, Coleman CI, Phung OJ. Cinnamon use in type 2 diabetes: an updated systematic review and meta-analysis. Ann Fam Med. 2013 Sep-Oct 2013;11(5):452-9. doi:10.1370/afm.1517
  93. Baker WL, Gutierrez-Williams G, White CM, Kluger J, Coleman CI. Effect of cinnamon on glucose control and lipid parameters. Diabetes Care. Jan 2008;31(1):41-3. doi:10.2337/dc07-1711
  94. Moridpour AH, Kavyani Z, Khosravi S, et al. The effect of cinnamon supplementation on glycemic control in patients with type 2 diabetes mellitus: An updated systematic review and dose-response meta-analysis of randomized controlled trials. Phytother Res. Jan 2024;38(1):117-130. doi:10.1002/ptr.8026
  95. Leach MJ, Kumar S. Cinnamon for diabetes mellitus. Cochrane Database Syst Rev. Sep 12 2012;2012(9):Cd007170. doi:10.1002/14651858.CD007170.pub2
  96. Deyno S, Eneyew K, Seyfe S, et al. Efficacy and safety of cinnamon in type 2 diabetes mellitus and pre-diabetes patients: A meta-analysis and meta-regression. Diabetes Res Clin Pract. Oct 2019;156:107815. doi:10.1016/j.diabres.2019.107815
  97. Lu T, Sheng H, Wu J, Cheng Y, Zhu J, Chen Y. Cinnamon extract improves fasting blood glucose and glycosylated hemoglobin level in Chinese patients with type 2 diabetes. Nutr Res. Jun 2012;32(6):408-12. doi:10.1016/j.nutres.2012.05.003
  98. Khan A, Safdar M, Ali Khan MM, Khattak KN, Anderson RA. Cinnamon improves glucose and lipids of people with type 2 diabetes. Diabetes Care. Dec 2003;26(12):3215-8.
  99. Vanschoonbeek K, Thomassen BJ, Senden JM, Wodzig WK, van Loon LJ. Cinnamon supplementation does not improve glycemic control in postmenopausal type 2 diabetes patients. J Nutr. Apr 2006;136(4):977-80. doi:10.1093/jn/136.4.977
  100. Crawford P. Effectiveness of cinnamon for lowering hemoglobin A1C in patients with type 2 diabetes: a randomized, controlled trial. J Am Board Fam Med. 2009 Sep-Oct 2009;22(5):507-12. doi:10.3122/jabfm.2009.05.080093
  101. Felter SP, Vassallo JD, Carlton BD, Daston GP. A safety assessment of coumarin taking into account species-specificity of toxicokinetics. Food Chem Toxicol. Apr 2006;44(4):462-75. doi:10.1016/j.fct.2005.08.019
  102. Pepping J. Milk thistle: Silybum marianum. Am J Health Syst Pharm. Jun 1999;56(12):1195-7.
  103. Voroneanu L, Nistor I, Dumea R, Apetrii M, Covic A. Silymarin in Type 2 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. J Diabetes Res. 2016;2016:5147468. doi:10.1155/2016/5147468
  104. Flora K, Hahn M, Rosen H, Benner K. Milk thistle (Silybum marianum) for the therapy of liver disease. Am J Gastroenterol. Feb 1998;93(2):139-43. doi:10.1111/j.1572-0241.1998.00139.x
  105. Shahbazi F, Sadighi S, Dashti-Khavidaki S, et al. Effect of Silymarin Administration on Cisplatin Nephrotoxicity: Report from A Pilot, Randomized, Double-Blinded, Placebo-Controlled Clinical Trial. Phytother Res. Jul 2015;29(7):1046-53. doi:10.1002/ptr.5345
  106. Soleymani S, Ayati MH, Mansourzadeh MJ, Namazi N, Zargaran A. The effects of Silymarin on the features of cardiometabolic syndrome in adults: A systematic review and meta-analysis. Phytother Res. Feb 2022;36(2):842-856. doi:10.1002/ptr.7364
  107. Huseini HF, Larijani B, Heshmat R, et al. The efficacy of Silybum marianum (L.) Gaertn. (silymarin) in the treatment of type II diabetes: a randomized, double-blind, placebo-controlled, clinical trial. Phytother Res. Dec 2006;20(12):1036-9. doi:10.1002/ptr.1988
  108. Soto C, Pérez J, García V, Uría E, Vadillo M, Raya L. Effect of silymarin on kidneys of rats suffering from alloxan-induced diabetes mellitus. Phytomedicine. Dec 2010;17(14):1090-4. doi:10.1016/j.phymed.2010.04.011
  109. Detaille D, Sanchez C, Sanz N, Lopez-Novoa JM, Leverve X, El-Mir MY. Interrelation between the inhibition of glycolytic flux by silibinin and the lowering of mitochondrial ROS production in perifused rat hepatocytes. Life Sci. May 2008;82(21-22):1070-6. doi:10.1016/j.lfs.2008.03.007
  110. Xiao F, Gao F, Zhou S, Wang L. The therapeutic effects of silymarin for patients with glucose/lipid metabolic dysfunction: A meta-analysis. Medicine (Baltimore). Oct 2 2020;99(40):e22249. doi:10.1097/md.0000000000022249
  111. Hussain SA. Silymarin as an adjunct to glibenclamide therapy improves long-term and postprandial glycemic control and body mass index in type 2 diabetes. J Med Food. Sep 2007;10(3):543-7. doi:10.1089/jmf.2006.089
  112. Di Pierro F, Putignano P, Villanova N, Montesi L, Moscatiello S, Marchesini G. Preliminary study about the possible glycemic clinical advantage in using a fixed combination of Berberis aristata and Silybum marianum standardized extracts versus only Berberis aristata in patients with type 2 diabetes. Clin Pharmacol. 2013;5:167-74. doi:10.2147/CPAA.S54308
  113. Mulrow C, Lawrence V, Jacobs B, et al. Milk thistle: effects on liver disease and cirrhosis and clinical adverse effects. Evid Rep Technol Assess (Summ). 2000;(21):1-3.
  114. Albassam AA, Frye RF, Markowitz JS. The effect of milk thistle (Silybum marianum) and its main flavonolignans on CYP2C8 enzyme activity in human liver microsomes. Chem Biol Interact. Jun 2017;271:24-29. doi:10.1016/j.cbi.2017.04.025
  115. Kawaguchi-Suzuki M, Frye RF, Zhu HJ, et al. The effects of milk thistle (Silybum marianum) on human cytochrome P450 activity. Drug Metab Dispos. Oct 2014;42(10):1611-6. doi:10.1124/dmd.114.057232
  116. Center TR. Milk thistle. 12 March 2024. https://naturalmedicines.therapeuticresearch.com
  117. Onakpoya IJ, O'Sullivan J, Heneghan CJ. The effect of cactus pear (Opuntia ficus-indica) on body weight and cardiovascular risk factors: a systematic review and meta-analysis of randomized clinical trials. Nutrition. May 2015;31(5):640-6. doi:10.1016/j.nut.2014.11.015
  118. López-Romero P, Pichardo-Ontiveros E, Avila-Nava A, et al. The effect of nopal (Opuntia ficus indica) on postprandial blood glucose, incretins, and antioxidant activity in Mexican patients with type 2 diabetes after consumption of two different composition breakfasts. J Acad Nutr Diet. Nov 2014;114(11):1811-8. doi:10.1016/j.jand.2014.06.352
  119. Argáez-López N, Wacher NH, Kumate-Rodríguez J, et al. The use of complementary and alternative medicine therapies in type 2 diabetic patients in Mexico. Diabetes Care. Aug 2003;26(8):2470-1.
  120. K R, R M, M E. Glycemic effects of various species of nopal (Opuntia sp.) in type 2 diabetes mellitus. Texas J Rural Health. 1998;26:68-76.
  121. RM W, H K, Y E, J S, . SH. Effect of prickly pear (Opuntia robusta) on glucose- and lipid-metabolism in non-diabetics with hyperlipidemia--a pilot study. Wien Klin Wochenschr. 2002;114(19-20):840-6.
  122. Gouws CA, Georgousopoulou EN, Mellor DD, McKune A, Naumovski N. Effects of the Consumption of Prickly Pear Cacti (Opuntia spp.) and its Products on Blood Glucose Levels and Insulin: A Systematic Review. Medicina (Kaunas). May 15 2019;55(5)doi:10.3390/medicina55050138
  123. Godard MP, Ewing BA, Pischel I, Ziegler A, Benedek B, Feistel B. Acute blood glucose lowering effects and long-term safety of OpunDia supplementation in pre-diabetic males and females. J Ethnopharmacol. Aug 9 2010;130(3):631-4. doi:10.1016/j.jep.2010.05.047
  124. Frati AC, Gordillo BE, Altamirano P, Ariza CR, Cortés-Franco R, Chavez-Negrete A. Acute hypoglycemic effect of Opuntia streptacantha Lemaire in NIDDM. Diabetes Care. Apr 1990;13(4):455-6.
  125. Frati-Munari AC, Gordillo BE, Altamirano P, Ariza CR. Hypoglycemic effect of Opuntia streptacantha Lemaire in NIDDM. Diabetes Care. Jan 1988;11(1):63-6.
  126. Lopez-Romero P, Pichardo-Ontiveros E, Avila-Nava A, et al. The effect of nopal (Opuntia ficus indica) on postprandial blood glucose, incretins, and antioxidant activity in Mexican patients with type 2 diabetes after consumption of two different composition breakfasts. J Acad Nutr Diet. Nov 2014;114(11):1811-8. doi:10.1016/j.jand.2014.06.352
  127. T. H. On the domestication of the soybean. Econ Bot. 1970;24(4):408-21.
  128. Erdman JW. AHA Science Advisory: Soy protein and cardiovascular disease: A statement for healthcare professionals from the Nutrition Committee of the AHA. Circulation. Nov 2000;102(20):2555-9.
  129. Zand RS, Jenkins DJ, Diamandis EP. Steroid hormone activity of flavonoids and related compounds. Breast Cancer Res Treat. Jul 2000;62(1):35-49.
  130. Tham DM, Gardner CD, Haskell WL. Clinical review 97: Potential health benefits of dietary phytoestrogens: a review of the clinical, epidemiological, and mechanistic evidence. J Clin Endocrinol Metab. Jul 1998;83(7):2223-35. doi:10.1210/jcem.83.7.4752
  131. Deplancke B, Gaskins HR. Microbial modulation of innate defense: goblet cells and the intestinal mucus layer. Am J Clin Nutr. Jun 2001;73(6):1131S-1141S. doi:10.1093/ajcn/73.6.1131S
  132. Tang J, Wan Y, Zhao M, Zhong H, Zheng JS, Feng F. Legume and soy intake and risk of type 2 diabetes: a systematic review and meta-analysis of prospective cohort studies. Am J Clin Nutr. Mar 1 2020;111(3):677-688. doi:10.1093/ajcn/nqz338
  133. Zuo X, Zhao R, Wu M, Wan Q, Li T. Soy Consumption and the Risk of Type 2 Diabetes and Cardiovascular Diseases: A Systematic Review and Meta-Analysis. Nutrients. Mar 10 2023;15(6)doi:10.3390/nu15061358
  134. Li W, Ruan W, Peng Y, Wang D. Soy and the risk of type 2 diabetes mellitus: A systematic review and meta-analysis of observational studies. Diabetes Res Clin Pract. Mar 2018;137:190-199. doi:10.1016/j.diabres.2018.01.010
  135. Yang B, Chen Y, Xu T, et al. Systematic review and meta-analysis of soy products consumption in patients with type 2 diabetes mellitus. Asia Pac J Clin Nutr. 2011;20(4):593-602.
  136. Liu ZM, Chen YM, Ho SC. Effects of soy intake on glycemic control: a meta-analysis of randomized controlled trials. Am J Clin Nutr. May 2011;93(5):1092-101. doi:10.3945/ajcn.110.007187
  137. Albertazzi P, Pansini F, Bonaccorsi G, Zanotti L, Forini E, De Aloysio D. The effect of dietary soy supplementation on hot flushes. Obstet Gynecol. Jan 1998;91(1):6-11.
  138. Messina M, Redmond G. Effects of soy protein and soybean isoflavones on thyroid function in healthy adults and hypothyroid patients: a review of the relevant literature. Thyroid. Mar 2006;16(3):249-58. doi:10.1089/thy.2006.16.249
  139. Divi RL, Chang HC, Doerge DR. Anti-thyroid isoflavones from soybean: isolation, characterization, and mechanisms of action. Biochem Pharmacol. Nov 1997;54(10):1087-96.
  140. Shulman KI, Walker SE. Refining the MAOI diet: tyramine content of pizzas and soy products. J Clin Psychiatry. Mar 1999;60(3):191-3.
  141. Harland BF, Harden-Williams BA. Is vanadium of human nutritional importance yet? J Am Diet Assoc. Aug 1994;94(8):891-4.
  142. Mukherjee B, Patra B, Mahapatra S, Banerjee P, Tiwari A, Chatterjee M. Vanadium--an element of atypical biological significance. Toxicol Lett. Apr 2004;150(2):135-43. doi:10.1016/j.toxlet.2004.01.009
  143. Cusi K, Cukier S, DeFronzo RA, Torres M, Puchulu FM, Redondo JC. Vanadyl sulfate improves hepatic and muscle insulin sensitivity in type 2 diabetes. J Clin Endocrinol Metab. Mar 2001;86(3):1410-7. doi:10.1210/jcem.86.3.7337
  144. Li X, Zhu Y, Yin J, et al. Inverse Association of Plasma Vanadium Concentrations with Gestational Diabetes Mellitus. Nutrients. Mar 29 2022;14(7)doi:10.3390/nu14071415
  145. Funakoshi T, Shimada H, Kojima S, et al. Anticoagulant action of vanadate. Chem Pharm Bull (Tokyo). Jan 1992;40(1):174-6.
  146. Panel CIRE. Final report on the safety assessment of AloeAndongensis Extract, Aloe Andongensis Leaf Juice,aloe Arborescens Leaf Extract, Aloe Arborescens Leaf Juice, Aloe Arborescens Leaf Protoplasts, Aloe Barbadensis Flower Extract, Aloe Barbadensis Leaf, Aloe Barbadensis Leaf Extract, Aloe Barbadensis Leaf Juice,aloe Barbadensis Leaf Polysaccharides, Aloe Barbadensis Leaf Water, Aloe Ferox Leaf Extract, Aloe Ferox Leaf Juice, and Aloe Ferox Leaf Juice Extract. Int J Toxicol. 2007;26 Suppl 2:1-50. doi:10.1080/10915810701351186
  147. Akaberi M, Sobhani Z, Javadi B, Sahebkar A, Emami SA. Therapeutic effects of Aloe spp. in traditional and modern medicine: A review. Biomed Pharmacother. Dec 2016;84:759-772. doi:10.1016/j.biopha.2016.09.096
  148. Vogler BK, Ernst E. Aloe vera: a systematic review of its clinical effectiveness. Br J Gen Pract. Oct 1999;49(447):823-8.
  149. Choi HC, Kim SJ, Son KY, Oh BJ, Cho BL. Metabolic effects of aloe vera gel complex in obese prediabetes and early non-treated diabetic patients: randomized controlled trial. Nutrition. Sep 2013;29(9):1110-4. doi:10.1016/j.nut.2013.02.015
  150. Beppu H, Shimpo K, Chihara T, et al. Antidiabetic effects of dietary administration of Aloe arborescens Miller components on multiple low-dose streptozotocin-induced diabetes in mice: investigation on hypoglycemic action and systemic absorption dynamics of aloe components. J Ethnopharmacol. Feb 2006;103(3):468-77. doi:10.1016/j.jep.2005.10.034
  151. Araya-Quintanilla F, Gutiérrez-Espinoza H, Cuyul-Vásquez I, Pavez L. Effectiveness of aloe vera in patients with type 2 Diabetes Mellitus and pre-diabetes: An overview of systematic reviews. Diabetes Metab Syndr. Nov-Dec 2021;15(6):102292. doi:10.1016/j.dsx.2021.102292
  152. Dick WR, Fletcher EA, Shah SA. Reduction of Fasting Blood Glucose and Hemoglobin A1c Using Oral Aloe Vera: A Meta-Analysis. J Altern Complement Med. Jun 2016;22(6):450-7. doi:10.1089/acm.2015.0122
  153. Alinejad-Mofrad S, Foadoddini M, Saadatjoo SA, Shayesteh M. Improvement of glucose and lipid profile status with Aloe vera in pre-diabetic subjects: a randomized controlled-trial. J Diabetes Metab Disord. 2015;14:22. doi:10.1186/s40200-015-0137-2
  154. Suksomboon N, Poolsup N, Punthanitisarn S. Effect of Aloe vera on glycaemic control in prediabetes and type 2 diabetes: a systematic review and meta-analysis. J Clin Pharm Ther. Apr 2016;41(2):180-8. doi:10.1111/jcpt.12382
  155. Bloedon LT, Szapary PO. Flaxseed and cardiovascular risk. Nutr Rev. Jan 2004;62(1):18-27.
  156. Adachi T, Tanaka T, Takemoto K, Koshimizu T-a, Hirasawa A, Tsujimoto G. Free fatty acids administered into the colon promote the secretion of glucagon-like peptide-1 and insulin. Biochemical and Biophysical Research Communications. 2006/02/03/ 2006;340(1):332-337. doi:https://doi.org/10.1016/j.bbrc.2005.11.162
  157. Javidi A, Mozaffari-Khosravi H, Nadjarzadeh A, Dehghani A, Eftekhari MH. The effect of flaxseed powder on insulin resistance indices and blood pressure in prediabetic individuals: A randomized controlled clinical trial. J Res Med Sci. 2016;21:70. doi:10.4103/1735-1995.189660
  158. Jenkins DJ, Kendall CW, Vidgen E, et al. Health aspects of partially defatted flaxseed, including effects on serum lipids, oxidative measures, and ex vivo androgen and progestin activity: a controlled crossover trial. Am J Clin Nutr. Mar 1999;69(3):395-402. doi:10.1093/ajcn/69.3.395
  159. Nettleton JA, Katz R. n-3 long-chain polyunsaturated fatty acids in type 2 diabetes: a review. J Am Diet Assoc. Mar 2005;105(3):428-40. doi:10.1016/j.jada.2004.11.029
  160. Xi H, Zhou W, Sohaib M, et al. Flaxseed supplementation significantly reduces hemoglobin A1c in patients with type 2 diabetes mellitus: A systematic review and meta-analysis. Nutr Res. Feb 2023;110:23-32. doi:10.1016/j.nutres.2022.12.008
  161. Soltanian N, Janghorbani M. A randomized trial of the effects of flaxseed to manage constipation, weight, glycemia, and lipids in constipated patients with type 2 diabetes. Nutr Metab (Lond). 2018;15:36. doi:10.1186/s12986-018-0273-z
  162. Pan A, Sun J, Chen Y, et al. Effects of a flaxseed-derived lignan supplement in type 2 diabetic patients: a randomized, double-blind, cross-over trial. PLoS One. Nov 2007;2(11):e1148. doi:10.1371/journal.pone.0001148
  163. Mani UV, Mani I, Biswas M, Kumar SN. An open-label study on the effect of flax seed powder (Linum usitatissimum) supplementation in the management of diabetes mellitus. J Diet Suppl. Sep 2011;8(3):257-65. doi:10.3109/19390211.2011.593615
  164. Hutchins AM, Brown BD, Cunnane SC, Domitrovich SG, Adams ER, Bobowiec CE. Daily flaxseed consumption improves glycemic control in obese men and women with pre-diabetes: a randomized study. Nutr Res. May 2013;33(5):367-75. doi:10.1016/j.nutres.2013.02.012
  165. Nordström DC, Honkanen VE, Nasu Y, Antila E, Friman C, Konttinen YT. Alpha-linolenic acid in the treatment of rheumatoid arthritis. A double-blind, placebo-controlled and randomized study: flaxseed vs. safflower seed. Rheumatol Int. 1995;14(6):231-4. doi:10.1007/bf00262088
  166. Laitinen LA, Tammela PS, Galkin A, Vuorela HJ, Marvola ML, Vuorela PM. Effects of extracts of commonly consumed food supplements and food fractions on the permeability of drugs across Caco-2 cell monolayers. Pharm Res. Oct 2004;21(10):1904-16.
  167. Araújo CC, Leon LL. Biological activities of Curcuma longa L. Mem Inst Oswaldo Cruz. Jul 2001;96(5):723-8.
  168. Zhang DW, Fu M, Gao SH, Liu JL. Curcumin and diabetes: a systematic review. Evid Based Complement Alternat Med. 2013;2013:636053. doi:10.1155/2013/636053
  169. Kumar S, Sharma SK, Mudgal SK, et al. Comparative effectiveness of six herbs in the management of glycemic status of type 2 diabetes mellitus patients: A systematic review and network meta-analysis of randomized controlled trials. Diabetes Metab Syndr. Aug 2023;17(8):102826. doi:10.1016/j.dsx.2023.102826
  170. Altobelli E, Angeletti PM, Marziliano C, Mastrodomenico M, Giuliani AR, Petrocelli R. Potential Therapeutic Effects of Curcumin on Glycemic and Lipid Profile in Uncomplicated Type 2 Diabetes-A Meta-Analysis of Randomized Controlled Trial. Nutrients. Jan 27 2021;13(2)doi:10.3390/nu13020404
  171. Chuengsamarn S, Rattanamongkolgul S, Phonrat B, Tungtrongchitr R, Jirawatnotai S. Reduction of atherogenic risk in patients with type 2 diabetes by curcuminoid extract: a randomized controlled trial. J Nutr Biochem. Feb 2014;25(2):144-50. doi:10.1016/j.jnutbio.2013.09.013
  172. Daveluy A, Géniaux H, Thibaud L, Mallaret M, Miremont-Salamé G, Haramburu F. Probable interaction between an oral vitamin K antagonist and turmeric (Curcuma longa). Therapie. 2014 Nov-Dec 2014;69(6):519-20. doi:10.2515/therapie/2014062
  173. Garrow D, Egede LE. Association between complementary and alternative medicine use, preventive care practices, and use of conventional medical services among adults with diabetes. Diabetes Care. Jan 2006;29(1):15-9.
  174. Hegde SV, Adhikari P, Kotian S, Pinto VJ, D'Souza S, D'Souza V. Effect of 3-month yoga on oxidative stress in type 2 diabetes with or without complications: a controlled clinical trial. Diabetes Care. Oct 2011;34(10):2208-10. doi:10.2337/dc10-2430
  175. Innes KE, Selfe TK. Yoga for Adults with Type 2 Diabetes: A Systematic Review of Controlled Trials. J Diabetes Res. 2016;2016:6979370. doi:10.1155/2016/6979370
  176. Wu S, Wang L, He Y, et al. Effects of different mind-body exercises on glucose and lipid metabolism in patients with type 2 diabetes: A network meta-analysis. Complement Ther Clin Pract. Nov 2023;53:101802. doi:10.1016/j.ctcp.2023.101802
  177. Cangelosi G, Acito M, Grappasonni I, et al. Yoga or Mindfulness on Diabetes: Scoping Review for Theoretical Experimental Framework. Ann Ig. Mar-Apr 2024;36(2):153-168. doi:10.7416/ai.2024.2600
  178. T F, M H-R, A L. Glucose levels decreased after giving massage therapy to children with diabetes mellitus. . Spectrum. 1997;10:23-5.
  179. Zhao H, Teng J, Song G, et al. The optimal exercise parameters of Tai Chi on the effect of glucose and lipid metabolism in patients with type 2 diabetes mellitus: A meta-analysis. Complement Ther Med. Dec 2023;79:102995. doi:10.1016/j.ctim.2023.102995
  180. Champagne CP, Gardner NJ, Roy D. Challenges in the addition of probiotic cultures to foods. Crit Rev Food Sci Nutr. 2005;45(1):61-84. doi:10.1080/10408690590900144
  181. Tsang T, Orr R, Lam P, Comino E, Singh MF. Effects of Tai Chi on glucose homeostasis and insulin sensitivity in older adults with type 2 diabetes: a randomised double-blind sham-exercise-controlled trial. Age Ageing. Jan 2008;37(1):64-71. doi:10.1093/ageing/afm127
  182. Lam P, Dennis SM, Diamond TH, Zwar N. Improving glycaemic and BP control in type 2 diabetes. The effectiveness of tai chi. Aust Fam Physician. Oct 2008;37(10):884-7.
  183. Administration USFaD. 6 Tip-offs to Rip-offs: Don't Fall for Health Fraud Scams. Updated 2021 March 4. Accessed June 26, 2024. https://www.fda.gov/consumers/consumer-updates/6-tip-offs-rip-offs-dont-fall-health-fraud-scams

 

Clinical Management of Dyslipidemia in Youth with Chronic Kidney Disease

ABSTRACT

 

Chronic kidney disease (CKD) is commonly associated with abnormal lipid metabolism which may contribute to the morbidity and premature mortality associated with impaired renal function.  Dyslipidemia often occurs in the early phases and becomes progressively worse with disease severity and progression to end stage renal disease (ESRD). In this review, we discuss the clinical features, diagnosis, and management of dyslipidemia in children with renal disease, focusing primarily on nephrotic syndrome (NS) and ESRD.  There are limited data on treatment of dyslipidemia, outcomes, and prevention of CVD in youth with these conditions to help inform clinical decision-making and define best practices. 

 

INTRODUCTION

 

Chronic kidney disease (CKD) is characterized by a progressive decrease in renal function, divided into five stages (Table 1).  The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) defines CKD as a glomerular filtration rate (GFR) persistently < 60 mL/min (1). Further decline in kidney function results in ESRD, with permanent and complete loss of renal function, necessitating either dialysis or renal transplantation. Due to a wide variety of common causes, including diabetes and hypertension, the prevalence of CKD is increasing (2).  In individuals with CKD, CVD is the leading cause of death and dyslipidemia is recognized as a major risk factor (3).  Mortality in up to half of individuals with CKD is the result of CVD (4).

 

Table 1. CKD Stages

Stage

GFR

1

> 90

mL/min

2

60-90

mL/min

3A

45-59

mL/min

3B

30-44

mL/min

4

15-29

mL/min

5

< 15

mL/min

Modified from Table 1 Hager et al (1).

 

Nephrotic Syndrome (NS), clinically characterized by proteinuria, hypoalbuminemia, and edema, is one of the most common kidney diseases affecting youth. Injury to podocytes and glomeruli in NS is well described. Complications include acute injury of the kidney, systemic infection, and thromboembolism. Dyslipidemia is common and corresponds to the severity of proteinuria with or without CKD. In adults, risk of fatal and non-fatal MI is based upon the degree of proteinuria and the GFR. Despite the presence of dyslipidemia similar to that in adults, youth with CKD are often undertreated. This, in part, may reflect a lack of data regarding CVD risk in this population (5).

 

In addition to traditional risk factors, CVD disease in youth with ESRD appears to be directly related to the effects of renal impairment, exacerbated, in part, by medications necessary for treatment. Because mono and polygenic disorders affecting lipid and lipoprotein metabolism are common, some youth may also have an underlying predisposition to atherosclerosis in addition to the risk associated with renal failure – the impact of these on the risk of coronary artery disease and of congestive heart failure may well be substantially larger among younger patients (6,7).

 

Early onset of risk factors in children with kidney disease provides a longer period of exposure, significantly increasing risk of premature CVD. Although unproven, it is likely that optimum management of risk factors, such as elevated cholesterol and blood pressure, especially when implemented at an early age, may result in substantial reduction in subsequent incidence of CVD-related events. It is important, therefore, that youth with ESRD undergo global risk factor assessment and that all risk factors be optimally managed. Based on randomized trials, data suggests that reduction of LDL-C concentrations may decrease the risk of CVD among individuals with renal failure who have average (or even below average) LDL-C concentrations (8-11).

 

ETIOLOGY AND PATHOGENESIS OF DYSLIPIDEMIA IN KIDNEY DISEASE

 

The pattern of dyslipidemia seen in CKD is typically characterized by hypertriglyceridemia (HTG), decreased HDL-C, variable changes in LDL-C, increase in non-HDL-C, and an increase in small dense LDL-C (12), as well as an increase in the apoB to apoA-I ratio. Elevations in Lp (a) are also common in CKD.  However, elevations in Lp (a) generally occur in subgroups of individuals who express larger Lp (a) isoforms (13). HTG is present in early stages of renal disease and its origin is multifactorial, including impaired catabolism of VLDL and chylomicrons secondary to decreased lipoprotein lipase (LPL) activity. With the onset of uremia, inhibitors of LPL are increased, including apoC-III and pre-beta-HDL.  A decrease in lecithin cholesterol ester transfer protein (LCAT), important for the maturation of HDL, and reduced expression of the apoA-I gene APOA1, the main apolipoprotein of HDL, have also been reported. These changes in gene expression and protein availability lead to alterations in two key HDL functions: 1) reverse cholesterol transport; and 2) anti-oxidation (1).

 

Individuals with NS often have elevated triglycerides (TG) and other atherogenic apoB-containing lipoproteins, including VLDL, IDL, LDL, and lipoprotein(a).  A decrease in oncotic pressure may be contributory to increased production of lipoproteins by stimulating the synthesis of apoB.  However, the mechanisms are not well understood. HDL-C levels are similar to those of healthy individuals.  Despite normal levels, however, it is likely the efficiency of the HDL-related reverse cholesterol transport in NS is decreased. The elevation in TG is likely due to decreased LPL activity. There is also downregulation of glycosylphosphatidylinositol-anchored HDL-binding protein 1 (GPIHBP1), which serves to anchor LPL to heparin sulfate proteoglycans on endothelial cells. The increased levels of LDL-C seen in NS is believed to be the result of increased production through increased acyl-CoA cholesterol acyltransferase (ACAT) and HMG-CoA reductase activity and decreased clearance through decreased LDL-receptor activity.  Increased activity of proprotein convertase subtilisin/kexin type 9 (PCSK9) has also been reported, leading to a decrease in the number of LDL receptors and a reduction in hepatic uptake (5).

 

Table 2- Lipid Patterns in Kidney Disease

Lipid / Lipoprotein

CKD 1-5

Nephrotic Syndrome

Hemodialysis

Peritoneal Dialysis

Total Cholesterol

Progressive increase

↑↑

↔ ↓

TG

Progressive increase

↑↑

HDL-C

LDL-C

Progressive increase

↑↑

↔ ↓

Non-HDL cholesterol

Progressive increase

↑↑

↔ ↓

Lipoprotein (a)

Progressive increase

↑↑

↑↑

Modified from Mikolasevic et al (14).

 

CLINICAL FEATURES

 

Nephrotic Syndrome

 

Elevated fractions of apoB-containing particles in NS can increase the risk for formation of atherosclerotic plaque, leading to CVD-related events, such as MI and stroke, and may contribute to the increased risk for thrombosis and other adverse events (Table 3).  Progressive loss of renal function and development of CKD further increases the risk of morbidity (5).

 

Dyslipidemia may also contribute to glomerulosclerosis (15), further damaging the kidney (i.e., the lipid nephrotoxicity hypothesis). Excess accumulation of lipids, particularly in the interstitium and glomeruli (16), is accompanied by a pronounced inflammatory response, which appears to injure glomerular podocytes and mesangial cells. Such changes contribute to renal injury and impaired function. 

 

Table 3. Nephrotic Syndrome and CKD Estimates of Clinical Consequences of Dyslipidemia

 

NS

CKD

NS and CKD

CVD

·       Atherosclerosis

++

+

+++

·       Myocardial infarction

++

+

+++

·       Stroke

++

+

+++

Progressive Kidney Disease

·       Glomerulosclerosis

++

+

+++

·       Mesangial Proliferation

+

+/-

+

·       Podocyte injury

+

+

++

·       Tubuloinsterstitial disease

++

+

+++

·       Proximal tubular cell injury

+

+

++

NS=nephrotic syndrome; CKD=chronic kidney disease.

Adapted from Table 2 Agrawal, et al (5).

 

Chronic Kidney Disease  

 

Dyslipidemia in CKD is characterized by increased serum levels of TG, decreased HDL-C, variable levels of LDL-C and an increase in apoB to apoA-I ratio. HTG is often present even in the early stages of CKD and is one of the most common lipid abnormalities encountered in this population. A large cross-sectional analysis of 391 children ((236 male, 154 female aged 1-16 years (median age 12 years), 71% Caucasian) with moderate CKD (median GFR 43 mL/min/1.73m2) enrolled in the Chronic Kidney Disease in Children (CKiD) Study noted 32% of children with HTG, 21% low HDL-C and 16% elevated non-HDL-C (17). Overall, 45% children with CKD had dyslipidemia, and of those 179 children, 45% had two or more lipid abnormalities.

 

There was a higher prevalence of HTG in children with nephrotic-range proteinuria (61%), as compared to 21%, 30%, and 24% in children with normal, mild, and moderate proteinuria, respectively. Twenty-one percent (21%) had a total cholesterol (TC) >200 mg/dl.  However, no relationship was observed between TC and GFR. Twenty-one percent (21%) had HDL-C <40 mg/d, and obese children had an average HDL-C 14% lower than children with normal BMI. Changes in LDL-C levels were not discussed in this study (17).

 

Longitudinal data of 508 children (76% non-glomerular CKD, 24% glomerular CKD) from the CKiD study, representing 1,514 person-visits and a median follow-up of 4 years (interquartile range, 2.1–6.0), showed that non-HDL-C and TG worsened in proportion to declining GFR, increasing BMI and worsening proteinuria (18).  A waist to height ratio of >0.49 has also been shown to be associated with lower HDL-C, higher left ventricular mass index, TGs, and non-HDL cholesterol compared to lean controls (19).

 

The prevalence of dyslipidemia was 61.5% among 356 East Asian pediatric patients < 20 years of age (median age 10.8 years; 246 males, 110 females) with CKD who participated in the KoreaN cohort study for Outcomes in patients WithPediatric Chronic Kidney Disease (KNOW-PedCKD) (20). Twenty-five percent (25%) had elevated TC, 19% elevated LDL-C, 15.2% low HDL-C, and 15.2% elevated TG. The authors demonstrated that children with glomerulonephropathy and nephrotic range proteinuria exhibited increased risk for high TC; whereas increased BMI z-score, elevated proteinuria, hypocalcemia, and 1,25-dihydroxyvitamin D deficiency were associated with low HDL-C. Glomerular filtration rate stage 3b or higher and hyperphosphatemia were associated with increased the risk for HTG (20).

 

Dialysis

 

While dyslipidemia is common in ESRD, the need for chronic dialysis, either hemodialysis (HD) or continuous ambulatory peritoneal dialysis (CAPD), often results in further alteration in lipids and lipoproteins (21,22). Some studies demonstrate no significant differences in TC, LDL-C, HDL-C, TG, ApoA, ApoB, or Lp(a) serum levels between individuals receiving HD when compared to PD (23).  However other studies reported important differences in lipoprotein concentrations and their composition in adults undergoing HD and CAPD. A more atherogenic profile was observed in the latter group, consisting mainly of lower concentrations of HDL-C with higher levels of TC, TG, LDL-C, ApoB and ApoE. CAPD patients showed significantly higher TG and LDL-C levels, with a different pattern of apoprotein profile characterized by lower ApoA-I levels and higher ApoE levels than controls. Similar differences in ApoA-I and ApoE were also seen between controls and HD patients, whereas in the hemodialysis group a significant increase in ApoB was also observed (24).

 

There have been studies demonstrating different lipid patterns in children receiving dialysis.  Children (aged 12.6 +/- 4.7 years) undergoing treatment with continuous ambulatory peritoneal dialysis/continuous cycling peritoneal dialysis (CAPD/CCPD) were found to have fasting mean levels of TGs (90%) and cholesterol (69%) above the 95th percentile of published normal values prior to the start of dialysis. The authors found a high prevalence of hyperlipidemia at baseline with no significant change of serum lipid levels during 2 years of treatment with CAPD/CCPD. (25).

 

Renal Transplantation

 

Second only to infection, cardiovascular disease is a significant cause of mortality in pediatric renal transplant patients (26). Analysis of retrospective data from the CERTAIN registry (386-transplant recipients aged 0.5-25 years) showed the prevalence of dyslipidemia to be 95% before engraftment and 88% at 1-year following transplant (27). TC and LDL-C levels are considerably higher post-renal transplant compared to children undergoing hemodialysis (27). Risk factors include elevated pre-transplant serum cholesterol, years since renal transplant (28), and use of certain immunosuppressive medications (28).

 

Immunosuppressive drugs, including prednisone, cyclosporine, and sirolimus, have been shown to be associated with dyslipidemia, whereas the use of tacrolimus and mycophenolic acid is associated with lower lipid parameters (27,28,29). TC and LDL-C in these children have not been shown to have direct association with age, sex, ethnicity, duration of ESRD, stage of chronic kidney disease, diabetes mellitus, or BMI (27,28). Reduced GFR is a risk factor for elevated TGs in this population (27,30). 

 

DIAGNOSIS

 

Dyslipidemia in children with renal disease is the result of complex interactions of a variety of factors, including the primary disease process, use of medications such as corticosteroids, the presence of malnutrition or obesity, diet, and genetics.  When present in NS or those who have undergone renal transplantation, dyslipidemia it is easily recognized; while often less obvious in those with chronic renal insufficiency or ESRD.  Detection of dyslipidemia in the latter requires more careful analysis and knowledge of normal laboratory ranges for children. Current KDIGO clinical practice guidelines recommend an initial lipid profile in all newly diagnosed children with CKD, including those who require chronic dialysis therapy or kidney transplant therapy. After the initial lipid profile, annual testing is recommended (31).

 

MANAGEMENT

 

Since publication of the 2003 National Kidney Foundation-Kidney Disease Outcomes Quality Initiative (NKF-KDOQI) clinical guidelines for management of dyslipidemia in CKD, data from randomized controlled trials on statin therapy in adults with CKD KDIGO (Kidney Disease: Improving Global Outcomes or KDIGO) have helped inform management guidelines.  Recommendations for treatment (Table 4 and Table 5) are based on risk for coronary heart disease (32, 33, 34). It should be recognized, however, that clinical recommendations (Table 5) differ for adults as well as children. While all guidelines target CVD prevention, none specifically address treatment of lipid abnormalities to prevent deterioration of kidney function, especially in youth with NS (15,16).

 

Table 4.  Assessment of lipid status and treatment in children (< 18 years-of-age) with chronic kidney disease (CKD)

Clinical Scenario

Lipid Profile

Statins ± Ezetimibe

Management of HTG

CKD, including those treated with chronic dialysis or kidney transplantation.

Recommended at initial diagnosis and repeated annually.

Not recommended.

Therapeutic lifestyle changes are recommended.

Lipid profile=TC, TG, HDL-C and LDL-C. Modified from: Wanner (32).

 

Table 5. Lipid management guidelines for CKD in Children < 18 years-of-age

KDIGO

ACC/AHA

2014 ADA

AACE

Do not initiate.

Prior AHA statement for high-risk patients (including CKD) recommends therapeutic lifestyle intervention; if >10 years-of-age and LDL-C remains >100 mg/dL despite therapeutic lifestyle recommendations, treat with statin.

If patient has DM, consider statin use ≥10 years-of-age if, following changes in diet and lifestyle, LDL-C >160 or >130 mg/dL with multiple risk factors.

Recommend pharmacotherapy for > 8 years-of-age if no response to therapeutic lifestyle, especially if LDL-C ≥ 190 or ≥ 160 mg/dL with additional risk factors.

Adapted from Table 1; Sarnak (33).  ACC/AHA, 2014 ADA, and AACE guidelines not CKD specific.

 

Nephrotic Syndrome

 

Treatment options for dyslipidemia in children with NS include lifestyle changes and pharmacologic agents.  Little evidence exists on optimal lifestyle management in children with NS, and the majority of studies have included adult populations. Studies of soy-based vegetarian diets have shown promising results, but include limited subjects and these findings have not been confirmed (35,36). The addition of omega-3 fatty acids has demonstrated a small decrease in TG and postprandial chylomicron levels (37,38).

 

There is also very limited data on pharmacologic treatment in youth compared with the adult population. Medications commonly used in adults include statins, bile acid sequestrants, and fibric acid derivatives. Most of the studies in youth have been limited to statins. These studies have shown reductions in TG and LDL-C levels but tend to be small in number and often lack a control group (5).

 

The utility of lipid apheresis, a technique used to lower cholesterol in patients with homozygous familial hypercholesterolemia, has been assessed in youth with NS.  A study of children who underwent lipid apheresis in combination with prednisone found reductions in both cholesterol and TG.  Of the study group, 7/11 youth achieved a partial or complete remission of NS; and all remained in remission at their 10-year follow-up (39).  However, as discussed in other chapters of Endotext, lipid apheresis is currently not preformed specifically for lipid management.  At present, apheresis is only FDA approved for new onset focal segmental glomerulosclerosis in pediatric patients who are resistant to standard forms of treatment (40).

 

Chronic Kidney Disease

 

The American Heart Association (AHA) classifies youth with ESRD in the highest risk group and those with pre-dialysis CKD at moderate risk for development of CVD and its sequelae. It recommends therapeutic lifestyle changes (TLC) as the initial management strategy, with the goal of lowering LDL to ≤130 mg/dL and TG <400; with addition of pharmacological therapy if these goals are not met (41).  In the SHARP trial, 9270 adult patients with CKD or ESRD were randomly divided into simvastatin plus ezetimibe, simvastatin, and placebo groups (42).  The goal of the study was to look at primary prevent of a major atherosclerotic cardiac event.  The patients were followed for a median of 4.9 years, and the simvastatin and ezetimibe group had significant risk reduction of a major atherosclerotic event.

 

In contrast, the KDIGO 2013 clinical practice guidelines recommend assessment of fasting lipids annually, while discouraging the use of statin or statin/ezetimibe combination in youth <18 years with CKD (33,43).  Boys >10 years-of-age and post-menarche girls with severely elevated LDL-C in the setting of a family history of premature coronary disease, diabetes, hypertension, smoking, and ESRD might be candidates for low dose statin use. However multi-drug regimens, even in youth with severely elevated LDL-C (43), is not recommended.

 

In youth with fasting TG >500 mg/dL, KDIGO recommendations a very low-fat diet (<15% total calories), use of medium-chain triglycerides, and fish oil. Pharmacologic treatment can be considered in those with TG >1000 mg/dL, however, the safety or efficacy of fibric acid or niacin for this population is unknown (44).

 

In 2011, the NHLBI, although focused primarily on youth with FH, recommended pharmacologic management for children >10 years-of-age with LDL-C >190 mg/dL alone, >160 mg/dL with one high-risk condition, or >130 mg/dL with two high-risk conditions despite lifestyle modifications. High-risk conditions include high blood pressure (treated with antihypertensive medication), BMI >97th percentile, smoking, and chronic kidney disease (45).

 

Dialysis

 

CVD-related events are the leading cause of death among adults with ESRD receiving maintenance dialysis.  It accounts for 45% of deaths, a rate 10-30 times higher than that in the general population (46-50).

