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Anatomy and Ultrastructure of Bone – Histogenesis, Growth and Remodeling

ABSTRACT

 

Bones have three major functions: to serve as mechanical support, sites of muscle insertion and as a reserve of calcium and phosphate for the organism. Recently, a fourth function has been attributed to the skeleton: an endocrine organ. The organic matrix of bone is formed mostly of collagen, but also non-collagenous proteins. Hydroxyapatite crystals bind to both types of proteins. Most components of the bone matrix are synthesized and secreted by osteoblasts.  Resorption of the bone matrix is required for adaptation to growth, repair and mineral mobilization. This process is performed by the macrophage-related osteoclast. Bone is remodeled throughout life through a coordinated sequence of events which involve the sequential actions of osteoclasts and osteoblasts, replacing old bone with new bone. In the normal adult skeleton, remodeling is coupled such that the level of resorption is equal to the level of formation and bone density remains constant. Intramembranous ossification is the process by which flat bones are formed. For this process, osteoblasts differentiate directly from mesenchymal cells to form the bone matrix. Long bones are formed by endochondral ossification, which is characterized by the presence of a cartilaginous model in which chondrocytes differentiate and mineralized cartilage is replaced with bone through remodeling.

 

INTRODUCTION

 

Bone, a specialized and mineralized connective tissue, makes up, with cartilage, the skeletal system, which serves three main functions: A mechanical function as support and site of muscle attachment for locomotion; a protective function for vital organs and bone marrow; and finally a metabolic function as a reserve of calcium and phosphate used for the maintenance of serum homeostasis, which is essential to life.  Recently, a fourth important function has been attributed to bone tissue – that of an endocrine organ.  Bone cells produce fibroblast growth factor 23 (FGF23) and osteocalcin. FGF23 regulates phosphate handling in the kidney and osteocalcin regulates energy and glucose metabolism (see below) (1,2).

 

In this chapter the anatomy and cell biology of bone is described as well as the mechanisms of bone remodeling, development, and growth. Remodeling is the process by which bone is turned-over, allowing the maintenance of the shape, quality, and amount of the skeleton. This process is characterized by the coordinated actions of osteoclasts and osteoblasts, organized in bone multicellular units (BMUs) which follow an Activation-Resorption-Formation sequence of events. During embryonic development, bone formation occurs by two different means: intramembranous ossification and endochondral ossification. Bone Growth is a term used to describe the changes in bone structure once the skeleton is formed and during the period of skeletal growth and maturation.

 

BONE AS AN ORGAN: MACROSCOPIC ORGANIZATION

 

Two types of bones are found in the skeleton: flat bones (skull bones, scapula, mandible, and ileum) and long bones (tibia, femur, humerus, etc.). These are derived by two distinct types of development: intramembranous and endochondral, respectively, although the development and growth of long bones actually involve both cellular processes. The main difference between intramembranous and endochondral bone formation is the presence of a cartilaginous model, or anlage, in the latter.

Long bones have two wider extremities (the epiphyses), a cylindrical hollow portion in the middle (the midshaft or diaphysis), and a transition zone between them (the metaphysis). The epiphysis on the one hand and the metaphysis and midshaft on the other hand originate from two independent ossification centers, and are separated by a layer of cartilage, the epiphyseal cartilage (which also constitutes the growth plate) during the period of development and growth. This layer of proliferative cells and expanding cartilage matrix is responsible for the longitudinal growth of bones; it progressively mineralizes and is later remodeled and replaced by bone tissue by the end of the growth period (see section on Skeletal Development). The external part of the bones is formed by a thick and dense layer of calcified tissue, the cortex (compact bone) which, in the diaphysis, encloses the medullary cavity where the hematopoietic bone marrow is housed. Toward the metaphysis and the epiphysis, the cortex becomes progressively thinner and the internal space is filled with a network of thin, calcified trabeculae forming the cancellous or trabecular bone. The spaces enclosed by these thin trabeculae are also filled with hematopoietic bone marrow and are continuous with the diaphyseal medullary cavity. The outer cortical bone surfaces at the epiphyses are covered with a layer of articular cartilage that does not calcify.

 

Bone is consequently in contact with the soft tissues along two surfaces: an external surface (the periosteal surface) and an internal surface (the endosteal surface). These surfaces are lined with osteogenic cells along the periosteum and the endosteum, respectively.

 

Cortical and trabecular bone are made up of the same cells and the same matrix elements, but there are structural and functional differences. The primary structural difference is quantitative: 80% to 90% of the volume of compact bone is calcified, whereas only 15% to 25% of the trabecular volume is calcified (the remainder being occupied by bone marrow, blood vessels, and connective tissue). The result is that 70% to 85% of the interface with soft tissues is at the endosteal bone surface, including all trabecular surfaces, leading to the functional difference: the cortical bone fulfills mainly a mechanical and protective function and the trabecular bone mainly a metabolic function, albeit trabeculae definitively participate in the biomechanical function of bones, particularly in bones like the vertebrae.

 

Recently, more attention has been given to cortical bone structure since cortical porosity is intimately linked to the remodeling process as well as to bone strength.  Indeed, an increase in cortical porosity is associated with an increase in fragility fractures (3).

 

BONE AS A TISSUE: BONE MATRIX AND MINERAL

 

Bone matrix consists mainly of type I collagen fibers (approximately 90%) and non-collagenous proteins. Within lamellar bone, the fibers are forming arches for optimal bone strength. This fiber organization allows the highest density of collagen per unit volume of tissue. The lamellae can be parallel to each other if deposited along a flat surface (trabecular bone and periosteum), or concentric if deposited on a surface surrounding a channel centered on a blood vessel (cortical bone Haversian system). Spindle- or plate-shaped crystals of hydroxyapatite [3Ca 3 (PO 42 ·(OH) 2] are found on the collagen fibers, within them, and in the matrix around. They tend to be oriented in the same direction as the collagen fibers.

When bone is formed very rapidly during development and fracture healing, or in tumors and some metabolic bone diseases, there is no preferential organization of the collagen fibers. They are then not as tightly packed and found in somewhat randomly oriented bundles: this type of bone is called woven bone, as opposed to lamellar bone. Woven bone is characterized by irregular bundles of collagen fibers, large and numerous osteocytes, and delayed, disorderly calcification which occurs in irregularly distributed patches. Woven bone is progressively replaced by mature lamellar bone during the remodeling process that follows normally development or healing (see below).

 

Numerous non-collagenous proteins present in bone matrix have been purified and sequenced, but their role has been only partially characterized (Table 1) (4). Most non-collagenous proteins within the bone matrix are synthesized by osteoblasts, but not all: approximately a quarter of the bone non-collagenous proteins are plasma proteins which are preferentially absorbed by the bone matrix, such as a 2-HS-glycoprotein, which is synthesized in the liver. The major non-collagenous protein produced is osteocalcin, which makes up 1% of the matrix, and may play a role in calcium binding and stabilization of hydroxyapatite in the matrix and/or regulation of bone formation, as suggested by increased bone mass in osteocalcin knockout mice. Another negative regulator of bone formation found in the matrix is matrix gla protein, which appears to inhibit premature or inappropriate mineralization, as demonstrated in a knockout mouse model. In contrast to this, biglycan, a proteoglycan, is expressed in the bone matrix, and positively regulates bone formation, as demonstrated by reduced bone formation and bone mass in biglycan knockout mice.  Osteocalcin has recently been shown to have an important endocrine function acting on the pancreatic beta cell.  Its hormonally active form (undercarboxylated osteocalcin, stimulates insulin secretion and enhances insulin sensitivity in adipose tissues and muscle, improving glucose utilization in peripheral tissues (2).