 

The relationship between serum cholesterol and CVD is more complex in individuals with CKD, particularly those receiving maintenance hemodialysis. A history of coronary heart disease, coronary artery bypass surgery, coronary angioplasty or an abnormal coronary angiogram was present in 36% (peritoneal dialysis) and 42% (hemodialysis dialysis) (51).

 

In contrast, comparable data in youth receiving maintenance dialysis are limited in regards to the prevalence of CVD-related risk factors, clinical management of modifiable risk factors, and the incidence of morbidity and mortality.  Despite the common occurrence of hyperlipidemia in youth with ESRD, monitoring is rarely performed (52,53). The relative risk of CVD, however, appears to be even greater in younger dialysis patients (8).

 

A study by Blanche and colleagues suggests CVD is also common amongst children who require chronic dialysis. (Table 6) The type of cardiac-related events differed significantly among ethnic groups, being highest among Black youth (54).

 

Table 6.  Adjusted annual cardiac events/1000 patient-years in children receiving chronic dialysis

Event

1991

1992

1993

1994

1995

1996

Trend

Arrhythmia

90.9

115

138.9

145.0

141.3

128.6

P= NS

Cardiac Arrest

19.1

18.0

10.0

19.5

11.6

22.0

P= NS

Valvular disease

59.3

66.3

55.4

91.2

79.6

68.1

P= NS

Cardiomyopathy

42.0

44.9

50.9

60.7

73.8

84.8

P= 0.003

All-cause death

56.9

30.7

31.1

48.1

32.2

31.4

P=NS

Cardiac death

14.4

10.4

12.6

18.1

12.4

4.5

P=NS

Adapted from Table 2, Chavers (54).

 

Despite the increased prevalence of CVD, randomized controlled trials have not shown definitive evidence that lipid-lowering therapies are effective in reducing risk in adults with ESRD who require chronic dialysis. This lack of benefit may be the result of 1) a significant difference in the pathophysiology and spectrum of CVD in adults who require chronic dialysis compared to the general population; and 2) although affected by atherosclerosis, the majority of deaths in dialysis patients are not related to coronary artery disease and, therefore, would not be expected to respond favorably to lipid-lowering therapy.

 

As noted in the Table 6, coronary disease in youth with ESRD receiving chronic dialysis is also rare. Most of the CVD involves cardiomyopathy and/or dysrhythmia. Therefore, as in adults, lipid-lowering therapy may be of limited benefit in this population.

 

In its 2014 clinical practice guidelines, the KDIGO Work Group noted that the magnitude of any relative risk reduction in individuals who require chronic dialysis appears to be substantially smaller than in earlier stages of CKD. Therefore, the KDIGO Work Group does not recommend initiation of statin treatment for most adults and children undergoing chronic dialysis. Previous guidelines in this population suggested the use of targets for LDL-C, with treatment escalation to higher doses of statin when LDL-C targets are not achieved with lower dose therapy. Current recommendations, however, do not support this strategy since higher doses of statins have not been proven to be safe in the setting of CKD. Furthermore, since LDL-C levels do not necessarily suggest the need to increase statin doses, follow-up measurement of lipid levels is not recommended (55).

 

While there is little evidence that lifestyle changes will reduce serum TG levels and/or improve clinical outcomes in adults, the KDIGO Work Group recommend advising youth with high fasting levels of serum TGs (>5.65 mmol/l or >500 mg/dl) to adopt lifestyle changes (54). Dietary modification should be used judiciously, if at all, in youth who are malnourished. The safety and efficacy of fibric acid and niacin have not been established in youth nor FDA approved for use in this population. Prescription omega-3-fatty acids appear to lower serum TGs in adults. The benefits, harms, and tolerability of such treatment in children is unproven, nor are there data to suggest preferential use of EPA vs combination EPA/DHA productions.

 

Renal Transplantation

 

TLC remains the first-line intervention for treatment of dyslipidemia in youth who undergo renal transplantation. The KDOQI clinical practice guidelines for nutrition in youth recommend that families receive intensive nutrition guidance to promote a heart-healthy diet and ≥60 minutes of active play time daily, along with limiting screen time (television + computer + video games) to ≤2 hours per day (56). KDIGO guidelines recommends against the use of statin or statin/ezetimibe combination in youth <18 years, although low dose statin should be considered in boys >10 years and post-menarche girls with severely elevated LDL-C in the setting of a family history of premature coronary disease, diabetes, hypertension, smoking, and ESRD (43).

 

NHLBI and AHA both recommended considering pharmacologic therapy if LDL-C goals are not met with TLC alone. If statins are considered, caution needs to be exercised and low doses given concommitentlly with medications that utilize the CYP3A4 pathway, like cyclosporine, as they may increase serum concentration of the statin and risk of statin-induced rhabdomyolysis. There are no randomized trials for use of ezetimibe or bile acid sequestrants in pediatric renal transplant patients; and KDIGO does not recommend multi-drug regimens even in those with severely elevated LDL-C. The use of fibrates in adult renal transplant recipients with HTG has been accompanied by elevations in serum creatinine and also with reduced cyclosporine concentrations when used concomitantly (57).  It should be noted that the effect of cyclosporine is more complex than CYP3A4 inhibition alone (see chapter 18 of Endotext on medications which states, in part, “ Most statins are transported into the liver and other tissues by organic anion transporting polypeptides, particularly OATP1B1. Drugs, such as clarithromycin, ritonavir, indinavir, saquinavir, and cyclosporine that inhibit OATP1B1 can increase serum statin levels thereby increasing the risk of statin muscle toxicity. Fluvastatin is the statin that is least affected by OATP1B1 inhibitors. In fact, fluvastatin 40mg per day has been studied in adults receiving renal transplants concomitantly treated with cyclosporine and over a five year study period the risk of myopathy or rhabdomyolysis was not increased in the fluvastatin treated patients compared to those treated with placebo.”)

 

Several studies have shown an impact of cyclosporine mTOR inhibitor and prednisone immunosuppressive regimen on post-transplant dyslipidemia and this may contribute to CVD morbidity and mortality in pediatric renal transplant recipients (27,28,58).  One study noted the prevalence of post-transplant dyslipidemia may be decreasing with the use of newer immunosuppressive regimens that include tacrolimus and lower doses of prednisone (28). Thus, improvement of the CVD risk profile may be accomplished by alteration of the immunosuppressive regimen.

 

CONCLUSIONS

 

Chronic kidney disease and nephrotic syndrome are often accompanied by dyslipidemia, contributing to disease-related morbidity and increasing risk of premature CVD. Given the lack of randomized controlled trials in youth and long-term clinical outcomes, such as CVD-related events and mortality, optimum management is unknown. Further research is needed to demonstrate the benefit of strategies to improve health and wellbeing in this vulnerable population, including use of lipid-lowering medications, with the aim of decreasing CVD-related events. In addition, given the role of dyslipidemia in potentially contributing to deterioration of renal function in youth with NS, aggressive lipid-lowering therapy may be beneficial. Further studies, however, are needed.

 

ACKNOWLEDGEMENTS

 

The authors would like to acknowledge Luke Hamilton, Suzanne Beckett, Dena Hanson, and Ashley Brock for their assistance in preparing and editing this manuscript.

 

REFERENCES

 

  1. Hager MR, Narla AD, Tannock LR. Dyslipidemia in patients with chronic kidney disease. Rev Endocr Metab Disord. 2017;18(1):29-40.
  2. Reiss AB, Voloshyna I, De Leon J, et al. Cholesterol metabolism in CKD. Am J Kidney Dis. 2015;66(6):1071-1082.
  3. Vaziri ND, Norris K. Lipid disorders and their relevance to outcomes in chronic kidney disease. Blood Purif. 2011;31(1-3):189-196.
  4. Matsushita K, Ballew SH, Coresh J. Cardiovascular risk prediction in people with chronic kidney disease. Curr Opin Nephrol Hypertens. 2016;25(6):518-523.
  5. Agrawal S, Zaritsky JJ, Fornoni A, Smoyer WE. Dyslipidaemia in nephrotic syndrome: mechanisms and treatment. Nat Rev Nephrol. 2018;14(1):57-70.
  6. Prospective Studies Collaboration. Cholesterol, diastolic blood pressure, and stroke: 13,000 strokes in 450,000 people in 45 prospective cohorts. Lancet. 1995;346(8991-8992):1647-1653.
  7. Law MR, Wald NJ, Thompson SG. By how much and how quickly does reduction in serum cholesterol concentration lower risk of ischaemic heart disease? BMJ. 1994;308(6925):367-372.
  8. Baigent C, Burbury K, Wheeler D. Premature cardiovascular disease in chronic renal failure. Lancet. 2000;356(9224):147-152.
  9. Baigent C, Armitage J. Cholesterol reduction among patients at increased risk of coronary heart disease. Proceedings-Royal College of Physicians of Edinburgh. 1999;29(Suppl 5):10-15.
  10. Baigent C, Wheeler DC. Should we reduce blood cholesterol to prevent cardiovascular disease among patients with chronic renal failure.Nephrol Dial Transplant. 2000;15(8):1118-1119.
  11. Saland JM, Ginsberg H, Fisher EA. Dyslipidemia in pediatric renal disease: epidemiology, pathophysiology, and management. Curr Opin Pediatr. 2002;14(2):197-204.
  12. Chu M, Wang AYM, Chan IHS, Chui SH, Lam CWK.Serum small-dense LDL abnormalities in chronic renal disease patients. Br J Biomed Sci.2012(69):99-102.
  13. Hopewell JC, Haynes R, Baigent C. The role of lipoprotein (a) in chronic kidney disease. Journal of Lipid Research. 2018; (59):577-585.
  14. Mikolasevic I, Zutelija M, Mavrinac V, Orlic L. Dyslipidemia in patients with chronic kidney disease: etiology and management. International Journal of Nephrology and Renovascular Disease. 2017; (10):35-45
  15. Moorhead JF, Chan MK, El-Nahas M, Varghese Z. Lipid nephrotoxicity in chronic progressive glomerular and tubulo-interstitial disease. Lancet. 1982;2(8311):1309-1311.
  16. Gyebi L, Soltani Z, Reisin E. Lipid nephrotoxicity: new concept for an old disease. Curr Hypertens Rep. 2012;14(2):177-181.
  17. Saland JM, Pierce CB, Mitsnefes MM, et al. Dyslipidemia in children with chronic kidney disease. Kidney Int. 2010;78(11):1154-1163.
  18. Saland JM, Kupferman JC, Pierce CB, et al. Change in dyslipidemia with declining glomerular filtration rate and increasing proteinuria in children with CKD. Clin J Am Soc Nephrol. 2019;14(12):1711-1718.
  19. Sgambat K, Roem J, Mitsnefes M, et al. Waist-to-height ratio, body mass index, and cardiovascular risk profile in children with chronic kidney disease. Pediatr Nephrol. 2018;33(9):1577-1583.
  20. Baek HS, Kim SH, Kang HG, et al. Dyslipidemia in pediatric CKD patients: results from KNOW-PedCKD (KoreaN cohort study for Outcomes in patients wwth Pediatric CKD). Pediatr Nephrol. 2020;35(8):1455-1461.
  21. Sentí M, Romero R, Pedro-Botet J, et al. Lipoprotein abnormalities in hyperlipidemic and normolipidemic men on hemodialysis with chronic renal failure. Kidney Int. 1992;41(5):1394-1399.
  22. Lacour B, Roullet JB, Beyne P, et al. Comparison of several atherogenicity indices by the analysis of serum lipoprotein composition in patients with chronic renal failure with or without haemodialysis, and in renal transplant patients. J Clin Chem Clin Biochem. 1985;23(12):805-810.
  23. Kanbay M, Delibasi T, Kaya A, et al. Effect of dialysis type on serum lipids, apolipoproteins, and lipoproteins. Ren Fail. 2006;28(7):567-571.
  24. Fytili CI, Progia EG, Panagoutsos SA, et al. Lipoprotein abnormalities in hemodialysis and continuous ambulatory peritoneal dialysis patients. Ren Fail. 2002;24(5):623-630.
  25. Querfeld U, Salusky IB, Nelson Pet al. Hyperlipidemia in pediatric patients undergoing peritoneal dialysis. Pediatr Nephrol. 1988;2(4):447-452.
  26. Mitsnefes MM. Cardiovascular disease in children with chronic kidney disease. J Am Soc Nephrol. 2012;23(4):578-585.
  27. Habbig S, Volland R, Krupka K, et al. Dyslipidemia after pediatric renal transplantation-the impact of immunosuppressive regimens. Pediatr Transplant. 2017;21(3): e12914.
  28. Sgambat K, He J, McCarter RJ, Moudgil A. Lipoprotein profile changes in children after renal transplantation in the modern immunosuppression era. Pediatr Transplant. 2008;12(7):796-803.

29     Herink M, Ito Mk.  Medication Induced Changes in Lipids and Lipoproteins. Endotext [Internet]. May 8, 2018.

  1. Silverstein DM, Palmer J, Polinsky MS, et al. Risk factors for hyperlipidemia in long-term pediatric renal transplant recipients. Pediatr Nephrol. 2000;14(2):105-110.
  2. Chapter 3: Assessment of lipid status in children with CKD. Kidney Int Suppl (2011). 2013;3(3):280-281.
  3. Wanner C, Tonelli M, Kidney Disease: Improving Global Outcomes Lipid Guideline Development Work Group Members. KDIGO Clinical Practice Guideline for Lipid Management in CKD: summary of recommendation statements and clinical approach to the patient. Kidney Int. 2014;85(6):1303-1309.
  4. Sarnak MJ, Bloom R, Muntner P, et al. KDOQI US commentary on the 2013 KDIGO Clinical Practice Guideline for Lipid Management in CKD. Am J Kidney Dis. 2015;65(3):354-366.
  5. Tannock L.Dyslipidemia in Chronic Kidney Disease. Endotext [Internet]. January 22, 2018.
  6. D'Amico G, Gentile MG, Manna G, et al. Effect of vegetarian soy diet on hyperlipidaemia in nephrotic syndrome. Lancet. 1992;339(8802):1131-1134.
  7. Gentile MG, Fellin G, Cofano F, et al. Treatment of proteinuric patients with a vegetarian soy diet and fish oil. Clin Nephrol. 1993;40(6):315-320.
  8. Bell S, Cooney J, Packard CJ, et al. The effect of omega-3 fatty acids on the atherogenic lipoprotein phenotype in patients with nephrotic range proteinuria. Clin Nephrol. 2012;77(6):445-453.
  9. Hall AV, Parbtani A, Clark WF, et al. Omega-3 fatty acid supplementation in primary nephrotic syndrome: effects on plasma lipids and coagulopathy. J Am Soc Nephrol. 1992;3(6):1321-1329.
  10. Hattori M, Chikamoto H, Akioka Y, et al. A combined low-density lipoprotein apheresis and prednisone therapy for steroid-resistant primary focal segmental glomerulosclerosis in children. Am J Kidney Dis. 2003;42(6):1121-1130.
  11. Feingold KR, Grunfeld C.Lipoprotein Apheresis.  Endotext [Internet]. January 18,2020.
  12. de Ferranti SD, Steinberger J, Ameduri R, et al. Cardiovascular risk reduction in high-risk pediatric patients: a scientific statement from the American Heart Association. Circulation. 2019;139(13):e603-e634.
  13. Suh SH, Kim SW.Dyslipidemia in Patients with Chronic Kidney Disease: An Updated Overview. Diabetes Metab J 2023; 47:612-629.
  14. Chapter 4: Pharmacological cholesterol-lowering treatment in children. Kidney Int Suppl (2011). 2013;3(3):282-283.
  15. Chapter 6: Triglyceride-lowering treatment in children. Kidney Int Suppl (2011). 2013;3(3):286.
  16. Expert Panel on Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents, National Heart, Lung, and Blood Institute. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011;128 Suppl 5(Suppl 5):213.
  17. United States Renal Data System Coordinating Center. USRDS 2013 annual data report: atlas of chronic kidney disease and end-stage renal disease in the United States. Bethesda, MD, United States: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, 2013.
  18. Foley RN, Parfrey PS, Sarnak MJ. Clinical epidemiology of cardiovascular disease in chronic renal disease. Am J Kidney Dis. 1998;32(5 Suppl 3):112.
  19. Foley RN, Collins AJ. End-stage renal disease in the United States: an update from the United States Renal Data System. J Am Soc Nephrol. 2007;18(10):2644-2648.
  20. Herzog CA, Asinger RW, Berger AK, et al. Cardiovascular disease in chronic kidney disease. A clinical update from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2011;80(6):572-586.
  21. Sarnak MJ, Levey AS, Schoolwerth AC, et al. Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention. Circulation. 2003;108(17):2154-2169.
  22. The USRDS Dialysis Morbidity and Mortality Study: Wave 2. United States Renal Data System. Am J Kidney Dis. 1997;30(2):S67-S85.
  23. Querfeld U, Lang M, Friedrich JB, et al. Lipoprotein(a) serum levels and apolipoprotein(a) phenotypes in children with chronic renal disease. Pediatr Res. 1993;34(6):772-776.
  24. Ma KW, Greene EL, Raij L. Cardiovascular risk factors in chronic renal failure and hemodialysis populations. Am J Kidney Dis. 1992;19(6):505-513.
  25. Chavers BM, Li S, Collins AJ, Herzog CA. Cardiovascular disease in pediatric chronic dialysis patients. Kidney Int. 2002;62(2):648-653.
  26. Wanner C, Tonelli M.KDIGO Clinical Practice Guideline for Lipid Management in CDK: Summary of Recommendation statements and clinical approach to the Patient. Kidney Int. 2014:85(6):1303-09.
  27. KDOQI Work Group. KDOQI Clinical Practice Guideline for Nutrition in Children with CKD: 2008 update. Executive summary. Am J Kidney Dis. 2009;53(3 Suppl 2):S11-S104.
  28. Devuyst O, Goffin E, Pirson Y, et al. Creatinine rise after fibrate therapy in renal graft recipients. Lancet. 1993;341(8848):840.
  29. Filler G, Medeiros M. Improving long-term outcomes after pediatric renal transplantation by addressing dyslipidemia. Pediatr Transplant. 2017;21(3):e12880.

Diabetes Mellitus and Infections

ABSTRACT

 

Diabetes presents a significant risk factor for all kinds of infections. It has been well described to increase rates of outpatient infection as well as the incidence of infections requiring hospitalization. This appears to be related to deficits in the immune system, particularly changes seen in innate immunity. Respiratory infections, skin and soft tissue infections, gastrointestinal and genitourinary infections all appear to occur more frequently in patients with DM. Not only are they more frequent, but these infections appear to have a poorer response to therapy and more rapid progression to severe forms of infection. There is good evidence that reduction of hyperglycemia can improve outcomes. Among the antihyperglycemic agents available, translational and clinical data exists that insulin can help to improve immune function and potentially metformin as well.

 

INTRODUCTION

 

The 2020 release of the US Centers for Disease Control and Prevention National Diabetes Statistics Report revealed that in 2018, 34.2 million individuals had diabetes mellitus (DM), representing approximately 10.5% of the US population and a total cost of care in excess of US $300 billion (1). Part of these numbers reflects the impact of DM on infection rates and morbidity/mortality. Both type 1 and type 2 DM are associated with a significantly higher risk of infection, both in the outpatient and inpatient context, and the outcomes are generally worse than in those without diabetes. We will discuss here the impact of diabetes on the immune system, specific infections which are commonly seen in diabetes, and the influence of various therapies targeted both at glycemic control and also on immunomodulation on infection outcomes.

 

EPIDEMIOLOGY

 

DM, both type 1 and type 2, is associated with a high risk of infection. A large retrospective study of primary care patients revealed that diabetes is likely to account for 6% of infection-related hospitalizations and 12% of infection-related deaths, with the strongest associations being for bone and joint infections, development of sepsis, and cellulitis (2).

 

Outpatient

 

A number of studies have been performed on the rate of infection among patients with diabetes in the primary care and other outpatient settings. In a Canadian cohort of 1,779 patients with DM matched to 11,066 without DM the patients with DM had an increased risk of infection (adjusted odds ratio 1.21, adjusted for confounding variables). with skin and soft tissue infections having the strongest association with having DM. Interestingly, DM was not found in this study to be associated with head and neck, musculoskeletal, or viral infections (3). Another large Canadian study including more than a million individuals matched those with DM to those without, and assessed all physician and hospital claims for infectious disease. It found that almost half of all individuals with DM had a claim for an infectious disease within a cohort year compared with 38% of those without DM. The risk ratio was skewed most towards those with DM for upper respiratory tract infections, cystitis, and pneumonia (4).

 

Inpatient

 

In one study, having diabetes led to a 2-fold increased risk for hospitalization when presenting with an infection to the emergency room, and up to 12% of inpatient admissions in patients with diabetes were the consequence of an infection (5). A South Korean showed that those with diabetes had a significantly greater risk of infection-related ICU admission and death when hospitalized with infections of skin or soft tissue, central nervous system infection, or bone and joints (6). The previously-mentioned Canadian retrospective cohort study showed that, while the overall risk ratio for infection in those with diabetes versus without was 1.21, this number rose to 2.17 and 1.92 when considering infection which led to hospitalization and death, respectively (4). These and other studies (7,8) have revealed that not only is diabetes associated with (and causative of) an increased risk of infection, but also with higher rates of hospitalization, ICU stays, and death related to these infections. Of note, many of these patients with DM have other comorbidities which may not be able to be fully controlled for in these epidemiologic studies demonstrating higher estimates of the risk of infection with DM.

 

One important entity to consider in the inpatient arena is sepsis. The studies on sepsis are not consistent — though some show worse outcomes from DM, others have suggested either no effect or even a protective effect from DM (9). Data for the latter come from studies assessing acute respiratory failure and respiratory distress syndrome in the ICU, and it may be that the blunted immune response that we see in some patients with DM are responsible for the findings (i.e., reduced inflammation and injury related to impaired neutrophil function as described in section on Innate Immunity) (10). More studies are needed to better understand in what specific clinical contexts DM results in higher risk.

 

PATHOPHYSIOLOGY OF DIABETES AND IMMUNE SYSTEM

 

There is well-known disruption of the immune system in diabetes which occurs at multiple levels. Innate and adaptive immunity are affected along with cytokine signaling within both. This dysregulation occurs both in those with type 1 and 2 DM. Microvascular complications such as neuropathy also increase susceptibility to an accidental lesion in the barrier of the skin which forms one of the first lines of defense. Furthermore, poor vascular flow to sites of infection can further compromise an appropriate immune response and healing leading to worsening or secondary infections (11,11b). In our discussion on alterations of the immune system, it is important to note that we have focused on alterations in function as opposed to baseline differences in the number of immune cells or cytokine levels between those with and without DM. Table 1 provides a summary of the alterations in immune dysfunction that are known.

 

Innate Immunity

 

COMPLEMENT SYSTEM

The complement system plays a critical role in both innate and adaptive immunity and leads to the opsonization, lysis and phagocytosis of pathogens along with recruitment of immune cells to the site of infection. There is known to be a reduction in the complement factor 4 (C4) level in those with type 1 DM, although it is unclear if that alone can precipitate an increased risk of infection (12). A variety of studies demonstrate that hyperglycemia can inhibit phagocytosis through the system, potentially by reducing complement binding to immunoglobulins. Glycosylation of C3 can also impair its ability to attach to the pathogen surfaces (13).

 

Table 1. Impact of Diabetes and Hyperglycemia on the Immune System

Innate Immunity

Complement System

-  Reduction in C4 levels (Unclear relevance for infection risk)

-  Reduction complement binding to immunoglobulins

-  Glycosylation of C3 can impair binding to pathogen surface

Recruitment and Pathogen Recognition

-  Reduced CAM expression leading to reduced leukocyte recruitment

-    In setting of hyperglycemia reduced production of chemokine in response to bacterial LPS

-    Advanced glycation end products inhibit neutrophil transendothelial migration

-  Reduced expression TLR (which allows for recognition LPS)

Cellular Dysfunction

-    Reduced H2O2 production leading to reduced bactericidal ability in both macrophage and neutrophils

-    Impairment of macrophage phagocytic ability through complement pathway

-  Impaired metabolism of glucose in macrophages reducing activity

-    NK cell activity reduced through reduced expression activating receptors NKG2D and NKp46

Adaptive Immunity

-  Depletion and dysfunction memory CD4+ cells

-  Not as well described as alterations in innate immunity

Cytokine Signaling

- Deficiency of IL-1, IL-2, IL-6, IL-10, IL-22, IFN-γ, TNF α

Skin and Mucosal

Barriers

-  Vascular compromise leading to impaired healing

-  Neuropathy making breakage of the skin more likely

 

RECRUITMENT AND PATHOGEN RECOGNITION

 

A number of older studies reported reduced chemotaxis of polymorphonuclear leukocytes (PMNs) in patients who have DM (14,15). One of the mechanisms appears to be related to disruption of cellular adhesion molecules (CAMs) which are critical for the recruitment of leukocytes to the site of infection. This was seen when db/db (a diabetic mouse model) and wild type mice were infected with West Nile Virus and subsequent analysis of the brains of the db/db showed less leukocyte recruitment consistent with reduced CAM expression compared with the brains of the wild type mice (16). When hyperglycemia was induced in mice exposed to Klebsiella pneumoniae, there was a reduced recruitment of granulocytes to the site of infection as compared with control mice. This was felt to be related to a reduction in the chemokine production able to be induced by the bacterial lipopolysaccharide (LPS) (17). There are also in vitro data which reveal that advanced glycation end products are able to inhibit neutrophil transendothelial migration (18). A reduction in the expression of Toll- like receptors (TLR, which bind to LPS and allow for pathogen recognition) in patients with poorly controlled diabetes has been described as well (19).

 

SPECIFIC CELLULAR DYSFUNCTION

 

Multiple immune cells are impacted in DM. Neutrophil recruitment is not only reduced, but there are also good data demonstrating their reduced phagocytic activity and hydrogen peroxide production, leading to reduced bactericidal ability (20-23). The mechanism for the alteration appears may be partially linked to impaired metabolism of glucose and glutamine, as was demonstrated in streptozotocin-induced diabetic rats (24). Macrophages are also similarly affected. Examination of cells from patients with type 2 DM have revealed that there is impairment of both the complement and Fc-gamma receptor-mediated pathways by which macrophages are able to phagocytize pathogens (25). When macrophages from diabetic mice were cultured in normal versus high glucose, there was a reduction in the phagocytic and bactericidal activity, apparently through a defect similar to that seen in neutrophils, specifically impaired metabolism of glucose (26). NK cell activity is also known to be reduced in a manner which is related to level of glycemic control, demonstrated in multiple studies comparing NK cells from patients with DM, prediabetes, and also without DM (27). The mechanism of the reduced activity may be in part related to decreased expression of activating receptors NKG2D and NKp46 on the NK cells in patients with DM (28).

 

Adaptive Immunity

 

The adaptive immune system is activated in response to specific pathogens and involves the immunologic memory for those pathogens. There are two components of adaptive immunity, the humoral and cellular, which carry out the major purposes of generating an antibody and cellular (involving B and T cells) response to a specific antigen. The adaptive humoral immunity is involved in antibody production. This appears to be preserved in those with DM on the basis of overall appropriate response to various vaccines (29,30). However, there may be some dysregulation of the adaptive cellular immunity. There is a depletion of memory CD4+ cells that has been noted prior to the development of type 1 DM (31). Furthermore, a dysfunction of and an impaired response of these cells to Streptococcus pneumoniae has been described (32). However, the dysfunction seen in DM with innate immunity is better understood than that the dysfunction in adaptive immunity (33).

 

Cytokine Signaling Defects

 

Cytokines play a vital role in the signaling cascades which underpin the immune system, allowing for full activation of both innate and adaptive immune responses. Multiple points of dysregulation have been identified in DM. With stimulation, multiple of these cytokines have been shown to be secreted at lower levels than would be typical with stimulation. In vitro studies done on monocytes isolated from patients without DM showed suppression of IL-1, IL-2, IL-6, and IL-10 secretion in the presence of hyperglycemia (34-36). In diabetic mice, there was noted to be immune dysregulation and also inflammation which was related to IL-22 deficiency reversed with provision of IL-22 (37). There is also evidence for impaired interferon gamma (IFN-γ) and TNF alpha production from T cells in the setting of methylglyoxal, a compound which is increased in those with DM (38). The end result of these deficits is that there is attenuation of the phagocytic and cellular immune response.

 

COMMON INFECTIONS, OUTCOMES, AND GENERAL DRUG OF CHOICE

 

In addition to many infections having a worse course in those with diabetes, specific types of infections are also significantly more common in those with diabetes. We will review these diabetes-predominant infections (39-42). Table 2 also provides an overview of common infections and considerations in those with DM.

 

 

Table 2. Common infections seen in patients with diabetes with attention to diagnosis,

common responsible organisms, management, and outcomes

Respiratory Infections

Pneumonia

-  Higher rates of hospitalization and also mortality in those with DM compared with those without

-  Less commonly presents with purulent cough and pleuritic chest pain, more commonly with altered consciousness

-  Aspiration and skin colonization common etiologies

S pneumonia, S aureus, and K pneumoniae among most common organism

-  Rx with amoxicillin/clavulanate or cephalosporin +

macrolide/doxycycline vs fluoroquinolone

Tuberculosis

-  Higher risk contracting with risk corresponding with level of glycemic control

-  Higher risk of treatment failure

-  Isoniazid needs to be taken with pyridoxine to prevent neuropathy

-  Rifampin can cause hyperglycemia and also induces cyp450 leading to increased clearance of various DM agents

Skin and Soft Tissue

Cellulitis/Abscess

-  Most common SSTI seen in those with DM

-  Most common organism Staph species

-  For abscess culture is needed to determine organism and resistance

-  Oral abx: Doxycycline, clindamycin, TMP-SMX, cephalexin

-  Presence SIRS or other complication: IV vancomycin, linezolid, ceftaroline

Necrotizing Fasciitis

-  Comorbid DM much more common

-  Limb loss seen more often

-  Polymicrobial typically but can be only K pneumoniae

-  Surgical rx most common and need broad spectrum coverage

Fournier Gangrene

-  More commonly seen in those with DM

-  Anaerobic and aerobic bacteria such as S aureus and

Pseudomonas species

-  Debridement a must

-  Seen with SGLT2 inhibitors

Sternal Wound Infection

-  DM one of strongest predictors for infection

-  Improved glycemic control with insulin shown to reduce rate of infection

Gastrointestinal

Hepatitis

- HCV outcomes worse with more frequent cirrhosis and failure of

Antivirals

Emphysematous Cholecystitis

-  Diagnosis through sonography or CT typically as first step

-  Most common organism C perfringens and E coli

-  Rx is typically cholecystectomy but can try abx in mild case

Genitourinary

Urinary Tract Infection

-  Higher rate of infection and failure/relapse with rx

-  Most common organism E choli and Enterobacteriaceae

-  Urine culture is strongly recommended

-  Do not treat asx bacteriuria

-  Decision for abx is based on local organism and resistance trend

-    Higher risk of progression to pyelonephritis which is more severe and often bilateral

Head and Neck

Necrotizing Otitis Externa

-  DM higher risk of abscess formation requiring draining

-    Vascular compromise and pseudomonal vasculitis much more commonly seen in DM

-  P aeruginosa most common organism

-  Confirm with CT

-    Systemic abx with antipseudomonal action and local therapy to the canal including cleaning/debridement

Fungal Infections

Onychomycosis

-  Potentially up to 1/3 of all patients with DM impacted

-  Diagnosis based on fungal culture/microscopy

-  Oral agents most effective

Genitourinary

-  Most common Candida specie

-  Increased ability to bind with receptor in DM

UTI

-  Communicate with lab on culture that Candida specie is suspected

-  If symptomatic, then fluconazole first line

Mucormycosis

-  Causative agents are the mucormycetes

-  Most commonly sinus +/- cerebrum/orbits

-  Respiratory tract second most common

-  Skin third most common and has ulcerative necrotic lesion

-    Tissue biopsy needed and imaging helpful to identify extent of infection

-  Debulking of infection with adjuvant

 

 

Abbreviations: Rx (Treatment), Abx (Antibiotics), Asx (Asymptomatic), SSTI (Skin and soft tissue infections), UTI (Urinary tract infection)

 

 

Respiratory Infections

 

Pneumonia is a frequently-seen infection in those with DM. In a large Danish population-based case-control study of 34,239 patients, the relative risk for hospitalization from community-acquired pneumonia was 1.26 compared with patients without DM. Furthermore, the risk appeared to be correlated with level of glycemic control with relative risk (RR) for those with HbA1c <7% being 1.22, versus a RR of 1.6 when HbA1c was ≥9% (43). A Portuguese study similarly showed DM prevalence was higher in those with pneumonia and that outcomes were worse with a longer hospital stay and significantly higher mortality in patients with DM versus those without (15.2% vs 13.5%) (44). These trends were also seen in another Danish study which showed mortality was greater in those with type 2 DM compared with other patients at both 30 and 90 days after the initial pneumonia episode (45). The presentation of pneumonia is potentially different in those with DM as typically bacterial pneumonia presents with a purulent cough and pleuritic chest pain, symptoms which are less commonly seen in those with DM. The hypothesis is that the lowered immune defense results in a decreased inflammatory response and symptoms. Notably, altered consciousness is more common on presentation with pneumonia in those with DM. The causative agent of pneumonia is similar in those with and without DM with the most common being Streptococcus pneumoniae (46). However, there is an over-representation of organisms such as Staphylococcus aureus and Klebsiella pneumoniae related to skin colonization and more frequent aspiration in those with DM. Management is using combination therapy with amoxicillin/clavulanate or cephalosporin and a macrolide or doxycycline versus monotherapy with respiratory fluoroquinolone (47). Use of certain DM medications like metformin have been shown to reduce the risk of development of bacterial pneumonia (odds ratio 0.89) and also morbidity and mortality when pneumonia develops, hypothesized to be related to improvement in function of the innate immune system and reduction in levels of inflammation which is explored later in this chapter (47b).

 

Diabetes also represents an important risk factor for contracting tuberculosis (TB). The odds of developing tuberculosis appear to be higher in those with DM compared to those without with the odds ratio ranging from 2.44-8.33 in various studies. Furthermore, severity of DM appears to be correlated with greater risk of contracting TB based on studies comparing the incidence of TB in those with insulin-dependent versus non-insulin dependent DM. Risk of treatment failure despite good adherence to medication regimen and also death from tuberculosis all appear to be increased (48). There are side effects of medications targeted at tuberculosis with particular relevance in DM. Isoniazid can cause peripheral neuropathy that could be mistaken for diabetic neuropathy, and pyridoxine should be administered to ameliorate this risk. Rifampicin has the ability to cause hyperglycemia. Rifampicin also is a powerful inducer of the cytochrome P450 system leading to increased clearance of multiple DM agents (i.e., sulfonylurea, pioglitazone, meglitinides). Hence while the regimen to treat TB seen in patients with DM is the same as the regimen in those without, special attention must be paid to these DM specific issues.

 

Skin and Soft Tissue Infections (SSTI)

 

There is a significantly increased risk of skin and soft tissue infections (SSTI) in DM. Up to 80% of patients with DM will experience a skin complication related to DM during their lifetime, many of which are SSTIs (48b). Using a large administrative claims database (HealthCore Integrated Research Database), Suaya et al were able to demonstrate complications from SSTI were five times higher, and hospitalization four times higher, in patients with DM than those without DM in their cohort (49). The most common agent of infection is Staphylococcus aureus (S aureus). The foot represents the most common site of infection as well which has been expertly covered in another chapter (50). In the last few years, a number of therapies directed at improving immune function, blood flow, and better restoring integrity of the barrier of the skin have been developed that likely have implications for other non-foot related infections (50b).

 

For cellulitis, the diagnosis is typically clinical, as opposed to an abscess which often is cultured for organism identification and resistance profiling. The decision for antibiotics in cellulitis and with abscess is often empiric, and in those with DM it is imperative that the choice cover Staphylococcus species. Potential first line therapy for outpatient oral antibiotics includes doxycycline, clindamycin, trimethoprim-sulfamethoxazole, and cephalexin. If there is admission due to SIRS criteria being present or a suspected complication, then the recommendations change to IV predominant choices including vancomycin, linezolid, and ceftaroline (51).

 

Necrotizing fasciitis is a life-threatening condition involving the subcutaneous fat and deep fascial layers. A retrospective report of 59 necrotizing fasciitis cases at a single center revealed that 11 of the cases had DM, and another study showed that 51% of 84 patients in the cohort with necrotizing fasciitis had DM (52,53). Though most commonly a polymicrobial infection, Klebsiella pneumoniae is also commonly seen as a single isolate (53). Prognosis appears to be poorer in those with DM, with a higher rate of limb loss than that seen in those without DM. Broad spectrum antibiotics are utilized, related to the frequent polymicrobial nature of the infection. However, ischemia compromises appropriate antibiotic concentration at the site, therefore the management is primarily surgical involving a combination of debridement, necrosectomy, and fasciotomy frequently (54).

 

Fournier gangrene represents a particularly serious SSTI, defined as a necrotizing skin infection of the scrotum and penis or vulva. Typically, patients are between the age of 50-60 years and DM represents a serious risk factor for development. Usually, the infection will begin in the perianal or retroperitoneal region and then spreads to the genitalia or as a urinary tract infection which then also moves towards the genitalia. There will be necrosis and crepitus which is an indication of involvement of the underlying skin and soft tissue. The etiology is usually a mix of aerobic and anaerobic bacteria which can commonly include S aureus and Pseudomonas (51). Surgical debridement is typically necessary. This condition has become of particular relevance with the release of a warning from the US Food and Drug Administration in August 2018 that Fournier’s represented a rare but serious complication of sodium-glucose cotransporter 2 inhibitors (SGLT2i), a newer but increasingly utilized class of DM medications (55). There were 55 cases of Fournier’s reported to the FDA between March 2013 and January 2019 (56). However, it is important to note that while this number appears to be higher than for other anti-hyperglycemic agents, that there has not been a clear establishment of causality here. In fact, other studies including a meta-analysis of randomized controlled trials involving SGLT2i and a “real-world” study using IBM MarketScan were unable to confirm an increased risk of Fournier’s Gangrene for those using SGLT2i versus those who did not (57,58). Intriguingly, a single center retrospective review of cases of Founier Gangrene admitted actually suggested use of SGLT2i and metformin were both protective in reducing length of ICU and hospital stay (58b).

 

Sternal wound infections after surgery are also known to occur more frequently in those with DM. After coronary artery bypass, presence of DM is one the strongest predictors for a deep sternal wound infection (odds ratio 2.6) (59). Improved glycemic control in the post-operative period has been shown to be able to significantly reduce the rate of sternal wound infection (60-62). Furnary et al in their seminal study were able to demonstrate in a prospective manner that use of an IV insulin infusion to keep glucose <200 mg/dL resulted in a 66% reduction in risk of sternal infection compared with nonrandomized historical controls (60).

 

Gastrointestinal Infections

 

The presence of DM has been known to worsen viral hepatitis. The outcome in chronic hepatitis C infection is worse in those with DM as compared to those without, corresponding to a significantly increased risk for cirrhosis and a reduced response to antiviral therapy in those with DM and hepatitis C (63). Emphysematous cholecystitis is a rare progression of acute cholecystitis, defined as presence of gas in the gallbladder wall for which DM serves as a major risk factor. The prevalence of DM among those with emphysematous cholecystitis has been described as high as 50% in the literature (64). Sonography is able to detect the presence of gas within the gallbladder wall and an abdominal radiograph will show a curvilinear lucency around the gallbladder. CT can also detect the condition with nearly 100% sensitivity. The two most common causative agents are Clostridium perfringens and Escherichia coli. The treatment is often surgical with prompt cholecystectomy although for a mild case antibiotic therapy can be initiated but without improvement within 3-4 days then the recommendation is still for cholecystectomy (65).

 

Genitourinary Infections

 

Urinary tract infections (UTI) are significantly more common in patients with DM with a large UK study showing an incidence of UTI of 46.9 per 1000 person- years among those who had type 2 DM versus 29.9 for those without DM (66). The most common pathogens in those with DM are Escherichia coli and the Enterobacteriaceae (Klebsiella, Proteus, Enterobacter, etc.). There is an increased risk of drug- resistant organisms being present. In making the diagnosis, beyond the typical clinical symptoms of dysuria and increased frequency, it is important to note that a urine culture really should be obtained in all individuals with DM prior to therapy (67). Outcomes are worse in those with DM, being associated with increased relapse and reinfection (at 7.1% and 15.9% respectively in those with DM versus 2% and 4.1% in those without) (68). Asymptomatic bacteriuria should not be treated even in those with DM. In those with symptoms, trimethoprim-sulfamethoxazole and ciprofloxacin are good choices but the general consensus is to follow local infection and resistance trends and tailor antibiotic therapy towards those organisms (67). From a lower UTI, there is also more risk of progression to pyelonephritis (both emphysematous and nonemphysematous) which tends to be more severe requiring hospitalization and are often bilateral in those with DM (69,70).

 

It would be important to note that the class of medications called SGLT2i, previously mentioned under the section of Fournier gangrene, was initially thought to be associated with increased risk of UTIs. The purported mechanism is the increased glucose level in the urine, favoring the growth of microorganisms. However, database-driven studies and meta-analyses have not borne out this association (70b,70c). The initial observation of increased rates of UTI may have been related to surveillance bias or mycotic infections being mistaken for UTI in patients on SGLT2i.

 

Head and Neck Infections

 

Consistent with the findings in many types of infections, head and neck infections are more common and appear to be more severe in those with DM. An assessment of 185 patients at the National Taiwan University Hospital with deep neck infections found that those with DM had a significantly higher rate of abscess formation than those without (89.3% vs 71.3%) and that surgical drainage was required more frequently as well (86% vs 65.2%) (71). One concerning entity commonly associated with DM is necrotizing external otitis. This term references an infection which has spread to the temporal and adjacent bones at the base of the skull. The causative agent is often Pseudomonas aeruginosa. The increased frequency of this in those with DM appears to be related in part to the vascular compromise seen in DM combined with a pseudomonal vasculitis (72,72b). A certain level of suspicion for this condition needs to be present when there is external otitis in a patient at risk of necrotizing progression. Imaging is often needed to confirm with CT used. Systemic antibiotics are a requirement along with local treatment of the canal (i.e., cleaning, antimicrobial topicals, etc.). The antibiotic chosen needs to have antipseudomonal action such as the fluoroquinolones with the understanding that poor vascularization of the area often means higher doses are required (72).

 

Fungal Infections

 

Infection with Candida species is common in those with DM (73). Skin and soft tissue along with mucosa can be commonly impacted. Assessment of mouth swabs from patients with and without DM revealed that there was a higher frequency of Candida infection in the patients with DM (74). This appears to be related to decreased salivary pH and salivary flow which promoted colonization with the yeast. But there is also the possibility that in DM there is increased ability of Candida to bind to its receptor (75). Onychomycosis, a fungal infection of the nails, is also very common with DM with some studies suggesting up to 1/3 of individuals with DM are impacted. Diagnosis is made based on a positive fungal culture for a dermatophyte or microscopy showing fungus prior to initiation of therapy. Oral agents tend to be the most efficacious but topical lacquers are used as well (76).