 

Table 1. Non-Collagenous Proteins in Bone (4)

PROTEIN

MW

ROLE

Osteonectin (SPARC)

32K

Calcium, apatite and matrix protein binding

Modulates cell attachment

α-2-HS-Glycoprotein

46-67K

Chemotactic for monocytes

Mineralization via matrix vesicles

Osteocalcin (Bone GLA protein)

6K

Involved in stabilization of hydroxyapatite

Binding of calcium

Chemotactic for monocytes

Regulation of bone formation

Matrix-GLA-protein

9K

Inhibits matrix mineralization

Osteopontin

(Bone Sialoprotein I)

50K

Cell attachment (via RGD sequence)

Calcium binding

Bone Sialoprotein II

75K

Cell attachment (via RGD sequence)

Calcium binding

24K Phosphoprotein

(α-1(I) procollagen N-propeptide)

24K

Residue from collagen processing

Biglycan (Proteoglycan I)

45K core

Regulation of collagen fiber growth

Mineralization and bone formation

Growth factor binding

Decorin (Proteoglycan II)

36K core + side chains

Collagen fibrillogenesis

Growth factor binding

Thrombospondin & Fibronectin

 

Cell attachment (via RGD sequence)

Growth factor binding

Hydroxyapatite formation

Others (including proteolipids

 

Mineralization

Growth Factors

IGFI & IGFII

TGFβ

Bone morphogenetic proteins (BMPs)

 

Differentiation, proliferation and activity of osteoblasts

Induction of bone and cartilage in osteogenesis and fracture repair

 

CELLULAR ORGANIZATION WITHIN THE BONE MATRIX: OSTEOCYTES

 

The calcified bone matrix is not metabolically inert, and cells (osteocytes) are found embedded deep within the bone in small lacunae (Figure 1). All osteocytes are derived from bone forming cells (osteoblasts) which have been trapped in the bone matrix that they produced and which became calcified. Even though the metabolic activity of the osteoblast decreases dramatically once it is fully encased in bone matrix, now becoming an osteocyte, these cells still produce matrix proteins.

 

Figure 1. Wnt signaling determines the cell fate of mesenchymal progenitor cells and regulates bone formation and resorption. The Wnt canonical pathway represses adipocyte differentiation and chondrocyte differentiation from progenitor cells, whereas it is required for the transition of chondrocytes to hypertrophy. In contrast, Wnt pathway activation promotes the osteoblast cell lineage by controlling proliferation, maturation, terminal differentiation, and bone formation. Differentiated osteoblasts and/or osteocytes produce Wnt inhibitors such as Dickkopf (Dkk1) and sclerostin (Sost) proteins as a negative feedback control of osteoblast differentiation and function. Wnt signaling also induces osteoblasts to produce more osteoprotegerin (OPG), increasing the ratio of OPG to receptor activator of NF-κB ligand (RANKL) to decrease osteoclast differentiation and bone resorption.

 

Osteocyte morphology varies according to cell age and functional activity. A young osteocyte has most of the ultrastructural characteristics of the osteoblast from which it was derived, except that there has been a decrease in cell volume and in the importance of the organelles involved in protein synthesis (rough endoplasmic reticulum, Golgi). An older osteocyte, located deeper within the calcified bone, shows a further decrease in cell volume and organelles, and an accumulation of glycogen in the cytoplasm. These cells synthesize small amounts of new bone matrix at the surface of the osteocytic lacunae, which can subsequently calcify. Osteocytes express, in low levels, a number of osteoblast markers, including osteocalcin, osteopontin, osteonectin and the osteocyte marker E11.

 

Osteocytes have numerous long cell processes rich in microfilaments, which are in contact with cell processes from other osteocytes (there are frequent gap junctions), or with processes from the cells lining the bone surface (osteoblasts or flat lining cells). These processes are organized during the formation of the matrix and before its calcification; they form a network of thin canaliculi permeating the entire bone matrix. Osteocytic canaliculi are not distributed evenly around the cell, but are mainly directed toward the bone surface. Between the osteocyte's plasma membrane and the bone matrix itself is the periosteocytic space. This space exists both in the lacunae and in the canaliculi, and it is filled with extracellular fluid (ECF), the only source of nutrients, cytokines and hormones for the osteocyte. ECF flow through the canalicular network is altered during bone matrix compression and tension and is believed not only to allow exchanges with the extracellular fluids in the surrounding tissues but also to create shear forces that are directly involved in mechanosensing and regulation of bone remodeling. Current understanding of mechanotransduction is based upon the presence of a mechanosensing cilium at the level of the osteocyte’s cell body, capable of detecting the changes in fluid flow determined by mechanical loading of bone. In turn, the activation of the mechanosensing cilium may determine the local concentration of cytokines capable of regulating bone formation and/or bone resorption, such as RANKL, OPG or sclerostin (see below).

 

Indeed, given the structure of the network and the location of osteocytes within lacunae where ECF flow can be detected, it is likely that osteocytes respond to bone tissue strain and influence bone remodeling activity by recruiting osteoclasts to sites where bone remodeling is required. Osteocyte cellular activity is increased after bone loading; studies in cell culture have demonstrated increased calcium influx and prostaglandin production by osteocytes after mechanical stimulation, but there is no direct evidence for osteocytes signaling to cells on the bone surface in response to bone strain or microdamage to date. Osteocytes can become apoptotic and their programmed cell death may be one of the critical signals for induction of bone remodeling. Ultimately, the fate of the osteocyte is to be phagocytosed and digested together with the other components of bone during osteoclastic bone resorption. The recent ability to isolate and culture osteocytes, as well as the creation of immortalized osteocytic cell lines now allows the study of these cells at the molecular level and this is expected to significantly further our understanding of their role in bone biology and disease.(5) In particular, the discoveries that osteocytes can secrete the Wnt antagonist sclerostin and that this secretion is inhibited both by PTH treatment and by mechanical loading establishes the first direct link between biomechanics, endocrine hormones, bone formation and osteocytes. Similarly, osteocytes can secrete RANKL and OPG, contributing also to the regulation of bone resorption. Thus, osteocytes are emerging as the critical cell type linking mechanical forces in bone to the regulation of bone mass and shape through remodeling.

 

THE OSTEOBLAST AND BONE FORMATION  

 

The osteoblast is the bone lining cell responsible for the production of the bone matrix constituents, collagen and non-collagenous proteins (Figure 2). Osteoblasts never appear or function individually but are always found in clusters of cuboidal cells along the bone surface (~100–400 cells per bone-forming site).

Figure 2. Osteocyte. Electron micrograph of an osteocyte within a lacuna in calcified bone matrix. The cell has a basal nucleus, cytoplasmic extensions, and well-developed Golgi and endoplasmic reticulum.

 

Osteoblasts do not operate in isolation and gap junctions are often found between osteoblasts working together on the bone surface. Osteoblasts also appear to communicate with the osteocyte network within the bone matrix (see above), since cytoplasmic processes on the secreting side of the osteoblast extend deep into the osteoid matrix and are in contact with processes of the osteocytes dwelling there.

 

At the light microscope level, the osteoblast is characterized morphologically by a round nucleus at the base of the cell (away from the bone surface), an intensely basophilic cytoplasm, and a prominent Golgi complex located between the nucleus and the apex of the cell. Osteoblasts are always found lining the layer of bone matrix that they are producing, but before it is calcified (osteoid tissue). Osteoid tissue exists because of a time lag of approximately 10 days between matrix formation and its subsequent calcification. Behind the osteoblast can usually be found one or two layers of cells: activated mesenchymal cells and preosteoblasts (see below). A mature osteoblast does not divide.