 

Beyond the skin and mucosa, there is a high rate of genitourinary infections with Candida species. Among fungal infections of the urinary tract system, the vast majority involve Candida species. For both outpatient and inpatient urinary tract infections where Candida species was the causative agent, DM is present as a comorbid condition in 29% and 39% of cases respectively. Initial work-up would be similar to that of any other for urinary tract infection including urinalysis and culture. If there is a concern for Candida then that should be communicated with the reporting lab as there can be slow growth on certain cultures. It is important to remember that symptomatic urinary tract infections with Candida are rare. However, if truly a symptomatic infection is felt to be present, then fluconazole is typically the first line therapy of choice because of its ability to accumulate in high concentrations within the urine. If there is progression to pyelonephritis then speciation and sensitivities will be required given the presence of resistant strains and often dual agent therapy is required (77).

 

Mycotic genital infections are driven by Candida species. in both men and women (78). A very large percentage of women will experience symptomatic vulvovaginal candidiasis within their lifetime, and DM represents a risk factor for development of infection, with worsening glycemic control predisposing to an even higher risk (73). This appears to be related to known defects in immune cell function (PMNs and macrophages) and the impact of glucose in the urine, leading to worsening virulence in addition to improved adherence of yeast. Clinically, women present with pruritis and discomfort. Diagnosis is best made with microscopy and can be suspected in those with a negative amine (“whiff”) test and normal pH. Treatment is typically with a short course of intravaginal imidazole or triazole as opposed to oral fluconazole (78). For male patients, a similar finding of increased risk of balanitis (i.e., inflammation of the glans penis and prepuce) with DM and with increasing HbA1c is noted (73,79). This condition also occurs almost exclusively in males who have not been circumcised. Diagnosis is best made based on clinical presentation (burning and itching of penis worse after intercourse) in combination with a subpreputial culture. Imidazole or triazole creams represent the mainstay of therapy (78). 

 

It is worth mentioning that SGLT2i as a class are known to be associated with genital infections, particularly mycotic genital infections caused by Candida species. Using information from two US based health insurance databases, Dave et al were able to demonstrate in a retrospective cohort study that use of an SGLT2i compared with dipeptidyl peptidase 4 inhibitors and glucagon-like peptide 1 receptor agonists led to an approximately three-fold increase in risk of genital infection (80). This might be mitigated in part by improved hygiene (i.e., rinsing the genital area with water after every episode of urination and before going to bed) (81). Interestingly, the association between use of SGLT2i and genital infections does not appear to extend to UTIs (82). This may be related to increased volume and flow through the urinary tract preventing excess bacterial load from developing (83). As SGLT2i are increasingly a mainstay of therapy for patients with type 2 DM, this association with mycotic genital infections needs to be carefully considered.

 

Mucormycosis is a rare but life-threatening fungal infection caused by a mucormycetes, a group of molds (commonly the mucor and rhizppus species). A metanalysis of cases of mucormycosis showed that DM was the commonest underlying condition present in 40% of cases (84). Frequently the DM associated is type 2 and uncontrolled. It carries with it a high fatality rate which ranges from 32-57%. The most common site of infection (66% of cases in a large 929 case series) is the sinus-cavity leading to rhinocerebral infection which can also impact the orbits. In these cases, there are often symptoms of sinus congestion/inflammation, fever, facial swelling along with ophthalmoplegia, cellulitis, and cranial nerve palsies. Necrotic eschars in the nasal cavity and on the hard palate are classic findings and also indicate a rapidly progressive infection. The respiratory tract is the second most commonly affected location (16%) with endobronchial lesions commonly found in those with DM. The subsequent invasion of the vasculature can lead to more distant infection. Finally, the third most common site is the skin (10%). Cutaneous mucormycosis presents with erythematous or ulcerative necrotic lesions which can also lead to osteomyelitis (85,86). Tissue biopsy is a requirement for diagnosis while various imaging modalities can help provide further evidence of an infection. Debulking of the infection through surgery is necessary. Amphotericin B and isavuconazole have been utilized as adjunctive therapies (85,87).

 

COVID-19 and DM

 

There is clearly a significant interaction between DM and SARS-CoV-2 (causative agent of coronavirus disease 2019 (COVID-19)). Multiple risk factors for contracting and having a more severe course of COVID-19 have been identified, including advanced age and male gender, but both type 1 and type 2 DM are now known to be important risk factors for morbidity and mortality with the disease (88). An assessment of patients who contracted COVID-19 and were tested within the Vanderbilt University Medical system demonstrated that there was a significantly increased risk for hospitalization in those with DM compared to without DM (odds ratio 3.36 for type 2 and 3.9 for type 1) and also for more severe disease course (odds ratio 3.42 for type 2 and 3.35 for type 1) (89). From a cohort of patients in England, there is evidence that poorly-controlled DM as compared with well-controlled DM (HbA1c 6.5-7% versus  greater than 10%) results in significantly increased mortality in both type 1 and type 2 DM (hazard ratio 2.23 and 1.61 respectively) (90). Increased mortality has also been seen in another English cohort (83). A more comprehensive review on this topic is offered by Lim et al, where the multiple points at which COVID-19 and DM interact – including the impact of glucotoxicity on the lungs, increased thromboembolic risk, worsened oxidative stress. and inappropriately high levels of cytokine production leading to organ damage – are outlined (91).

 

 

IMPACT OF GLYCEMIC CONTROL AND OTHER THERAPIES

 

Glycemic Control and Diabetes Therapies

 

There is good evidence that glycemic control is correlated with infection. A study of 69,318 patients with type 2 DM in Denmark revealed an association between increased risk for community- and hospital- treated infection in those with higher HbA1c ≥10.5% compared with HbA1c 5.5-<6.4% (92). Similarly, in a large English cohort there was an increasing risk of infection in parallel with HbA1c for patients with both type 1 and type 2 (2). In a Taiwanese study looking at outcomes from a community-based health screening program, the authors found that fasting plasma glucose >200 mg/dL and DM was associated with the highest risk of infection and also a 3-fold higher risk of death than those without DM (93). Looking at an older population, the risk of certain infections was significantly higher in those with poor glycemic control HbA1c >8.5% compared with good glycemic control (relative risk infections ranging from 1.28-2.38) (94). Intervening to lower glucose appears to mitigate the risks. Zerr et al assessed incidence of sternal wound infection in patients with and without DM before and after implementation of a postoperative continuous IV insulin protocol to keep blood glucose <200 mg/dL. They found that lower glucose in the first 2 days postoperatively was associated with a decrease in deep wound infection from 2.4% to 1.5% (62).

 

Insulin, in both translational and clinical studies, has been suggested to have a protective effect against infection risk in those with DM (Table 3). A large surgical ICU trial assessing tight (80-110 mg/dL) versus conventional (treatment with insulin only if glucose >215 mg/dL) glycemic control using IV insulin found a lower mortality with tight glycemic control, and the greatest reduction in mortality was seen in those with sepsis leading to multi-organ dysfunction. In those treated with IV insulin, there was a significant reduction in the risk of developing sepsis (46%) (95).

 

While these data were later brought into question by the findings of the NICE-SUGAR trial (96) which demonstrated increased mortality with intensive glycemic control using IV insulin, other studies have suggested that there is improvement in rates of infection with use of insulin (60,97) particularly in the post-cardiac surgery setting for sternal wound infections. Furthermore, the increased risk of mortality in the intensive glycemic control arm in NICE-SUGAR is felt to be related to an excess of hypoglycemia seen in the cohort compared with normal care. If improved glycemic control can be achieved without causing a significant increase in hypoglycemia, a different outcome may be able to be achieved (98). Translational studies have been able to show in vivo that T cells which lack insulin receptor expression are unable to proliferate and produce cytokines properly and that insulin enables the cells to take up nutrient which supports their function (99). As mentioned earlier chemotaxis of PMNs is impaired in patients with DM and it has been noted that provision of glucose and insulin can restore these to baseline (15).

 

While data for immune function improvement and infection using other antihyperglycemic medications are relatively sparse, there are some suggestions that therapies beyond insulin can have an immune- restorative effect (Table 3). Metformin has demonstrated an ability to increase the number and action of CD8+ tumor-infiltrating lymphocytes, resulting in improved production of cytokines IL-2, TNFα, and IFNγ (100). In a mice model with an absence of the TNF receptor-associated factor 6 (TRAF6), there is a relative inability to generate memory T cells that is related to defects in fatty acid metabolism. When TRAF6-deficient antigen specific effector T cells and TRAF6-deficient mice were exposed to metformin, there was a restoration of the production of memory T cells (101). While a number of other diabetes therapies have well-established anti- inflammatory effects (i.e., peroxisome proliferator- activated receptor-γ agonists, glucagon-like peptide-1 receptor agonists, sodium-glucose cotransporter 2 inhibitors) data are lacking as to their specific impact on immune function with regards to infection risk apart from their reduction of hyperglycemia (102-104).

 

Immunomodulating Therapies

 

There are data showing that the use of granulocyte- colony stimulating factor (G-CSF), which induces differentiation and release of PMN from marrow, is able to assist with healing in foot infections (105). While a subsequent meta-analysis did not show that the use of G-CSF was able to significantly impact the resolution or healing of wounds, there was a reduction in risk of needing amputation or surgical intervention (106).

 

While not a “medication”, physical activity has long been known to be associated with improvement in the immune system which are known to extend as well to those with DM (107). In diabetic rats, exercise was able to improve the neutrophil and lymphocyte count significantly (108).

 

Table 3. Anti-Hyperglycemic Agents Associated with a Reduced Risk of Infection

Insulin

-    T cells in vivo which lack insulin receptor are unable to proliferate and produce cytokines due to the inability to take up nutrients

-  Chemotaxis in PMNs impaired in DM which is restored with glucose and

Insulin

Metformin

-    Increase number of tumor-infiltrating lymphocytes and improved cytokine production

-  Restoration of production of memory T cells from effector T cells

 

 

CONCLUSION

 

Diabetes represents an incredibly important risk factor for infection raising the likelihood of infection for both outpatient treated conditions and those which lead to hospitalization. Beyond raising the risk for contracting an infection, prognosis is frequently worse for many of these conditions which increases the frequency of rare and life-threatening infectious processes seen in those with DM. This is the consequence of disturbances in the immune system which have been well described involving both innate and adaptive immunity. However, glucose lowering therapies appear to be able to counteract some of the increased risk of infection and worsened prognosis by improving function of immune cells. More work is needed to fully elucidate if and how newer diabetes agents may be able to reduce risk of infection.

 

REFERENCES

 

  1. Centers for Disease Control and Prevention. National Diabetes Statistics Report, 2020. Atlanta, GA: Centers for Disease Control and Prevention, U.S. Dept of Health and Human Services; 2020.
  2. Carey IM, Critchley JA, DeWilde S, Harris T, Hosking FJ, Cook DG. Risk of Infection in Type 1 and Type 2 Diabetes Compared With the General Population: A Matched Cohort Study. Diabetes Care. 2018;41(3):513-521.
  3. Abu-Ashour W, Twells LK, Valcour JE, Gamble JM. Diabetes and the occurrence of infection in primary care: a matched cohort study. BMC Infect Dis. 2018;18(1):67.
  4. Shah BR, Hux JE. Quantifying the risk of infectious diseases for people with diabetes. Diabetes Care. 2003;26(2):510-3.
  5. Korbel L, Spencer JD. Diabetes mellitus and infection: an evaluation of hospital utilization and management costs in the United States. J Diabetes Complications. 2015;29(2):192-5.
  6. Kim EJ, Ha KH, Kim DJ, Choi YH. Diabetes and the Risk of Infection: A National Cohort Study. Diabetes Metab J. 2019;43(6):804-814.
  7. Muller LM, Gorter KJ, Hak E, Goudzwaard WL, Schellevis FG, Hoepelman AI, Rutten GE. Increased risk of common infections in patients with type 1 and type 2 diabetes mellitus. Clin Infect Dis. 2005;41(3):281-8.
  8. Fine MJ, Smith MA, Carson CA, Mutha SS, Sankey SS, Weissfeld LA, Kapoor WN. Prognosis and outcomes of patients with community-acquired pneumonia. A meta- analysis. JAMA. 1996;275(2):134-41.
  9. Schuetz P, Castro P, Shapiro NI. Diabetes and sepsis: preclinical findings and clinical relevance. Diabetes Care. 2011 Mar;34(3):771-8.
  10. Esper AM, Moss M, Martin GS. The effect of diabetes mellitus on organ dysfunction with sepsis: an epidemiological study. Crit Care 2009;13:R18
  11. Forbes J.M., Cooper M.E. Mechanisms of diabetic complications. Physiological Reviews. 2013;93(1):137-188.

11b.      Holt RIG, Cockram CS, Ma RCW, Luk AOY. Diabetes and infection: review of the epidemiology, mechanisms and principles of treatment. Diabetologia. 2024 Jul;67(7):1168-1180.

  1. Vergani D, Johnston C, B-Abdullah N, Barnett AH. Low serum C4 concentrations: an inherited predisposition to insulin dependent diabetes?. Br Med J (Clin Res Ed). 1983;286(6369):926-928.
  2. Jafar N, Edriss H, Nugent K. The Effect of Short-Term Hyperglycemia on the Innate Immune System. Am J Med Sci. 2016;351(2):201-11.
  3. Delamaire M, Maugendre D, Moreno M, Le Goff MC, Allannic H, Genetet B. Impaired leucocyte functions in diabetic patients. Diabet Med. 1997;14(1):29-34.
  4. Mowat A, Baum J. Chemotaxis of polymorphonuclear leukocytes from patients with diabetes mellitus. N Engl J Med. 1971;284(12):621-7.
  5. Kumar M, Roe K, Nerurkar PV, Orillo B, Thompson KS, Verma S, Nerurkar VR.. Reduced immune cell infiltration and increased pro-inflammatory mediators in the brain of Type 2 diabetic mouse model infected with West Nile virus. J Neuroinflammation. 2014;11:80.
  6. Martinez N, Ketheesan N, Martens GW, West K, Lien E, Kornfeld H. Defects in early cell recruitment contribute to the increased susceptibility to respiratory Klebsiella pneumoniae infection in diabetic mice. Microbes Infect. 2016;18(10):649-655.
  7. Collison KS, Parhar RS, Saleh SS, Meyer BF, Kwaasi AA, Hammami MM, Schmidt AM, Stern DM, Al-Mohanna FA. RAGE-mediated neutrophil dysfunction is evoked by advanced glycation end products (AGEs). J Leukoc Biol. 2002;71(3):433-44.
  8. Gupta S, Maratha A, Siednienko J, Natarajan A, Gajanayake T, Hoashi S, Miggin S. Analysis of inflammatory cytokine and TLR expression levels in Type 2 Diabetes with complications. Sci Rep. 2017 Aug 9;7(1):7633. doi:10.1038/s41598-017-07230-8.Erratum  in: Sci  Rep.201.;
  9. Bagdade JD, Nielson KL, Bulger RJ. Reversible abnormalities in phagocytic function in poorly controlled diabetic patients. Am J Med Sci. 1972;263(6):451-6.
  10. Bybee JD, Rogers DE. The phagocytic activity of polymorphonuclear leukocytes obtained from patients with diabetes mellitus. J Lab Clin Med. 1964;64:1-13.
  11. Inoue S, Lan Y, Muran J, Tsuji M. Reduced hydrogen peroxide production in neutrophils from patients with diabetes. Diabetes Res Clin Pract. 1996;33(2):119-27.
  12. Repine JE, Clawson CC, Goetz FC. Bactericidal function of neutrophils from patients with acute bacterial infections and from diabetics. J Infect Dis. 1980;142(6):869-75.
  13. Alba-Loureiro TC, Hirabara SM, Mendonça JR, Curi R, Pithon-Curi TC. Diabetes causes marked changes in function and metabolism of rat neutrophils. J Endocrinol. 2006;188(2):295-303.
  14. Restrepo BI, Twahirwa M, Rahbar MH, Schlesinger LS. Phagocytosis via complement or Fc-gamma receptors is compromised in monocytes from type 2 diabetes patients with chronic hyperglycemia. PLoS One. 2014 Mar 26;9(3):e92977.
  15. Pavlou S, Lindsay J, Ingram R, Xu H, Chen M. Sustained high glucose exposure sensitizes macrophage responses to cytokine stimuli but reduces their phagocytic activity. BMC Immunol. 2018;19(1):24.
  16. Kim JH, Park K, Lee SB, Kang S, Park JS, Ahn CW, Nam JS. Relationship between natural killer cell activity and glucose control in patients with type 2 diabetes and prediabetes. J Diabetes Investig. 2019;10(5):1223-1228.
  17. Berrou J, Fougeray S, Venot M, Chardiny V, Gautier JF, Dulphy N, Toubert A, Peraldi MN. Natural killer cell function, an important target for infection and tumor protection, is impaired in type 2 diabetes. PLoS One. 2013;8(4):e62418.
  18. Beam, T.R.J., Crigler, E.D., Goldman, J.R. and Schifmann, G. Antibody response to polyvalent pneumococcal polysaccharide vaccine in diabetics. J Am Med Assoc. 1980;244:2641-2644.
  19. Diepersloot RJ, Bouter KP, Beyer WE, Hoekstra JB, Masurel N. Humoral immune response and delayed type hypersensitivity to influenza vaccine in patients with diabetes mellitus. Diabetologia. 1987;30(6):397-401.
  20. Moutschen MP, Scheen AJ, Lefebvre PJ. Impaired immune responses in diabetes mellitus: analysis of the factors and mechanisms involved. Relevance to the increased susceptibility of diabetic patients to specific infections. Diabete Metab. 1992 May-Jun;18(3):187-201.
  21. Martinez PJ, Mathews C, Actor JK, Hwang SA, Brown EL, De Santiago HK, Fisher Hoch SP, McCormick JB, Mirza S. Impaired CD4+ and T-helper 17 cell memory response to Streptococcus pneumoniae is associated with elevated glucose and percent glycated hemoglobin A1c in Mexican Americans with type 2 diabetes mellitus. Transl Res. 2014 Jan;163(1):53-63.
  22. Geerlings SE, Hoepelman AI. Immune dysfunction in patients with diabetes mellitus (DM). FEMS Immunol Med Microbiol. 1999 Dec;26(3-4):259-65.
  23. Mooradian AD, Reed RL, Meredith KE, Scuderi P. Serum levels of tumor necrosis factor and IL-1 alpha and IL-1 beta in diabetic patients. Diabetes Care. 1991;14(1):63-5. doi: 10.2337/diacare.14.1.63. PMID: 1991438.
  24. Ohno Y, Aoki N, Nishimura A. In vitro production of interleukin-1, interleukin-6, and tumor necrosis factor-alpha in insulin-dependent diabetes mellitus. J Clin Endocrinol Metab. 1993;77(4):1072-7.
  25. Reinhold D, Ansorge S, Schleicher ED. Elevated glucose levels stimulate transforming growth factor-beta 1 (TGF- beta 1), suppress interleukin IL-2, IL-6 and IL-10 production and DNA synthesis in peripheral blood mononuclear cells. Horm Metab Res. 1996;28(6):267-70.
  26. Wang X, Ota N, Manzanillo P, Kates L, Zavala-Solorio J, Eidenschenk C, Zhang J, Lesch J, Lee WP, Ross J, Diehl L, van Bruggen N, Kolumam G, Ouyang W. Interleukin-22 alleviates metabolic disorders and restores mucosal immunity in diabetes. Nature. 2014;514(7521):237-41.
  27. Price CL, Hassi HO, English NR, Blakemore AI, Stagg AJ, Knight SC. Methylglyoxal modulates immune responses: relevance to diabetes. J Cell Mol Med. 2010;14(6B):1806- 15.
  28. Akash MSH, Rehman K, Fiayyaz F, Sabir S, Khurshid M. Diabetes-associated infections: development of antimicrobial resistance and possible treatment strategies. Arch Microbiol. 2020l;202(5):953-965.
  29. Casqueiro J, Casqueiro J, Alves C. Infections in patients with diabetes mellitus: A review of pathogenesis. Indian J Endocrinol Metab. 2012;16 Suppl 1(Suppl1):S27-36.
  30. Joshi N, Caputo GM, Weitekamp MR, Karchmer AW. Infections in patients with diabetes mellitus. N Engl J Med. 1999;341(25):1906-12.
  31. Peleg AY, Weerarathna T, McCarthy JS, Davis TM. Common infections in diabetes: pathogenesis, management and relationship to glycaemic control. Diabetes Metab Res Rev. 2007;23(1):3-13.
  32. Kornum JB, Thomsen RW, Riis A, Lervang HH, Schønheyder HC, Sørensen HT. Diabetes, glycemic control, and risk of hospitalization with pneumonia: a population-based case- control study. Diabetes Care. 2008;31(8):1541-5.
  33. Martins M, Boavida JM, Raposo JF, Froes F, Nunes B, Ribeiro RT, Macedo MP, Penha-Gonçalves C. Diabetes hinders community-acquired pneumonia outcomes in hospitalized patients. BMJ Open Diabetes Res Care. 2016;4(1):e000181.
  34. Kornum JB, Thomsen RW, Riis A, Lervang HH, Schønheyder HC, Sørensen HT. Type 2 diabetes and pneumonia outcomes: a population-based cohort study. Diabetes Care. 2007;30(9):2251-7.
  35. Di Yacovo S, Garcia-Vidal C, Viasus D, Adamuz J, Oriol I, Gili F, Vilarrasa N, García-Somoza MD, Dorca J, Carratalà J. Clinical features, etiology, and outcomes of community- acquired pneumonia in patients with diabetes mellitus. Medicine (Baltimore). 2013;92(1):42-50.
  36. Metlay JP, Waterer GW, Long AC, Anzueto A, Brozek J, Crothers K, Cooley LA, Dean NC, Fine MJ, Flanders SA, Griffin MR, Metersky ML, Musher DM, Restrepo MI, Whitney CG. Diagnosis and Treatment of Adults with Community-acquired Pneumonia. An Official Clinical Practice Guideline of the American Thoracic Society and Infectious Diseases Society of America. Am J Respir Crit Care Med. 2019;200(7):e45-e67.

47b.      Yen FS, Wei JC, Shih YH, Hsu CC, Hwu CM. Metformin use and the risk of bacterial pneumonia in patients with type 2 diabetes. Sci Rep. 2022 Feb 28;12(1):3270

  1. Dooley KE, Chaisson RE. Tuberculosis and diabetes mellitus: convergence of two epidemics. Lancet Infect Dis. 2009;9(12):737-46.

48b.  David P, Singh S, Ankar R. A Comprehensive Overview of Skin Complications in Diabetes and Their Prevention. Cureus. 2023 May 13;15(5):e38961.

  1. Suaya JA, Eisenberg DF, Fang C, Miller LG. Skin and soft tissue infections and associated complications among commercially insured patients aged 0-64 years with and without diabetes in the U.S. PLoS One. 2013;8(4):e60057.
  2. Boulton AJM, Whitehouse RW. The Diabetic Foot. In: Feingold KR, Anawalt B, Boyce A, et al., eds. Endotext (Internet). South Dartmouth, MA; 2020. Available from: https://www.ncbi.nlm.nih.gov/books/NBK409609/

50b.      Oyebode OA, Jere SW, Houreld NN. Current Therapeutic Modalities for the Management of Chronic Diabetic Wounds of the Foot. J Diabetes Res. 2023 Feb 10;2023:1359537.

  1. Stevens DL, Bisno AL, Chambers HF, Dellinger EP, Goldstein EJ, Gorbach SL, Hirschmann JV, Kaplan SL, Montoya JG, Wade JC; Infectious Diseases Society of America. Practice guidelines for the diagnosis and management of skin and soft tissue infections: 2014 update by the Infectious Diseases Society of America. Clin Infect Dis. 2014;59(2):e10-52.
  2. Cheng NC, Tai HC, Chang SC, Chang CH, Lai HS. Necrotizing fasciitis in patients with diabetes mellitus: clinical characteristics and risk factors for mortality. BMC Infect Dis. 2015;15:417.
  3. Gürlek A, Firat C, Oztürk AE, Alaybeyoğlu N, Fariz A, Aslan S. Management of necrotizing fasciitis in diabetic patients. J Diabetes Complications. 2007;21(4):265-71.
  4. Misiakos EP, Bagias G, Patapis P, Sotiropoulos D, Kanavidis P, Machairas A. Current concepts in the management of necrotizing fasciitis. Front Surg. 2014;1:36.
  5. Fadini GP, Sarangdhar M, De Ponti F, et al Pharmacovigilance assessment of the association between Fournier’s gangrene and other severe genital adverse events with SGLT-2 inhibitors BMJ Open Diabetes Research and Care 2019;7:e000725.
  6. Bersoff-Matcha SJ, Chamberlain C, Cao C, Kortepeter C, Chong WH. Fournier Gangrene Associated With Sodium- Glucose Cotransporter-2 Inhibitors: A Review of Spontaneous Postmarketing Cases. Ann Intern Med. 2019;170(11):764-769.
  7. Silverii GA, Dicembrini I, Monami M, Mannucci E. Fournier's gangrene and sodium-glucose co-transporter-2 inhibitors: A meta-analysis of randomized controlled trials. Diabetes Obes Metab. 2020;22(2):272-275.
  8. Yang JY, Wang T, Pate V, Buse JB, Stürmer T. Real-world evidence on sodium-glucose cotransporter-2 inhibitor use and risk of Fournier's gangrene. BMJ Open Diabetes Res Care. 2020 Jan;8(1):e000985.’

58b.      Venugopal S, Patel S, Wu Z. Improved Fournier’s Gangrene Outcomes With Prior SGLT2i Or Metformin Usage. J Endocr Soc. 2023;7(Suppl 1):A388.

  1. Borger MA, Rao V, Weisel RD, Ivanov J, Cohen G, Scully HE, David TE. Deep sternal wound infection: Risk factors and outcomes. Ann Thorac Surg 1998;65:1050-1056.
  2. Furnary AP, Zerr KJ, Grunkemeier GL, Starr A. Continuous intravenous insulin infusion reduces the incidence of deep sternal wound infection in diabetic patients after cardiac surgical procedures. Ann Thorac Surg 1999;67:352-360.
  3. Kramer R, Groom R, Weldner D, Gallant P, Heyl B, Knapp R, Arnold A.. Glycemic control and reduction of deep sternal wound infection rates: A multidisciplinary approach. Arch Surg 2008;143:451-456.
  4. Zerr KJ, Furnary AP, Grunkemeier GL, Bookin S, Kanhere V, Starr A. Glucose control lowers the risk of wound infection in diabetics after open heart operations. Ann Thorac Surg. 1997;63(2):356-61.
  5. Hammerstad SS, Grock SF, Lee HJ, Hasham A, Sundaram N, Tomer Y. Diabetes and Hepatitis C: A Two-Way Association. Front Endocrinol (Lausanne). 2015;6:134.
  6. Ito T, Shiraki K, Sekoguchi K. Metastatic gas gangrene of the leg due to acute emphysematous cholecystitis. Dig Dis Sci. 2001;46(11):2480-2483.
  7. Safwan M, Penny SM. Emphysematous Cholecystitis: A Deadly Twist to a Common Disease. Journal of Diagnostic Medical Sonography. 2016;32(3):131-137.
  8. Hirji I, Guo Z, Andersson SW, Hammar N, Gomez-Caminero A. Incidence of urinary tract infection among patients with type 2 diabetes in the UK General Practice Research Database (GPRD). J Diabetes Complications. 2012;26(6):513–516.
  9. Nitzan O, Elias M, Chazan B, Saliba W. Urinary tract infections in patients with type 2 diabetes mellitus: review of prevalence, diagnosis, and management. Diabetes Metab Syndr Obes. 2015;8:129-36.
  10. Gorter KJ, Hak E, Zuithoff NP, Hoepelman AI, Rutten GE. Risk of recurrent acute lower urinary tract infections and prescription pattern of antibiotics in women with and without diabetes in primary care. Fam Pract. 2010;27(4):379-85.
  11. Kumar S, Ramachandran R, Mete U, Mittal T, Dutta P, Kumar V, Rathi M, Jha V, Gupta KL, Sakhuja V, Kohli HS. Acute pyelonephritis in diabetes mellitus: Single center experience. Indian J Nephrol. 2014;24(6):367-71.
  12. Ronald A, Ludwig E. Urinary tract infections in adults with diabetes. Int J Antimicrob Agents. 2001;17(4):287-92.

70b.      Dave CV, Schneeweiss S, Kim D, Fralick M, Tong A, Patorno E. Sodium-Glucose Cotransporter-2 Inhibitors and the Risk for Severe Urinary Tract Infections: A Population-Based Cohort Study. Ann Intern Med. 2019 Aug 20;171(4):248-256.

70c.      Wilding J. SGLT2 inhibitors and urinary tract infections. Nat Rev Endocrinol. 2019 Dec;15(12):687-688.

  1. Huang TT, Tseng FY, Liu TC, Hsu CJ, Chen YS. Deep neck infection in diabetic patients: comparison of clinical picture and outcomes with nondiabetic patients. Otolaryngol Head Neck Surg. 2005;132(6):943-7.
  2. Handzel O, Halperin D. Necrotizing (malignant) external otitis. Am Fam Physician. 2003;68(2):309-12.

72b.      Arsovic N, Radivojevic N, Jesic S, Babac S, Cvorovic L, Dudvarski Z. Malignant Otitis Externa: Causes for Various Treatment Responses. J Int Adv Otol. 2020 Apr;16(1):98-103.

  1. Rodrigues CF, Rodrigues ME, Henriques M. Candida sp. Infections in Patients with Diabetes Mellitus. J Clin Med. 2019;8(1):76.
  2. Mohammadi F, Javaheri MR, Nekoeian S, Dehghan P. Identification of Candida species in the oral cavity of diabetic patients. Curr Med Mycol. 2016;2(2):1-7.
  3. Darwazeh AM, MacFarlane TW, McCuish A, Lamey PJ. Mixed salivary glucose levels and candidal carriage in patients with diabetes mellitus. J Oral Pathol Med. 1991; 20(6):280-3.
  4. Cathcart S, Cantrell W, Elewski B. Onychomycosis and diabetes. J Eur Acad Dermatol Venereol. 2009;23(10):1119-22.
  5. Thomas L, Tracy CR. Treatment of Fungal Urinary Tract Infection. Urol Clin North Am. 2015 Nov;42(4):473-83.
  6. Nyirjesy P, Sobel JD. Genital mycotic infections in patients with diabetes. Postgrad Med. 2013 May;125(3):33-46.
  7. Grandy S, Fox KM; SHIELD Study Group. Self-reported prevalence of vaginitis and balanitis among individuals with type 2 diabetes mellitus. Presented at: 70th Annual Scientific Sessions of the American Diabetes Association; June 25–29, 2010; Orlando, FL. Abstract 2369-PO.
  8. Dave CV, Schneeweiss S, Patorno E. Comparative risk of genital infections associated with sodium-glucose co- transporter-2 inhibitors. Diabetes Obes Metab. 2019;21(2):434-438.
  9. Williams SM, Ahmed SH. Improving compliance with SGLT2 inhibitors by reducing the risk of genital mycotic infections: the outcomes of personal hygiene advice. Diabetes. 2019;68(suppl 1):1224-P.
  10. Liu J, Li L, Li S, Jia P, Deng K, Chen W, Sun X. Effects of SGLT2 inhibitors on UTIs and genital infections in type 2 diabetes mellitus: a systematic review and meta-analysis. Sci Rep. 2017;7(1):2824.
  11. Fralick M, MacFadden DR. A hypothesis for why sodium glucose co-transporter 2 inhibitors have been found to cause genital infection, but not urinary tract infection. Diabetes Obes Metab. 2020 May;22(5):755-758.
  12. Jeong W, Keighley C, Wolfe R, Lee WL, Slavin MA, Kong DCM, Chen SC. The epidemiology and clinical manifestations of mucormycosis: a systematic review and meta-analysis of case reports. Clin Microbiol Infect. 2019;25(1):26-34.
  13. Rammaert B, Lanternier F, Poirée S, Kania R, Lortholary O. Diabetes and mucormycosis: a complex interplay. Diabetes Metab. 2012;38(3):193-204.
  14. Roden MM, Zaoutis TE, Buchanan WL, Knudsen TA, Sarkisova TA, Schaufele RL, Sein M, Sein T, Chiou CC, Chu JH, Kontoyiannis DP, Walsh TJ. Epidemiology and outcome of zygomycosis: a review of 929 reported cases. Clin Infect Dis. 2005;41(5):634-53.
  15. Jenks JD, Salzer HJ, Prattes J, Krause R, Buchheidt D, Hoenigl M. Spotlight on isavuconazole in the treatment of invasive aspergillosis and mucormycosis: design, development, and place in therapy. Drug Des Devel Ther. 2018;12:1033-1044.
  16. Lim S, Bae JH, Kwon HS, Nauck MA. COVID-19 and diabetes mellitus: from pathophysiology to clinical management. Nat Rev Endocrinol. 2021;17(1):11-30.
  17. Gregory JM, Slaughter JC, Duffus SH, Smith TJ, LeStourgeon LM, Jaser SS, McCoy AB, Luther JM, Giovannetti ER, Boeder S, Pettus JH, Moore DJ. COVID-19 Severity Is Tripled in the Diabetes Community: A Prospective Analysis of the Pandemic's Impact in Type 1 and Type 2 Diabetes. Diabetes Care. 2021;44(2):526-532.
  18. Holman N, Knighton P, Kar P, O'Keefe J, Curley M, Weaver A, Barron E, Bakhai C, Khunti K, Wareham NJ, Sattar N, Young B, Valabhji J. Risk factors for COVID-19-related mortality in people with type 1 and type 2 diabetes in England: a population-based cohort study. Lancet Diabetes Endocrinol. 2020;8(10):823-833.
  19. Dennis JM, Mateen BA, Sonabend R, et al. Type 2 Diabetes and COVID-19-Related Mortality in the Critical Care Setting: A National Cohort Study in England, March-July 2020. Diabetes Care. 2021;44(1):50-57.
  20. Mor A, Dekkers OM, Nielsen JS, Beck-Nielsen H, Sørensen HT, Thomsen RW. Impact of Glycemic Control on Risk of Infections in Patients With Type 2 Diabetes: A Population- Based Cohort Study. Am J Epidemiol. 2017;186(2):227- 236.
  21. Chang CH, Wang JL, Wu LC, Chuang LM, Lin HH. Diabetes, Glycemic Control, and Risk of Infection Morbidity and Mortality: A Cohort Study. Open Forum Infect Dis. 2019;6(10):ofz358.
  22. McGovern AP, Hine J, de Lusignan S. Infection risk in elderly people with reduced glycaemic control. Lancet Diabetes Endocrinol. 2016;4(4):303-4.
  23. van den Berghe G, Wouters P, Weekers F, Verwaest C, Bruyninckx F, Schetz M, Vlasselaers D, Ferdinande P, Lauwers P, Bouillon R. Intensive insulin therapy in critically ill patients. N Engl J Med. 2001;345(19):1359-67.
  24. NICE-SUGAR Study Investigators, Finfer S, Chittock DR, Su SY, Blair D, Foster D, Dhingra V, Bellomo R, Cook D, Dodek P, Henderson WR, Hébert PC, Heritier S, Heyland DK, McArthur C, McDonald E, Mitchell I, Myburgh JA, Norton R, Potter J, Robinson BG, Ronco JJ. Intensive versus conventional glucose control in critically ill patients. N Engl J Med. 2009;360(13):1283-97.
  25. Hruska LA, Smith JM, Hendy MP, Fritz VL, McAdams S. Continuous insulin infusion reduces infectious complications in diabetics following coronary surgery. J Card Surg. 2005;20(5):403-7.
  26. The NICE-SUGAR Study Investigators. Hypoglycemia and risk of death in critically ill patients. N Engl J Med. 2012;367:1108.
  27. Tsai S, Clemente-Casares X, Zhou AC, Lei H, Ahn JJ, Chan YT, Choi O, Luck H, Woo M, Dunn SE, Engleman EG, Watts TH, Winer S, Winer DA. Insulin Receptor-Mediated Stimulation Boosts T Cell Immunity during Inflammation and Infection. Cell Metab. 2018;28(6):922-934.
  28. Eikawa S, Nishida M, Mizukami S, Yamazaki C, Nakayama E, Udono H. Immune-mediated antitumor effect by type 2 diabetes drug, metformin. Proc Natl Acad Sci USA. 2015;112(6):1809-14.
  29. Pearce EL, Walsh MC, Cejas PJ, Harms GM, Shen H, Wang LS, Jones RG, Choi Y. Enhancing CD8 T-cell memory by modulating fatty acid metabolism. Nature. 2009;460(7251):103-7.
  30. Bonnet F, Scheen AJ. Effects of SGLT2 inhibitors on systemic and tissue low-grade inflammation: The potential contribution to diabetes complications and cardiovascular disease. Diabetes Metab. 2018 Dec;44(6):457-464.
  31. Croasdell A, Duffney PF, Kim N, Lacy SH, Sime PJ, Phipps RP. PPARγ and the Innate Immune System Mediate the Resolution of Inflammation. PPAR Res. 2015;2015:549691.
  32. Lee YS, Jun HS. Anti-Inflammatory Effects of GLP-1-Based Therapies beyond Glucose Control. Mediators Inflamm. 2016;2016:3094642.
  33. Yonem A, Cakir B, Guler S, Azal OO, Corakci A. Effects of granulocyte-colony stimulating factor in the treatment of diabetic foot infection. Diabetes Obes Metab 2001;3:332– 337.
  34. Cruciani M, Lipsky BA, Mengoli C, de Lalla F. Are granulocyte colony-stimulating factors beneficial in treating diabetic foot infections?: A meta-analysis. Diabetes Care. 2005;28(2):454-60.
  35. Nieman DC, Wentz LM. The compelling link between physical activity and the body's defense system. J Sport Health Sci. 2019;8(3):201-217.

108.     Crespilho DM, de Almeida Leme JA, de Mello MA, Luciano E. Effects of physical training on the immune system in diabetic rats. Int J Diabetes Dev Ctries. 2010;30(1):33-7.

Genetic Testing in Youth – A Primer for Pediatric Lipidologists

ABSTRACT

 

The genetic causes of several dyslipidemias have been identified. Our knowledge of the role of genetics in disorders affecting lipid and lipoprotein metabolism continues to improve along with advancements in technology and access of testing. Genetic testing offers diagnostic confirmation of disease, risk stratification, the ability to identify at risk biologic relatives, and individualized treatment options. While currently underutilized, genetic testing will increasingly play a key role in the treatment and management of children with lipid disorders.

 

INTRODUCTION

 

In 2003, the cost of sequencing the first human genome was $2.7 billion. This pioneering work paved the way for genetic testing to become a practical tool in clinical practice. By 2016, the cost of genetic testing was under $1,000. With the cost continuing to decline, genetic testing is being utilized more frequently to help clinicians make informed decisions about clinical care. As genetic testing plays an increasingly important role in clinical management, it has become imperative of clinicians to understand the basic principles of genetic testing to provide appropriate care and accurate counseling, especially for youth with abnormalities of lipids and lipoproteins.

 

Although often underutilized, genetic testing helps to identify variants that play a causal role in disturbances of lipid and lipoprotein metabolism. Despite its benefits, the decision to perform a genetic test in youth requires a thorough understanding of the utility of genetic testing, as well as the nuances associated with testing of those under 18 years of age. Are youth able to understand the purpose of the test being recommended and the potential short- and long-term consequences associated with genetic test results? What rights do youth have in deciding whether to undergo testing?  While many excellent and comprehensive publications are available on the genetic causes of lipid and lipoprotein disorders, the goal of this chapter is to discuss basic concepts of genetic testing and assist providers in its use, including the interpretation of test results, counseling and effective communication of results. Furthermore, this chapter will address unique aspects of genetic testing in youth and discuss future directions in the field of diagnostic genetics as it relates to the practice of pediatric lipidology.

 

WHY IS GENETIC TESTING IMPORTANT?

 

When correctly utilized and properly communicated, genetic testing has the potential to provide significant benefits for both clinical management and patient education (1). Correct diagnosis of a genetic disorder can accurately assess risk and help inform clinical decision-making for the child as well as family members.    

 

For example, familial hypercholesterolemia (FH), a common condition (1:220), significantly increases an individual’s risk of premature cardiovascular disease (CVD) due to elevated levels of low-density lipoprotein cholesterol (LDL-C) (2). Although individuals with heterozygous FH have a variable phenotype, the presence of a genetic variant results in a significantly higher risk for development of CVD due to lifelong exposure of elevated levels of atherogenic LDL-C (3, 4).  The CDC has designated FH as a Tier 1 genetic condition, with strong evidence and potential to improve public health, alongside international recommendations supporting implementation of genetic testing for FH (5). Because FH is inherited in an autosomal co-dominant manner, first degree family members of those identified with a causative FH variant have a 50% chance of being affected and are at increased risk for developing CVD prematurely. Genetic testing can assist in therapeutic decision-making for the index case and at-risk family members known to have hypercholesterolemia or identified through cascade screening (6, 7). A government funded cascade screening program in the Netherlands identified over 30,000 genetically confirmed cases of FH – similar programs in several European countries have been successfully implemented.

 

Value to Youth

 

When considering FH, unique benefits exist in identifying the genotype of those under 18 years of age. While CVD-related events typically occur in adulthood, the presence of persistently elevated cholesterol levels from an early age leads to atherosclerosis, beginning in childhood (8), and plays a key role in CVD risk and progression (9). By identifying an at-risk child, properly assessing risk and initiating treatment, including early introduction of a heart-healthy lifestyle and appropriate lipid-lowering medication, risk of future ASCVD-related events such as a heart attack or stroke can be dramatically reduced (9, 10).

 

Furthermore, when youth are identified with FH, reverse cascade screening has the potential of identifying other affected family members. Because of its mode of inheritance, 50% of first-degree relatives of a child with genetically confirmed heterozygous FH are also affected, often unaware of their condition and not receiving lipid lowering medications (Figure 1) (11).

Figure 1. Sample pedigree from reverse cascade screening of proband. From Journal of Pediatric Nursing, 2019, with permission.

 

COMMON GENETIC TERMINOLOGY

 

Proper ordering and interpretation of a genetic test requires an understanding of commonly terms used. The following list of and diagram will help clinicians develop an understanding of some of the basic concepts of and visual image involved in genetic testing. 

 

Coverage: Number of genes sequenced. 

Depth: Number of times each nucleotide within a gene is sequenced.

Exome: Part of the genome that consists of exons. The exome accounts for roughly 1% of the genome.

Exon: A segment of a gene that encodes a protein.

Genome: A complete set of genetic information that provides all the necessary information required for a human to function. 