 

At the ultrastructural level, the osteoblast is characterized by the presence of a well-developed rough endoplasmic reticulum with dilated cisternae and a dense granular content, and the presence of a large circular Golgi complex comprising multiple Golgi stacks. These organelles are involved in the major activity of the osteoblast: the production and secretion of collagenous and non-collagenous bone matrix proteins, including type I collagen. Osteoblasts also produce a range of growth factors under a variety of stimuli, including the insulin-like growth factors (IGFs), platelet-derived growth factors (PDGFs), basic fibroblast growth factor (bFGF), transforming growth factor-beta (TGFb), a range of cytokines, the bone morphogenetic proteins (BMPs and Wnts.(3) Osteoblast activity is regulated in an autocrine and paracrine manner by these growth factors, whose receptors can be found on osteoblasts, as well as receptors for a range of endocrine hormones. Classic endocrine receptors include receptors for parathyroid hormone/ parathyroid hormone related protein receptor, thyroid hormone, growth hormone, insulin, progesterone and prolactin. Osteoblastic nuclear steroid hormone receptors include receptors for estrogens, androgens, vitamin D 3 and retinoids. Receptors for paracrine and autocrine effectors include those for epidermal growth factor (EGF), IGFs, PDGF, TGFb, interleukins, FGFs, BMPs and Wnts (LRP5/6 and Frizzled) (6,7) Osteoblasts also have receptors for several adhesion molecules (integrins) involved in cell attachment to the bone surface.

 

Among the cytokines secreted by the osteoblast are the main regulators of osteoclast differentiation, i.e. M-CSF, RANKL and osteoprotegerin (OPG) (8,9). M-CSF is essential in inducing the commitment of monocytes to the osteoclast lineage whereas RANKL promotes the differentiation and activity of osteoclasts (see below).

 

Osteoblasts originate from local pluripotent mesenchymal stem cells, either bone marrow stromal stem cells (endosteum) or connective tissue mesenchymal stem cells (periosteum). These precursors, with the right stimulation, undergo proliferation and differentiate into preosteoblasts, at which point they are committed to differentiate into mature osteoblasts.

 

The committed preosteoblast is located in apposition to the bone surface, and usually present in layers below active mature osteoblasts. They are elliptical cells, with an elongated nucleus, and are still capable of proliferation. Preosteoblasts lack the well-developed protein synthesizing capability of the mature osteoblast, and do not have the characteristically localized, mature rough endoplasmic reticulum or Golgi apparatus of the mature cell.

 

The development of the osteoblast phenotype is gradual, with a defined sequence of gene expression and cell activity during development and maturation, controlled by a sequence of transcription factors and cytokines (Figure 3).

Figure 3. Osteoblasts and Osteoid Tissue. A: Light micrograph of a group of osteoblasts producing osteoid; note the newly embedded osteocyte. B: Electron micrograph of 3 osteoblasts covering a layer of mineralizing osteoid tissue. Note the prominent Golgi and endoplasmic reticulum characteristic of active osteoblasts. The black clusters in the osteoid tissue are deposits of mineral. C: Osteoblast Lineage. Osteoblasts originate from undifferentiated mesenchymal cells which are capable of proliferation and which may differentiate into one of a range of cell types. The preosteoblast is also capable of proliferation and may be already committed to an osteoblast phenotype. The mature osteoblast no longer proliferates, but can differentiate further into an osteocyte once embedded in the bone matrix, or to a lining cell on the bone surface.

 

Two transcription factors, Runx2 and Osterix (Osx), which is downstream of Runx2, are absolutely required for osteoblast differentiation. Runx2 is expressed in mesenchymal condensations and chondrocytes, in addition to osteoblasts. Runx2 target genes include several genes expressed by the mature osteoblast including osteocalcin, bone sialoprotein, osteopontin and collagen a1(I), as well as the Runx2 gene itself. Osx may be mostly important for pushing precursors cells away from the chondrocyte and into the osteoblast lineage.