Intron: A noncoding region of DNA, or a segment of DNA that does not encode a protein.

Single Nucleotide Polymorphism (SNP): A common (present in >1% of population), typically low effect variant, occurring at a single nucleotide in the genome.

Splicing: A process by which introns are removed from a transcript to produce mature RNA, made up of exons.

Variant: An alteration in the DNA nucleotide sequence. Variants can be benign, pathogenic, or of unknown significance.

 

Figure 2. Visual depiction of a gene, nucleotide, introns and exons, splicing, and genome and exome sequencing.

 

AVAILABLE GENETIC TESTING

 

Targeted Panel

 

When considering conditions with known causal genetic loci, such as FH, targeted panels are often considered as a primary testing method. Four genes – LDLR, APOB, PCSK9, and LDLRAP1 – are principally considered when identifying pathogenic variants causing FH. While coverage is low (i.e., 4 genes), depth – depending on the performing laboratory – is high, often 100X or more, up to 1,000X.

 

Targeted panels are most accurate when used to identify variants in exons and smaller deletions or duplications. Using a combination of next generation sequencing technologies, Sanger sequencing, and deletion/duplication analysis, genetic variation often identified with >99% sensitivity and specificity. Introns are typically not sequenced beyond +/- 10 to 15 exon flanking base pairs.

 

Whole Exome Sequencing (WES)

 

As NGS technologies continue to evolve and cost declines, sequencing DNA of higher volume has become more feasible. WES allows for sequencing of all protein coding regions of a person’s genome—also known as the exome—along with flanking intronic regions. WES is often performed when the differential diagnosis is unclear or broad, or after a targeted genetic testing returns negative.

 

In the case of FH, WES can be helpful when no known variant is found in a traditional targeted panel. Several other conditions affecting lipid metabolism with known genetic variants – in APOE, ABCG5, ABCG8, LIPA, etc. – can produce a “FH phenotype,” in which conditions associated with variants in these genes create an overlap in elevated LDL-C levels with those seen in pathogenic FH variant carriers. Coverage in WES is high (i.e., 95 to >99% of the exome), while depth is often 20X up to 100X.

 

Secondary Findings

 

It is important to note that targeted panels inclusive of candidate genes and WES have the potential for identifying unintentional or secondary findings. For example, certain variants in APOE are associated with a FH phenotype; however, other APOE variants are associated with a predisposition for Alzheimer’s disease. When WES is performed, secondary findings for variants in gene sites unrelated to the condition under suspicion can occur.  For example, WES ordered for suspicion of FH could identify variants in BRCA1/2 associated with a predisposition to develop breast or ovarian cancer, which carry implications for other potentially affected family members. When secondary findings are identified, it is helpful to refer the family to either to a geneticist or other qualified specialist.  However, secondary findings can be excluded, directed by the preferences of family and provider. Concerns about secondary findings in WES and targeted panels can be alleviated by masking extraneous results.

 

Should Family Members Be Tested?

 

Low or no cost genetic testing is sometimes offered to family members to both identify additional at-risk family members and help inform genotype/phenotype correlations for more accurate classification of gene variants.

 

INTERPRETING TEST RESULTS

 

How Are Genetic Variants Classified?

 

Understanding the classification of an individual’s genetic variant can be a daunting task. No standardization of classification is uniformly adhered to, with each genomics laboratory offering their own definition or algorithm for classification. This ultimately results in the potential for one laboratory to define a variant as benign, while another may define the same variant as pathogenic. To further complicate matters, classification for each variant is subject to change as new and additional data about the variant is considered (12).

 

Interpretation of a pathogenic classification is the most straightforward. In the case of FH, the observed variant is considered to be the cause of the phenotype based on sufficient evidence of 1) the variant type, and 2) other individuals previously identified with the same variant.

 

Interpretation becomes more complicated in those with a variant of unknown significance (VUS) and for individuals in whom no mutation is identified. When faced with a VUS, it is important to consider how important additional data is in determining a causal link between a VUS and the clinical condition. Fortunately, many, but not all, genetic testing laboratories offer first degree relatives testing at low or no cost. Familial testing provides additional data to assist in more accurate classification of the finding in question, and guides health care decision-making.

 

In the case of a negative result, it is important to understand any limitations that exist with the test that was ordered. If a targeted panel for FH is performed and no mutation is found, 1) the test ordered may not cover all known variant sites; 2) additional potential variants exist; and 3) additional testing (WES) may be helpful.

 

COMMUNICATING TEST RESULTS

 

What Is The Role Of A Genetic Counselor?

 

Given the complex nature of genetic testing as a diagnostic tool, genetic testing plays a crucial role in youth and family members understanding of the risks and benefits of testing (13). However, genetic counseling is highly underutilized in current clinical practice (5). Counseling is a process that should begin prior to testing, and should continue after as a conversation with both the child, when appropriate, and their family.

 

Prior to testing, the child and family should be informed of: the suspected condition and how genetics may play a role, the possible benefits and risks of performing testing, and the potential of discovering uncertain or secondary findings.

 

After completion, test results and interpretation of their impact on both direct patient care and family members should be discussed. If necessary, counseling for family planning and any further testing should be provided.

 

What Is The Potential Impact Of Genetic Testing Upon The Child? The Family?

 

Proper communication of genetic test results and counseling provide the child and family information of high utility, usually with minimal adverse impact (14). In 2017, Hallowell et al. found during interviews of patients treated for FH who were the first to be genetically tested in their family, testing was considered beneficial, as it provided patients with an origin of their disease and assessed their own and their family members’ risk (15). The majority of parents of children with FH want their children to be tested (16) and children have been found to understand and articulate their understanding of testing being conducted (17). A majority of families do not report psychological problems due to a diagnosis of FH (18).

 

WHAT’S NEXT?

 

Progression of genetic testing has resulted in slowly changing the paradigm of clinical practice.  Having most recently experienced the evolution of evidence-based medicine, we are entering an era of personalized medicine, and eventually, predictive medicine. In the coming years, existing methods and results will become better understood, and additional testing will likely become more affordable, accurate, and widely used, leading to a potential shift in the clinical focus from phenotype to genotype.

 

Genomic Medicine

 

The current focus of genetic testing involves sequencing of exomes, accounting for only 1% of the genome. In contrast, whole genome sequencing (WGS) offers sequencing of both exons – protein encoding regions – and introns, containing regulatory information which controls exon splicing, transcription, and translation. Deep intronic variants are currently associated with over 75 genetic conditions (19).

 

RNA testing also offers similar benefits to WGS without having to analyze such a large volume of data. RNA testing potentially identifies any errors, including intronic variants, leading to incorrect splicing or transcript sequence. In the realm of lipidology, those with FH caused by a variant affecting apolipoprotein B (apoB) may have the most to benefit from RNA testing. ApoB circulates in 2 forms: apoB48, produced by the small intestine, and apoB100, produced by the liver, the latter involved in LDL assembly and uptake of LDL-C by the LDL receptor. Both forms are encoded by a single APOB gene, which undergoes a RNA editing process, producing both forms (20). In the future, investigating transcription and translation of APOB may prove useful in determining etiology of disease in patients with a currently unidentified variant.

 

Predictive Medicine

 

A significant portion of the general population, including those with a monogenic cause of FH, contain variants in genes associated with elevated cholesterol and CVD risk other than LDLR, APOB, PCSK9, and LDLRAP1.  These SNPs in “low effect genes,” or genetic locations that do not greatly affect the phenotype, when cumulatively expressed, alter both cholesterol and CVD risk.  LDL and CAD polygenic risk scores have proven to be accurate and appear to be nearing their time in clinical care (21-25).

 

Screening and Preventive Medicine

 

Considering the future of current methodologies, genetic testing of youth and their parents has proven feasible and effective in the UK, and universal phenotypic screening of young children in the US is currently recommended (2, 26). The first successfully implemented universal pediatric FH screening initiative occurred in Slovenia in 1995, within which a two-step approach was utilized – conducting universal biochemical cholesterol testing at 5 years of age, followed by genetic testing for those with elevated total cholesterol (7). FH also has potential to be a target for prenatal testing (27). Bellow et al. combined UK Biobank whole exome data with NHANES survey data, creating a predictive model which would yield 3.7, 3.8, and 6.6 identified FH cases per 1,000 people through clinical criteria alone, genetic testing alone, and combining clinical criteria and genetic testing, respectively (28). By combining established universal phenotypic childhood screening29 with reflex genetic and parental testing, the potential exists to identify every existing case of FH within one generation of testing. From then on, targeted testing of affected patient’s children would identify future cases.  

 

SPECIAL CONSIDERATIONS FOR YOUTH

 

While benefits exist that are unique to a pediatric population, additional unique circumstances should be also be considered when testing a child for a condition in which the onset occurs during adulthood.

 

Should Children Be Given A Choice?

 

The American Academy of Pediatrics (AAP) advocates for youth to have an increasingly important role in their own health care decision-making as they age and mature. From a legal perspective, virtually no legal rights exist, nor are protections in place, to ensure a child possesses any autonomy in the decision-making process of their health care (30). The decision whether to include the child in the decision-making process is ultimately left to the child’s parents and health care provider. 

 

Should Testing Be Deferred Until A Child Is 18 Years-Of-Age Or Older?

 

In 2013, the AAP and American College of Medical Genetics (ACMG) released a joint policy statement on the use of genetic testing and screening of children (31), agreeing that the principal factor in determining whether to offer genetic testing should be the best interest of the child. When considering FH, clear benefit exists in testing of children, as atherosclerosis can be reduced or prevented with early identification and treatment, ultimately reducing CVD risk.  

 

Do The Results Of Genetic Testing Create The Potential For Discrimination?

 

Once a child has undergone testing, results are entered into the clinical record. The 2008 Genetic Information Nondiscrimination Act (GINA) protects individuals from discrimination in health insurance and employment based on genetic information; however, individuals are not protected against discrimination in life or disability insurance. 

 

All of this must be weighed and discussed in the benefit-to-risk analysis when ordering a genetic testing involving a child. Whenever possible, the child should be provided age and developmentally appropriate information, allowed to participate in the discussion, encouraged to ask questions and share concerns, and help formulate the best course of action. 

 

SUMMARY

 

Genetic testing offers 1) diagnostic confirmation; 2) enhanced risk assessment; 3) an ability to identify affected family members; and 4) the opportunity to individualized treatment options.  Lipidologists are encouraged to use this emerging technology judiciously, mindful of the unique needs of youth. In the near future, genetic testing will likely be used on a wide scale to screen children and family members at-risk of CVD with the goal of prevention. Given its current trajectory, genetic testing is becoming increasingly critical in our ability to provide accurate risk assessment as well as age appropriate and timely intervention to help guide our efforts in educating and managing youth with disorders of lipid and lipoprotein metabolism.

 

RESOURCES

 

Select Laboratories Offering Genetic Testing For Dyslipidemias

 

Ambry Genetics: https://www.ambrygen.com/

Blueprint Genetics: https://blueprintgenetics.com/

GeneDx: https://www.genedx.com/

Invitae: https://www.invitae.com/en/

 

The Genetic Information Nondiscrimination Act (GINA) of 2008

 

https://www.eeoc.gov/laws/statutes/gina.cfm

 

ACKNOWLEDGEMENTS

 

The authors would like to acknowledge Ryan Lokkesmoe, MD, and Ariel Brautbar, MD, for their contributions in editing this manuscript.

 

REFERENCES

 

  1. W Burke. “Genetic testing.” New England Journal of Medicine, 2002.
  2. D Wald et al. “Child-parent familial hypercholesterolemia screening in primary care.” New England Journal of Medicine, 2016.
  3. A Sturm et al. “Clinical genetic testing for familial hypercholesterolemia.” Journal of the American College of Cardiology, 2018.
  4. A Khera et al. “Diagnostic yield and clinical utility of sequencing familial hypercholesterolemia genes in patients with severe hypercholesterolemia.” Journal of the American College of Cardiology, 2016.
  5. GF Watts et al. “International Atherosclerosis Society guidance for implementing best practice in the care of familial hypercholesterolemia.” Nature Reviews Cardiology, 2023.
  6. DM Kusters et al. “Carotid intima-media thickness in children with familial hypercholesterolemia.” Circulation Research, 2014.
  7. AM Medeiros et al. “Genetic testing in familial hypercholesterolemia: Is it for everyone?” Current Atherosclerosis Reports, 2024.
  8. DP Wilson et al. “Screening for genetic variants in children and adolescents with dyslipidemia: importance of early identification and implications of missed diagnoses.” Expert Opinions on Orphan Drugs, 2016.
  9. M Braamskamp et al. “Statin initiation during childhood in patients with familial hypercholesterolemia: consequences for cardiovascular risk.” Journal of the American College of Cardiology, 2016.
  10. A Wiegman et al. “Familial hypercholesterolemia in children and adolescents: gaining decades of life by optimizing detection and treatment.” European Heart Journal, 2015.
  11. A Vinson et al. “Reverse cascade screening for familial hypercholesterolemia.” Journal of Pediatric Nursing, 2018.
  12. S Aronson et al. “Communicating new knowledge on previously reported genetic variants.” Genetics in Medicine, 2012.
  13. A Brautbar et al. “Genetics of familial hypercholesterolemia.” Current Atherosclerosis Reports, 2015.
  14. N Jenkins et al. “How do index patients participating in genetic screening programmes for familial hypercholesterolemia (FH) interpret their DNA results? A UK-based qualitative interview study.” Patient Education and Counseling, 2013.
  15. N Hallowell et al. “A qualitative study of patients’ perceptions of the value of molecular diagnosis for familial hypercholesterolemia (FH).” Journal of Community Genetics, 2017.
  16. M Umans-Eckenhausen et al. “Parental attituate towards genetic testing for familial hypercholesterolemia in children.” Journal of Medical Genetics, 2002.
  17. E Smets et al. “Health-related quality of life of children with a positive carrier status for inherited cardiovascular diseases.” American Journal of Medical Genetics, Part A, 2008.
  18. S Tonstead. “Familial hypercholesterolaemia: a pilot study of parents’ and children’s concerns.” Acta Paediatrica, 1996.
  19. R Vaz-Drago et al. “Deep intronic variants and human disease.” Human Genetics, 2017.
  20. N Davidson et al. “Apolipoprotein B: mRNA editing, lipoprotein assembly, and presecretory degredation.” Annual Review of Nutrition, 2000.
  21. J Dron et al. “The evolution of genetic-based risk scores for lipids and cardiovascular disease.” Current Opinions in Lipidology, 2019.
  22. P Talmud et al. “Use of low-density lipoprotein cholesterol gene score to distinguish patients with polygenic and monogenic familial hypercholesterolaemia: a case-control study.” The Lancet, 2013.
  23. M Paquette et al. “Polygenic risk score predicts prevalence of cardiovascular disease in patients with familial hypercholesterolemia.” Journal of Clinical Lipidology, 2017.
  24. A Rao et al. “Polygenic risk scores in coronary artery disease.” Current Opinions in Caridiology, 2019.
  25. A Sarraju et al. “Genetic testing and risk scores: impact on familial hypercholesterolemia.” Frontiers in Cardiovascular Medicine, 2019.
  26. BK Bellows et al. “Estimated yield of screening for heterozygous familial hypercholesterolemia with and without genetic testing in US adults.” Journal of the American Heart Association, 2022.
  27. L Hamilton et al. “Implementation of cholesterol screening at 2 years of age.” Journal of Clinical Lipidology, 2019.
  28. J Vergotine et al. “Prenatal diagnosis of familial hypercholesterolemia: importance of DNA analysis in the high-risk South African population.” Genetic Counseling, 2001.
  29. “Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents.” NHLBI, 2011.
  30. E Clayton. “How much control do children and adolescents have over genomic testing, parental access to their results, and parental communication of those results to others?” Journal of Law, Medicine & Ethics, 2016.
  31. “Ethical and policy issues in genetic testing and screening of children.” Pediatrics, 2013.

 

Adrenal Insuffciency Due To X-Linked Adrenoleukodystrophy

ABSTRACT

 

X-linked adrenoleukodystrophy (X-ALD) is a rare inherited neurodegenerative disorder, involving mainly the white matter and axons of the central nervous system and the adrenal cortex and is a frequent but under-recognized cause of primary adrenocortical insufficiency. X-ALD is caused by a defect in the gene ABCD1 that maps to Xq 28 locus. The primary biochemical disorder is the accumulation of saturated very long chain fatty acids (VLCFA) secondary to peroxisomal dysfunction. The incidence in males is estimated to be 1:14,700 live births, without any difference among different ethnicities. X-ALD presents with a variable clinical spectrum that includes primary adrenal insufficiency, myelopathy, and cerebral ALD; however, there is no correlation between X-ALD phenotype and specific mutations in the ABCD1 gene. When suspected, the diagnosis is established biochemically with the gold standard for diagnosis being genetic testing (ABCD1 analysis). Currently, there is no satisfying treatment to prevent the onset or modify the progression of the neurologic or endocrine components of the disease. Allogeneic hematopoietic stem cell (HSC) transplantation is the treatment of choice for individuals with early stages of the cerebral form of the disease. An alternative option for patients without HLA-matched donors is autologous HSC-gene therapy with lentivirally corrected cells. Once adrenal insufficiency is present, hormonal replacement therapy is identical to that of autoimmune Addison’s disease.

 

INTRODUCTION

 

Leukodystrophies are inherited neurodegenerative disorders, primarily affecting the brain myelin. X-linked adrenoleukodystrophy (X-ALD; OMIM:300100) is the most common leukodystrophy usually presenting as chronic myelopathy and peripheral neuropathy, a clinical entity called adrenomyeloneuropathy (AMN), frequently accompanied by adrenocortical insufficiency (1). The pattern of inheritance is X- linked and the disease is clinically evident in almost all male patients and in more than 80% of female carriers older than 60 years, though with milder clinical presentation. Occasionally, male patients and very rarely female carriers may develop a rapidly progressive, devastating cerebral form of the disease known as Cerebral Adrenoleukodystrophy (CALD). The pathophysiological basis of the disease is peroxisome dysfunction and accumulation of very long chain fatty acids (VLCFA) due to impaired VLCFA degradation (2).

 

In the early 20th century, patients with signs and symptoms belonging to the Leukodystrophies spectrum were grouped under the name “Addison–Schilder disease”. It was not until the 1960s that Blaw introduced the term “adrenoleukodystrophy” as a distinct disease entity with X-linked inheritance (3). In 1976 it was shown that the principal biochemical disorder in X-ALD was the accumulation of VLCFA (4). In 1993, the gene responsible for the disease was identified at the Xq28 locus and it was subsequently shown to be the ABCD1 gene, which encodes the Adrenoleukodystrophy Protein (ALDP) (5).

 

This chapter summarizes the latest data in the literature regarding the progress made in elucidating the pathogenesis of the disease, the strategies for early diagnosis, and the results of established as well as newer experimental therapies.

 

GENETICS & PATHOPHYSIOLOGY

 

ALD is a rare progressive neurodegenerative disorder with an annual incidence of 1:14,700 live births (considering both hemizygous males and heterozygous females), and no marked difference between males and females (6).  

 

X-ALD is caused by mutations in the ABCD1 gene located on the X chromosome (Xq28), which covers 19.9 kb and contains 10 exons (7) with approximately 900 different mutations reported (8). Mutations in the ABCD1 gene include missense, nonsense, frameshift, and splice-site variants (9). However, identical variants can result in highly diverse clinical phenotypes, suggesting the presence of unknown additional factors that have an impact on the expression of the disease (2). Thus, there is a lack of a genotype-phenotype correlation in ALD (10, 11).

 

The ABCD1 gene encodes a peroxisomal trans-membrane protein of 745 amino acids, ALDP, a member of the ATP binding cassette (ABC) transport protein family, which helps to form the channel through which VLCFAs move into the peroxisome as VLCFA-CoA (12). ALDP deficiency leads to an impaired peroxisomal β-‑oxidation of saturated straight-chain very long-chain fatty acids (VLCFA) (13) resulting in the accumulation of VLCFAs in plasma and tissues, including the white matter of the brain, spinal cord, and adrenal cortex (14). Chronic accumulation of cholesterol with saturated VLCFA in the zona fasciculata and reticularis of the adrenal cortex is believed to result in cytotoxic effects, apoptosis and ultimately atrophy of the adrenal cortex and with loss of cortisol production (15, 16). The pathogenesis of X-ALD is summarized in Figure 1.

Figure 1. The pathogenesis of ALD. Adapted with permission from www.adrenoleukodystrophy.info.

 

The mode of inheritance of X-ALD is X-linked recessive (figure 2), thus the possibility of a son of a female carrier developing X-ALD is 50%, whilst 50% of female offsprings will also be heterozygous carriers. All female offsprings of an affected male will be carriers but none of his male offsprings will be affected. Since X-ALD is an X-linked inherited disorder, males are more severely affected than females. Some heterozygous X-ALD females can exhibit symptoms due to skewed X-chromosome inactivation or other genetic factors. Females who carry the defective gene used to be referred to as “carriers” because it was thought that only a small percentage of them will develop clinical symptoms. However, it has been recently shown that 80% of female patients will eventually develop symptoms although milder in severity than males. The most likely explanation for this clinical manifestation is the presence of a normal copy of the ABCD1 gene on their other X-chromosome that protects women with ALD from developing the brain variant (cerebral ALD) or other still unexplored genetic factors.

 

Figure 2. Adapted with permission from www.adrenoleukodystrophy.info.

 

Significant intra-familiar phenotype variability has been observed as different clinical phenotypes can occur even among monozygotic twins (17). Fifty percent of ABCD1 mutations lead to a truncated ALDP, whereas many missense mutations result in the formation of an unstable protein (18). The complete absence of a functional ALDP does not necessarily lead to the severe form of X-ALD, implicating the existence of additional factors that could modify the disease’s clinical expression. Factors, such as moderate head trauma, have been shown to trigger the progression of the disease to the severe central nervous system (CNS) form (19), but other unknown genetic and environmental factors are likely required for the development of CALD. In contrast, mutations with residual transporter activity or over-expression of ALDP-related protein (ALDRP, ABCD2), the closest homolog of ALDP, might prevent this progression (20). Variations in methionine metabolism have also been associated with the wide phenotypic spectrum of X-ALD (21).

 

CLINICAL MANIFESTATIONS OF X-ALD

 

The range of clinical expression of X-ALD varies widely. The main phenotypes of X-ALD are primary adrenal insufficiency (Addison’s disease), myelopathy, and cerebral ALD (CALD), either alone or in any combination.

 

The most devastating form of ALD is CALD which presents early in life between 4-12 years of age, affecting 1/3 of boys with X-ALD and is rare after 15 years of age (22). It is characterized by inflammatory demyelination mainly of the supratentorial and infratentorial white matter and brain magnetic resonance imaging (MRI) findings usually precede clinical symptomatology (23). The onset of CALD is insidious, with symptoms at school age such as learning, behavioral, and cognitive disabilities often being attributed to Attention Deficit/Hyperactivity Disorder that delay the diagnosis. As the disease progresses, overt neurologic deficits become apparent, including cortical blindness, central deafness, hemiplegia, and quadriparesis. Progression of the disease is often rapid, leading to death within 5 – 10 years following diagnosis (24). Most men who do not develop CALD during childhood develop myelopathy in adult life.

 

Myelopathy manifests later in life, typically presents in adult males between 20 and 40 years of age, with a median age at onset of 28 years (25). The primary clinical presentation is spinal cord and peripheral nerve dysfunction, leading to progressive spastic paraparesis, abnormal sphincter control, sensory ataxia, and sexual dysfunction. Symptoms are progressive over years or decades, with most patients losing unassisted functionality by the 5th – 6th decade of life. Brain MRI is usually normal but spinal cord atrophy can be detected by conventional T2-weighted MRI sequences. Although myelopathy is a milder form of ALD, cerebral involvement can occur in 27% to 63% of patients (26). Cerebral involvement leads to rapid neurologic deterioration with disabilities and early death in 10% to 20% of adult males (26). Adrenal insufficiency is often present at the time of myelopathy diagnosis, a clinical entity called adrenomyeloneuropathy (AMN).

 

Incidence Of Primary Adrenal Deficiency In X-ALD

 

The natural history of adrenal insufficiency in ALD is largely unknown because large prospective natural history studies are lacking. However, the loss of adrenal function evolves gradually and initially starts with elevated plasma corticotropin hormone (ACTH) levels before overt adrenal insufficiency with an abnormal cortisol response after cosyntropin stimulation and endocrine symptoms become apparent (10, 27). The average time to adrenal insufficiency or time from initial plasma ACTH elevation to the onset of endocrine symptoms is unknown (27, 28).

 

The estimated lifetime prevalence of adrenal insufficiency in ALD is considered to be approximately 80% (27, 29, 30). Addison’s disease is reported to be the initial clinical manifestation of ALD in 38% of cases, representing the most common presenting symptom of ALD in childhood (10, 29). ALD has been reported to account for 4% to 35% of cases of idiopathic primary adrenal insufficiency with no detectable steroid-21-hydroxylase antibodies or other obvious cause (31, 32, 33).

 

Therefore, all boys must be tested for ALD upon diagnosis of adrenal insufficiency if the cause is otherwise not clear. The risk for adrenal insufficiency varies throughout the lifetime and peaks during the first decade of life between 3 and 10 years of age (27, 29). The youngest patients suffering from adrenal insufficiency and ALD have been reported to be as young as 3, 5 and 7 months of age (27, 29, 34). it has therefore been recommended to start adrenal testing in the first six months of life (29).

 

In a large natural history study of adrenal insufficiency in ALD (29) the cumulative probability of adrenal insufficiency was highest until the age of 10 years, remained prominent until 40 years of age, and decreased substantially thereafter. A timeframe for adrenal testing has been suggested as follows: Besides on-demand testing if endocrine symptoms are present, screening for adrenal insufficiency should be initiated in the first 6 months of life, then routine adrenal testing should be performed every 3 to 6 months until 10 years of age, annual testing thereafter until 40 years of age, and solely on-demand testing in case of endocrine symptoms from age 41 years onward (29).

 

In this context, International Recommendations for the Diagnosis and Management of Patients with Adrenoleukodystrophy have been recently issued emphasizing the need for early and regular adrenal testing (35, figure 3).

 

Figure 3. Screening and management overview in ALD. Adapted with permission from: International Recommendations for the Diagnosis and Management of Patients with Adrenoleukodystrophy. Neurology 2022.

 

The most recent Endocrine Society and Pediatric Endocrine Society clinical practice recommendations for the evaluation of adrenal insufficiency are used as guides for establishing cutoff values for ACTH and cortisol (36).

 

An ACTH value of > 100 pg/mL and a cortisol value of < 10 mcg/dL is suggestive of adrenal insufficiency. Children with normal ACTH and cortisol levels (<100 pg/mL and ≥5 mcg/dL respectively) do not require immediate treatment and should be retested in 3 to 4 months. Children with clearly abnormal ACTH (> 300 pg/mL) and inappropriately low cortisol levels should begin daily and stress-dose glucocorticoid replacement. ACTH and cortisol values of 100 - 299 pg/mL and < 10 mcg/dL respectively should prompt high-dose ACTH (cosyntropin) stimulation testing (34). The median time to transition from stress to maintenance dose has been reported as short as 1.46 years (30). The recommended hormonal workup is depicted in figure 4.

 

Figure 4. Suggested hormonal work up for glucocorticoid deficiency in ALD.

 

Of note, the mineralocorticoid function often remains intact, reflecting the relative sparing of the zona glomerulosa in the adrenal cortex (10). Mineralocorticoid deficiency, leading to salt wasting, is not typically described in patients with ALD, consistent with the preservation of aldosterone production and the lack of VLCFA accumulation (37, 38). As VLCFAs mainly accumulate in the zona fasciculata and reticularis, the relative preservation of the zona glomerulosa aligns with the observation that mineralocorticoid function remains functional in approximately 50% of the patients (29). Therefore, mineralocorticoid replacement therapy should not be initiated unless abnormal signs/plasma renin activity and electrolyte levels become evident.

 

Once the diagnosis of glucocorticoid deficiency has been made, further evaluation of aldosterone production should be considered in case of symptoms, such as salt craving and hypotension. Because symptoms are difficult to assess in infancy, it is recommended that serum plasma renin activity and electrolytes be tested every 6 months (34). Fludrocortisone should be started when there is evidence of mineralocorticoid deficiency. Infants would also require additional salt supplementation.

 

Mineralocorticoid deficiency is reported to be present in 40% of patients with ALD with the vast majority presenting in adulthood (30). Given that mineralocorticoid deficiency is less common and generally follows glucocorticoid deficiency, evaluation with plasma renin activity and electrolytes is recommended every 6 months starting after diagnosis of glucocorticoid deficiency (34). The median time until mineralocorticoid replacement therapy has been reported to be 56 years of age in contrast to a much shorter time for glucocorticoid replacement therapy which was 16 years of age (29).

 

Female Patients

 

As ALD is an X-linked disease, women were previously considered to be asymptomatic carriers. It is now known that even though adrenal insufficiency and cerebral disease are rare in women, more than 80% eventually develop progressive spinal cord disease (39, 40); however, the progression rate of myeloneuropathy remains slow (29). Female patients with ALD typically remain asymptomatic in childhood and adolescence, while, myeloneuropathy symptoms usually arise in adulthood.

 

Fewer than 1% of female patients are reported to develop adrenal insufficiency (30, 35, 39, 41). Therefore, routine monitoring for adrenal insufficiency and MRI of the brain in women are not recommended (34). Only a few females have been reported to develop CALD and this has been attributed to skewed inactivation of the X-chromosome carrying the mutated ABCD1 gene (42).

 

Primary Hypogonadism

 

Gonadal function can also be affected in ALD. Abnormal hormone levels indicating gonadal insufficiency have been described in boys and men with ALD (35, 43, 44). Levels of testosterone in men with ALD are usually in the low-normal range with elevation of luteinizing hormone in some patients (45). These findings indicate primary hypogonadism, possibly due to the toxicity of VLCFA in Leydig cells, but tissue androgen receptor resistance has also been suggested as an alternative hypothesis to explain this finding (46).

 

To date, no trials have been performed to test the outcome of testosterone supplementation in men with ALD. In most men with ALD, fertility seems to be normal (29, 47). No data exists on fertility in women with ALD.

 

Tables 1 and 2 summarize the clinical phenotypes in male and female patients.

 

Table 1. X-ALD Phenotypes in Males

Phenotype

Description

Estimated Relative Frequency

Adrenocortical 

Insufficiency

Childhood cerebral

Onset 3-10 years.

31-35%

79%

Progressive behavioral, cognitive, neurologic deficits.

 

Total disability often within 3 years.

 

 

Adolescent cerebral

Like childhood cerebral; somewhat slower progression

4-7%

62%

Adult cerebral

Dementia, behavioral disturbances, focal neurologic deficits without preceding adrenomyeloneuropathy

2-3%

>50%

Adrenomyeloneuropathy

Onset 28 ± 9 years.

40-46%

50-70%

 

Slowly progressive paraparesis, sphincter disturbances

 

 

Addison only

Primary adrenal insufficiency without neurologic involvement.

Varies with age. Up to 50% in childhood

100%

 

Most common onset 5-7 years. Most eventually develop AMN or cerebral forms

 

 

Asymptomatic

No demonstrable neurologic or adrenal involvement

Common before 4 years. Diminishes with age.

50% plus with testing

 

Table 2. Phenotypes In Female X-ALD Carriers

Phenotype

Description

Estimated relative frequency

Asymptomatic

No neurologic or adrenal involvement

Diminishes with age

Mild myeloneuropathy

Increased deep tendon reflexes and sensory changes in lower extremities

Increases with age.

~ 50% at age >40 years.

Moderate to severe myeloneuropathy

Resembles AMN, but milder and later onset

Increases with age

>15% at age >40.

Clinically evident Addison’s disease

Rare at any age

<1%

 

DIAGNOSIS OF X-ALD

 

In patients highly suspected of having ALD, measurement of very long chain fatty acids (VCLFA) in the blood is diagnostic, with high specificity and sensitivity (48). VLCFA levels are already increased on the day of birth and in untreated patients remain stable throughout life. Testing typically includes three VLCFA parameters: the level of hexacosanoic acid (C26:0) and tetracosanoic acid (C24:0), and the ratio of these two compounds to docosanoic acid (normal values of C24:0/C22:0 ratio <1.0 and C26:0/C22:0 ratio <0.02). Hexacosanoic acid is the one most consistently elevated and is therefore considered to be diagnostic of the disease. Of note, VLCFA levels are also elevated in other peroxisomal disorders whereas they can be falsely elevated in patients with liver insufficiency or on ketogenic diets (49). False negative results may occur in approximately 20% of female patients, thus, any woman with symptoms of myelopathy with or without a family history of ALD should undergo further genetic testing (48). Plasma C26:0/C22:0 and C24:0/C22:0 ratios, although diagnostic for ALD, are not associated with the (age-dependent) risk of developing adrenal insufficiency, spinal cord disease, or cerebral disease (50, 51).  

 

However, genetic testing (ABCD1 analysis) is the gold standard for diagnosis.

The diagnosis of X-ALD should be sought (35):

 

  1. In boys and men with confluent white matter abnormalities on brain MRI in a pattern suggestive of ALD with or without cognitive and neurologic symptoms
  2. In adult men and women with symptoms and signs of chronic myelopathy with a normal MRI;
  3. In boys and men with primary adrenal insufficiency with no detectable steroid-21-hydroxylase antibodies or other organ-specific antibodies;
  4. In all at-risk patients with a relative diagnosed with ALD.

 

Genetic Testing

 

To date, more than 800 ABCD1 mutations have been described in the X-ALD database (52). Mutations include missense mutations (49%), large deletions (3%), frameshifts (24%), amino acid insertions/ deletions (6%), and nonsense mutations (12%), leading to decreased or absent ABCD1 protein expression. De novo mutation rate is reported to range from 5% to 19% (53). Importantly all clinical phenotypes of X-ALD can occur within the same nuclear family and there is no correlation between ABCD1 mutation and clinical phenotype except for rare cases such as all reported cases of translation initiation mutations in ABCD1 have presented with an AMN-only phenotype (54, 55).

 

Newborn Screening

 

Newborn screening (NBS) is justified for a disorder, provided that therapy is available, and that early diagnosis allows timely implementation. This is particularly relevant for X-ALD as early diagnosis at birth would allow for the early detection of adrenal insufficiency for timely initiation of adrenal steroid replacement therapy and early detection of cerebral ALD would permit hematopoietic stem cell transplantation (HSCT) before severe neurologic impairment is established. Important improvements towards this target were the development of mass spectrometry methods to assess the presence of VLCFA in dried-blood spots as well as a combined liquid chromatography/tandem mass spectrometry (LC-MS/MS) high-throughput assay that could measure VLCFA enriched lysophosphatidylcholine (lysoPC), thus providing the technical background for NBS (56).

 

New York State (NYS) in 2013 was the first authority to include screening for X-ALD in the NBS program and since February 2016, X-ALD has been added to the United States Recommended Uniform Screening Panel (RUSP) (57).

 

NYS NBS for X-ALD is used by most states in the United States (US) and is based on a 3-tier algorithm: the first tier is tandem mass spectrometry (MS/MS) of C26:0-lysophosphatidylcholine (LPS); the second tier is a confirmatory HPLC-MS/MS; and the third tier is Sanger DNA sequencing of the ABCD1 gene (58). If ABCD1 mutation analysis is negative, then other peroxisomal disorders which are also C26:0-HLPC positive should be sought, such as Zellweger Spectrum Disorders, ACOX1, HSD1B4, ACBD5 deficiency, and CADDS (Contiguous ABCD1 DXS1357/BCAP31 Deletion Syndrome) (57).

 

As of January 2023, thirty-five US states have successfully added ALD to the conditions screened via NBS with plans to expand to all states (59, 60, 61, 62, 63, 64, 65, 66). Globally, the Netherlands is the only other country that is actively screening for ALD through the Screening for ALD in the Netherlands (SCAN) pilot study, a sex-specific newborn screen for boys (67). Since the implementation of Newborn screening for ALD, data show a rise in the diagnosis of ALD up to ~1 in 10,500 births as well as an earlier diagnosis of adrenal insufficiency (30).

 

Genetic Counseling

 

As soon as an index case is detected either as a consequence of symptoms or as a result of NBS, genetic counseling should be offered to the family. If the index case is male, testing should be offered to his mother and female offspring.  If the mother is confirmed to be a carrier for an ABCD1 mutation, testing should also include all the male siblings of the index case. If the index case is female, initial testing should include both parents. Regarding mutation testing of minor females of an affected family, there is no consensus on whether it should be performed on a routine base. (57).

 

Imaging

 

All individuals with confirmed ALD/AMN complex should undergo neuroimaging to determine if cerebral involvement is present. Brain MRI abnormalities precede symptoms in patients with the cerebral forms of X-ALD (23). Findings are always abnormal in symptomatic patients, demonstrating cerebral white matter demyelination (Figure 5). The lesions typically begin in the splenium of the corpus callosum before gradually expanding to the occipito-parietal region and they are usually bilateral but occasionally can be limited to only one side, particularly if previous head trauma has triggered CALD (19). The presence of contrast enhancement just behind the outermost edge of the lesions as seen in T1-weighted images (WI), heralds the progression to inflammatory devastating form of CALD (68). A grading system to assess the degree of MRI abnormalities in X-ALD has been proposed by Loes et al. (69). This is a 32-point scale score (0: normal, 32: most severe) that assesses the degree and extent of hyperintense lesions on FLAIR or T2W images as well as the degree of regional atrophy and has proven to have predictive value for the response to allogenic hematopoietic stem cell transplantation (70).

 

Regarding AMN, MRI of the spinal cord is unremarkable on standard sequences, it can however show atrophy in advanced cases (71). Contrast enhancement is not observed in AMN, since inflammation is not a feature of extra-cerebral lesions.

 

Brain F18 fludeoxy-glucose positron emission tomography (PET) may reveal hypometabolic regions particularly in the cerebellum and temporal lobe areas, before lesions emerge in MRI (72). In contrast, hypermetabolism may be evident in the frontal lobes, related to the clinical severity of the disease (73).

 

Figure 5. MRI of a patient with cerebral ALD, showing reduced volume and increased signal intensity of the white matter localized mainly at the parieto-occipital regions. The anterior white matter is spared. (http://en.wikipedia.org/w/index.php?title=Adrenoleukodystrophy&oldid=506277486).

 

THERAPY

 

Dietary Treatment

 

Τherapeutic options include dietary therapies with restriction of fat intake and particularly of VLCFAs and saturated fats to avoid their accumulation. In order to achieve this, total fat intake is restricted to 15% of the total calorie supply and a maximum of 5-10 mg of C26:0 is allowed on a daily basis (Table 3).

 

Table 3. Dietary Restrictions In X-ALD. Adopted Form Ref. 2

Foods rich in VLCFAs

Foods rich in saturated fat

Vegetable oils

Fatty fish and meat

Plant cover and cuticle

Fruit peel and seeds

Grains and nuts

Vegetable oils

Fatty fish and meat

Milk and milk products

Egg yolk

Industrial pastry

 

However, since the majority of VLCFA are of endogenous origin (74), this approach is not sufficient. A mixture of oleic acid [C18:1] and erucic acid [C22:1], also referred to as Lorenzo's Oil (LO), has also been applied (75). LO has been shown to halt the elongation of VLCFA by inhibiting ELOVL1, the primary enzyme responsible for VLCFA synthesis.

 

LO in combination with a low-fat diet nearly normalizes plasma VLCFA levels within four weeks and in a study involving asymptomatic X-ALD patients with normal brain MRI, dietary treatment with LO resulted in a two-fold or greater reduction in the risk of developing the childhood cerebral form of X-ALD (76). However, in patients who are already symptomatic, controlled clinical trials failed to show improved neurological or endocrine function, nor did it arrest the progression of the disease (35, 77, 78). Treatment with LO may be continued for an indefinite time until disease progression and/or severe side effects occur. It is not recommended in children under one year of age, as it causes a decrease in the levels of other fatty acids, particularly docosahexaenoic acid, which is essential for neurocognitive development.

 

Allogenic Hematopoietic Stem Cell Transplantation (HSCT)

 

Allogeneic HSCT is the treatment of choice for individuals with early stages of cerebral involvement of X-ALD, which may increase disease-specific survival and can lead to long-term stabilization and improvement of neurological status (77, 79, 80). Stem cells can be harvested from peripheral blood, bone marrow, and umbilical cord blood of immune-compatible donors. Although the mechanism of this effect is still unclear, bone marrow cells do express the ABCD1 gene and plasma VLCFA levels are reduced after bone marrow transplantation, offering a useful biomarker for the assessment of engraftment, graft failure, or rejection (81). It has been shown that bone marrow-derived cells do enter the brain-blood barrier and that a portion of perivascular microglia is gradually replaced by donor-derived cells (82).

 

Allogeneic HSCT has been shown to increase 5-year survival compared to no transplant (95% versus 54%) and arrest the progression of the neurologic disease when undertaken early in the course of cerebral disease (44). In contrast, hematopoietic stem cell transplantation is not effective in patients with advanced cerebral ALD, therefore the general criteria for eligibility are a genetically and/or clinically confirmed diagnosis of ALD and the presence of cerebral disease that is not advanced, based on neurological symptoms and brain MRI findings (83). Eligibility of a patient for transplantation can be assessed using the ALD-specific Neurologic Function Scale (NFS) and the Loes MRI severity score (54). The NFS scale is a 25-point, ALD-specific tool that assesses the severity of neurological disability according to the severity of symptoms, but no score absolutely determines the decision for HSCT. HSCT affects not only survival, but also the long-term functional status of patients. Studies have shown that post-transplant survival and major functional disability (MFD)-free survival are superior in patients with lower NFS and Loes score (84, 85). A recent multi-center analysis showed that in early-stage transplanted patients the overall survival at 5 years from CALD diagnosis was 94% and the MFD -free survival was 91%, whereas in patients with advanced disease the overall survival and the MFD-free survival were 90% and 10% respectively (83).

 

Allogeneic HSCT has its limitations. Transplantation is not effective in patients with advanced disease. Neurologic findings present at the time of HSCT do not reverse and symptoms can progress after HSCT as cerebral disease stabilization is not achieved before 3 to 24 months after stem cell infusion (54). Furthermore, the identification of an acceptable donor for HSCT could be very challenging. Significant risks associated with HSCT include acute mortality (10% at day 100 from transplant), failure of donor cell engraftment (5% risk), and graft-versus-host disease (GVHD) (10-40% risk of acute GVHD and 20% risk of chronic GVHD) (85).

 

HSCT has not been tested systematically in AMN because of concerns that the risk-benefit ratio may not be favorable: up to 50% of AMN patients will never develop cerebral involvement, whereas it is highly unlikely that HSCT will affect the non-inflammatory distal axonopathy which is the main pathological feature in AMN (86). Moreover, in retrospective series of patients who successfully underwent HSCT for CALD in childhood, it was shown that it could not prevent the onset of AMN in adulthood (87).