 

The most important breakthrough in the understanding of the regulation of bone formation in recent years, is the finding of a clear link between LRP5, a co-receptor for Wnts, and bone mass in humans and in mice. Loss of function in LRP5 leads to the Osteoporosis Pseudo-Glioma syndrome (OPPG), with extremely low bone mass, whereas gain of function leads to the High Bone Mass (HBM) phenotype in humans. In addition, deletion mutations in the gene encoding sclerostin (Sost), another endogenous inhibitor of the Wnt pathway, also lead to osteosclerotic phenotypes (Sclerosteosis, Van Buchem syndrome).(7) These findings have opened a whole new field of investigation both in terms of understanding the mechanism that regulate osteoblasts and their bone-matrix secreting activity and in terms of drug discovery in the hope to target one component of the Wnt signaling pathway and thereby increase bone mass in osteoporotic patients. Of note, in 2019, the FDA approved romosozumab, a monoclonal antibody to sclerostin, for the treatment of postmenopausal women with osteoporosis at high risk for fracture.

 

Toward the end of the matrix secreting period, a further step is involved in osteoblast maturation. Approximately 15% of the mature osteoblasts become encapsulated in the new bone matrix and differentiate into osteocytes. In contrast, some cells remain on the bone surface, becoming flat lining cells.

 

Mechanism of Bone Formation

 

Bone formation occurs by three coordinated processes: the production of osteoid matrix, its maturation, and the subsequent mineralization of the matrix. In normal adult bone, these processes occur at the same rate, so that the balance between matrix production and mineralization is equal. Initially, osteoblasts deposit collagen rapidly, without mineralization, producing a thickening osteoid seam. This is followed by an increase in the mineralization rate to equal the rate of collagen synthesis. In the final stage, the rate of collagen synthesis decreases, and mineralization continues until the osteoid seam is fully mineralized. This time lag (termed the mineralization lag time or osteoid maturation period) appears to be required for osteoid to be modified so it is able to support mineralization. While this delay is not yet understood, it is likely that either collagen cross-linking occurs or an inhibitor of mineralization, such as matrix gla protein, is removed during this time, thus allowing mineralization to proceed.

 

To initiate mineralization in woven bone, or in growth plate cartilage, high local concentrations of Ca2+ and PO43- ions must be reached in order to induce their precipitation into amorphous calcium phosphate, leading to hydroxyapatite crystal formation. This is achieved by membrane-bound matrix vesicles, which originate by budding from the cytoplasmic processes of the chondrocyte or the osteoblast and are deposited within the matrix during its formation. In the matrix, these vesicles are the first structure wherein hydroxyapatite crystals are observed. The membranes are very rich in alkaline phosphatases and in acidic phospholipids, which hydrolyze inhibitors of calcification in the matrix including pyrophosphate and ATP allowing condensation of apatite crystals. Once the crystals are in the matrix environment, they will grow in clusters which later coalesce to completely calcify the matrix, filling the spaces between and within the collagen fibers. In adult lamellar bone, matrix vesicles are not present, and mineralization occurs in an orderly manner through progression of the mineralization front into the osteoid tissue.

 

THE OSTEOCLAST AND BONE RESORPTION

 

The osteoclast is the bone lining cell responsible for bone resorption (Figure 4). The osteoclast is a giant multinucleated cell, up to 100mm in diameter and containing four to 20 nuclei. It is usually found in contact with a calcified bone surface and within a lacuna (Howship's lacunae) that is the result of its own resorptive activity. It is possible to find up to four or five osteoclasts in the same resorptive site, but there are usually only one or two. Under the light microscope, the nuclei appear to vary within the same cell: some are round and euchromatic, and some are irregular in contour and heterochromatic, possibly reflecting asynchronous fusion of mononuclear precursors. The cytoplasm is "foamy" with many vacuoles. The zone of contact with the bone is characterized by the presence of a ruffled border with dense patches on each side (the sealing zone).

Figure 4. Osteoclasts and the Mechanism of Bone Resorption. A: Light micrograph and B: electron micrograph of an osteoclast, demonstrating the ruffled border and numerous nuclei. C: Osteoclastic resorption. The osteoclast forms a sealing zone via integrin mediated attachment to specific peptide sequences within the bone matrix, forming a sealed compartment between the cell and the bone surface. This compartment is acidified such that an optimal pH is reached for lysosomal enzyme activity and bone resorption.