 

Although data are limited, HSCT is unlikely to affect adrenal insufficiency (35). The proposed underlying mechanism is that VLCFAs accumulation in the adrenal cortex has already reached a critical point that is irreversible by the time of transplant, whereas cerebral ALD has a considerable progressive inflammatory component that is stabilized by the transplant (88).

 

Gene Therapy

 

In case of patients without HLA-matched donors or adult patients with CALD (given the higher mortality risk of allogeneic HSCT compared to children), an alternative option is autologous HSC-gene therapy with lentivirally corrected cells (89). In this procedure, CD34+ cells from X-ALD patients are transfected ex vivo using a lentiviral vector encoding the wild-type ABCD1 cDNA. As a result of this therapy, 7-14% of granulocytes, monocytes, T and B lymphocytes express the lentivirally encoded ALDP. In a recent phase 2-3 study including 17 boys, short-term clinical outcomes were reported to be comparable to that of allogeneic HSCT (90). The procedure called Lenti-D gene therapy resulted in clinical disease and imaging stabilization according to neurological symptoms and brain MRI findings in the vast majority of enrolled patients. An ongoing study recruiting for a phase III trial that has been recently opened across the US and Europe (NCT03852498) will further evaluate the efficacy and safety of Lenti-D gene therapy in participants with CALD.Nevertheless, concerns regarding long-term efficacy, biosafety of lentiviral vectors, as well as the high cost of this therapy need to be taken into account (91, 92). An alternative approach is performing allogeneic HSCT from healthy siblings conceived after preimplantation HLA matching which offers the possibility of selecting unaffected embryos that are HLA compatible with the sick child (93).

 

Regarding adrenal function, similarly to HSCT, there is no evidence for the reversal of adrenal failure after autologous HSC gene therapy (88). Advances in gene therapy could offer new treatment options for ALD. Potential therapies include a) antisense oligonucleotides which target specific mutations to exclude pathogenic variants or to establish a normal reading frame shift, b) gene editing through the use of endonucleases that allows permanent modifications to specific DNA segments and c) targeted viral vector therapy that could deliver a normal copy of the ABCD1 gene to steroidogenic and to microglial cells to prevent adrenal disease and neurological dysfunction respectively (54).

 

Treatment Of Adrenal Insufficiency and Hypogonadism

 

For those patients with X-ALD who have impaired adrenal function, glucocorticoid replacement therapy is mandatory. Glucocorticoid replacement requirements are generally the same as in other forms of PAI, whereas most patients may not require mineralocorticoid replacement.

 

 Male patients who present clinical manifestations of hypogonadism and confirmed low serum testosterone levels, should be treated with testosterone. Nevertheless, careful evaluation should be warranted, since impotence, in most instances may imply spinal cord involvement or neuropathy, rather than testosterone deficiency.

 

Experimental Therapies

 

Experimental treatment options include a) agents that bypass the defective ALDP by inducing alternative pathways for VLCFA degradation, b) combinations of antioxidants that diminish oxidative stress, c) agents that halt VLCFA elongation and d) the use of neurotrophic factors.

 

 Apart from ALDP, three additional closely related ABC half-transporters exist: ALDRP, PMP70, and PMP69, which are located on the membrane of peroxisomes. ALDP must dimerize with one of these half-transporters to form a functional full transporter (94). Over-expression of ABCD2, the gene producing ALDRP has been shown to compensate for ABCD1 deficiency and ameliorate VLCFA production from X-ALD cell series (95). Valproic acid (VPA), a widely used anti-epileptic drug, 4-phenylbutyrate, and other histone deacetylase inhibitors, are known inducers of the expression of ALDRP. In a 6-month pilot trial of VPA in X-ALD patients marked correction of the protein oxidative damage was observed (96). Other agents known to evoke induction of the ABCD2 gene are ligands to several nuclear receptors: fibrates for PPAR alpha, thyroid hormones and thyromimetics, retinoids, and lately LXR antagonists, which are being tested in vitro and in vivo for the treatment of X-ALD (97, 98, 99). Lately, it has been shown that AMP-activated protein kinase (AMPKα1) is reduced in X-ALD, raising the question if metformin, a well-known AMPKα1inducer, may have a therapeutic role for X-ALD (100).

 

 Regarding the use of antioxidative treatments, experimental data show that treatment of ABCD1 null mice with a combination of antioxidants containing α-tocopherol, N-acetyl-cysteine and α-lipoic acid reversed oxidative damage, axonal degeneration, and locomotor impairment (101). Similar results have been observed with the oral administration of pioglitazone, an agonist of the PPAR gamma receptor, which restored oxidative damage to mitochondrial proteins and DNA, and reversed bioenergetic failure. Lately, bezafibrate, a PPAR pan agonist has been demonstrated to reduce VLCFA levels in X-ALD fibroblasts (102). The mechanism for this action is by decreasing the synthesis of C26:0 through a direct inhibition of ELOVL-1 and subsequent fatty acid elongation activity. Unfortunately, these actions could not be confirmed in vivo as in a recent clinical trial, bezafibrate was unable to lower VLCFA levels in plasma or lymphocytes of X-ALD patients (103).

 

The options for treatment of the advanced progressive form of CALD remain limited. Even though the presence of inflammatory lesions is well recognized, trials of immunosuppressive therapies have yielded poor results. Cyclophosphamide, interferon, IVIG, and other immunomodulators have been used without success (104, 105). Promising results have been extracted by the use of the antioxidant N-acetyl-L-cysteine as adjunctive therapy to HSCT in patients with advanced CALD (106, 107).

 

REFERENCES

 

  1. Moser HW. Adrenoleukodystrophy: phenotype, genetics, pathogenesis and therapy. 1997;120 ( Pt 8:1485–508.
  2. Engelen M, Kemp S, Poll-The BT. X-linked adrenoleukodystrophy: pathogenesis and treatment. Curr Neurol Neurosci Rep. 2014;14(10):486.
  3. Blaw ME, Osterberg K, Kozak P, Nelson E. Sudanophilic Leukodystrophy and Adrenal Cortical Atrophy. Arch Neurol. 1964;11:626–31.
  4. Igarashi M, Schaumburg HH, Powers J, Kishmoto Y, Kolodny E, Suzuki K. Fatty acid abnormality in adrenoleukodystrophy. J Neurochem. 1976;26(4):851–60.
  5. Mosser J, Douar AM, Sarde CO, Kioschis P, Feil R, Moser H, et al. Putative X-linked adrenoleukodystrophy gene shares unexpected homology with ABC transporters. Nature. 1993;361(6414):726–30.
  6. Moser A, Jones R, Hubbard W, Tortorelli S, Orsini J, Caggana M, Vogel B, Raymond G. Newborn screening for X-linked adrenoleukodystrophy. Int J Neonatal Screen. 2016;2(4):15.
  7. Kemp S, Berger J, Aubourg P. X-linked adrenoleukodystrophy: clinical, metabolic, genetic and pathophysiological aspects. Biochim Biophys Acta 2012;1822 (9):1465–74.
  8. X-linked adrenoleukodystrophy.
  9. ALD info website. ProMED-mail website https://adrenoleukodystrophy.info/mutations-and-variants-in-abcd1.
  10. Kemp S, Huffnagel IC, Linthorst GE, Wanders RJ, Engelen M. Adrenoleukodystrophy - neuroendocrine pathogenesis and redefinition of natural history. Nat Rev Endocrinol. 2016;12(10):606-615.
  11. Di Rocco M, Doria-Lamba L, Caruso U. Monozygotic twins with X-linked adrenoleukodystrophy and different phenotypes. Ann Neurol. 2001;50(3):424.
  12. Higgins CF. ABC transporters: from microorganisms to man. Annu Rev Cell Biol. 1992;8: 67–113.
  13. Kemp, S. & Wanders, R. Biochemical aspects of Xlinked adrenoleukodystrophy. Brain Pathol. 2010; 20, 831–837.
  14. Moser, H. W., Smith, K. D., Watkins, P. A., Powers, J. & Moser, A. B. in The Metabolic and Molecular Bases of Inherited Disease 3257–3301 (McGraw Hill, 2001)
  15. Powers, J. M., Schaumburg, H. H., Johnson, A. B. & Raine, C. S. A correlative study of the adrenal cortex in adreno-leukodystrophy — evidence for a fatal intoxication with very long chain saturated fatty acids. Invest. Cell Pathol 1980;3: 353–376.
  16. Johnson, A. B., Schaumburg, H. H. & Powers, J. M. Histochemical characteristics of the striated inclusions of adrenoleukodystrophy. J. Histochem Cytochem 1976;24: 725–730.
  17. Pereira Fdos S, Matte U, Habekost CT, de Castilhos RM, El Husny AS, Lourenco CM, et al. Mutations, clinical findings and survival estimates in South American patients with X-linked adrenoleukodystrophy. PLoS One. 2012;7(3):e34195.
  18. Kemp S, Pujol A, Waterham HR, van Geel BM, Boehm CD, Raymond G V, et al. ABCD1 mutations and the X-linked adrenoleukodystrophy mutation database: role in diagnosis and clinical correlations. Hum Mutat. 2001;18(6):499–515.
  19. Raymond G V, Seidman R, Monteith TS, Kolodny E, Sathe S, Mahmood A, et al. Head trauma can initiate the onset of adreno-leukodystrophy. J Neurol Sci. 2010;290(1–2):70–4.
  20. Netik A, Forss-Petter S, Holzinger A, Molzer B, Unterrainer G, Berger J. Adrenoleukodystrophy-related protein can compensate functionally for adrenoleukodystrophy protein deficiency (X-ALD): implications for therapy. Hum Mol Genet. 1999;8(5):907–13.
  21. Hudspeth MP, Raymond G V. Immunopathogenesis of adrenoleukodystrophy: current understanding. J Neuroimmunol. 2007;182(1–2):5–12.
  22. Liberato AP, Mallack  EJ, Aziz-Bose R, et al. X-linked adrenoleukodystrophy. Neurology. 2019;92(15):1698–1708.
  23. Moser HW, Loes DJ, Melhem ER, Raymond G V, Bezman L, Cox CS, et al. X-Linked adrenoleukodystrophy: overview and prognosis as a function of age and brain magnetic resonance imaging abnormality. A study involving 372 patients. Neuropediatrics 2000;31(5):227–39.
  24. Zhu J, Eichler F, Biffi A, Christine N,Williams D, Majzoub J. The Changing Face of Adrenoleukodystrophy. Endocrine Reviews, 2020; 41(4):577–593.
  25. Van Geel  BM, Bezman  L, Loes  DJ, et  al. Evolution of phenotypes in adult male patients with X-linked adrenoleukodystrophy. Ann Neurol. 2001;49(2):186–94.
  26. De Beer M, Engelen M, van Geel BM. Frequent occurrence of cerebral demyelinaion in adrenomyeloneuropathy. Neurology. 2014;83(24):2227–2231.
  27. Dubey P, Raymond GV, Moser AB, Kharkar S, Bezman L, Moser HW. Adrenal insufficiency in asymptomatic adrenoleukodystrophy patients identified by very long-chain fatty acid screening. J Pediatr. 2005;146(4):528–532.
  28. Blevins LS Jr, Shankroff J, Moser HW, Ladenson PW. Elevated plasma adrenocorticotropin concentration as evidence of limited adrenocortical reserve in patients with adrenomyeloneuropathy. J Clin Endocrinol Metab. 1994;78(2):261–265.
  29. Huffnagel IC, Laheji FK, Aziz-Bose R, et al. The Natural History of Adrenal Insufficiency in X-Linked Adrenoleukodystrophy: An International Collaboration. J Clin Endocrinol Metab. 2019;104(1):118-126.
  30. Alcantara JR, Grant NR, Sethuram S, et al. Early Detection of Adrenal Insufficiency: The Impact of Newborn Screening for Adrenoleukodystrophy. J Clin Endocrinol Metab. 2023;108(11):1306-1315.
  31. Laureti S, Casucci G, Santeusanio F, et al. X-linked adrenoleukodystrophy is a frequent cause of idiopathic Addison’s disease in young adult male patients. J Clin Endocrinol Metab. 1996;81(2):470–4.
  32. Laureti S, Aubourg P, Calcinaro  F, et al. Etiological diagnosis of primary adrenal insufficiency using an original flowchart of immune and biochemical markers. J Clin Endocrinol Metab. 1998;83(9):3163–3168.
  33. Guran T, Buonocore F, Saka N, et al.Rare causes of primary adrenal insufficiency: genetic and clinical characterization of a large nationwide cohort. J Clin Endocrinol Metab. 2016;101(1):284–292.
  34. Regelmann MO, Kamboj MK, Miller BS, et al. Adrenoleukodystrophy: Guidance for Adrenal Surveillance in Males Identified by Newborn Screen. J Clin Endocrinol Metab. 2018;103(11):4324-4331.
  35. Engelen M, van Ballegoij WJC, Mallack EJ, et al. International Recommendations for the Diagnosis and Management of Patients with Adrenoleukodystrophy: A Consensus-Based Approach. Neurology. 2022;99(21):940-951.
  36. Bornstein SR, Allolio B, Arlt W, Barthel A, Don-Wauchope A, Hammer GD, Husebye ES, Merke DP, Murad MH, Stratakis CA, Torpy DJ. Diagnosis and treatment of primary adrenal insufficiency: an Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab. 2016;101(2):364–389.
  37. Powers JM, Schaumburg HH. Adreno-leukodystrophy (sex-linked Schilder’s disease). A pathogenetic hypothesis based on ultrastructural lesions in adrenal cortex, peripheral nerve and testis. Am J Pathol 1974;76(3):481–491.
  38. Schaumburg HH, Powers JM, Raine CS, Suzuki K, Richardson EP Jr. Adrenoleukodystrophy. A clinical and pathological study of 17 cases. Arch Neurol. 1975;32(9):577–591.
  39. Engelen M, Barbier M, Dijkstra IM, Schur R, de Bie RM, Verhamme C, Dijkgraaf MG, Aubourg PA, Wanders RJ, van Geel BM, de Visser M, Poll-The BT, Kemp S. X-linked adrenoleukodystrophy in women: a cross-sectional cohort study. Brain. 2014; 137:693–706.
  40. Habekost CT, Schestatsky P, Torres VF, de Coelho DM, Vargas CR, Torrez V, Oses JP, Portela LV, Pereira Fdos S, Matte U, Jardim LB. Neurological impairment among heterozygote women for X-linked Adrenoleukodystrophy: a case control study on a clinical, neurophysiological and biochemical characteristics. Orphanet J Rare Dis. 2014; 9:6.
  41. Schmidt S, Traber F, Block W, et al. Phenotype assignment in symptomatic female carriers of X-linked adrenoleukodystrophy. J Neurol. 2001;248(1):36-44
  42. Maier EM, Kammerer S, Muntau AC, Wichers M, Braun A, Roscher AA. Symptoms in carriers of adrenoleukodystrophy relate to skewed X inactivation. Ann Neurol. 2002;52(5):683–8.
  43. Kuhl JS, Suarez F, Gillett GT, et al. Long-term outcomes of allogeneic haematopoietic stem cell transplantation for adult cerebral X-linked adrenoleukodystrophy. Brain. 2017;140(4):953-966.
  44. Mahmood A, Raymond GV, Dubey P, Peters C, Moser HW. Survival analysis of haematopoietic cell transplantation for childhood cerebral X-linked adrenoleukodystrophy: a comparison study. Lancet Neurol. 2007;6(8):687-692.
  45. Brennemann, W., Kohler, W., Zierz, S. & Klingmuller, D. Testicular dysfunction in adrenomyeloneuropathy. J. Endocrinol. 1997;137: 34–39.
  46. Karapanou, O. et al. Xlinked adrenoleukodystrophy: are signs of hypogonadism always due to testicular failure? Hormones (Athens) 13, 146–152 (2014).
  47. Stradomska, T. J., Kubalska, J., Janas, R. & TylkiSzymanska, A. Reproductive function in men affected by Xlinked adrenoleukodystrophy/ adrenomyeloneuropathy. Eur. J. Endocrinol. 2012;166: 291–294.
  48. Moser AB, Kreiter N, Bezman L, et al. Plasma very long chain fatty acids in 3,000 peroxisome disease patients and 29,000 controls. Ann Neurol. 1999;45(1):100–110.
  49. Stradomska TJ, Bachański M, Pawłowska J, et al. The impact of a ketogenic diet and liver dysfunction on serum very long-chain fatty acids levels. Lipids. 2013;48(4):405–409.
  50. Korenke GC, Roth C, Krasemann E, H¨ufner M, Hunneman DH, Hanefeld F. Variability of endocrinological dysfunction in 55 patients with X-linked adrenoleucodystrophy: clinical, laboratory and genetic findings. Eur J Endocrinol. 1997;137(1):40–47.
  51. Tran C, Patel J, Stacy H, Mamak EG, Faghfoury H, Raiman J, et al. Long-term outcome of patients with X-linked adrenoleukodystrophy: A retrospective cohort study. Eur J Paediatr Neurol (2017) 21(4):600–9.
  52. ALD info website. ProMED-mail website. https:// adrenoleukodystrophy.info/.
  53. Horn MA, Retterstøl  L, Abdelnoor  M, et al. Adrenoleukodystrophy in Norway: high rate of de novo mutations and age-dependent penetrance. Pediatr Neurol. 2013;48(3):212–219.
  54. Zhu J, Eichler F, Biffi A, Duncan CN, Williams DA, Majzoub JA. The Changing Face of Adrenoleukodystrophy. Endocr Rev. 2020;41(4):577-593. 
  55. O’Neill GN, Aoki M, Brown RH Jr. ABCD1 translation-initiator mutation demonstrates genotype-phenotype correlation for AMN. Neurology. 2001;57(11):1956–1962.
  56. Hubbard WC, Moser AB, Tortorelli S, Liu A, Jones D, Moser H. Combined liquid chromatography-tandem mass spectrometry as an analytical method for high throughput screening for X-linked adrenoleukodystrophy and other peroxisomal disorders: preliminary findings. Mol Genet Metab. 2006;89(1–2):185–7.
  57. Vogel BH, Bradley SE, Adams DJ, Aco KD, Erbe RW, Fong C, et al. Newborn screening for X-linked adrenoleukodystrophy in New York State: Diagnostic protocol, surveillance protocol and treatment guidelines. Mol Genet Metab. 2015;114(4):599–603.
  58. Kemper AR, Brosco J, Comeau AM, et al. Newborn screening for X-linked adrenoleukodystrophy: evidence summary and advisory committee recommendation. Genet Med. 2017;19: 121–126.
  59. Prinzi J, Pasquali M, Hobert JA, et al. Diagnosing X-Linked Adrenoleukodystrophy after Implementation of Newborn Screening: A Reference Laboratory Perspective. Int J Neonatal Screen. 2023;9(4):64.
  60. Wiens K, Berry SA, Choi H, Gaviglio A, Gupta A, Hietala A, et al. A report on state-wide implementation of newborn screening for Xlinked Adrenoleukodystrophy. Am J Med Genet. 2019; 179:1205–13.
  61. Tang H, Matteson J, Rinaldo P, Tortorelli S, Currier R SS. The clinical impact of CLIR tools toward rapid resolution of post-newborn screening confirmatory testing for X-linked adrenoleukodystrophy in California. Int J Neonatal Screen. 2020; 6:62.
  62. Lee S, Clinard K, Young SP, Rehder CW, Fan Z, Calikoglu AS, et al. Evaluation of X-linked adrenoleukodystrophy newborn screening in North Carolina. JAMA Netw Open. 2020;3: 1–12.
  63. Hall PL Li H, Hagar AF, Caleb Jerris S, Wittenauer A, Wilcox W. Newborn screening for X-linked Adrenoleukodystrophy in Georgia: experiences from a pilot study screening of 51,081 newborns. Int J Neonatal Screen. 2020;6: 81.
  64. Matteson J, Sciortino S, Feuchtbaum L, Bishop T, Olney RS, Tang H. Neonatal screening adrenoleukodystrophy newborn screening in California since 2016: programmatic outcomes and follow-Up. Int J Neonatal Screen. 2021; 7:22.
  65. Moser AB, Raymond G V, Burton BK, Hickey R, Hitchins L, Shively V, et al. Neonatal screening newborn screening for X-linked adrenoleukodystrophy: the initial Illinois experience. Int J Neonatal Screen. 2022; 8:6.
  66. Priestley JRC, Adang LA, Drewes Williams S, Lichter-Konecki U, Menello C, Engelhardt NM, et al. Newborn screening for X-linked adrenoleukodystrophy : review of data and outcomes in Pennsylvania. Int J Neonatal Screen. 2022; 8:24.
  67. Barendsen RW, Dijkstra IME, Visser WF, Alders M, Bliek J, Boelen A, et al. Adrenoleukodystrophy newborn screening in the Netherlands (SCAN Study): the X-factor. Front. Cell Develop. Biol. 2020; 8:499.
  68. Melhem ER, Loes DJ, Georgiades CS, Raymond G V, Moser HW. X-linked adrenoleukodystrophy: the role of contrast-enhanced MR imaging in predicting disease progression. Am J Neuroradiol. 2000;21(5):839–44.
  69. Loes DJ, Hite S, Moser H, Stillman AE, Shapiro E, Lockman L, et al. Adrenoleukodystrophy: a scoring method for brain MR observations. Am J Neuroradiol. 1994;15(9):1761–6.
  70. McKinney AM, Nascene D, Miller WP, Eisengart J, Loes D, Benson M, et al. Childhood cerebral X-linked adrenoleukodystrophy: diffusion tensor imaging measurements for prediction of clinical outcome after hematopoietic stem cell transplantation. Am J Neuroradiol. 2013;34(3):641–9.
  71. Dubey P, Fatemi A, Huang H, Nagae-Poetscher L, Wakana S, Barker PB, van Zijl P, Moser HW, Mori S, Raymond GV. Diffusion tensor-based imaging reveals occult abnormalities in adrenomyeloneuropathy. Ann Neurol. 2005;58:758-66. 
  72. Renard D, Castelnovo G, Collombier L, Kotzki PO, Labauge P. Brain fludeoxyglucose F 18 positron emission tomography hypometabolism in magnetic resonance imaging-negative x-linked adrenoleukodystrophy. Arch Neurol. 2011;68(10):1338–9.
  73. Salsano E, Marotta G, Manfredi V, Giovagnoli AR, Farina L, Savoiardo M, et al. Brain fluorodeoxyglucose PET in adrenoleukodystrophy. Neurology. 2014;83(11):981–9.
  74. Tsuji S, Sano T, Ariga T, Miyatake T. Increased synthesis of hexacosanoic acid (C23:0) by cultured skin fibroblasts from patients with adrenoleukodystrophy (ALD) and adrenomyeloneuropathy (AMN). J Biochem. 1981;90(4):1233–6.
  75. Rizzo WB, Leshner RT, Odone A, Dammann AL, Craft DA, Jensen ME, et al. Dietary erucic acid therapy for X-linked adrenoleukodystrophy. Neurology. 1989;39(11):1415–22.
  76. Moser HW, Raymond G V, Lu SE, Muenz LR, Moser AB, Xu J, et al. Follow-up of 89 asymptomatic patients with adrenoleukodystrophy treated with Lorenzo’s oil. Arch Neurol. 2005;62(7):1073–80.
  77. Aubourg P, Blanche S, Jambaque I, Rocchiccioli F, Kalifa G, Naud-Saudreau C, et al. Reversal of early neurologic and neuroradiologic manifestations of X-linked adrenoleukodystrophy by bone marrow transplantation. N Engl J Med. 1990;322(26):1860–6.
  78. Van Geel BM, Assies J, Haverkort EB, Koelman JH, Verbeeten B. J, Wanders RJ, et al. Progression of abnormalities in adrenomyeloneuropathy and neurologically asymptomatic X-linked adrenoleukodystrophy despite treatment with “Lorenzo’s oil.” J Neurol Neurosurg Psychiatry. 1999;67(3):290–9.
  79. Shapiro E, Krivit W, Lockman L, Jambaque I, Peters C, Cowan M, et al. Long-term effect of bone-marrow transplantation for childhood-onset cerebral X-linked adrenoleukodystrophy. Lancet. 2000; 356:713–8.
  80. Miller WP, Rothman SM, Nascene D, Kivisto T, DeFor TE, Ziegler RS, et al. Outcomes after allogeneic hematopoietic cell transplantation for childhood cerebral adrenoleukodystrophy: the largest single-institution cohort report. Blood. 2011;118(7):1971–8.
  81. Stradomska TJ, Drabko K, Moszczynska E, Tylki-Szymanska A. Monitoring of very long-chain fatty acids levels in X-linked adrenoleukodystrophy, treated with haematopoietic stem cell transplantation and Lorenzo’s Oil. Folia Neuropathol. 2014; 52:159–63.
  82. Hickey WF, Kimura H. Perivascular microglial cells of the CNS are bone marrow-derived and present antigen in vivo. Science. 1988; 239:290–2.
  83. Raymond G, Aubourg P, Paker  A, et  al. Survival and functional outcomes in boys with cerebral adrenoleukodystrophy with and without hematopoietic stem cell transplantation. Biol Blood Marrow Transplant. 2019;25(3):538–548
  84. Orchard, P. J. et al. Hematopoietic cell therapy for metabolic disease. J. Pediatr. 151, 340–346 (2007).
  85. Peters, C. et al. Cerebral X-linked adrenoleukodystrophy: the international hematopoietic cell transplantation experience from 1982 to 1999. Blood 104, 881–888 (2004).
  86. Powers JM, DeCiero DP, Ito M, Moser AB, Moser HW. Adrenomyeloneuropathy: a neuropathologic review featuring its noninflammatory myelopathy. J Neuropathol Exp Neurol. 2000;59(2):89–102.
  87. van Geel BM, Poll-The BT, Verrips A, Boelens JJ, Kemp S, Engelen M. Hematopoietic cell transplantation does not prevent myelopathy in X-linked adrenoleukodystrophy: a retrospective study. J Inherit Metab 2015; 38(2):359-61
  88. Petryk A, Polgreen LE, Chahla S, Miller W, Orchard PJ. No evidence for the reversal of adrenal failure after hematopoietic cell transplantation in X-linked adrenoleukodystrophy. Bone Marrow Transplant. 2012;47(10):1377–1378.
  89. Cartier N, Hacein-Bey-Abina S, Bartholomae CC, Bougneres P, Schmidt M, Kalle C V, et al. Lentiviral hematopoietic cell gene therapy for X-linked adrenoleukodystrophy. Methods Enzym. 2012; 507:187–98.
  90. Eichler F, Duncan C, Musolino PL, Orchard PJ, De Oliveira S, Thrasher AJ, et al. Hematopoietic Stem-Cell Gene Therapy for Cerebral Adrenoleukodystrophy. N Engl J Med. 2017;377(17):1630–8.
  91. Rothe M, Modlich U, Schambach A. Biosafety challenges for use of lentiviral vectors in gene therapy. Curr Gene Ther. 2013;13(6):453–68.
  92. Engelen M. Optimizing Treatment for Cerebral Adrenoleukodystrophy in the Era of Gene Therapy. N Engl J Med. 2017;377, 1682–1684.
  93. Kahraman, S. et al. Successful haematopoietic stem cell transplantation in 44 children from healthy siblings conceived after preimplantation HLA matching. Reprod. Biomed. Online 29, 340–351 (2014).
  94. Kemp S, Berger J, Aubourg P. X-linked adrenoleukodystrophy: Clinical, metabolic, genetic and pathophysiological aspects. Biochim Biophys Acta. 2012;1822(9):1465–74.
  95. Netik A, Forss-Petter S, Holzinger A, Molzer B, Unterrainer G, Berger J. Adrenoleukodystrophy-related protein can compensate functionally for adrenoleukodystrophy protein deficiency (X-ALD): implications for therapy. Hum Mol Genet. 1999;8(5):907–13.
  96. Fourcade S, Ruiz M, Guilera C, Hahnen E, Brichta L, Naudi A, et al. Valproic acid induces antioxidant effects in X-linked adrenoleukodystrophy. Hum Mol Genet. 2010;19(10):2005–14.
  97. Jang J, Kim HS, Kang JW, Kang HC. The genetically modified polysialylated form of neural cell adhesion molecule-positive cells for potential treatment of X-linked adrenoleukodystrophy. Yonsei Med J. 2013;54(1):246–52.
  98. Gondcaille C, Genin EC, Lopez TE, Dias AM, Geillon F, Andreoletti P, et al. LXR antagonists induce ABCD2 expression. Biochim Biophys Acta. 2014;1841(2):259–66.
  99. Park CY, Kim HS, Jang J, Lee H, Lee JS, Yoo JE, et al. ABCD2 is a direct target of beta-catenin and TCF-4: implications for X-linked adrenoleukodystrophy therapy. PLoS One. 2013;8(2): e 56242.
  100. Singh J, Olle B, Suhail H, Felicella MM, Giri S. Metformin-induced mitochondrial function and ABCD2 up-regulation in X-linked adrenoleukodystrophy involves AMP-activated protein kinase. J Neurochem. 2016;138(1):86–100.
  101. Galea E, Launay N, Portero-Otin M, Ruiz M, Pamplona R, Aubourg P, et al. Oxidative stress underlying axonal degeneration in adrenoleukodystrophy: A paradigm for multifactorial neurodegenerative diseases? Biochim Biophys Acta. 2012;1822(9):1475–88.
  102. Morato L, Galino J, Ruiz M, Calingasan NY, Starkov AA, Dumont M, et al. Pioglitazone halts axonal degeneration in a mouse model of X-linked adrenoleukodystrophy. Brain. 2013;136(Pt 8):2432–43.
  103. Engelen M, Tran L, Ofman R, Brennecke J, Moser AB, Dijkstra IME, et al. Bezafibrate for X-Linked Adrenoleukodystrophy. Baud O, editor. PLoS One. 2012 Jul 20;7(7): e41013
  104. Berger J, Pujol A, Aubourg P, Forss-Petter S. Current and future pharmacological treatment strategies in X-linked adrenoleukodystrophy. Brain Pathol. 2010;20(4):845–56.
  105. Horvath GA, Eichler F, Poskitt K, Stockler-Ipsiroglu S. Failure of repeated cyclophosphamide pulse therapy in childhood cerebral X-linked adrenoleukodystrophy. Neuropediatrics. 2012;43(1):48–52.
  106. Casasnovas C, Montserrat R, Schlüter A, Naudí A, Fourcade S, Veciana M, Castañer S, Albertí A, Bargalló N, Johnson M, Gerald V, Raymond G, Fatemi A, Moser A, Villarroya F, Portero-Otín M, Artuch R, Pamplona R, Aurora Pujol A. Biomarker Identification, Safety, and Efficacy of High-Dose Antioxidants for Adrenomyeloneuropathy: a Phase II Pilot Study. Neurotherapeutics (2019) 16:1167–1182.
  107. Zhou J, Terluk M, Orchard P, Cloyd J,  Kartha R. N-Acetylcysteine Reverses the Mitochondrial Dysfunction Induced by Very Long-Chain Fatty Acids in Murine Oligodendrocyte Model of Adrenoleukodystrophy. 2021 Dec; 9(12): 1826

 

Cardiovascular Risk Reduction In Youth With Diabetes- Opportunities And Challenges

ABSTRACT

 

Despite a notable decline over the past few decades, cardiovascular disease (CVD) remains the leading cause of premature mortality in individuals with diabetes mellitus. Compared to individuals without diabetes, there is ~2-fold or higher increase in CVD and mortality in those with diabetes. While CVD-related complications are seen predominantly during adulthood, the atherosclerotic process begins in childhood and is accelerated in individuals with type 1 diabetes (T1D), and even more so in type 2 diabetes (T2D). While there are improved methods of achieving glycemic control, earlier recognition and management of CVD risk factors, and advances in treatment, an increase in the prevalence of both T1D and T2D among youth continues to present additional challenges, especially because newer medications are underutilized. In this review, we discuss the origin and progression of atherosclerosis in youth with both T1D and T2D, CVD risk factors, and current guidelines. We conclude with key clinical questions that urgently need to be addressed to increase risk factor screening rates and treatment to improve outcomes in this high-risk population.

 

INTRODUCTION

 

Cardiovascular disease remains the leading cause of premature mortality in individuals with diabetes (1, 2).  There is ~2-fold increase in CVD and premature mortality in those with versus those without diabetes (3-5). Moreover, the incidence and prevalence of diabetes continues to increase, both in adults and children. It is estimated that by 2025, 1.3 billion individuals are projected to have diabetes worldwide.  In addition to the individual burden of this disease, diabetes increases health care utilization and costs. Despite these challenges, within the past two decades there has been a significant reduction in all-cause and CV-related mortality in this population (6). When CV risk factors (hemoglobin A1c, LDL cholesterol, albuminuria, smoking and blood pressure) are within the target ranges, risk of death, myocardial infarction, or stroke appears similar to the general population (6).

 

TYPES OF DIABETES IN YOUTH

 

T1D results from destruction of pancreatic beta-cells, secondary to an autoimmune process. It is characterized by dysregulation of plasma glucose, resulting in chronic hyperglycemia. An inability to secrete insulin necessitates exogenous insulin to maintain normal or near-normal levels of plasma glucose. Improved formulations of insulin, automated delivery systems, and continuous glucose monitoring devices have significantly improved the management of T1D.

 

T2D likely results from a combination of genetic, environmental, and metabolic risk factors. The pathophysiology of youth-onset T2D includes hepatic, peripheral, and adipose tissue insulin resistance together with relative insulin deficiency due to impaired pancreatic beta (β)-cell function (6-9), hyperglucagonemia due to alpha (α)-cell dysfunction, and impaired incretin effect (10). While youth share similar pathophysiological features with adults with T2D, some unique characteristics have been identified in youth. Youth with T2D have greater insulin resistance (11, 12), more rapid pancreatic beta cell decline, and poorer responses to diabetes medications compared to adults (13-17). In the last five years, medications including glucagon like peptide-1 receptor agonists and sodium-glucose transport protein 2 inhibitors have been approved for use in pediatric patients. Interested readers can find more information about the pathophysiology and types of diabetes at Endotext: Etiology and Pathogenesis of Diabetes Mellitus in Children and Adolescents. 2021 Jun 19. PMID: 29714936.; Pathogenesis of Type 2 Diabetes Mellitus. 2021 Sep 27. PMID: 25905339 (18).

 

There are other types of diabetes that develop in childhood including monogenic forms of diabetes, diabetes secondary to medications (e.g steroids), and diabetes associated with exocrine pancreas dysfunction (cystic fibrosis-related diabetes). CVD risk in these rare forms of diabetes is relatively unknown and, therefore, not the focus of this chapter. Interested readers can find more information about atypical forms of diabetes at Endotext: Atypical Forms of Diabetes. 2022 Feb 24. PMID: 25905351 (19).

 

EPIDEMIOLOGY

 

Among youth 19 years-of-age or younger, 7,759 in a population of 3.61 million in 2017 had T1D i.e. a prevalence of  approximately 1:500.This represents an increase of 45.1% (95% CI, 40.0%-50.4%) from 2001 (20). The greatest absolute increases were observed among non-Hispanic White (0.93 per 1000 youth [95% CI, 0.88-0.98]) and non-Hispanic Black (0.89 per 1000 youth [95% CI, 0.88-0.98]) (20). The increased incidence of T1D in children 5 years-of-age and younger is of particular concern, since adverse CVD outcomes are associated with duration of diabetes (21).

 

Among youth 10 to 19 years-of-age, 1,230 in a population of 1.85 million in 2017 had T2D. This represents a prevalence of ~1:1500 and an increase of 95.3% (95% CI, 77.0%-115.4%) from 2001. The increase largely parallels the rise in childhood obesity. The incidence of T2D from 2002 to 2012 differed across race/ethnic groups with the largest increases observed in non-Hispanic Black, Native American, and Asian/Pacific Islander youth, followed by Hispanic youth, with a low and stable incidence in non-Hispanic White youth.

 

CARDIOVASCULAR DISEASE RISK IN YOUTH WITH DIABETES

 

It is estimated that 14-45% of children with T1D have at least 2 CVD risk factors and this risk increases with age (22); 32% of youth with T2D had ≥2 and 32% had ≥3 CVD risk factors. The two most common CVD risk factors independent of diabetes type were increased waist circumference and low HDL-C, despite the traditional presentation of T1D thought to be in youth without obesity. The SEARCH for Diabetes in Youth study found participants with youth-onset T2D were 5-fold more likely to have ≥2 CVD risk factors, relative to T1D participants (OR = 5.1 [4.8, 5.4], P < 0.0001) (23).

 

Long term observational data from Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study found 60% of young adults with youth-onset T2D had ≥1 microvascular complication by a mean age of 26 years and 17/500 youth had already experienced a serious cardiovascular event (myocardial infarction [4 events], congestive heart failure [6 events], coronary artery disease [3 events], and stroke [4 events]) (24). Observations from the SEARCH for Diabetes in Youth study have shown microvascular complications, including diabetes-related kidney disease, retinopathy, and peripheral neuropathy, are >2-fold higher in youth with T2D compared to T1D, though complications were frequent in both teenagers and young adults with T1D and T2D (25).

 

The presence of CV risk factors in diabetes, including dyslipidemia, hypertension, and adiposity, confers an increased risk of myocardial infarction (MI), stroke, incident peripheral arterial disease, heart failure hospitalization, and CV death that increases with age (26). While the latter events occur during adulthood, their origins begin much earlier. Ample evidence supports the presence of atherosclerosis, the underlying origin of CVD, beginning in childhood, and is accelerated in youth with T1D and T2D (27).

 

Although randomized controlled trials (RCT) have conclusively demonstrated that intense glycemic control can reduce the risk of microvascular complications in both T1D and T2D (28), the relationship of glycemia per se to macrovascular risk in diabetes has been mixed (29). Risk factors other than hyperglycemia (e.g. hypertension, dyslipidemia, overweight/obesity, chronic inflammation, and renal impairment) are key determinants of atherosclerotic cardiovascular disease (ASCVD) event risk and often precede the onset of hyperglycemia, especially in T2D (30, 31). Additionally, chronic hyperglycemia, if present, is strongly associated with worsening of retinopathy, neuropathy, and nephropathy (32). There may also be aspects of less-than-ideal medication adherence which also contribute to higher CVD risk (33). Reduction in ASCVD related morbidity and mortality is possible with early identification and aggressive management of concomitant risk factors (34-36). Further, optimal glycemic control, is helpful to achieve better clinical outcomes in both T1D and T2D (6).

 

To improve outcomes for youth with diabetes, global risk factor screening, including assessment of modifiable and non-modifiable risk factors (enhancers), health behaviors and social determinants of health (Figure 1) screening should be performed to help appropriately categorize risk and define targets for early intervention. Particularly concerning are genetic disorders, such as familial hypercholesterolemia (FH) and elevated levels of lipoprotein (a) which, when present, result in lifetime exposure to atherogenic lipoproteins and a significant increase in CVD risk independent of diabetes (37, 38).

 

Figure 1. Global risk factors associated with cardiovascular disease. Adapted from (39).

Non-Modifiable Risk Factors

 

Risk factors for CVD are generally classified as non-modifiable or modifiable. Non-modifiable risk factors are those that cannot be changed. These include sex, race/ethnicity, and family history of premature CVD. There is evidence that the in-utero environment (gestational diabetes, maternal hypercholesterolemia), low birth weight, and polygenic risk factors play a significant role in the future CVD risk of a child. While non-modifiable risk factors are not amenable to therapy, their presence suggests the need for early identification and optimal management of modifiable risk factors.

 

Modifiable Risk Factors

 

CV biomarkers, such as lipids and lipoprotein levels are commonly used to assess risk and serve as therapeutic targets. Published guidelines provide recommendations for initial and follow-up measurements of key CV risk factors in youth with diabetes, as well as goals to achieve optimum health (40, 41). While an in-depth discussion of modifiable risk factors is beyond the scope of this review, several highlights by diabetes type are discussed below and in the Table 1.

 

Table 1. Recommendations for Cardiovascular Risk Factor Screening in Youth with Diabetes

 

Risk Factor

 

Recommendations for T1D

 

Differences for T2D

 

Goals

 

Comments

Hyperglycemia

Real-time CGM or intermittently scanned CGM should be offered

 

Glycemic status should be assessed at least every 3 months

 

Automated insulin delivery systems may be considered to improve glycemic control.

Glycemic status should be assessed at least every 3 months

 

Real-time CGM or intermittently scanned CGM should be offered when on multiple daily injections or on continuous subcutaneous insulin infusion

An A1C of <7% is appropriate for many children and adolescents with T1D and T2D.

In T1D an A1c target of 7.5 or 8% may be appropriate for selected individuals.

In T2D an A1c target <6.5% may be appropriate for selected individuals.

A1c targets need to consider risk of hypoglycemia and be adjusted accordingly.

Dyslipidemia

Initial lipid profile should be performed soon after diagnosis, preferably after glycemia has improved and age is ≥2 years. If initial LDL-C is ≤100 mg/dL (2.6 mmol/L), subsequent testing should be performed at 9-11 years of age.

 

If LDL-C values are within the accepted risk level (<100 mg/dL [2.6 mmol/L]), a lipid profile repeated every 3 years is reasonable.

 

 

 

Initial lipid profile should be performed soon after diagnosis, preferably after glycemia has improved.

 

If LDL-C values are within the accepted risk level (<100 mg/dL [2.6 mmol/L]), a lipid profile repeated annually.

 

 

 

 

 

LDL-C value <100 mg/dL (2.6 mmol/L).

 

Non-HDL-C level has been identified as a significant predictor of the presence of atherosclerosis—as powerful as any other lipoprotein cholesterol measure in children and adolescents. Non-HDL-C target is <130mg/dL

Initial testing may be done with a non-fasting lipid level with confirmatory testing with a fasting lipid panel.

Children with a primary lipid disorder (e.g., familial hyperlipidemia) should be referred to a lipid specialist.

 

A major advantage of non-HDL-C is that it can be accurately calculated in a non-fasting state and therefore is practical to obtain in clinical practice as a screening test

Blood Pressure

BP should be measured at every routine visit.

Same as T1D

BP <90th percentile for age, sex, and height or, in adolescents aged ≥13 years, <130/80 mmHg.

In youth with high BP (≥90th percentile for age, sex, and height or, in adolescents aged ≥13 years, BP ≥120/80 mmHg) on three separate measurements, ambulatory BP monitoring should be strongly considered.

Abbreviations: BP, blood pressure; GFR, glomerular filtration rate; HbA1c, glycated hemoglobin; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; Non-HDL-C, non-high-density lipoprotein cholesterol; T1D, type 1 diabetes mellitus

 

HYPERGLYCEMIA

 

Although glycemic control is critically important in managing diabetes, data linking improved glycemic control to a reduction in macrovascular complications are limited (27). Nonetheless, compared to those receiving standard care, CVD events in individuals with T1D who received intense insulin treatment at diabetes onset were reduced by 42% (95% CI, 9-63%) and the combined end-point of non-fatal MI, stroke or mortality by 57% (95% CI, 12-79%), despite similar treatment and glycemic control after completion of the study (42, 43). Similarly, results from the UK Prospective Diabetes Study (UKPDS) (44) and its 10-year cohort follow-up (45) suggest that intensive glucose control may be of greater CVD benefit when initiated early in T2D. One study found a 1% increase in HbA1c was associated with a 6-fold increase in coronary artery stenosis (46). In youth with diabetes, noninvasive measures of subclinical CVD, such as arterial stiffness and carotid intima media thickness (cIMT) are correlated with glycemic control (46-51). While hyperglycemia promotes endothelial dysfunction and arterial stiffness, there is growing evidence that optimum glycemic control alone is insufficient to significantly reduce the burden of CVD in persons with diabetes (52, 53). Glycemic recommendations for youth with diabetes are shown in Table 1.

 

DYSLIPIDEMIA

 

There is a high prevalence of dyslipidemia in adolescents with T1D; with 24-35% estimated to have hypercholesterolemia (54, 55). In the SEARCH for Diabetes in Youth study, approximately 15% of youth with T1D had high triglycerides,10% with low HDL-C and 10% with elevated apoB levels (56). In youth with T2D, 65% had elevated triglyceride levels, 60% had low HDL-C levels and 35% had elevated apoB levels. In a Denver cohort of youth, Maahs et al. demonstrated sustained abnormalities of total cholesterol, HDL-C and LDL-C over 10 years in children and adolescents with T1D, with 28% and 11 % having LDL-C levels ≥160 and 190 mg/dL, respectively. They also reported that 40-63% of childhood lipid abnormalities track from childhood to adulthood (57). In a retrospective analysis by Pelham et al, higher hemoglobin A1c levels were associated with higher LDL-C and apoB levels in youth with type 2 (58). Moreover, youth with T2D who had hemoglobin A1c levels of greater than 8% had significantly higher total cholesterol, LDL-C, and apoB levels compared to youth whose hemoglobin A1c levels were <8% (58).

 

The adverse vascular effects of prolonged exposure to atherogenic lipoproteins are well known and likely contribute to the subclinical atherosclerosis at an early age and accelerated in youth with diabetes (59). The current LDL-C goal of < 100 mg/dL (< 2.6 mmol/L) is supported by data in adults with childhood onset T1D which show that LDL-C levels of > 100 mg/dL are associated with increased CVD (54). Currently, guidelines for youth with diabetes do not recommend screening or treatment for apoB or lipoprotein (a) concentrations. Lipid recommendations are shown in Table 1. Interested readers can find more information about the roles of lipid and lipoprotein atherosclerosis at Endotext [Internet]: Linton MF, Yancey PG, Davies SS, Jerome WG, Linton EF, Song WL, Doran AC, Vickers KC. The Role of Lipids and Lipoproteins in Atherosclerosis. PMID: 26844337 (19).

 

There has been one RTC evaluating atorvastatin 10mg in youth 10-16 years of age with T1D. Compared to placebo, in the statin treated group there was a significant reduction in total, LDL-C, and non-HDL-C levels as well as in triglyceride levels, and in the ratio of apolipoprotein B to apolipoprotein A1. Of note, statin use during 48 months of the trial was not associated with differences between groups in carotid intima-media thickness (cIMT), glomerular filtration rate, or progression of retinopathy (60).

 

HYPERTENSION

 

Hypertension in youth with diabetes is common, with an estimated prevalence of 4-7% in youth with T1D (61); and 25-40% in those with T2D (62). In the TODAY study baseline prevalence of hypertension among youth with T2D was 19.2%. Over 14- years the cumulative incidence was 59.2%. Males were at higher risk of developing hypertension as were non- Hispanic whites compared with Hispanic youth (63). Hypertension is likely under-recognized, in part related to the challenges of measuring blood pressure in an ambulatory setting. Increases in arterial stiffness and cIMT have been observed in the setting of hypertension (2, 62), and correlate with the progression of diabetic nephropathy (64). While there are data that support hypertension-related target organ damage beginning in youth, CV clinical trials with measures of hard outcomes, such as fatal and non-fatal MI and stroke, are lacking in children. Nonetheless, current guidelines recommend blood pressures of < 90th percentile for age, sex and height (<120/80 if over age 13 years) and intervention when higher BP levels are sustained, Table 1.

 

OVERWEIGHT AND OBESITY

 

The prevalence of obesity (BMI > 95th percentile), a known risk factor for CVD, has been estimated to be 4.4-25% in T1D youth (65-67). T1D youth with obesity have a higher prevalence of hypertension, metabolic syndrome, and elevated alanine aminotransferase than those with a normal BMI (68). Prevalence of obesity approaches ~80% among youth with T2D; ~10% being overweight (67). In the SEARCH for Diabetes in Youth study among children 3-19 years-of-age, the prevalence of a BMI >85th in those with diabetes was higher than those without diabetes. In a 20-year follow-up of 655 individuals with T1D, an age-independent increase in overweight/obesity was observed; the relationship of adiposity with mortality resembling that of the general population, albeit with a marked increased risk in those who are underweight (69). Increased food intake secondary to concerns of hypoglycemia and intense insulin regimens may also contribute to excessive weight gain (69). Compared with BMI or percent body fat, central adiposity may be a better predictor of cardiovascular risk (2, 70). Higher waist circumference is an independent risk factor of subclinical CVD (arterial stiffness and cIMT) in youth with diabetes (2, 47, 49, 71). Current guidelines utilize BMI targets for weight optimization.

 

Health Behaviors and Conditions

 

PHYSICAL ACTIVITY

 

Numerous studies have found that a sedentary lifestyle is a risk factor for future CVD. Moreover, physical activity is inversely related to hemoglobin A1c, occurrence of diabetic ketoacidosis, BMI, dyslipidemia, and hypertension as well as retinopathy and microalbuminuria (72). Conversely, interventions to increase physical activity have demonstrated positive effects on hemoglobin A1c, BMI, triglycerides, and total cholesterol (73); the most effective being interventions >12 weeks in duration, with 3 or more 60-minute sessions per week which include resistance and aerobic exercise (74). Exercise once a week for 30 minutes has also been reported to lower hemoglobin A1c and diastolic blood pressure and improve dyslipidemia (72). Regardless of diabetes type, current pediatric guidelines recommend 3 or more 60-minute sessions per week which include resistance training and aerobic exercise.

 

SMOKING

 

In adults, active as well as passive smoking has been shown to be major risk factor for CVD and associated with poor glycemic control, adverse changes in lipid profile, nephropathy, endothelial dysfunction, and vascular inflammation (75-77).  Although limited, there are data that demonstrate similar findings in teens (77). The prevalence of smoking in children and young adults with T1D is estimated to be 3-28 %, with higher prevalence in those 15 years-of-age and older (2, 54, 78). In the TODAY study smoking incidence increased 6-fold over 14 year study with the average prevalence of 24% in youth 18 years and older (63). All youth should be encouraged to avoid/cease cigarette smoking, including electronic cigarettes.

 

KIDNEY DISEASE

 

The presence of target organ damage, particularly related to renal function, is a strong risk factor for CVD (1, 64). Persistent albumin excretion rate of 30 to 299 mg/24h and >300 mg/24hr are associated with CVD, and increased mortality with reduced glomerular filtration rates in individuals with T1D (79-81). Although the underlying mechanisms are incompletely understood, reduced glomerular filtration rate, independent of albuminuria, is also associated with increased risk of CVD (82, 83). Optimum control of modifiable risk factors, such as glucose, smoking, blood pressure, and dyslipidemia has been shown to reduce the incidence of both albuminuria and impaired renal function (28, 84-86).  Interested readers can find more information about kidney disease in diabetes at Endotext [Internet]: Diabetic Kidney Disease. 2022 Aug 3. PMID: 25905328 (87).

 

MASLD

 

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a risk factor for ASCVD. MASLD is commonly associated with other CV risk factors including visceral adiposity, atherogenic dyslipidemia (low HDL-C, elevated triglycerides/remnant lipoproteins, and small dense low-density lipoprotein [LDL]), and insulin resistance with or without hyperglycemia (88). Although a portion of the risk is attributable to these comorbidities, a diagnosis of MASLD is associated with greater risk than the sum of these individual components (88).

 

FAMILIAL HYPERCHOLESTEROLEMIA (FH)

 

Youth with diabetes may also experience other independent health conditions associated with increased risk of CVD (89). For example, FH is a genetic disorder which is highly prevalent (1:200) in the general population and may coexist with diabetes. Although outcome studies are not available for children, adults with both diabetes and phenotypic FH had higher risk of CV mortality (T1D: hazard ratio 21.3 [95% CI 14.6–31.0]; T2D: 2.40 [2.19–2.63]) and of a CV event (T1D: 15.1 [11.1–20.5]; T2D: 2.73 [2.58–2.89]) compared to those with T1D and no FH. Further, patients with diabetes and phenotypic FH had increased risk of all major cardiovascular outcomes (p < 0.0001). These findings were observed despite a greater proportion of diabetes and phenotypic FH receiving lipid-lowering treatment (p < 0.0001) (90).

 

Of note, an association between T2D prevalence and FH has been reported. A cross-sectional study of 63,320 individuals who underwent DNA testing for FH in the Netherlands found the prevalence of T2D among those found to have FH was significantly lower than among unaffected relatives, with variability by mutation type. This finding, if confirmed, raises the possibility of a causal relationship between LDL receptor-mediated transmembrane cholesterol transport and T2D (91).

 

OTHER DISORDERS

 

Other chronic conditions known to be associated with CVD include connective tissue disorders, thyroid abnormalities, and acquired conditions, such as HIV/AIDS. In addition to accelerating risk, the presence of other health conditions may present unique challenges, including financial, psychosocial, relational, and quality of life. Keeping up with personal, social, and work demands is often challenging for young adults with one or more chronic conditions in addition to diabetes. Growing up with a chronic disease showed a lower likelihood of having a paid job (92), higher unemployment and sick leave rates compared to the general population (93, 94), and fatigue. (95, 96). Figure 2 below outlines several health conditions commonly associated with increased risk of premature CVD. Children with these conditions should be monitored frequently and abnormal values optimally managed to improve outcomes.

 

Figure 2. Health Conditions Associated With Increased Risk of CVD (97). †Any moderate-risk condition with ≥2 additional risk enhancers. ‡Severe obesity is defined as BMI ≥99th percentile or ≥35 kg/m2, and obesity is defined as BMI ≥95th percentile to <99th percentile. §Defined as blood pressure >95th percentile or ≥130/80 mmHg on 3 separate occasions. ΔDefined as ≥3 risk enhancers. ‖ Involves obstructive lesions of the left ventricle and aorta, cyanotic congenital heart defects leading to Eisenmenger syndrome, and congenital coronary artery anomalies in isolation or in association with other congenital defects. ApoB, apolipoprotein B; BMI, body mass index; CKD, chronic kidney disease; CVD, cardiovascular disease; DM, diabetes mellitus; ESRD, end-stage renal disease; FH, familial hypercholesterolemia; HeFH, heterozygous familial hypercholesterolemia; HIV, human immunodeficiency virus; HoFH, homozygous familial hypercholesterolemia; Lp(a), lipoprotein (a); MI, myocardial infarction.

 

Social Determinants of Health

 

Social determinants of health (SDOH) play a major role in access to appropriate health care and clinical outcomes including CVD. These include food insecurity, housing instability, transportation barriers, low socioeconomic status, limited access to healthcare, early childhood adversity, and social isolation, all of which adversely influence the level and distribution of health within a society. Political systems and racism have been cited as upstream drivers of SDOH (98). Although recognized as obstacles, appropriate assessment and understanding of SDOH in youth with diabetes is limited, and strategies to improve health challenging. Lack of understanding of what interventions work, entrenched interests that benefit from health-harming aspects of the status quo, and the need to establish new mechanisms of finance for these programs have all made progress difficult (99).

 

In the U.S. T2D affects racial and ethnic minorities, including children, and low-income populations disproportionately, resulting in consistently higher risk of diabetes and rates of diabetes complications and premature mortality (100). Evidence supports an association of socioeconomic status (SES), neighborhood and physical environment, food environment, health care, and social context with diabetes-related outcomes. The living and working conditions and the environments in which children reside have a direct impact on biological and behavioral outcomes associated with diabetes prevention and control.

 

Food insecurity and adverse childhood experiences have been highlighted as important mediators of CVD in children (101, 102). For a comprehensive review, see https://www.fao.org/publications/home/fao-flagship-publications/the-state-of-food-security-and-nutrition-in-the-world/2022/en. Although food insecurity has been associated with the development of childhood obesity and cardiometabolic disease in adults, this relationship is inconsistent in youth (103, 104). While some studies have detected relationships, the National Human and Nutrition Examination Survey 2007-2012 (NHANES) in adolescents at or below 300% of the poverty line did not find a relationship between food insecurity and childhood CVD risk factors (105). Further analysis of these findings suggests that socio-ecological factors such as household income and parental education as well as individual level of physical activity, sedentary time, and smoking status may be interdependent mediators of CVD risk in youth. Youth and young adults with T1D and T2D report nearly twice the prevalence of food insecurity; predictors of household food insecurity include youth without insurance or receiving Medicaid or Medicare, level of parental education, and lower household income (106).

 

Adverse childhood experiences (ACEs) are also closely associated with poor cardiovascular outcomes with or without underlying food insecurity (107) resulting from 1) unhealthy behaviors such as physical inactivity, poor-quality diet, poor quality and duration of sleep, and smoking; 2) adverse physiologic mechanisms including inflammation and hypercortisolemia; 3) substance abuse and mental health disorders and mental health conditions such as depression and anxiety.

 

Current recommendations for the care of children with diabetes include assessing psychosocial concerns (e.g., diabetes distress, depressive symptoms, and disordered eating), family factors, and behavioral health concerns that could impact diabetes management. Health care professionals should also screen for food security, housing stability/homelessness, health literacy, financial barriers, and social/community support and incorporate that information in treatment decisions. Social workers and behavioral health professionals should be considered integral members of the pediatric diabetes interprofessional team to aid in screening, assessment and interventions (108).

 

PRINCIPLE OF RISK FACTOR SCREENING AND MANAGEMENT

 

Guidance for screening and management of youth with diabetes has been published by a number of professional organizations (40, 41). Cardiovascular risk in diabetes arises from microvascular and macrovascular pathology, as well as changes in cardiac structure and function. Therefore, the objectives of efforts to reduce CV risk are to maintain glycemic control, which is a key driver of microvascular complications and a contributor to macrovascular complications, as well as optimally managing cardiometabolic risk factors to reduce the risks for ASCVD and heart failure (26).

 

Challenges to Cardiovascular Risk Reduction in Youth with Diabetes

 

SCREENING

 

Despite evidence in youth with T1D and T2D demonstrating an increased prevalence of modifiable risk factors, and risk factors present at an early age predict premature CVD during adulthood, screening rates are less than ideal based on the limited available data. A study in the United Kingdom found 83.5% compliance with lipid screening in patients with T1D (109), while in children with T2D only half had lipid testing (68). In a survey of 1,514 US clinicians, blood pressure was stated to be measured at most or all visits in 95% and lipid screening in 88% of patients (although less frequently in older patients with T2D (69%) (110). When adherence to the International Society of Pediatric and Adolescent Diabetes (ISPAD) clinical practice guidelines was assessed for patients with T1D, two-thirds of physicians reported adherence to nephropathy and retinopathy screening and only half reported adherence to recommendations for neuropathy and macrovascular disease risk factors. Patient financial issues, the lack of laboratory resources and/or other equipment, and the need for referral were cited as the main reasons for variation in screening practices (111).

 

TREATMENT

 

Treatment with lipid lowering and blood pressure medications are low in pediatric patients with diabetes. When the SEARCH for Diabetes in Youth study examined their data in 2007, only 1% of T1D youth and 5% of T2D youth were on lipid lowering medications despite lipid abnormalities present in ~30-60% of youth (112). In 2020 the T1D Exchange Clinic Network (TIDX, US) and the Prospective Diabetes Follow-up Registry (DPV, Austria and Germany) examined medication use in young adults <26 years of age. Anti-hypertensive medication use was reported as 5% in T1DX and 3% in DPV and lipid lowering medication was 3% in the T1DX and 1% in DPV in those with T1D(113).  Slightly higher medication use, but still low rates, were reported in the TODAY study cohort.  Approximately half of the youth with hypertension were on blood pressure lowering medication and one third of those with a high LDL-C were on lipid lowering medication (63).

 

ACHIEVING TARGETS

 

Data were evaluated for 13,316 participants in the T1D Exchange clinic registry (<20 years old) to see how many youth and young adults with T1D met lipid, blood pressure, and BMI targets. Among participants with available data, 86% met HDL-C target of >40mg/dL, 65% had an LDL-C <100mg/dL, and 90% had triglycerides <150mg/dL. For blood pressure 78% had readings < 90th percentile for age, sex and height and 63% had a BMI of <85th percentile by CDC charts. Moreover, 17% of patients <18 years of age (in the 2016–2018 study) (114) and only 22% of children 6-12 years of age and 17% of children 13-17 years of age (in the 2010–2012 study) met the prior ADA A1C target of <7.5% (115). At the end of the TODAY study 73.2% of youth with T2D met optimal targets for blood pressure and 56.1% met optimal targets for LDL-C (63). Achieving targets in youth with T1D has been shown to be associated with greater insulin sensitivity, improved cardiopulmonary fitness (116), and cardiorenal protection at 2-year follow-up (117).

 

GUIDELINES AND RECOMMENDATIONS

 

Inconsistencies in pediatric versus adult guidelines for risk factor screening and management in individuals with diabetes creates challenges when children transition into adult health care. Complex treatment algorithms to determine the timing and frequency of risk factor assessment also appear to complicate screening of CV risk factors. Multiple guidelines for the identification and management CVD risk factors in youth with diabetes have been published (43, 118-122) with the goal of achieving CVD risk reduction. While some guidelines are applicable to all children, others specifically address risk assessment and management in those with diabetes. The latter contains unique recommendations based upon the type of diabetes, necessitating an accurate classification (i.e. T1D vs T2D). While highly desirable, differentiation between the diagnosis of T1D and T2D in youth can be challenging and not always performed/feasible in clinical practice. Although all published guidelines identify glycemic control, hypertension, and dyslipidemia as targets for CVD risk reduction, differences exist in optimum goals and approaches to risk factor reduction as outlined in Table 1.

 

Additional research is needed to understand the role of CVD risk factors in diabetes and identify barriers to screening and treatment in clinical practice. While the advantages of early CV risk reduction appear clear, there is also potential hesitancy due to unanswered questions. Ideally, professional societies and organizations would work together to provide viable solutions to several urgent clinical questions, Table 2.

 

Table 2. Key Clinical Questions Regarding CV Risk Management and Treatment in Youth 

Screening

·       What is the ideal age to begin screening?

·       Which CV risk factors should be measured and how often?

·       If low risk (or values are normal), how often should risk factors measurements be repeated?

Management

·       What BMI/waist circumference is ideal to aid in CV risk reduction?

·       How do we define optimal therapeutic goals?

·       What is the impact of MASLD and other diabetes related co-morbidities and complications?

·       Should risk factor screening and management be the same for T1D and T2D?

·       Should risk factor screening differ in children vs adults? What if there is concomitant FH?

Treatment

·       Is lowering hemoglobin A1c, blood pressure and lipids enough to reduce CV risk and disease?

·       What thresholds suggest the need for pharmacotherapy? Dose escalation? Dose reduction?

·       Should certain risk factors be more aggressively targeted to reduce future CV risk and CVD?

Outcomes

·       What are the barriers for risk factor screening and treatment?

·       Would utilization of implementation science help increase screening rates?

·       Can artificial intelligence analyze big data to determine what diabetes therapies achieve the best CV reduction?

 

CONCLUSION

 

Individuals with diabetes have a 2-fold increase in CVD and premature mortality. Duration of diabetes is a predictor of premature mortality, placing youth at significant risk. Glycemic control alone appears to be insufficient to substantially reduce macrovascular complications, such as fatal and non-fatal MI and stroke. Global risk factor assessment and early intervention play a key role in reducing CVD-related risk and improving outcomes. While helpful, current recommendations for risk factor assessment and optimum management in youth are often inconsistent amongst published guidelines and the need for complex algorithms to determine the timing and frequency of risk factor assessment challenging. Additional research is needed to understand the role of CVD risk factors in youth-onset diabetes and identify barriers to screening and optimum management in clinical practice.

 

 REFERENCES

 

  1. de Ferranti SD, de Boer IH, Fonseca V, Fox CS, Golden SH, Lavie CJ, et al. Type 1 diabetes mellitus and cardiovascular disease: a scientific statement from the American Heart Association and American Diabetes Association. Diabetes Care. 2014;37(10):2843-63.
  2. Shah AS, Wadwa RP, Dabelea D, Hamman RF, D'Agostino R, Jr., Marcovina S, et al. Arterial stiffness in adolescents and young adults with and without type 1 diabetes: the SEARCH CVD study. Pediatr Diabetes. 2015;16(5):367-74.
  3. Alman AC, Talton JW, Wadwa RP, Urbina EM, Dolan LM, Daniels SR, et al. Cardiovascular health in adolescents with type 1 diabetes: the SEARCH CVD study. Pediatr Diabetes. 2014;15(7):502-10.
  4. Htay T, Soe K, Lopez-Perez A, Doan AH, Romagosa MA, Aung K. Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes. Curr Cardiol Rep. 2019;21(6):45.
  5. Krishnan P, Balamurugan A, Urbina E, Srinivasan SR, Bond G, Tang R, et al. Cardiovascular risk profile of asymptomatic healthy young adults with increased carotid artery intima-media thickness: the Bogalusa Heart Study. J La State Med Soc. 2003;155(3):165-9.
  6. Rawshani A, Rawshani A, Franzén S, Eliasson B, Svensson AM, Miftaraj M, et al. Mortality and Cardiovascular Disease in Type 1 and Type 2 Diabetes. N Engl J Med. 2017;376(15):1407-18.
  7. Hannon TS, Arslanian SA. The changing face of diabetes in youth: lessons learned from studies of type 2 diabetes. Ann N Y Acad Sci. 2015;1353:113-37.
  8. Kim JY, Bacha F, Tfayli H, Michaliszyn SF, Yousuf S, Arslanian S. Adipose Tissue Insulin Resistance in Youth on the Spectrum From Normal Weight to Obese and From Normal Glucose Tolerance to Impaired Glucose Tolerance to Type 2 Diabetes. Diabetes Care. 2019;42(2):265-72.
  9. Kim JY, Nasr A, Tfayli H, Bacha F, Michaliszyn SF, Arslanian S. Increased Lipolysis, Diminished Adipose Tissue Insulin Sensitivity, and Impaired β-Cell Function Relative to Adipose Tissue Insulin Sensitivity in Obese Youth With Impaired Glucose Tolerance. Diabetes. 2017;66(12):3085-90.
  10. Michaliszyn SF, Mari A, Lee S, Bacha F, Tfayli H, Farchoukh L, et al. β-cell function, incretin effect, and incretin hormones in obese youth along the span of glucose tolerance from normal to prediabetes to type 2 diabetes. Diabetes. 2014;63(11):3846-55.
  11. Metabolic Contrasts Between Youth and Adults With Impaired Glucose Tolerance or Recently Diagnosed Type 2 Diabetes: II. Observations Using the Oral Glucose Tolerance Test. Diabetes Care. 2018;41(8):1707-16.
  12. Metabolic Contrasts Between Youth and Adults With Impaired Glucose Tolerance or Recently Diagnosed Type 2 Diabetes: I. Observations Using the Hyperglycemic Clamp. Diabetes Care. 2018;41(8):1696-706.
  13. Effects of Treatment of Impaired Glucose Tolerance or Recently Diagnosed Type 2 Diabetes With Metformin Alone or in Combination With Insulin Glargine on β-Cell Function: Comparison of Responses In Youth And Adults. Diabetes. 2019;68(8):1670-80.
  14. Hannon TS, Edelstein SL, Arslanian SA, Caprio S, Zeitler PS, Buchanan TA, et al. Withdrawal of medications leads to worsening of OGTT parameters in youth with impaired glucose tolerance or recently-diagnosed type 2 diabetes. Pediatr Diabetes. 2020;21(8):1437-46.
  15. Shankar RR, Zeitler P, Deeb A, Jalaludin MY, Garcia R, Newfield RS, et al. A randomized clinical trial of the efficacy and safety of sitagliptin as initial oral therapy in youth with type 2 diabetes. Pediatr Diabetes. 2022;23(2):173-82.
  16. Tamborlane WV, Barrientos-Pérez M, Fainberg U, Frimer-Larsen H, Hafez M, Hale PM, et al. Liraglutide in Children and Adolescents with Type 2 Diabetes. N Engl J Med. 2019;381(7):637-46.
  17. Zeitler P, Hirst K, Pyle L, Linder B, Copeland K, Arslanian S, et al. A clinical trial to maintain glycemic control in youth with type 2 diabetes. N Engl J Med. 2012;366(24):2247-56.
  18. Yau M, Maclaren NK, Sperling MA. Etiology and Pathogenesis of Diabetes Mellitus in Children and Adolescents. In: Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, et al., editors. Endotext. South Dartmouth (MA): MDText.com, Inc. Copyright © 2000-2024, MDText.com, Inc.; 2000.
  19. Feingold KR. Atypical Forms of Diabetes. In: Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, et al., editors. Endotext. South Dartmouth (MA): MDText.com, Inc. Copyright © 2000-2024, MDText.com, Inc.; 2000.
  20. Lawrence JM, Divers J, Isom S, Saydah S, Imperatore G, Pihoker C, et al. Trends in Prevalence of Type 1 and Type 2 Diabetes in Children and Adolescents in the US, 2001-2017. Jama. 2021;326(8):717-27.
  21. Mayer-Davis EJ, Lawrence JM, Dabelea D, Divers J, Isom S, Dolan L, et al. Incidence Trends of Type 1 and Type 2 Diabetes among Youths, 2002-2012. N Engl J Med. 2017;376(15):1419-29.
  22. Donaghue K, Jeanne Wong SL. Traditional Cardiovascular Risk Factors in Adolescents with Type 1 Diabetes Mellitus. Curr Diabetes Rev. 2017;13(6):533-43.
  23. Kim G, Divers J, Fino NF, Dabelea D, Lawrence JM, Reynolds K, et al. Trends in prevalence of cardiovascular risk factors from 2002 to 2012 among youth early in the course of type 1 and type 2 diabetes. The SEARCH for Diabetes in Youth Study. Pediatr Diabetes. 2019;20(6):693-701.
  24. Bjornstad P, Drews KL, Caprio S, Gubitosi-Klug R, Nathan DM, Tesfaldet B, et al. Long-Term Complications in Youth-Onset Type 2 Diabetes. N Engl J Med. 2021;385(5):416-26.
  25. Dabelea D, Stafford JM, Mayer-Davis EJ, D'Agostino R, Jr., Dolan L, Imperatore G, et al. Association of Type 1 Diabetes vs Type 2 Diabetes Diagnosed During Childhood and Adolescence With Complications During Teenage Years and Young Adulthood. Jama. 2017;317(8):825-35.
  26. ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D, et al. 14. Children and Adolescents: Standards of Care in Diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S230-s53.
  27. Maahs DM, Daniels SR, de Ferranti SD, Dichek HL, Flynn J, Goldstein BI, et al. Cardiovascular disease risk factors in youth with diabetes mellitus: a scientific statement from the American Heart Association. Circulation. 2014;130(17):1532-58.
  28. Reichard P, Nilsson BY, Rosenqvist U. The effect of long-term intensified insulin treatment on the development of microvascular complications of diabetes mellitus. N Engl J Med. 1993;329(5):304-9.
  29. Skyler JS, Bergenstal R, Bonow RO, Buse J, Deedwania P, Gale EA, et al. Intensive glycemic control and the prevention of cardiovascular events: implications of the ACCORD, ADVANCE, and VA diabetes trials: a position statement of the American Diabetes Association and a scientific statement of the American College of Cardiology Foundation and the American Heart Association. Diabetes Care. 2009;32(1):187-92.
  30. Haffner SM, Stern MP, Hazuda HP, Mitchell BD, Patterson JK. Cardiovascular risk factors in confirmed prediabetic individuals. Does the clock for coronary heart disease start ticking before the onset of clinical diabetes? Jama. 1990;263(21):2893-8.
  31. Viigimaa M, Sachinidis A, Toumpourleka M, Koutsampasopoulos K, Alliksoo S, Titma T. Macrovascular Complications of Type 2 Diabetes Mellitus. Curr Vasc Pharmacol. 2020;18(2):110-6.
  32. Faselis C, Katsimardou A, Imprialos K, Deligkaris P, Kallistratos M, Dimitriadis K. Microvascular Complications of Type 2 Diabetes Mellitus. Curr Vasc Pharmacol. 2020;18(2):117-24.
  33. Weinstock RS, Trief PM, Burke BK, Wen H, Liu X, Kalichman S, et al. Antihypertensive and Lipid-Lowering Medication Adherence in Young Adults With Youth-Onset Type 2 Diabetes. JAMA Netw Open. 2023;6(10):e2336964.
  34. Ali MK, Bullard KM, Gregg EW. Achievement of goals in U.S. Diabetes Care, 1999-2010. N Engl J Med. 2013;369(3):287-8.
  35. Buse JB, Ginsberg HN, Bakris GL, Clark NG, Costa F, Eckel R, et al. Primary prevention of cardiovascular diseases in people with diabetes mellitus: a scientific statement from the American Heart Association and the American Diabetes Association. Diabetes Care. 2007;30(1):162-72.
  36. Gaede P, Lund-Andersen H, Parving HH, Pedersen O. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med. 2008;358(6):580-91.
  37. Nordestgaard BG, Chapman MJ, Humphries SE, Ginsberg HN, Masana L, Descamps OS, et al. Familial hypercholesterolaemia is underdiagnosed and undertreated in the general population: guidance for clinicians to prevent coronary heart disease: consensus statement of the European Atherosclerosis Society. Eur Heart J. 2013;34(45):3478-90a.
  38. Reyes-Soffer G, Ginsberg HN, Berglund L, Duell PB, Heffron SP, Kamstrup PR, et al. Lipoprotein(a): A Genetically Determined, Causal, and Prevalent Risk Factor for Atherosclerotic Cardiovascular Disease: A Scientific Statement From the American Heart Association. Arterioscler Thromb Vasc Biol. 2022;42(1):e48-e60.
  39. Peterson AL, McNeal CJ, Wilson DP. Prevention of Atherosclerotic Cardiovascular Disease in Children with Familial Hypercholesterolemia. Curr Atheroscler Rep. 2021;23(10):64.
  40. Shah AS, Zeitler PS, Wong J, Pena AS, Wicklow B, Arslanian S, et al. ISPAD Clinical Practice Consensus Guidelines 2022: Type 2 diabetes in children and adolescents. Pediatr Diabetes. 2022;23(7):872-902.
  41. 14. Children and Adolescents: Standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S258-s81.
  42. Nathan DM, Genuth S, Lachin J, Cleary P, Crofford O, Davis M, et al. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977-86.
  43. Management of dyslipidemia in children and adolescents with diabetes. Diabetes Care. 2003;26(7):2194-7.
  44. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UK Prospective Diabetes Study (UKPDS) Group. Lancet. 1998;352(9131):837-53.
  45. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med. 2008;359(15):1577-89.
  46. Aepfelbacher FC, Yeon SB, Weinrauch LA, D'Elia J, Burger AJ. Improved glycemic control induces regression of left ventricular mass in patients with type 1 diabetes mellitus. Int J Cardiol. 2004;94(1):47-51.
  47. Dabelea D, Talton JW, D'Agostino R, Jr., Wadwa RP, Urbina EM, Dolan LM, et al. Cardiovascular risk factors are associated with increased arterial stiffness in youth with type 1 diabetes: the SEARCH CVD study. Diabetes Care. 2013;36(12):3938-43.
  48. Shah AS, Dolan LM, Kimball TR, Gao Z, Khoury PR, Daniels SR, et al. Influence of duration of diabetes, glycemic control, and traditional cardiovascular risk factors on early atherosclerotic vascular changes in adolescents and young adults with type 2 diabetes mellitus. J Clin Endocrinol Metab. 2009;94(10):3740-5.
  49. Shah AS, El Ghormli L, Gidding SS, Bacha F, Nadeau KJ, Levitt Katz LE, et al. Prevalence of arterial stiffness in adolescents with type 2 diabetes in the TODAY cohort: Relationships to glycemic control and other risk factors. J Diabetes Complications. 2018;32(8):740-5.
  50. Shah AS, El Ghormli L, Vajravelu ME, Bacha F, Farrell RM, Gidding SS, et al. Heart Rate Variability and Cardiac Autonomic Dysfunction: Prevalence, Risk Factors, and Relationship to Arterial Stiffness in the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) Study. Diabetes Care. 2019;42(11):2143-50.
  51. Urbina EM, Dabelea D, D'Agostino RB, Jr., Shah AS, Dolan LM, Hamman RF, et al. Effect of type 1 diabetes on carotid structure and function in adolescents and young adults: the SEARCH CVD study. Diabetes Care. 2013;36(9):2597-9.
  52. Lind M, Svensson AM, Kosiborod M, Gudbjörnsdottir S, Pivodic A, Wedel H, et al. Glycemic control and excess mortality in type 1 diabetes. N Engl J Med. 2014;371(21):1972-82.
  53. Orchard TJ, Nathan DM, Zinman B, Cleary P, Brillon D, Backlund JY, et al. Association between 7 years of intensive treatment of type 1 diabetes and long-term mortality. Jama. 2015;313(1):45-53.
  54. Margeirsdottir HD, Larsen JR, Brunborg C, Overby NC, Dahl-Jørgensen K. High prevalence of cardiovascular risk factors in children and adolescents with type 1 diabetes: a population-based study. Diabetologia. 2008;51(4):554-61.
  55. Schwab KO, Doerfer J, Marg W, Schober E, Holl RW. Characterization of 33 488 children and adolescents with type 1 diabetes based on the gender-specific increase of cardiovascular risk factors. Pediatr Diabetes. 2010;11(5):357-63.
  56. Hamman RF, Bell RA, Dabelea D, D'Agostino RB, Jr., Dolan L, Imperatore G, et al. The SEARCH for Diabetes in Youth study: rationale, findings, and future directions. Diabetes Care. 2014;37(12):3336-44.
  57. Maahs DM, Wadwa RP, McFann K, Nadeau K, Williams MR, Eckel RH, et al. Longitudinal lipid screening and use of lipid-lowering medications in pediatric type 1 diabetes. J Pediatr. 2007;150(2):146-50, 50.e1-2.
  58. Pelham JH, Hanks L, Aslibekyan S, Dowla S, Ashraf AP. Higher hemoglobin A1C and atherogenic lipoprotein profiles in children and adolescents with type 2 diabetes mellitus. J Clin Transl Endocrinol. 2019;15:30-4.
  59. Urbina EM, Kimball TR, McCoy CE, Khoury PR, Daniels SR, Dolan LM. Youth with obesity and obesity-related type 2 diabetes mellitus demonstrate abnormalities in carotid structure and function. Circulation. 2009;119(22):2913-9.
  60. Marcovecchio ML, Chiesa ST, Bond S, Daneman D, Dawson S, Donaghue KC, et al. ACE Inhibitors and Statins in Adolescents with Type 1 Diabetes. N Engl J Med. 2017;377(18):1733-45.
  61. Knerr I, Dost A, Lepler R, Raile K, Schober E, Rascher W, et al. Tracking and prediction of arterial blood pressure from childhood to young adulthood in 868 patients with type 1 diabetes: a multicenter longitudinal survey in Germany and Austria. Diabetes Care. 2008;31(4):726-7.
  62. Rodriguez BL, Dabelea D, Liese AD, Fujimoto W, Waitzfelder B, Liu L, et al. Prevalence and correlates of elevated blood pressure in youth with diabetes mellitus: the SEARCH for diabetes in youth study. J Pediatr. 2010;157(2):245-51.e1.
  63. Shah RD, Braffett BH, Tryggestad JB, Hughan KS, Dhaliwal R, Nadeau KJ, et al. Cardiovascular risk factor progression in adolescents and young adults with youth-onset type 2 diabetes. J Diabetes Complications. 2022;36(3):108123.
  64. Donaghue KC, Wadwa RP, Dimeglio LA, Wong TY, Chiarelli F, Marcovecchio ML, et al. ISPAD Clinical Practice Consensus Guidelines 2014. Microvascular and macrovascular complications in children and adolescents. Pediatr Diabetes. 2014;15 Suppl 20:257-69.
  65. Canas JA, Ross JL, Taboada MV, Sikes KM, Damaso LC, Hossain J, et al. A randomized, double blind, placebo-controlled pilot trial of the safety and efficacy of atorvastatin in children with elevated low-density lipoprotein cholesterol (LDL-C) and type 1 diabetes. Pediatr Diabetes. 2015;16(2):79-89.
  66. Downie E, Craig ME, Hing S, Cusumano J, Chan AK, Donaghue KC. Continued reduction in the prevalence of retinopathy in adolescents with type 1 diabetes: role of insulin therapy and glycemic control. Diabetes Care. 2011;34(11):2368-73.
  67. Liu LL, Lawrence JM, Davis C, Liese AD, Pettitt DJ, Pihoker C, et al. Prevalence of overweight and obesity in youth with diabetes in USA: the SEARCH for Diabetes in Youth study. Pediatr Diabetes. 2010;11(1):4-11.
  68. Valent D, Pestak K, Otis M, Shubrook J. Type 2 diabetes in the pediatric population: Are we meeting ADA clinical guidelines in Ohio? Clin Pediatr (Phila). 2010;49(4):316-22.
  69. Conway B, Miller RG, Costacou T, Fried L, Kelsey S, Evans RW, et al. Adiposity and mortality in type 1 diabetes. Int J Obes (Lond). 2009;33(7):796-805.
  70. Savva SC, Tornaritis M, Savva ME, Kourides Y, Panagi A, Silikiotou N, et al. Waist circumference and waist-to-height ratio are better predictors of cardiovascular disease risk factors in children than body mass index. Int J Obes Relat Metab Disord. 2000;24(11):1453-8.
  71. Dalla Pozza R, Beyerlein A, Thilmany C, Weissenbacher C, Netz H, Schmidt H, et al. The effect of cardiovascular risk factors on the longitudinal evolution of the carotid intima medial thickness in children with type 1 diabetes mellitus. Cardiovasc Diabetol. 2011;10:53.
  72. Bohn B, Herbst A, Pfeifer M, Krakow D, Zimny S, Kopp F, et al. Impact of Physical Activity on Glycemic Control and Prevalence of Cardiovascular Risk Factors in Adults With Type 1 Diabetes: A Cross-sectional Multicenter Study of 18,028 Patients. Diabetes Care. 2015;38(8):1536-43.
  73. Quirk H, Blake H, Tennyson R, Randell TL, Glazebrook C. Physical activity interventions in children and young people with Type 1 diabetes mellitus: a systematic review with meta-analysis. Diabet Med. 2014;31(10):1163-73.
  74. MacMillan F, Kirk A, Mutrie N, Matthews L, Robertson K, Saunders DH. A systematic review of physical activity and sedentary behavior intervention studies in youth with type 1 diabetes: study characteristics, intervention design, and efficacy. Pediatr Diabetes. 2014;15(3):175-89.
  75. Eliasson B. Cigarette smoking and diabetes. Prog Cardiovasc Dis. 2003;45(5):405-13.
  76. Houston TK, Person SD, Pletcher MJ, Liu K, Iribarren C, Kiefe CI. Active and passive smoking and development of glucose intolerance among young adults in a prospective cohort: CARDIA study. Bmj. 2006;332(7549):1064-9.
  77. Schwab KO, Doerfer J, Hallermann K, Krebs A, Schorb E, Krebs K, et al. Marked smoking-associated increase of cardiovascular risk in childhood type 1 diabetes. Int J Adolesc Med Health. 2008;20(3):285-92.
  78. Herbst A, Kordonouri O, Schwab KO, Schmidt F, Holl RW. Impact of physical activity on cardiovascular risk factors in children with type 1 diabetes: a multicenter study of 23,251 patients. Diabetes Care. 2007;30(8):2098-100.
  79. Kim WY, Astrup AS, Stuber M, Tarnow L, Falk E, Botnar RM, et al. Subclinical coronary and aortic atherosclerosis detected by magnetic resonance imaging in type 1 diabetes with and without diabetic nephropathy. Circulation. 2007;115(2):228-35.
  80. Soedamah-Muthu SS, Chaturvedi N, Witte DR, Stevens LK, Porta M, Fuller JH. Relationship between risk factors and mortality in type 1 diabetic patients in Europe: the EURODIAB Prospective Complications Study (PCS). Diabetes Care. 2008;31(7):1360-6.
  81. Torffvit O, Lövestam-Adrian M, Agardh E, Agardh CD. Nephropathy, but not retinopathy, is associated with the development of heart disease in Type 1 diabetes: a 12-year observation study of 462 patients. Diabet Med. 2005;22(6):723-9.
  82. de Boer IH, Katz R, Cao JJ, Fried LF, Kestenbaum B, Mukamal K, et al. Cystatin C, albuminuria, and mortality among older adults with diabetes. Diabetes Care. 2009;32(10):1833-8.
  83. Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, de Jong PE, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010;375(9731):2073-81.
  84. de Boer IH, Sun W, Cleary PA, Lachin JM, Molitch ME, Steffes MW, et al. Intensive diabetes therapy and glomerular filtration rate in type 1 diabetes. N Engl J Med. 2011;365(25):2366-76.
  85. Lemley KV. When to initiate ACEI/ARB therapy in patients with type 1 and 2 diabetes. Pediatr Nephrol. 2010;25(10):2021-34.
  86. Lopes-Virella MF, Carter RE, Gilbert GE, Klein RL, Jaffa M, Jenkins AJ, et al. Risk factors related to inflammation and endothelial dysfunction in the DCCT/EDIC cohort and their relationship with nephropathy and macrovascular complications. Diabetes Care. 2008;31(10):2006-12.
  87. Caramori ML, Rossing P. Diabetic Kidney Disease. In: Feingold KR, Anawalt B, Blackman MR, Boyce A, Chrousos G, Corpas E, et al., editors. Endotext. South Dartmouth (MA): MDText.com, Inc. Copyright © 2000-2024, MDText.com, Inc.; 2000.
  88. Duell PB, Welty FK, Miller M, Chait A, Hammond G, Ahmad Z, et al. Nonalcoholic Fatty Liver Disease and Cardiovascular Risk: A Scientific Statement From the American Heart Association. Arterioscler Thromb Vasc Biol. 2022;42(6):e168-e85.
  89. Bronner MB, Peeters MAC, Sattoe JNT, van Staa A. The impact of type 1 diabetes on young adults' health-related quality of life. Health Qual Life Outcomes. 2020;18(1):137.
  90. Brinck J, Hagström E, Nåtman J, Franzén S, Eeg-Olofsson K, Nathanson D, et al. Cardiovascular Outcomes in Patients With Both Diabetes and Phenotypic Familial Hypercholesterolemia: A Nationwide Register-Based Cohort Study. Diabetes Care. 2022;45(12):3040-9.
  91. Besseling J, Kastelein JJ, Defesche JC, Hutten BA, Hovingh GK. Association between familial hypercholesterolemia and prevalence of type 2 diabetes mellitus. Jama. 2015;313(10):1029-36.
  92. Maurice-Stam H, Nijhof SL, Monninkhof AS, Heymans HSA, Grootenhuis MA. Review about the impact of growing up with a chronic disease showed delays achieving psychosocial milestones. Acta Paediatr. 2019;108(12):2157-69.
  93. Monaghan M, Helgeson V, Wiebe D. Type 1 diabetes in young adulthood. Curr Diabetes Rev. 2015;11(4):239-50.
  94. Nielsen HB, Ovesen LL, Mortensen LH, Lau CJ, Joensen LE. Type 1 diabetes, quality of life, occupational status and education level - A comparative population-based study. Diabetes Res Clin Pract. 2016;121:62-8.
  95. Menting J, Tack CJ, Donders R, Knoop H. Potential mechanisms involved in the effect of cognitive behavioral therapy on fatigue severity in Type 1 diabetes. J Consult Clin Psychol. 2018;86(4):330-40.
  96. Menting J, Tack CJ, van Bon AC, Jansen HJ, van den Bergh JP, Mol M, et al. Web-based cognitive behavioural therapy blended with face-to-face sessions for chronic fatigue in type 1 diabetes: a multicentre randomised controlled trial. Lancet Diabetes Endocrinol. 2017;5(6):448-56.
  97. Ashraf AP, Sunil B, Bamba V, Breidbart E, Brar PC, Chung S, et al. Case Studies in Pediatric Lipid Disorders and Their Management. J Clin Endocrinol Metab. 2021;106(12):3605-20.
  98. Hill-Briggs F, Fitzpatrick SL. Overview of Social Determinants of Health in the Development of Diabetes. Diabetes Care. 2023;46(9):1590-8.
  99. Hill-Briggs F, Adler NE, Berkowitz SA, Chin MH, Gary-Webb TL, Navas-Acien A, et al. Social Determinants of Health and Diabetes: A Scientific Review. Diabetes Care. 2020;44(1):258-79.
  100. Golden SH, Brown A, Cauley JA, Chin MH, Gary-Webb TL, Kim C, et al. Health disparities in endocrine disorders: biological, clinical, and nonclinical factors--an Endocrine Society scientific statement. J Clin Endocrinol Metab. 2012;97(9):E1579-639.
  101. Suglia SF, Koenen KC, Boynton-Jarrett R, Chan PS, Clark CJ, Danese A, et al. Childhood and Adolescent Adversity and Cardiometabolic Outcomes: A Scientific Statement From the American Heart Association. Circulation. 2018;137(5):e15-e28.
  102. Te Vazquez J, Feng SN, Orr CJ, Berkowitz SA. Food Insecurity and Cardiometabolic Conditions: a Review of Recent Research. Curr Nutr Rep. 2021;10(4):243-54.
  103. Clemens KK, Le B, Anderson KK, Shariff SZ. Childhood food insecurity and incident diabetes: A longitudinal cohort study of 34 042 children in Ontario, Canada. Diabet Med. 2021;38(5):e14396.
  104. Lee AM, Scharf RJ, Filipp SL, Gurka MJ, DeBoer MD. Food Insecurity Is Associated with Prediabetes Risk Among U.S. Adolescents, NHANES 2003-2014. Metab Syndr Relat Disord. 2019;17(7):347-54.
  105. Fulay AP, Vercammen KA, Moran AJ, Rimm EB, Leung CW. Household and child food insecurity and CVD risk factors in lower-income adolescents aged 12-17 years from the National Health and Nutrition Examination Survey (NHANES) 2007-2016. Public Health Nutr. 2022;25(4):922-9.
  106. Malik FS, Liese AD, Reboussin BA, Sauder KA, Frongillo EA, Lawrence JM, et al. Prevalence and Predictors of Household Food Insecurity and Supplemental Nutrition Assistance Program Use in Youth and Young Adults With Diabetes: The SEARCH for Diabetes in Youth Study. Diabetes Care. 2023;46(2):278-85.
  107. Suglia SF, Campo RA, Brown AGM, Stoney C, Boyce CA, Appleton AA, et al. Social Determinants of Cardiovascular Health: Early Life Adversity as a Contributor to Disparities in Cardiovascular Diseases. J Pediatr. 2020;219:267-73.
  108. 4. Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Care in Diabetes-2024. Diabetes Care. 2024;47(Suppl 1):S52-s76.
  109. Hussain T, Bagnall A, Agwu JC. NICE guidelines for hyperlipidaemia in children and young people with type I diabetes: time for a rethink? Arch Dis Child. 2006;91(6):545.
  110. Waitzfelder B, Pihoker C, Klingensmith G, Case D, Anderson A, Bell RA, et al. Adherence to guidelines for youths with diabetes mellitus. Pediatrics. 2011;128(3):531-8.
  111. Piona C, Chobot A, Dos Santos TJ, Giani E, Marcovecchio ML, Maffeis C, et al. Vascular complications in children and young people with type 1 diabetes: a worldwide assessment of diabetologists' adherence to international recommendations. Horm Res Paediatr. 2024.
  112. Petitti DB, Imperatore G, Palla SL, Daniels SR, Dolan LM, Kershnar AK, et al. Serum lipids and glucose control: the SEARCH for Diabetes in Youth study. Arch Pediatr Adolesc Med. 2007;161(2):159-65.
  113. Shah VN, Grimsmann JM, Foster NC, Dost A, Miller KM, Pavel M, et al. Undertreatment of cardiovascular risk factors in the type 1 diabetes exchange clinic network (United States) and the prospective diabetes follow-up (Germany/Austria) registries. Diabetes Obes Metab. 2020;22(9):1577-85.
  114. Foster NC, Beck RW, Miller KM, Clements MA, Rickels MR, DiMeglio LA, et al. State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016-2018. Diabetes Technol Ther. 2019;21(2):66-72.
  115. Miller KM, Foster NC, Beck RW, Bergenstal RM, DuBose SN, DiMeglio LA, et al. Current state of type 1 diabetes treatment in the U.S.: updated data from the T1D Exchange clinic registry. Diabetes Care. 2015;38(6):971-8.
  116. Bjornstad P, Cree-Green M, Baumgartner A, Coe G, Reyes YG, Schäfer M, et al. Achieving ADA/ISPAD clinical guideline goals is associated with higher insulin sensitivity and cardiopulmonary fitness in adolescents with type 1 diabetes: Results from RESistance to InSulin in Type 1 ANd Type 2 diabetes (RESISTANT) and Effects of MEtformin on CardiovasculaR Function in AdoLescents with Type 1 Diabetes (EMERALD) Studies. Pediatr Diabetes. 2018;19(3):436-42.
  117. Bjornstad P, Pyle L, Nguyen N, Snell-Bergeon JK, Bishop FK, Wadwa RP, et al. Achieving International Society for Pediatric and Adolescent Diabetes and American Diabetes Association clinical guidelines offers cardiorenal protection for youth with type 1 diabetes. Pediatr Diabetes. 2015;16(1):22-30.
  118. Expert panel on integrated guidelines for cardiovascular health and risk reduction in children and adolescents: summary report. Pediatrics. 2011;128 Suppl 5(Suppl 5):S213-56.
  119. Daniels SR, Greer FR. Lipid screening and cardiovascular health in childhood. Pediatrics. 2008;122(1):198-208.
  120. Donaghue KC, Chiarelli F, Trotta D, Allgrove J, Dahl-Jorgensen K. ISPAD Clinical Practice Consensus Guidelines 2006-2007. Microvascular and macrovascular complications. Pediatr Diabetes. 2007;8(3):163-70.
  121. Kavey RE, Allada V, Daniels SR, Hayman LL, McCrindle BW, Newburger JW, et al. Cardiovascular risk reduction in high-risk pediatric patients: a scientific statement from the American Heart Association Expert Panel on Population and Prevention Science; the Councils on Cardiovascular Disease in the Young, Epidemiology and Prevention, Nutrition, Physical Activity and Metabolism, High Blood Pressure Research, Cardiovascular Nursing, and the Kidney in Heart Disease; and the Interdisciplinary Working Group on Quality of Care and Outcomes Research: endorsed by the American Academy of Pediatrics. Circulation. 2006;114(24):2710-38.
  122. Silverstein J, Klingensmith G, Copeland K, Plotnick L, Kaufman F, Laffel L, et al. Care of children and adolescents with type 1 diabetes: a statement of the American Diabetes Association. Diabetes Care. 2005;28(1):186-212.

Body Weight Regulation

ABSTRACT

 

Body weight reflects the chronic balance between energy intake and energy expenditure. The pathophysiology of weight loss and gain is complex with genetic, physiological, and environmental factors contributing to a person’s ability to maintain, lose or gain weight. The inability for the body to counteract chronic caloric surplus leads to overweight and obesity. Among U.S. adults, overweight and obesity has dramatically increased over the last 60 years and, particularly within the past decade and more recently as a result of the COVID-19 global pandemic. The prevalence of children with obesity has also continued to rise, which is a major health concern for future generations. The objective of this chapter is to review of the current state of obesity in the United States, discuss mechanisms of body regulation in humans, and present key factors that may be contributing to its global epidemic.

 

INTRODUCTION

 

Body weight in the United States (US) has increased dramatically since the 1980s, with a steeper increase from 2011 to 2014 (Figure 1). Although controversial, to determine an individual’s body weight status, body mass index (BMI) is calculated from weight in kilograms divided by height in meters squared. This results in a general classification for body weight ranges attributable to health risks, including normal weight (18.5 kg/m2  > BMI < 24.9 kg/m2), overweight (25 kg/m2  > BMI < 29.9 kg/m2), and obesity (BMI > 30 kg/m2) (1). The National Health and Nutrition Examination Survey (NHANES) has been conducting BMI surveillance studies in the US since 1960. The first report (1971-1974) found that 44.9% of adults aged 20-74 years were living with overweight or obesity combined (2). The latest available survey 43 years later (2017-2018) reports that 31.0% of US adults are overweight and 42.8% are obese (3). Obesity prevalence is particularly high among American females, non-Hispanic Blacks, and individuals aged 60-69 years (3). Also, the prevalence of overweight and obesity in children (defined by weight for height above the 95th percentile for age) aged 2-20 years has increased from 14% to 19.2% and 3.9% to 6.1%, respectively, between 1992 and 2018. Hispanic, Mexican American, and Black children had a higher prevalence of developing obesity (26.9% and 24.2%, respectively) compared to non-Hispanic white children (16.1%) in 2017-2018 (4).

 

Figure 1. Prevalence of males and females aged 20-74 with overweight and obesity in the United States between 1988 and 2018. The table represents overweight and obesity trends overall. Values are age-adjusted by the direct method to the year 2000 U.S. Census Bureau estimates using the age groups 20-39, 40-59, and 60-74. Females who were pregnant were not included in the analysis. Source: CDC/NCHS, National Health Examination Survey and National Health and Nutrition Examination Survey.

 

The racial and ethnic disparities in overweight and obesity prevalence are a result of the effects of both social and environmental factors contributing to physiological changes over time (Figure 2). The growing health disparities following the COVID-19 pandemic encapsulate the interaction between social, environmental, and physiological components of health. Symptoms of COVID-19 were more severe in individuals with obesity, exposing them to greater risks of hospitalization, long-term comorbidities, and even death (5,6). Simultaneously, obesity prevalence increased at the height of the COVID-19 pandemic, most pointedly among children and individuals from marginalized backgrounds (7). During the pandemic, school shutdowns, limited access to exercise facilities and fresh foods, along with declining mental health rates culminated in increases in metabolic health risks including obesity, highlighting the importance of considering both biological and behavioral aspects of weight regulation (7,8).

 

The worldwide acceleration in obesity prevalence is commonly explained by a gene-environment interaction. Overtime global populations have endured rapid socioeconomic shifts from their traditional environment where human manual labor was the primary driver of economic growth and sustainability, to a modern environment characterized by industrial and technological advances. This shift lessened the need for physical activity and changed the food supply, leading to physiological and behavioral adaptations among people. As illustrated in Figure 2, the “traditional” environment is defined by whole food consumption and high occupational physical activity levels entrained normal appetite regulation which was coupled with energy expenditure to result in maintained leanness (leptogenic) and a lower BMI. In contrast, the industrial revolution and technology boom promoted obesogenic behaviors, such as the consumption of abundant, sweetened, and inexpensive calorie-dense and ultra processed food (UPF) and sedentariness. In obesogenic environments, food intake is uncoupled from energy expenditure and the population has a higher BMI than compared to that of the leptogenic environment.

 

Figure 2. The potential effects of genetic and environmental drivers on adiposity are assessed by body mass index (BMI). Some concepts described in this figure were proposed by Bouchard et al. (9). This figure was reprinted with permission from Galgani & Ravussin (42).

The following sections review the physiological regulators of energy balance and weight loss and maintenance to further understand the effects of changing environments on physiology and behaviors that affect weight regulation. The chapter concludes with a discussion of physiological factors that are contributing to weight gain and obesity.

 

ENERGY BALANCE

 

The balance between energy intake and energy expenditure determines the body energy stores (Figure 3). Energy intake is defined as the calories consumed and metabolized from food and drink, while energy expenditure consists of three components: 1) resting or basal metabolic rate – the energy required for basic organismal functions, 2) activity energy expenditure – the energy required for all non-sedentary activity, and 3) the thermic effects of food – the energy needed to digest and metabolize food. The thermic effect of food makes up approximately 8-10% of the total energy expenditure, while activity energy expenditure and resting metabolic rates are highly variable depending on an individual’s body composition and lifestyle. Fat free mass particularly is the largest determinant of energy expenditure (10). Energy is primarily stored in the body as fat. This renders the balance between energy intake and energy expenditure the main determinant of body fat acquisition and loss. For body weight to be maintained, a long-term energy balance with a possible variation of 100-250 calories per day (i.e., the energy imbalance gap) is required (11,12).

 

The energy balance equation (Energy Balance = Energy Intake - Energy Expenditure) is used to predict fluctuations in body weight when energy intake or energy expenditure change. Despite the intuitiveness of the energy balance equation, Alpert (13) elegantly demonstrated that it is inadequate for calculations on living organisms, given that it does not account for increasing or decreasing energy expenditure that ensues alongside weight gain or loss (14-16). Contrary to initial assumptions, small increases in energy intake sustained over several years do not lead to large weight gain. The more appropriate equation shown below incorporates the use of rates by introducing time dependency and allowing the effect of changing energy stores (especially fat-free mass and weight) on energy expenditure into the calculation (13).

 

Rate of Change of Energy Stores = Rate of Energy Intake - Rate of Energy Expenditure

 

This equation explains why a small initial positive energy balance (i.e., from an increased energy intake) will not lead to large weight increases over a number of years. After a short period of positive energy balance, the energy stores (fat mass and fat-free mass) will increase, in turn increasing energy expenditure thereby matching energy intake. These fluxes restore energy balance when there is a higher energy intake, greater energy expenditure, or larger energy storescompared to the initial energy balance state. Weight gain can therefore be viewed not only as the consequence of an initial positive energy balance, but also as the mechanism by which energy balance can eventually be re-established. This highlights the non-linear relationship between the changes in energy fluxes and the changes in energy stores.

 

To minimize fluxes in energy balance, it is important to calibrate energy intake with body weight. In January 2023, the National Academies of Science, Engineering, and Medicine published updated Dietary Reference Intake (DRI) providing the US and Canada populations with guidance on energy intake requirements to maintain a healthy weight status. The DRI includes estimated energy requirement equations for males and females in different age categories and separate DRI equations are provided for children, adolescents, and pregnant individuals. DRI equations account for factors contributing to energy expenditure such as gestational age, obesity category, and physical activity levels (17) In addition to providing energy intake estimates, the DRI also provides nutrient specific goals for maintaining a healthy weight and overall metabolic state. The following section will explore the role of nutrient balance in body weight regulation.

 

NUTRIENT BALANCE

 

Nutrition is a critical part of maintaining health and well-being and nutritional status affects clinical outcomes such as obesity. Nutrient intake requirements depend on various factors such as age, sex, and activity level. A classical approach to understanding how a chronic mismatch of intake and expenditure might occur is to examine dietary recommendations for macronutrients (i.e., carbohydrates, proteins, and fats) and their contribution to overall caloric intake.  

 

An imbalance in nutritional intake can lead to malnutrition and hidden hunger (18,19). In the US, the Food and Nutrition Board of the Academy of Medicine issues nutrition recommendations for populations across the lifespan providing Acceptable Macronutrient Distribution Ranges (AMDR) that can be used to assess nutrient intake. The AMDR expresses intake recommendations as a percentage of total caloric intake for proteins (10-35%), carbohydrates (45-65%), and fats (20-35%) (20). These ranges are based on evidence from intervention trials, suggesting they provide the lowest relative risk for chronic diseases and should be tailored to the individual to ensure proper nutrient intake.

 

Protein Balance

 

Protein stores constitute an important component of body composition, specifically lean body mass, and are vital for growth and development, physical functioning, and hormone balance. Protein stores respond to growth stimuli such as growth hormones, androgens, physical training, and weight gain. In addition, dietary protein intake is required to replace irreversibly oxidized amino acids that cannot be synthesized in the body (e.g., essential amino acids). The AMDR for protein is 10–35% of caloric intake which is 1.05–3.67 g/kg of body weight/day when the reference body weights (57 and 70 kg for women and men, respectively) are used. This translates to an estimated energy requirement of 36.5 kcal/kg body weight/day (Figure 3) (21,22). The actual protein requirement of an individual depends on sex, body weight, lean body mass, activity level and other factors that influence the rate of protein synthesis and degradation (e.g., protein turnover). Protein stores are ~1% and therefore tightly controlled and physiological mechanisms exist to ensure protein balance is achieved in healthy individuals on a day-to-day basis (23). As such, protein imbalance is not a direct cause of obesity. The fate of excess protein is not in tissue storage, but excretion through urea or other metabolic pathways (24). In a controlled inpatient study, 25 healthy individuals were overfed diets that contained either low (5%), normal (15%), or high (25%) protein for 8 weeks (25). Individuals in the low protein group gained significantly less weight [3.16 kg (95% CI 1.88, 4.44)] compared to individuals in the normal [6.05 kg (95% CI 4.84, 7.26)] or high protein [6.17 kg (95% CI 5.23, 7.79)] groups (p=0.0016). Body fat increased similarly in all 3 groups and represented up to 90% of the excess stored calories implying that differences in body mass were due to differences in the accumulation of body protein or lean body mass [normal protein group: 2.86 kg (CI 2.11, 3.62); high protein group: 3.17 kg (CI 2.37, 3.98)]. To reconcile the contradicting understandings of the effects of protein imbalance on weight regulation, the protein leverage hypothesis suggests that a diet with a low protein to non-protein energy nutrients (i.e., carbohydrates and fats) ratio is compensated for by overfeeding and through increased energy intake (26). The idea is that the body [and brain] prioritizes protein intake to ensure a chronic protein deficit does not impact tissues and organs, and hence through signaling molecules such as FGF21 (fibroblast growth factor 21), energy intake is stimulated with the signal being inhibited when protein balance is achieved (27). In the modern obesogenic environment, an increase in caloric intake for protein is often accompanied by an overconsumption of carbohydrate and fat. Prospective and cross-sectional studies have demonstrated that a smaller percentage of protein intake (e.g., <10%) can lead to excess energy intake (28). Compared to low carbohydrate and low fat diets, high-protein diets (>0.8 g/kg body weight/day) are often touted as robust nutritional strategies for weight management as protein increases satiety, reduces prospective food consumption and over time, leads to greater reductions in fat mass, supports lean mass growth, and increases thermic effect of food (25). 

 

Carbohydrate Balance

 

Dietary carbohydrates are eventually converted to glucose, which is the primary metabolic fuel for the body. Carbohydrates are stored as glycogen, yet the body storage capacity of glycogen is limited to 500-1000 g on average equating to ~2000-4000 kcals of energy stored as carbohydrates (500 g x 4kcal/g) (29). Dietary intake of carbohydrates corresponds to ~50-70% of carbohydrate stores, compared to ~1% for protein and fat (Figure 3). Because glucose is the main source of energy, the AMDR for carbohydrates is the highest of the macronutrients at 45-65% of caloric intake. The homeostatic regulatory mechanisms that occur to maintain euglycemia suggest that carbohydrate availability is important for energy balance. Intake of dietary carbohydrates stimulates both glycogen storage and glucose oxidation, thereby suppressing fat oxidation (30). However, a modern hypothesis to explain the increased prevalence of obesity is the carbohydrate-insulin model of obesity. Ludwig and colleagues postulate that diets with a large relative intake of carbohydrate elevate insulin section, thereby suppressing the release of fatty acids from adipose tissue (31). In turn, these decreases circulating fatty acid subsequently partitioning substrates away from fatty acid oxidation and directing them to adipose tissue storage. This metabolic dysregulation leads to a state of cellular ‘internal starvation’ triggering compensatory mechanisms of increasing hunger and decreasing energy expenditure (31,32). However, both animal models and human studies testing the carbohydrate-insulin model have mixed results, suggesting the important aspect of the model may relate to the relative intake of carbohydrate in the diet (31). Moreover, excess intake of carbohydrates during overall excess energy intake results in high levels of acetyl-CoA, which is eventually converted to malonyl-CoA, the precursor of de novo lipogenesis. During excess carbohydrate and energy intake, carbohydrate stores remain in balance while excess carbohydrates are converted to fat contributing to weight gain. This is supported by a large analysis of US dietary data that suggests the increased consumption of refined carbohydrates is positively associated with weight gain (33). While there is no clear evidence suggesting that altering the relative intake of total carbohydrate in the diet is an important determinant of energy intake (34), there is strong evidence that reducing total carbohydrate intake (e.g., < 45%) is effective for improving weight loss, high-density lipoprotein cholesterol (HDL), and triglyceride profiles (35). Indeed, a large randomized controlled trial examining the effects of diets varying in carbohydrate to fat ratio on energy expenditure during weight loss found in participants consuming low carbohydrates (20%), energy expenditure was increased by an average of 209 kcal/day compared to a 91 kcal/day increase in the moderate carbohydrate group (40%). Therefore, lowering dietary carbohydrate increased energy expenditure during weight loss maintenance (36).

 

Fat Balance

 

Dietary fat provides energy and essential fatty acids that cannot be synthesized in the body. Fatty acids, although often seen as harmful, are critical for life as they support membrane structure and function, cell signaling, steroid hormone production, and metabolism (37). The daily fat intake represents <1% of the total energy stored as fat (Figure 3), but the fat stores contain about 3 times the energy of the protein stores (38). The AMDR for dietary fats (20-35%) with the minimum recommendation ensuring there is adequate consumption of total energy and essential fatty acids to prevent atherogenic dyslipidemia that can occur with low fat, high carbohydrate diets (39,40). The maximum of 35% fat intake relies on limiting saturated fat and on the observation that higher fat diets lead to consumption of more calories often resulting in weight gain (39). Fat stores are the energy buffer for the body, and fat and energy balance are tightly positively associated (41). A deficit of 200 kcal of energy intake over 24 hours thus means that 200 kcal of energy expenditure comes from fat stores, and the same is assumed for an excess of 200 kcal of energy intake, which is stored as fat. As increased dietary fat intake leads to fat storage and, ultimately, to increased adipose tissue mass (42), a reduced fat oxidation that favors positive fat (and thus total) daily energy balance may indicate a greater predisposition to weight gain over time (43). This principal has been demonstrated in conditions of spontaneous overfeeding, where the entire excess fat intake was stored as body fat (44).One randomized controlled trial examining two 24-hr 200% overfeeding dietary intake (high carbohydrate and high fat) found a high fat overfeeding diet was linked to a decreased capacity to oxidize dietary fat, thereby leading to greater weight gain at 6 and 12 months (45). Interestingly, a 24-hour fast also disrupted metabolic oxidation rates such that a lower (or higher) 24-h oxidation during fasting was associated with lower (or higher) 24-h oxidation during feeding and overfeeding, respectively (45).

 

In contrast to the other macronutrients, body fat stores are large and fat intake has little influence on fat oxidation (30,46). When a mixed meal is consumed, there is an increase in carbohydrate oxidation and a decrease in fat oxidation, demonstrating the macronutrient composition of a meal significantly affects metabolism. The addition of extra fat in a mixed meal does not alter the nutrient oxidation pattern (30,46). The amount of total body fat exerts a small, but significant, effect on fat oxidation, with higher body fat levels leading to higher fat oxidation. This may be a mechanism allowing for the attenuation of the rate of weight gain when high levels of dietary fat are consumed (47). Given that energy balance is the driving force for fat oxidation (41,47), fat oxidation increases when energy balance is negative (i.e., energy expenditure exceeds energy intake). Additionally, the type of dietary fat consumed may have implications for metabolic health and weight balance, with recommendations encouraging the consumption of polyunsaturated fats over saturated fats for metabolic health (37).

 

Figure 3. The daily energy and nutrient balance in relationship to macronutrient intake, and oxidation for a 30-year-old female that is 90-kg and 165 cm tall with 35% body fat on a 2,400 kcal/day standard American diet (35% fat, 50% carbohydrate, 15% protein) (48). Energy stores were calculated using the energy coefficient for fat free mass (1.1 kcal/g) and fat mass (9.3 kcal/g) (49). Macronutrient intake and oxidation are based on individual energy requirements computed using the Dietary Reference Intake equations (17). Macronutrient percentage, equivalent to the USDA Dietary Guidelines for Americans (50), is shown on the left as absolute intake in kilocalories and on the right as a percentage of its respective nutrient store. Because carbohydrate and protein intake and oxidation rates are tightly regulated daily, any inherent differences between energy intake and energy expenditure therefore predominantly impact body fat stores. During chronic overfeeding (shown in red), the oxidation of carbohydrate and protein is increased to compensate for their increased intake and at the expense of fat intake and the increase in fat oxidation is not equally coupled with its intake. Thus, if sustained fat kilocalories are stored, fat stores expand, and body weight is gained. This figure was adapted with permission from Galgani & Ravussin (42).

Alcohol Balance

 

Alcohol consumption is considered a risk factor for weight gain and obesity contributing to other noncommunicable diseases and early mortality (51). Alcohol, an energy dense diet component, provides 7 kcal/g. Evidence suggest there is a hierarchy in macronutrient oxidation rate during the postprandial state with the sequence alcohol > protein > carbohydrate > fat (52-54). Diet induced thermogenesis is increased after meals rich in alcohol (~20% of energy) (54), suggesting the body recognizes the caloric contribution of alcohol similar to the other macronutrients. The energy derived from alcohol consumption is additive to other energy sources, promoting positive energy balance and leading to weight gain (55). Alcohol consumed before or with meals induces an orexigenic effect, which increases appetite and reduces satiation via mediation of the rewarding perception of food leading to greater food intake (55). However, prospective studies demonstrate that light-to-moderate alcohol intake is not associated with adiposity gain while heavy drinking is more consistently related to weight gain (56). The interindividual differences between alcohol consumption habits and the types of alcohol (e.g. beer, wine, liquor) may have a differential impact on abdominal adiposity and weight gain (57). A population-based cross-sectional study found alcohol intake was inversely associated to relative body fat in women whereas spirits consumption was positively related to central and general obesity in men (57). This may reflect a variance effect by sex and the type of alcohol consumed on body weight regulation. While the imbalance between alcohol intake and oxidation may not be a direct cause of obesity, it may be linked to behavioral factors that are related to obesity.

 

Energy Imbalance Is Buffered By Fat Stores

 

The intake of carbohydrates, protein, and alcohol, and subsequent oxidation rates, are tightly regulated. Amino acids, glucose, and alcohol oxidation rates adjust to the amount consumed. Fat oxidation, however, relies on various regulatory mechanisms such as leptin, peptide YY and ghrelin, to regulate energy expenditure, satiety, appetite and hence energy stores (58,59). Specifically, leptin, an adipose tissue derived hormone, controls adipose tissue mass by regulating energy intake and energy expenditure via negative feedback loop hormonal signaling to the hypothalamus (60). Lower leptin levels decrease energy expenditure and inhibit appetite regulation, which is an issue often observed in obesity (61). However, because fat provides a greater storage of energy, there may be a higher propensity for the body to store excess energy intake as fat, thus, directly contributing to the flux in adipose tissue mass and associated weight regulation (Figure 3). Another way energy imbalance is buffered by fat storage is through glucagon like peptide-1 [GLP-1], a gut hormone vital to glucose homeostasis, which acts through the GLP-1 receptor (62). GLP-1 decreases blood glucose levels by stimulating insulin secretion and by inhibiting glucagon secretion. These mechanisms decrease endogenous glucose production, subsequently reducing the need for energy intake and decreasing gastric emptying time (63,64). Obesity interferes with gut hormones’ (e.g., GLP-1) ability to secret peptides (e.g. AgRP, peptide tyrosine tyrosine [PPY]), thereby interfering with the homeostatic control of body mass via energy intake (brain) and energy expenditure (metabolism) regulation (65).

 

Is A Calorie Truly A Calorie?

 

Thermodynamically, a calorie is a unit of measurement that reflects the amount of energy needed to raise the temperature of 1 kg of water by 1°C. However, when evaluating the metabolizable energy content of calories from macronutrients, many factors influence the actual caloric value of food. For example, dietary fiber, often found in carbohydrate sources, has been shown to decrease transit time of food in the intestine, resulting in less time for digestion and absorption of energy (66). The thermic effect of food, the obligatory energy expenditure, increases with digestion and processing of ingested foods. Conversely, degradation of amino acids increases transit time of protein sources. Thus, diet composition has a strong effect on the thermic effect of foods with isocaloric amounts of protein having a greater thermic effect compared to carbohydrates and fat. Diets high in carbohydrates, fat, or both, produce a 4%-8% increase in energy expenditure (67), while meals high in protein cause an 11%-14% increase above resting metabolic rate due to the extra energy needed for amino acid degradation (68). One study comparing isocaloric low-fat and very low-carbohydrate diets found that total energy expenditure was approximately 300 kcal/day higher in the low-carbohydrate diet, an effect corresponding to the amount of energy typically expended in 1 h of moderate-intensity physical activity (69). As protein content was the same in both diets, the authors suggest the dietary composition differentially affected the availability of metabolic fuel types and efficiency, changes in hormone secretion, and skeletal muscle efficiency as regulated by leptin. As such, a calorie ingested does not necessarily correspond to a calorie absorbed, highlighting the importance of diet content on weight regulation. This is highlighted in an examination of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake showing that the low-fat diet led to ~690 kcal/day less energy intake than the low-carbohydrate diet over 2 weeks (70). Furthermore, the same research group assessed the effects of UPF on energy intake finding an ultra-processed diet increased calories (508 kcal/day), carbohydrates (280 kcal/day), and fat (230 kcal/day) when compared to an unprocessed diet (71). Notably, weight changes were highly correlated with energy intake with the ultra-processed diet leading to a ~1 kg weight gain in 2 weeks, whereas the unprocessed diet led to a loss of ~ 1 kg. 

 

DIETARY IMPLICATIONS FOR WEIGHT LOSS

 

Dietary modification is central for weight management and obesity treatment. A variety of approaches exist with weight loss diets including versions of energy restriction, manipulations of macronutrient composition, and dietary intake patterns (72). While caloric restriction is the most common method for weight loss, other methods such as time-restricted feeding, low-fat, and low-carbohydrate diets may be as effective. However, there are considerations with weight loss like weight cycling and disease status that should evaluated to ensure long-term success.

 

Calorie Restriction

 

Calorie restriction followed by macronutrient modification are the primary non-surgical and non-pharmaceutical drivers of weight loss (73). Caloric restriction is the reduction of average daily caloric intake below what is typical or habitual without causing malnutrition or restricting the intake of essential nutrients allowing for the diet to provide sufficient micronutrients, fiber, and energy needed for metabolic homeostasis (74). Caloric restriction may be more successful than other dietary strategies because it is an eating pattern rather than a temporary weight loss plan. Several approaches can be taken to achieve caloric restriction. A prescribed eating plan that consists of 1,200-1,500 kcal/day for women and 1,500-1,800 kcal/day for men (75). Another approach is to determine baseline energy requirements, modify them to factor in an individual's level of physical activity, and create a 500 kcal/day (women) or 750 kcal (men) energy deficit. When caloric restriction is paired with behavioral changes (e.g., monitoring food intake, physical activity), an average weight loss of 8 kg by 6 months can be expected (75). Tools like the NIH Body Weight Planner that estimate energy intake required for the target weight loss can be useful for self-management. Other options exist such as popular commercial diets such as Atkins, Weight Watchers, and Zone diets, which focus on macronutrient composition in addition to calorie reduction. These diets have shown modest long-term weight loss after 1 year (73). As discussed throughout this chapter, reducing daily calorie intake is the most important factor for weight loss and is outlined in theAmerican College of Cardiology/American Heart Association Task Force on Practice Guidelines 2013 for the management of overweight and obesity in adults (76). Results from a systematic review and meta-analysis of 8 clinical trials concluded that 20-30% caloric restriction induced weight loss in overweight (-6.50 kg) and obese (-3.30 kg) adults, with greater weight loss in studies that were ≥ 6 to ≤ 11 months (-8.70 kg) and ≥ 12 months long (-7.90 kg) compared to studies of shorter duration of calorie restriction (≤ 5 months; -4.26 kg). Further, 20-30% calorie restriction reduced fat mass in overweight ( -3.64 kg) and obese adults (-2.40 kg), again, with greater losses with > 6 months of calorie restriction (-5.80 kg) compared to ≤ 6 months of duration (-1.91 kg) (77). However, more human clinical trials are needed to fully understand the long-term implications such as weight maintenance.

 

Time-Restricted Feeding

 

In a fasting diet, an individual does not eat at all or severely limits dietary intake during certain times of the day, week, or month. Recently, intermittent fasting, limiting the number of hours (e.g., 6-8 h) each day food can is consumed, has become a popular and effective dietary pattern for weight loss, as the primary focus is on frequency of eating (78). This eating pattern may be a practical way to reduce caloric intake because there is less time for regular eating. Time-restricted feeding may improve body weight regulation through the extended fasting duration, which promotes the mobilization of free fatty acids and increases fat oxidation and the production of ketones (79). While there is no calorie goal for time-restricted feeding, there is about a 3-5% caloric reduction as a result of having less time to eat during the day (80). Currently, there are only a few human trials examining time-restricted feeding (eating window ≤ 8-10 h for ≥ 8 weeks). One study demonstrated weight loss of 3.3 kg (95% CI −5.6 to −0.9 kg) with a self-selected 20% reduction in daily caloric intake estimates (81). Another study examining restricted feeding (without calorie counting) to an 8 h window (10:00 to 18:00) for 12 weeks demonstrated a 2.6 ± 0.5% weight loss compared to control (82). Restricting energy intake to a short window during waking hours and extending the length of the overnight fast appears to provide metabolic and potential health benefits, but more human research is needed. Additionally, for time-restricted feeding to be effective, a reduced calorie intake relative to energy expenditure must be achieved. Compared to a traditional caloric restriction diet, time-restricted feeding may pose unique barriers to weight loss such as diet quality, scheduling conflicts, and social influences (80). 

 

Low-Carbohydrate vs Low-Fat

 

The most common adjustment to macronutrients for weight loss has been a reduction in fat intake since, in comparison to both carbohydrate and protein, fat contains more than twice as much energy per gram and fat tends to be overconsumed compared to dietary recommendations. Dietary macronutrient composition has been studied extensively regarding weight loss efficacy. The results of these studies were combined in a recent meta-analysis (83) where a total of 53 randomized controlled trials that imposed a low-fat diet or an alternative dietary intervention for 1 year. Collectively, these studies showed that dietary interventions targeting reduced fat intake do not lead to significantly greater weight loss than dietary interventions targeting reduced carbohydrate intake, which produced an average long-term weight loss of 1.15 kg (83). The reported weight loss with a low carbohydrate diet should be cautioned. It may be ill-advised to tout low-carbohydrate higher-fat diets as superior to low-fat diets since only 1 extra kg of weight was lost, which can be considered irrelevant and even indicative of weight maintenance in clinical settings.

 

Low-carbohydrate diets have had positive effects on health; however, the reduction of refined carbohydrates can induce weight loss through a decrease in the insulin-induced action for lipogenesis (storage of excess carbohydrates in adipose tissue) and the action to inhibit lipolysis (84). Since refined carbohydrates are strong stimulators of insulin, the unintentional reduction in refined carbohydrates as a result of improved overall diet quality in low-carbohydrate diets could be the reason for weight loss success (34). Furthermore, carbohydrates that are higher in fiber may reduce the metabolizable energy content leading to lower total calorie consumption. The low-fat versus low-carbohydrate diet debate for weight loss was recently put to the test in an elegant study conducted at the NIH (85). Individuals with obesity were randomized into 2 groups in an in-patient clinical setting where one group received 30% fewer calories from fat (~800 kcal/day) while keeping carbohydrates comparable to the baseline diet and the other group received 30% fewer calories from carbohydrates (~800 kcal/day) while keeping fat comparable to the baseline diet. Interestingly, only the reduced carbohydrate group had an increase in fat oxidation, whereas the reduced fat group did not. However, the reduced fat group astonishingly had a greater rate of body fat loss even though fat oxidation was unchanged (85). The reduced carbohydrate group, however, saw a reduction in insulin secretion. The mathematical model that was used to simulate the effects of these 2 diets on weight and fat suggests that the reduced fat diet group would continue to show enhanced fat loss for up to 6 months (85). Although as energy balance is reached again with weight loss, differences in fat loss between groups will likely diminish over time. Additionally, systematic review and meta-analysis comparing 14 dietary macronutrient patterns demonstrated that most macronutrient diets resulted in modest weight loss over 6 months, but weight reduction and improvements in cardiometabolic factors largely disappeared after 12 months (86). This suggests that caloric restriction, regardless of whether the diet is low fat or low carbohydrate, can lead to weight loss.

 

Recently, the focus on intra-individuality surrounding carbohydrate and fat oxidation has gained momentum. In a 12-week weight loss study, 145 participants with overweight/obesity were identified as fat-responders or carbohydrate-responders based on their combined genotypes at 10 genetic variants, and then randomized to a high-fat or high-carbohydrate diet. However, weight loss did not differ between the genotypes (87). Another randomized control trial examining whether a low-fat diet compared to a low-carbohydrate diet related to genotype patterns or insulin secretion found no significant differences in weight loss over 12 months between the low fat and low carbohydrate diets, and neither genotype pattern nor baseline insulin secretion was associated with the dietary effects on weight loss. Taken together, it appears that understanding who may benefit from a low-fat versus low-carbohydrate diet remains convoluted (88).

 

Weight Cycling

 

Weight regain following weight loss is a common issue that people with obesity encounter. Common mechanisms of action that spur weight regain are related to gut hormone secretion profiles, changes in appetite and reward centers related to food, decreases in energy expenditure, and changes in body composition (89). Indeed, research demonstrates that the ratio of fat mass to fat-free mass in an individual can predict food and macronutrient intake impacting energy homeostasis (90). Even with assisted weight loss (e.g., anti-obesity medications, bariatric surgery), weight regain can occur. Repeated episodes of weight loss and regain is popularly known as ‘weight cycling’ (91). Although a standardized definition is lacking (92), a 5% weight loss and regain is a common clinical definition of weight cycling (93). Weight cycling is thought to have an adverse impact on metabolism and increase the likelihood of increased fat regain. The weight-reduced state elicits a complex response of hunger, increased metabolic efficiency, and reduced energy expenditure, which together favor weight regain (94). Specifically, weight regain can lead to collateral fattening, the process where excess fat is deposited because of the body’s attempt to counter a deficit in lean mass through overeating. Under the weight regain conditions post weight loss, persistent hyperphagia driven by the need to complete the recovery of lean tissue will result in the excess fat deposition (hence collateral fattening) and fat overshooting (95).Achieving long-term weight reduction requires overcoming neuroendocrine systems that favor restoration of one’s initial weight (96).

 

Population-based studies have shown that individuals who reported a history of large weight fluctuations over adulthood (besides pregnancy) had an increased risk for cardiovascular and all-cause morbidity and mortality (97-100). In 441,199 participants, body-weight fluctuation was associated with increased risk for all-cause mortality (RR, 1.41; 95% confidence interval (CI): 1.27–1.57), CVD mortality (RR, 1.36; 95% CI 1.22–1.52), and morbidity of CVD (RR, 1.49, 95% CI 1.26–1.76) and hypertension (RR, 1.35, 95% CI 1.14–1.61) (98). A weight fluctuation of 4.5 kg between the ages of 40 and 60 y significantly increased the relative risk for diabetes by 1.7, even more so than a weight gain by the same amount (101). Furthermore, larger fluctuations in weight were associated with higher fasting insulin (102), impaired glucose tolerance (103) and greater risk for metabolic syndrome (104) independently of BMI. An inherent issue with these data is separating the contribution of pre-existing conditions, unintentional weight loss, and BMI to the outcomes (105-109). Therefore, individuals should be counselled on weight loss and the importance of weight loss maintenance because subsequent weight regain might be worse for long-term health than maintaining the original obese state.

 

Personalization of Weight Loss and Weight Loss Maintenance Interventions

 

The concept of precision medicine is rapidly gaining attention as an innovative approach for the management of obesity. Within this concept, individual differences in genes, demographics, environments, and lifestyles are considered for nutrition, exercise, and medical prescriptions. Individual-specific diet and physical activity components are identified and used for tailoring weight loss or weight maintenance strategies (110). By evaluating an individual’s cardiometabolic profile and other risk factors associated with obesity, precision health directly targets the disease. Laboratory tests for the assessment of metabolic profiles, metabolomics, and nutritional status are recommended along with the assessment of diet quality.

 

Better understanding the differing phenotypes of obesity may aid in addressing anti-obesity treatment response heterogeneity among individuals. Obesity-related cardiometabolic complications and metabolic disorders are often liked to a proinflammatory state (111). Yet, the occurrence of these obesity-related morbidities is not present in all individuals with obesity. Consequently, the terms “metabolically unhealthy obese” and “metabolically healthy obese”, have been introduced to define individuals with obesity who have cardiometabolic risk factors or those who do not, respectively (112). While there is no standard definition of these obesity phenotypes, the most common criteria to define metabolically unhealthy obese are based on the presence of ≥ 2 of the 4 diagnostic criteria for metabolic syndrome (112). Other proposed criteria to identify obesity phenotypes are the presence of insulin resistance, high-sensitivity C-reactive protein levels, and indices of visceral adiposity and fatty liver. Identifying the phenotype of obesity can provide a tailored approach to clinical care for those with overweight and obesity. Recent work by Acosta and colleagues suggests obesity presents in 4 distinct ways: hungry brain (abnormal satiation), emotional hunger (hedonic eating), hungry gut (abnormal satiety), and slow burn (decreased metabolic rate) (113). In a 12-month pragmatic weight management trial with 450 adults, 32% of patients were presented with hungry brain, 32% with hungry gut, 21% with emotional hunger, and 21% with slow burn. Addressing hedonic eating behavior (energy intake), homeostatic eating behavior (hunger, satiation, and satiety), and energy expenditure (resting metabolic rate) separately was shown by Acosta to provide a deeper assessment of potential mechanisms for precision health for obesity (113). Understanding the key determinants to an individual’s eating behavior and energy expenditure is the first step in addressing weight management with behavioral counseling.

 

FACTORS OF WEIGHT GAIN AND OBESITY

 

Sedentary Lifestyle and Energy Intake

 

A NHANES analysis on physical activity in adults ≥ 18 years old reported that sitting time has increased 19 minutes in 2007-2008 to 2017-2018 (from 332 min/day to 351 min/day, respectively) (114), with the highest point of sitting time being in 2013-2014 (426 min/day) (114). In 2007-2008, 33.6% adults (n = 5838) reporting sitting < 4 h/day, 23.6% 4-6 h/day, 24.8% 6-8 h/day, and 18.0% > 8 h/day (same as above). Sitting time increased in 2017-2018, with 26.9% adults (n = 5350) were sitting < 4 h/day, 26.3% 4-6 h/day, 27.2% 6-8 h/day, and 19.7% > 8 h/day (same citation as above).

 

Increased sitting time contributes to a sedentary lifestyle due to factors such as limited availability/feasibility to exercise facilities, occupation (e.g., office/desk job), television, video games, and smartphones and devices. Exercise facilities may be too expensive or too far commute for some people and households to get to. Sedentary occupational activities and the associated drop in energy expenditure have been related to the gradual increase in bodyweight in the US population (115).There is also growing evidence for a strong association between hours/day spent watching television and obesity in adults (116) and children (117). The iPhone was first released in 2007 exposing the world to easy access to the internet, applications, and games, and it has been shown that smartphone use is associated with obesity in children and adolescents (118). Lastly, according to NHANES, the average energy intake for adults aged 20 to 64 years is approximately 2,093 kcals/day from 2017-2018, only increasing slightly from 2,044 kcals/day in 2007-2010 (119). Based on the Dietary Guidelines for Americans 2020-2025 (120), the average calorie needs for adults ranges from 1,600 to 2,400 kcals/day for females and 2,000 to 3,200 for males (website above) depending on activity level and exact age (website above). Although US adults have not necessarily increased overall mean energy intake over the past 10-15 years, adults may be consuming more than the recommended number of calories per day which combined with increased sedentary behavior (e.g., sitting time) is likely contributing to weight gain and obesity.

 

Diet Quality and Ultra-Processed Foods

 

Overall diet quality is shown to contribute to weight gain and obesity (121). Increasing consumption of whole foods such as whole grains, vegetables, fruits, and fibers have been associated with weight loss and reduction of caloric intake (122) as well as lower rates of long-term weight gain (123,124). However, the opposite is found with the typical Westernized diet, which is known to be high in sugar, calories, and portion sizes (122,124). Diet index scores classify the quality of the diet, such as the NIH Healthy Eating Index (HEI). HEI score is widely used to assess diet quality based on the US Department of Agriculture 2015-202 Dietary Guidelines for Americans (125). Calculated on a scale of 0 (lowest quality) to 100 (highest quality), the HEI contains 13 components, 9 of which are classified as beneficial (total fruits, whole fruits, greens and beans, total vegetables, whole grains, seafood and plant proteins, fatty acids, total protein foods, and dairy) and 4 as harmful (sodium, refined grains, added sugar, and saturated fats) (125). A higher HEI score is indicative of a healthier diet and associated with lower BMI (126). NHANES analysis of 24-h food recall showed that a 1-point increase in HEI score was associated with a 0.8% decreased risk for abdominal obesity in adult women and 1.4% decreased risk in adult men (126,127). From 2001-2002 to 2017-2018, HEI-2015 decreased 47.82 to 45.25 (of 100 result in lower than the 50th percentile for diet quality) in adults 65 years and older who completed the NHANES 24-h dietary recall (125). Furthermore, another NHANES analysis of 24-h recalls in adults 20 years of age and older indicated that HEI-2015 for the overall population significantly decreased from 2011 to 2018 (128).

 

A possible reason for diet quality decreasing in the US could be due to the increase of UPF (129). UPF have become a large source of dietary food intake in high-income countries, including the US (130), and such foods have become increasingly available around the world due to the globalization of food systems (i.e., post 1970s). UPF are foods that have 5 or more ingredients, including chemically synthesized ingredients that are not found in unprocessed or minimally processed foods, such as artificial sweeteners, hydrogenated oils, and colorants (131,132). UPF are cheaper for consumers as they are mostly produced from high yielding crops such as soy, wheat, and maize. Data indicates that sales of UPF, but not ultra-processed beverages, per capita have been steadily increasing since 2012 in the US (130). A NHANES cross-sectional analysis in US adults age >19 years indicates that UPF consumption increased from 2001-2002 to 2017-2018 (129). Further, consumption of UPF has been positively associated with obesity possibly due to being energy dense and containing higher levels of trans- and saturated fatty acids, sodium, sugar, and refined carbohydrates (132). A randomized controlled clinical trial showed that energy intake was significantly increased in weight-stable adults during the UPF diet compared to the unprocessed food diet, with increased consumption of carbohydrates and fat (71). Weight gain was also correlated with UPF diet while losing weight was correlated with the unprocessed food diet (71).

 

Intrauterine and Intergenerational Effects

 

As obesity is continuously rising, the prevalence of obesity in pregnant women has also increased (133). In addition to the interrelated physiological and environmental components affecting metabolism, recent work shows that obesity (and other disorders) may be the result of genetic and epigenetic programming that occurs in utero and can be traced back up to two generations (Figure 4). Genetics alone are unlikely to be causing the ballooning of obesity observed the past decades, as genetic mutations are the result of evolutionary pressures occurring over multiple generations (134,135). Instead, environmental factors contributing to physiological changes can have implications for health and weight regulation in future generations. Rodent studies show that overfeeding results in increased body weight and adiposity both in sample animals and also in their offspring across 3 generations (136). Environmental changes, such as the shift towards predominantly obesogenic environments promote the expression of so-called “mal-adaptive” genes, predisposing the offspring to greater metabolic health risks (137). Accumulating evidence suggests that predisposition to obesity starts in utero if not earlier. Epigenetic factors such as the intrauterine environment affect health and phenotype outcomes in the offspring. Pregnant individuals with obesity are at risk for having infants born large for gestational age, which increases the infant’s risk for adult-onset obesity (138). Furthermore, pregnant individuals with obesity are also at higher risk of having overweight or obesity during postpartum and entering a subsequent pregnancy with obesity, perpetuating a cycle of weight gain, putting both parent and child at risk of adverse health outcomes. Lifestyle interventions during pregnancy focusing on altering the maternal milieu through increased physical activity, time-restricted eating, and individual feedback are likely to lead to healthy pregnancies and outcomes (139-142).

 

Obesogenics (Endocrine Disrupting Chemicals)

 

Obesogens, ingested or internalized environmental chemicals, interfere with endocrine signaling leading to adiposity and weight gain (143). Increased exposure to endocrine disrupting chemicals (EDCs) in the past half-century is both an ecological and a health concern. EDCs can be naturally occurring or man-made chemicals, with the most common including bisphenol A (BPA; used in plastic manufacturing), pesticides, phthalates (liquid plasticizers common in food packaging, cosmetics, and fragrances), and per- and polyfluoroalkyl substances (PFAS; chemicals common in paper, non-stick pans, and clothing) (144). All of these substances affect numerous metabolic outcomes, including adipocyte differentiation, number, size, and function, lipid profiles, energy intake, energy expenditure, the gut microbiome, basal inflammation, and insulin resistance (145). The most common methods of exposure include in utero, environmental exposures, food and beverages, cosmetics, household products, pollution, drugs, medical devices, and toys. Early exposure leads to higher risk for subsequent disease development later in life, as the umbilical cord, placenta, and breast milk are primary accumulation locations of EDCs and routes of exposure to developing young at their most susceptible (146). Given the abundance of obesogens in our everyday lives, it is imperative the obesogen hypothesis/model of obesity receive greater attention by the broader scientific community as a potential contributor to the increased prevalence of obesity.

 

SUMMARY

 

In the US, overweight and obesity among adults and children has dramatically increased in the last 50 years. While body weight is ultimately regulated by the interplay between energy intake and energy expenditure over the long term, it is likely that the drastic environmental changes that have occurred over the past decades have dramatically contributed to the epidemic of obesity. Changes in our environment not only directly influence the mechanisms regulating energy intake and energy expenditure, but also may indirectly reprogram the genetic and epigenetic background of human beings predisposing future generations to weight gain and adiposity. The obesity epidemic can be considered a predictable adaptation to changes in the pathogenic environment. In addition, more emphasis is being placed on the macronutrient content of diets. Not only are low-carbohydrate and low-fat diets showing differences in substrate use and fat loss, but low-protein diets may have a new place in the regulation of body weight due to the activation of FGF21. Although these various effects of each macronutrient are intriguing, it may still be the case that all calories are equal, and that weight loss follows a negative energy balance. Weight cycling resulting from repetitive intentional fluctuations in weight loss and regain is becoming more prevalent as well and could have negative implications on health. Furthermore, other factors that could be contributing to the consistent rise in obesity include increased sitting time, energy intake, consumption of ultra-processed food (UPF) and obesogens. This is something that must be addressed appropriately because it could add to an increased prevalence of cardiovascular episodes and other morbidities in upcoming decades.

 

REFERENCES

 

  1. Quetelet LA. A treatise on man and the development of his faculties. 1842. Obes Res. 1994;2(1):72-85.
  2. Ogden CL, Yanovski SZ, Carroll MD, Flegal KM. The epidemiology of obesity. Gastroenterology.2007;132(6):2087-2102.
  3. Li M, Gong W, Wang S, Li Z. Trends in body mass index, overweight and obesity among adults in the USA, the NHANES from 2003 to 2018: a repeat cross-sectional survey. BMJ Open. 2022;12(12):e065425.
  4. Tsoi MF, Li HL, Feng Q, Cheung CL, Cheung TT, Cheung BMY. Prevalence of Childhood Obesity in the United States in 1999-2018: A 20-Year Analysis. Obes Facts. 2022;15(4):560-569.
  5. Popkin BM, Du S, Green WD, Beck MA, Algaith T, Herbst CH, Alsukait RF, Alluhidan M, Alazemi N, Shekar M. Individuals with obesity and COVID-19: A global perspective on the epidemiology and biological relationships. Obes Rev. 2020;21(11):e13128.
  6. Aghili SMM, Ebrahimpur M, Arjmand B, Shadman Z, Pejman Sani M, Qorbani M, Larijani B, Payab M. Obesity in COVID-19 era, implications for mechanisms, comorbidities, and prognosis: a review and meta-analysis. Int J Obes (Lond). 2021;45(5):998-1016.
  7. Martinez-Ferran M, de la Guia-Galipienso F, Sanchis-Gomar F, Pareja-Galeano H. Metabolic Impacts of Confinement during the COVID-19 Pandemic Due to Modified Diet and Physical Activity Habits. Nutrients.2020;12(6).
  8. Lim S, Kong AP, Tuomilehto J. Influence of COVID-19 pandemic and related quarantine procedures on metabolic risk. Prim Care Diabetes. 2021;15(5):745-750.
  9. Bouchard C. The biological predisposition to obesity: beyond the thrifty genotype scenario. Int J Obes (Lond).2007;31(9):1337-1339.
  10. Hill JO, Wyatt HR, Peters JC. The Importance of Energy Balance. Eur Endocrinol. 2013;9(2):111-115.
  11. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity and the environment: where do we go from here? Science.2003;299(5608):853-855.
  12. Hall KD, Sacks G, Chandramohan D, Chow CC, Wang YC, Gortmaker SL, Swinburn BA. Quantification of the effect of energy imbalance on bodyweight. Lancet. 2011;378(9793):826-837.
  13. Alpert SS. Growth, thermogenesis, and hyperphagia. Am J Clin Nutr. 1990;52(5):784-792.
  14. Jequier E, Schutz Y. Long-term measurements of energy expenditure in humans using a respiration chamber. Am J Clin Nutr. 1983;38(6):989-998.
  15. Ravussin E, Lillioja S, Anderson TE, Christin L, Bogardus C. Determinants of 24-hour energy expenditure in man. Methods and results using a respiratory chamber. J Clin Invest. 1986;78(6):1568-1578.
  16. Weyer C, Snitker S, Rising R, Bogardus C, Ravussin E. Determinants of energy expenditure and fuel utilization in man: effects of body composition, age, sex, ethnicity and glucose tolerance in 916 subjects. Int J Obes Relat Metab Disord. 1999;23(7):715-722.
  17. . Dietary Reference Intakes for Energy. Washington (DC)2023.
  18. Kesari A, Noel JY. Nutritional Assessment. StatPearls. Treasure Island (FL)2024.
  19. Lowe NM. The global challenge of hidden hunger: perspectives from the field. Proc Nutr Soc. 2021;80(3):283-289.
  20. In: Ross AC, Taylor CL, Yaktine AL, Del Valle HB, eds. Dietary Reference Intakes for Calcium and Vitamin D. Washington (DC)2011.
  21. Medicine Io. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids. Washington, DC: The National Academies Press.
  22. Wolfe RR, Cifelli AM, Kostas G, Kim IY. Optimizing Protein Intake in Adults: Interpretation and Application of the Recommended Dietary Allowance Compared with the Acceptable Macronutrient Distribution Range. Adv Nutr.2017;8(2):266-275.
  23. Ross AB, Langer JD, Jovanovic M. Proteome Turnover in the Spotlight: Approaches, Applications, and Perspectives. Mol Cell Proteomics. 2021;20:100016.
  24. . Recommended Dietary Allowances: 10th Edition. Washington (DC)1989.
  25. Bray GA, Smith SR, de Jonge L, Xie H, Rood J, Martin CK, Most M, Brock C, Mancuso S, Redman LM. Effect of dietary protein content on weight gain, energy expenditure, and body composition during overeating: a randomized controlled trial. JAMA. 2012;307(1):47-55.
  26. Simonson M, Boirie Y, Guillet C. Protein, amino acids and obesity treatment. Rev Endocr Metab Disord.2020;21(3):341-353.
  27. Chen Z, Yang L, Liu Y, Huang P, Song H, Zheng P. The potential function and clinical application of FGF21 in metabolic diseases. Front Pharmacol. 2022;13:1089214.
  28. Gosby AK, Conigrave AD, Raubenheimer D, Simpson SJ. Protein leverage and energy intake. Obes Rev.2014;15(3):183-191.
  29. Acheson KJ, Schutz Y, Bessard T, Anantharaman K, Flatt JP, Jequier E. Glycogen storage capacity and de novo lipogenesis during massive carbohydrate overfeeding in man. Am J Clin Nutr. 1988;48(2):240-247.
  30. Flatt JP, Ravussin E, Acheson KJ, Jequier E. Effects of dietary fat on postprandial substrate oxidation and on carbohydrate and fat balances. J Clin Invest. 1985;76(3):1019-1024.
  31. Hall KD. A review of the carbohydrate-insulin model of obesity. Eur J Clin Nutr. 2017;71(5):679.
  32. Ludwig DS. Carbohydrate-insulin model: does the conventional view of obesity reverse cause and effect? Philos Trans R Soc Lond B Biol Sci. 2023;378(1888):20220211.
  33. Riera-Crichton D, Tefft N. Macronutrients and obesity: revisiting the calories in, calories out framework. Econ Hum Biol. 2014;14:33-49.
  34. van Dam RM, Seidell JC. Carbohydrate intake and obesity. Eur J Clin Nutr. 2007;61 Suppl 1:S75-99.
  35. Chawla S, Tessarolo Silva F, Amaral Medeiros S, Mekary RA, Radenkovic D. The Effect of Low-Fat and Low-Carbohydrate Diets on Weight Loss and Lipid Levels: A Systematic Review and Meta-Analysis. Nutrients.2020;12(12).
  36. Ebbeling CB, Feldman HA, Klein GL, Wong JMW, Bielak L, Steltz SK, Luoto PK, Wolfe RR, Wong WW, Ludwig DS. Effects of a low carbohydrate diet on energy expenditure during weight loss maintenance: randomized trial. BMJ. 2018;363:k4583.
  37. Wali JA, Solon-Biet SM, Freire T, Brandon AE. Macronutrient Determinants of Obesity, Insulin Resistance and Metabolic Health. Biology (Basel). 2021;10(4).
  38. Bray GA. Treatment for obesity: a nutrient balance/nutrient partition approach. Nutr Rev. 1991;49(2):33-45.
  39. Trumbo P, Schlicker S, Yates AA, Poos M, Food, Nutrition Board of the Institute of Medicine TNA. Dietary reference intakes for energy, carbohydrate, fiber, fat, fatty acids, cholesterol, protein and amino acids. J Am Diet Assoc. 2002;102(11):1621-1630.
  40. Fats and fatty acids in human nutrition. Report of an expert consultation. FAO Food Nutr Pap. 2010;91:1-166.
  41. Abbott WG, Howard BV, Christin L, Freymond D, Lillioja S, Boyce VL, Anderson TE, Bogardus C, Ravussin E. Short-term energy balance: relationship with protein, carbohydrate, and fat balances. Am J Physiol. 1988;255(3 Pt 1):E332-337.
  42. Galgani J, Ravussin E. Energy metabolism, fuel selection and body weight regulation. Int J Obes (Lond). 2008;32 Suppl 7(Suppl 7):S109-119.
  43. Astrup A, Raben A, Buemann B, Toubro S. Fat metabolism in the predisposition to obesity. Ann N Y Acad Sci.1997;827:417-430.
  44. Piaggi P, Thearle MS, Bogardus C, Krakoff J. Lower energy expenditure predicts long-term increases in weight and fat mass. J Clin Endocrinol Metab. 2013;98(4):E703-707.
  45. Begaye B, Vinales KL, Hollstein T, Ando T, Walter M, Bogardus C, Krakoff J, Piaggi P. Impaired Metabolic Flexibility to High-Fat Overfeeding Predicts Future Weight Gain in Healthy Adults. Diabetes. 2020;69(2):181-192.
  46. Schutz Y, Flatt JP, Jequier E. Failure of dietary fat intake to promote fat oxidation: a factor favoring the development of obesity. Am J Clin Nutr. 1989;50(2):307-314.
  47. Zurlo F, Lillioja S, Esposito-Del Puente A, Nyomba BL, Raz I, Saad MF, Swinburn BA, Knowler WC, Bogardus C, Ravussin E. Low ratio of fat to carbohydrate oxidation as predictor of weight gain: study of 24-h RQ. Am J Physiol.1990;259(5 Pt 1):E650-657.
  48. National Center for Health Statistics. In: Agriculture NHaNESaUSDo, ed. Centers for Disease Control and Prevention.
  49. Racette SB, Das SK, Bhapkar M, Hadley EC, Roberts SB, Ravussin E, Pieper C, DeLany JP, Kraus WE, Rochon J, Redman LM, Group CS. Approaches for quantifying energy intake and %calorie restriction during calorie restriction interventions in humans: the multicenter CALERIE study. Am J Physiol Endocrinol Metab.2012;302(4):E441-448.
  50. Dietary guidelines for Americans 2015-2020. In: Agriculture USDoHaHSaUSDo, ed. 8th ed2015.
  51. Yeomans MR. Alcohol, appetite and energy balance: is alcohol intake a risk factor for obesity? Physiol Behav.2010;100(1):82-89.
  52. Stubbs J, Raben A, Westerterp-Plantenga M, Steffens A, Tremblay A. Substrate metabolism and appetite in humans. Regulation of food intake and energy expenditure Milan: Edra. 1999:59-83.
  53. Westerterp KR. Diet induced thermogenesis. Nutr Metab (Lond). 2004;1(1):5.
  54. Raben A, Agerholm-Larsen L, Flint A, Holst JJ, Astrup A. Meals with similar energy densities but rich in protein, fat, carbohydrate, or alcohol have different effects on energy expenditure and substrate metabolism but not on appetite and energy intake. Am J Clin Nutr. 2003;77(1):91-100.
  55. Christiansen P, Rose A, Randall-Smith L, Hardman CA. Alcohol's acute effect on food intake is mediated by inhibitory control impairments. Health Psychol. 2016;35(5):518-522.
  56. Traversy G, Chaput JP. Alcohol Consumption and Obesity: An Update. Curr Obes Rep. 2015;4(1):122-130.
  57. Brandhagen M, Forslund HB, Lissner L, Winkvist A, Lindroos AK, Carlsson LM, Sjostrom L, Larsson I. Alcohol and macronutrient intake patterns are related to general and central adiposity. Eur J Clin Nutr. 2012;66(3):305-313.
  58. Erlanson-Albertsson C. Fat-Rich Food Palatability and Appetite Regulation. In: Montmayeur JP, le Coutre J, eds. Fat Detection: Taste, Texture, and Post Ingestive Effects. Boca Raton (FL)2010.
  59. Klok MD, Jakobsdottir S, Drent ML. The role of leptin and ghrelin in the regulation of food intake and body weight in humans: a review. Obes Rev. 2007;8(1):21-34.
  60. Pico C, Palou M, Pomar CA, Rodriguez AM, Palou A. Leptin as a key regulator of the adipose organ. Rev Endocr Metab Disord. 2022;23(1):13-30.
  61. Izquierdo AG, Crujeiras AB, Casanueva FF, Carreira MC. Leptin, Obesity, and Leptin Resistance: Where Are We 25 Years Later? Nutrients. 2019;11(11).
  62. Baggio LL, Huang Q, Brown TJ, Drucker DJ. Oxyntomodulin and glucagon-like peptide-1 differentially regulate murine food intake and energy expenditure. Gastroenterology. 2004;127(2):546-558.
  63. Willms B, Werner J, Holst JJ, Orskov C, Creutzfeldt W, Nauck MA. Gastric emptying, glucose responses, and insulin secretion after a liquid test meal: effects of exogenous glucagon-like peptide-1 (GLP-1)-(7-36) amide in type 2 (noninsulin-dependent) diabetic patients. J Clin Endocrinol Metab. 1996;81(1):327-332.
  64. Zander M, Madsbad S, Madsen JL, Holst JJ. Effect of 6-week course of glucagon-like peptide 1 on glycaemic control, insulin sensitivity, and beta-cell function in type 2 diabetes: a parallel-group study. Lancet.2002;359(9309):824-830.
  65. Sam AH, Troke RC, Tan TM, Bewick GA. The role of the gut/brain axis in modulating food intake. Neuropharmacology. 2012;63(1):46-56.
  66. Miles CW, Kelsay JL, Wong NP. Effect of dietary fiber on the metabolizable energy of human diets. J Nutr.1988;118(9):1075-1081.
  67. Westerterp KR, Wilson SA, Rolland V. Diet induced thermogenesis measured over 24h in a respiration chamber: effect of diet composition. Int J Obes Relat Metab Disord. 1999;23(3):287-292.
  68. Crovetti R, Porrini M, Santangelo A, Testolin G. The influence of thermic effect of food on satiety. Eur J Clin Nutr.1998;52(7):482-488.
  69. Ebbeling CB, Swain JF, Feldman HA, Wong WW, Hachey DL, Garcia-Lago E, Ludwig DS. Effects of dietary composition on energy expenditure during weight-loss maintenance. JAMA. 2012;307(24):2627-2634.
  70. Hall KD, Guo J, Courville AB, Boring J, Brychta R, Chen KY, Darcey V, Forde CG, Gharib AM, Gallagher I, Howard R, Joseph PV, Milley L, Ouwerkerk R, Raisinger K, Rozga I, Schick A, Stagliano M, Torres S, Walter M, Walter P, Yang S, Chung ST. Effect of a plant-based, low-fat diet versus an animal-based, ketogenic diet on ad libitum energy intake. Nat Med. 2021;27(2):344-353.
  71. Hall KD, Ayuketah A, Brychta R, Cai H, Cassimatis T, Chen KY, Chung ST, Costa E, Courville A, Darcey V, Fletcher LA, Forde CG, Gharib AM, Guo J, Howard R, Joseph PV, McGehee S, Ouwerkerk R, Raisinger K, Rozga I, Stagliano M, Walter M, Walter PJ, Yang S, Zhou M. Ultra-Processed Diets Cause Excess Calorie Intake and Weight Gain: An Inpatient Randomized Controlled Trial of Ad Libitum Food Intake. Cell Metab. 2019;30(1):67-77 e63.
  72. Chao AM, Quigley KM, Wadden TA. Dietary interventions for obesity: clinical and mechanistic findings. J Clin Invest. 2021;131(1).
  73. Johnston BC, Kanters S, Bandayrel K, Wu P, Naji F, Siemieniuk RA, Ball GD, Busse JW, Thorlund K, Guyatt G, Jansen JP, Mills EJ. Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA. 2014;312(9):923-933.
  74. Flanagan EW, Most J, Mey JT, Redman LM. Calorie Restriction and Aging in Humans. Annu Rev Nutr.2020;40:105-133.
  75. Ryan D, Heaner M. Guidelines (2013) for managing overweight and obesity in adults. Preface to the full report. Obesity (Silver Spring). 2014;22 Suppl 2:S1-3.
  76. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, Hu FB, Hubbard VS, Jakicic JM, Kushner RF, Loria CM, Millen BE, Nonas CA, Pi-Sunyer FX, Stevens J, Stevens VJ, Wadden TA, Wolfe BM, Yanovski SZ, Jordan HS, Kendall KA, Lux LJ, Mentor-Marcel R, Morgan LC, Trisolini MG, Wnek J, Anderson JL, Halperin JL, Albert NM, Bozkurt B, Brindis RG, Curtis LH, DeMets D, Hochman JS, Kovacs RJ, Ohman EM, Pressler SJ, Sellke FW, Shen WK, Smith SC, Jr., Tomaselli GF, American College of Cardiology/American Heart Association Task Force on Practice G, Obesity S. 2013 AHA/ACC/TOS guideline for the management of overweight and obesity in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and The Obesity Society. Circulation. 2014;129(25 Suppl 2):S102-138.
  77. Caristia S, Vito M, Sarro A, Leone A, Pecere A, Zibetti A, Filigheddu N, Zeppegno P, Prodam F, Faggiano F, Marzullo P. Is Caloric Restriction Associated with Better Healthy Aging Outcomes? A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Nutrients. 2020;12(8).
  78. Cho Y, Hong N, Kim KW, Cho SJ, Lee M, Lee YH, Lee YH, Kang ES, Cha BS, Lee BW. The Effectiveness of Intermittent Fasting to Reduce Body Mass Index and Glucose Metabolism: A Systematic Review and Meta-Analysis. J Clin Med. 2019;8(10).
  79. Hatori M, Vollmers C, Zarrinpar A, DiTacchio L, Bushong EA, Gill S, Leblanc M, Chaix A, Joens M, Fitzpatrick JA, Ellisman MH, Panda S. Time-restricted feeding without reducing caloric intake prevents metabolic diseases in mice fed a high-fat diet. Cell Metab. 2012;15(6):848-860.
  80. O'Connor SG, Boyd P, Bailey CP, Shams-White MM, Agurs-Collins T, Hall K, Reedy J, Sauter ER, Czajkowski SM. Perspective: Time-Restricted Eating Compared with Caloric Restriction: Potential Facilitators and Barriers of Long-Term Weight Loss Maintenance. Adv Nutr. 2021;12(2):325-333.
  81. Gill S, Panda S. A Smartphone App Reveals Erratic Diurnal Eating Patterns in Humans that Can Be Modulated for Health Benefits. Cell Metab. 2015;22(5):789-798.
  82. Gabel K, Hoddy KK, Haggerty N, Song J, Kroeger CM, Trepanowski JF, Panda S, Varady KA. Effects of 8-hour time restricted feeding on body weight and metabolic disease risk factors in obese adults: A pilot study. Nutr Healthy Aging. 2018;4(4):345-353.
  83. Tobias DK, Chen M, Manson JE, Ludwig DS, Willett W, Hu FB. Effect of low-fat diet interventions versus other diet interventions on long-term weight change in adults: a systematic review and meta-analysis. Lancet Diabetes Endocrinol. 2015;3(12):968-979.
  84. Brouns F. Overweight and diabetes prevention: is a low-carbohydrate-high-fat diet recommendable? Eur J Nutr.2018;57(4):1301-1312.
  85. Hall KD, Bemis T, Brychta R, Chen KY, Courville A, Crayner EJ, Goodwin S, Guo J, Howard L, Knuth ND, Miller BV, 3rd, Prado CM, Siervo M, Skarulis MC, Walter M, Walter PJ, Yannai L. Calorie for Calorie, Dietary Fat Restriction Results in More Body Fat Loss than Carbohydrate Restriction in People with Obesity. Cell Metab.2015;22(3):427-436.
  86. Ge L, Sadeghirad B, Ball GDC, da Costa BR, Hitchcock CL, Svendrovski A, Kiflen R, Quadri K, Kwon HY, Karamouzian M, Adams-Webber T, Ahmed W, Damanhoury S, Zeraatkar D, Nikolakopoulou A, Tsuyuki RT, Tian J, Yang K, Guyatt GH, Johnston BC. Comparison of dietary macronutrient patterns of 14 popular named dietary programmes for weight and cardiovascular risk factor reduction in adults: systematic review and network meta-analysis of randomised trials. BMJ. 2020;369:m696.
  87. Hochsmann C, Yang S, Ordovas JM, Dorling JL, Champagne CM, Apolzan JW, Greenway FL, Cardel MI, Foster GD, Martin CK. The Personalized Nutrition Study (POINTS): evaluation of a genetically informed weight loss approach, a Randomized Clinical Trial. Nat Commun. 2023;14(1):6321.
  88. Gardner CD, Trepanowski JF, Del Gobbo LC, Hauser ME, Rigdon J, Ioannidis JPA, Desai M, King AC. Effect of Low-Fat vs Low-Carbohydrate Diet on 12-Month Weight Loss in Overweight Adults and the Association With Genotype Pattern or Insulin Secretion: The DIETFITS Randomized Clinical Trial. JAMA. 2018;319(7):667-679.
  89. Busetto L, Bettini S, Makaronidis J, Roberts CA, Halford JCG, Batterham RL. Mechanisms of weight regain. Eur J Intern Med. 2021;93:3-7.
  90. Weise CM, Hohenadel MG, Krakoff J, Votruba SB. Body composition and energy expenditure predict ad-libitum food and macronutrient intake in humans. Int J Obes (Lond). 2014;38(2):243-251.
  91. Blackburn GL, Wilson GT, Kanders BS, Stein LJ, Lavin PT, Adler J, Brownell KD. Weight cycling: the experience of human dieters. Am J Clin Nutr. 1989;49(5 Suppl):1105-1109.
  92. Weight cycling. National Task Force on the Prevention and Treatment of Obesity. JAMA. 1994;272(15):1196-1202.
  93. Taing KY, Ardern CI, Kuk JL. Effect of the timing of weight cycling during adulthood on mortality risk in overweight and obese postmenopausal women. Obesity (Silver Spring). 2012;20(2):407-413.
  94. Greenway FL. Physiological adaptations to weight loss and factors favouring weight regain. Int J Obes (Lond).2015;39(8):1188-1196.
  95. Dulloo AG, Miles-Chan JL, Schutz Y. Collateral fattening in body composition autoregulation: its determinants and significance for obesity predisposition. Eur J Clin Nutr. 2018;72(5):657-664.
  96. Ravussin E, Smith SR, Ferrante AW, Jr. Physiology of Energy Expenditure in the Weight-Reduced State. Obesity (Silver Spring). 2021;29 Suppl 1(Suppl 1):S31-S38.
  97. Diaz VA, Mainous AG, 3rd, Everett CJ. The association between weight fluctuation and mortality: results from a population-based cohort study. J Community Health. 2005;30(3):153-165.
  98. Zou H, Yin P, Liu L, Liu W, Zhang Z, Yang Y, Li W, Zong Q, Yu X. Body-Weight Fluctuation Was Associated With Increased Risk for Cardiovascular Disease, All-Cause and Cardiovascular Mortality: A Systematic Review and Meta-Analysis. Front Endocrinol (Lausanne). 2019;10:728.
  99. Rhee EJ. Weight Cycling and Its Cardiometabolic Impact. J Obes Metab Syndr. 2017;26(4):237-242.
  100. Strohacker K, Carpenter KC, McFarlin BK. Consequences of Weight Cycling: An Increase in Disease Risk? Int J Exerc Sci. 2009;2(3):191-201.
  101. Holbrook TL, Barrett-Connor E, Wingard DL. The association of lifetime weight and weight control patterns with diabetes among men and women in an adult community. Int J Obes. 1989;13(5):723-729.
  102. Yatsuya H, Tamakoshi K, Yoshida T, Hori Y, Zhang H, Ishikawa M, Zhu S, Kondo T, Toyoshima H. Association between weight fluctuation and fasting insulin concentration in Japanese men. Int J Obes Relat Metab Disord.2003;27(4):478-483.
  103. Lissner L, Andres R, Muller DC, Shimokata H. Body weight variability in men: metabolic rate, health and longevity. Int J Obes. 1990;14(4):373-383.
  104. Vergnaud AC, Bertrais S, Oppert JM, Maillard-Teyssier L, Galan P, Hercberg S, Czernichow S. Weight fluctuations and risk for metabolic syndrome in an adult cohort. Int J Obes (Lond). 2008;32(2):315-321.
  105. Field AE, Malspeis S, Willett WC. Weight cycling and mortality among middle-aged or older women. Arch Intern Med. 2009;169(9):881-886.
  106. Stevens VL, Jacobs EJ, Sun J, Patel AV, McCullough ML, Teras LR, Gapstur SM. Weight cycling and mortality in a large prospective US study. Am J Epidemiol. 2012;175(8):785-792.
  107. Wannamethee SG, Shaper AG, Walker M. Weight change, weight fluctuation, and mortality. Arch Intern Med.2002;162(22):2575-2580.
  108. Field AE, Manson JE, Laird N, Williamson DF, Willett WC, Colditz GA. Weight cycling and the risk of developing type 2 diabetes among adult women in the United States. Obes Res. 2004;12(2):267-274.
  109. Schienkiewitz A, Schulze MB, Hoffmann K, Kroke A, Boeing H. Body mass index history and risk of type 2 diabetes: results from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Am J Clin Nutr. 2006;84(2):427-433.
  110. Cifuentes L, Hurtado AM, Eckel-Passow J, Acosta A. Precision Medicine for Obesity. Dig Dis Interv.2021;5(3):239-248.
  111. McLaughlin T, Abbasi F, Lamendola C, Reaven G. Heterogeneity in the prevalence of risk factors for cardiovascular disease and type 2 diabetes mellitus in obese individuals: effect of differences in insulin sensitivity. Arch Intern Med. 2007;167(7):642-648.
  112. Liu C, Wang C, Guan S, Liu H, Wu X, Zhang Z, Gu X, Zhang Y, Zhao Y, Tse LA, Fang X. The Prevalence of Metabolically Healthy and Unhealthy Obesity according to Different Criteria. Obes Facts. 2019;12(1):78-90.
  113. Acosta A, Camilleri M, Abu Dayyeh B, Calderon G, Gonzalez D, McRae A, Rossini W, Singh S, Burton D, Clark MM. Selection of Antiobesity Medications Based on Phenotypes Enhances Weight Loss: A Pragmatic Trial in an Obesity Clinic. Obesity (Silver Spring). 2021;29(4):662-671.
  114. Ussery EN, Whitfield GP, Fulton JE, Galuska DA, Matthews CE, Katzmarzyk PT, Carlson SA. Trends in Self-Reported Sitting Time by Physical Activity Levels Among US Adults, NHANES 2007/2008-2017/2018. J Phys Act Health. 2021;18(S1):S74-S83.
  115. Church TS, Thomas DM, Tudor-Locke C, Katzmarzyk PT, Earnest CP, Rodarte RQ, Martin CK, Blair SN, Bouchard C. Trends over 5 decades in U.S. occupation-related physical activity and their associations with obesity. PLoS One. 2011;6(5):e19657.
  116. Bowman SA. Television-viewing characteristics of adults: correlations to eating practices and overweight and health status. Prev Chronic Dis. 2006;3(2):A38.
  117. Gortmaker SL, Must A, Sobol AM, Peterson K, Colditz GA, Dietz WH. Television viewing as a cause of increasing obesity among children in the United States, 1986-1990. Arch Pediatr Adolesc Med. 1996;150(4):356-362.
  118. Ma Z, Wang J, Li J, Jia Y. The association between obesity and problematic smartphone use among school-age children and adolescents: a cross-sectional study in Shanghai. BMC Public Health. 2021;21(1):2067.
  119. Food Consumption and Nutrient Intakes. In: Agriculture USDo, ed2021.
  120. Dietary Guidelines for Americans, 2020-2025. In: Services USDoAaUSDoHaH, ed. 9th ed2020.
  121. Liu J, Rehm CD, Onopa J, Mozaffarian D. Trends in Diet Quality Among Youth in the United States, 1999-2016. JAMA. 2020;323(12):1161-1174.
  122. Rakhra V, Galappaththy SL, Bulchandani S, Cabandugama PK. Obesity and the Western Diet: How We Got Here. Mo Med. 2020;117(6):536-538.
  123. Estruch R, Ros E. The role of the Mediterranean diet on weight loss and obesity-related diseases. Rev Endocr Metab Disord. 2020;21(3):315-327.
  124. Mu M, Xu LF, Hu D, Wu J, Bai MJ. Dietary Patterns and Overweight/Obesity: A Review Article. Iran J Public Health. 2017;46(7):869-876.
  125. Long T, Zhang K, Chen Y, Wu C. Trends in Diet Quality Among Older US Adults From 2001 to 2018. JAMA Netw Open. 2022;5(3):e221880.
  126. Asghari G, Mirmiran P, Yuzbashian E, Azizi F. A systematic review of diet quality indices in relation to obesity. Br J Nutr. 2017;117(8):1055-1065.
  127. Tande DL, Magel R, Strand BN. Healthy Eating Index and abdominal obesity. Public Health Nutr. 2010;13(2):208-214.
  128. Tao MH, Liu JL, Nguyen UDT. Trends in Diet Quality by Race/Ethnicity among Adults in the United States for 2011-2018. Nutrients. 2022;14(19).
  129. Juul F, Parekh N, Martinez-Steele E, Monteiro CA, Chang VW. Ultra-processed food consumption among US adults from 2001 to 2018. Am J Clin Nutr. 2022;115(1):211-221.
  130. Baker P, Machado P, Santos T, Sievert K, Backholer K, Hadjikakou M, Russell C, Huse O, Bell C, Scrinis G, Worsley A, Friel S, Lawrence M. Ultra-processed foods and the nutrition transition: Global, regional and national trends, food systems transformations and political economy drivers. Obes Rev. 2020;21(12):e13126.
  131. Harb AA, Shechter A, Koch PA, St-Onge MP. Ultra-processed foods and the development of obesity in adults. Eur J Clin Nutr. 2023;77(6):619-627.
  132. Askari M, Heshmati J, Shahinfar H, Tripathi N, Daneshzad E. Ultra-processed food and the risk of overweight and obesity: a systematic review and meta-analysis of observational studies. Int J Obes (Lond). 2020;44(10):2080-2091.
  133. Reichetzeder C. Overweight and obesity in pregnancy: their impact on epigenetics. Eur J Clin Nutr.2021;75(12):1710-1722.
  134. Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments. Genome Med.2020;12(1):44.
  135. Casazza K, Brown A, Astrup A, Bertz F, Baum C, Brown MB, Dawson J, Durant N, Dutton G, Fields DA, Fontaine KR, Heymsfield S, Levitsky D, Mehta T, Menachemi N, Newby PK, Pate R, Raynor H, Rolls BJ, Sen B, Smith DL, Jr., Thomas D, Wansink B, Allison DB. Weighing the Evidence of Common Beliefs in Obesity Research. Crit Rev Food Sci Nutr. 2015;55(14):2014-2053.
  136. Diaz J, Taylor EM. Abnormally high nourishment during sensitive periods results in body weight changes across generations. Obes Res. 1998;6(5):368-374.
  137. Keating ST, El-Osta A. Epigenetics and metabolism. Circ Res. 2015;116(4):715-736.
  138. Silverman BL, Rizzo TA, Cho NH, Metzger BE. Long-term effects of the intrauterine environment. The Northwestern University Diabetes in Pregnancy Center. Diabetes Care. 1998;21 Suppl 2:B142-149.
  139. Kebbe M, Flanagan EW, Sparks JR, Redman LM. Eating Behaviors and Dietary Patterns of Women during Pregnancy: Optimizing the Universal 'Teachable Moment'. Nutrients. 2021;13(9).
  140. Gilmore LA, Redman LM. Weight gain in pregnancy and application of the 2009 IOM guidelines: toward a uniform approach. Obesity (Silver Spring). 2015;23(3):507-511.
  141. Flanagan EW, Most J, Altazan AD, Boyle KE, Redman LM. A role for the early pregnancy maternal milieu in the intergenerational transmission of obesity. Obesity (Silver Spring). 2021;29(11):1780-1786.
  142. Sparks JR, Flanagan EW, Kebbe M, Redman LM. Understanding Barriers and Facilitators to Physical Activity Engagement to Inform a Precision Prescription Approach during Pregnancy. Am J Lifestyle Med. 2023;17(1):108-122.
  143. Heindel JJ, Lustig RH, Howard S, Corkey BE. Obesogens: a unifying theory for the global rise in obesity. Int J Obes (Lond). 2024;48(4):449-460.
  144. Endocrine Disruptors. In: Sciences NIoEH, ed2024.
  145. Heindel JJ, Howard S, Agay-Shay K, Arrebola JP, Audouze K, Babin PJ, Barouki R, Bansal A, Blanc E, Cave MC, Chatterjee S, Chevalier N, Choudhury M, Collier D, Connolly L, Coumoul X, Garruti G, Gilbertson M, Hoepner LA, Holloway AC, Howell G, 3rd, Kassotis CD, Kay MK, Kim MJ, Lagadic-Gossmann D, Langouet S, Legrand A, Li Z, Le Mentec H, Lind L, Monica Lind P, Lustig RH, Martin-Chouly C, Munic Kos V, Podechard N, Roepke TA, Sargis RM, Starling A, Tomlinson CR, Touma C, Vondracek J, Vom Saal F, Blumberg B. Obesity II: Establishing causal links between chemical exposures and obesity. Biochem Pharmacol. 2022;199:115015.
  146. Miranda RA, Silva BS, de Moura EG, Lisboa PC. Pesticides as endocrine disruptors: programming for obesity and diabetes. Endocrine. 2023;79(3):437-447.