 

Characteristic ultrastructural features of this cell are abundant Golgi complexes around each nucleus, mitochondria, and transport vesicles loaded with lysosomal enzymes. The most prominent features of the osteoclast are, however, the deep foldings of the plasma membrane in the area facing the bone matrix (ruffled border) and the surrounding zone of attachment (sealing zone). The sealing zone is formed by a ring of focal points of adhesion (podosomes) with a core of actin and several cytoskeletal and regulatory proteins around it, that attach the cell to the bone surface, thus sealing off the subosteoclastic bone-resorbing compartment. The attachment of the cell to the matrix is performed via integrin receptors, which bind to specific RGD (Arginine-Glycine-Aspartate) sequences found in matrix proteins (see Table 1). The plasma membrane in the ruffled border area contains proteins that are also found at the limiting membrane of lysosomes and related organelles, and a specific type of electrogenic vacuolar proton ATPase involved in acidification. The basolateral plasma membrane of the osteoclast is specifically enriched in Na+, K+-ATPase (sodium pumps), HCO 3 - /Cl -exchangers, and Na+/H+ exchangers and numerous ion channels (10).

 

Lysosomal enzymes such as tartrate resistant acid phosphatase and cathepsin K are actively synthesized by the osteoclast and are found in the endoplasmic reticulum, Golgi, and many transport vesicles. The enzymes are secreted, via the ruffled border, into the extracellular bone-resorbing compartment where they reach a sufficiently high extracellular concentration because this compartment is sealed off. The transport and targeting of these enzymes for secretion at the apical pole of the osteoclast involves mannose-6-phosphate receptors. Furthermore, the cell secretes several metalloproteinases such as collagenase (MMP-13) and gelatinase B (MMP-9) which appear to be involved in preosteoclast migration to the bone surface as well as bone matrix digestion. Among the key enzymes being synthesized and secreted by the osteoclast is cathepsin K, an enzyme capable or degrading collagen at low pH and a target for inhibition of bone resorption. (11)

 

Attachment of the osteoclast to the bone surface is essential for bone resorption. This process involves transmembrane adhesion receptors of the integrin. Integrins attach to specific amino acid sequences (mostly RGD sequences) within proteins in or at the surface of the bone matrix. In the osteoclast, avb3 (vitronectin receptor), a2b1 (collagen receptor) and avb5 integrins are predominantly expressed. Without cell attachment the acidified microenvironment cannot be established and the osteoclast cannot be highly mobile, a functional property associated with the formation of podosomes.

 

After osteoclast adhesion to the bone matrix, avb3 binding activates cytoskeletal reorganization within the osteoclast, including cell spreading and polarization. In most cells, cell attachment occurs via focal adhesions, where stress fibers (bundles of microfilaments) anchor the cell to the substrate. In osteoclasts, attachment occurs via podosomes. Podosomes are more dynamic structures than focal adhesions, and occur in cells that are highly motile. It is the continual assembly and disassembly of podosomes that allows osteoclast movement across the bone surface during bone resorption. Integrin signaling and subsequent podosome formation is dependent on a number of adhesion kinases including the proto-oncogene src, which, while not required for osteoclast maturation, is required for osteoclast function, as demonstrated by osteopetrosis in the src knockout mouse. Pyk2, another member of the focal adhesion kinase family is also activated by avb3 during osteoclast attachment, and is required for bone resorption.(10) Several actin-regulatory proteins have also been shown to be present in podosomes and required for bone resorption, again pointing to the importance of integrin signaling and podosome assembly and disassembly in the function of osteoclasts. (12)

 

Osteoclasts resorb bone by acidification and proteolysis of the bone matrix and hydroxyapatite crystals encapsulated within the sealing zone. Carbonic anhydrase type II produces hydrogen ions within the cell, which are then pumped across the ruffled border membrane via proton pumps located in the basolateral membrane, thereby acidifying the extracellular compartment. The protons are highly concentrated in the cytosol of the osteoclast; ATP and CO2 are provided by the mitochondria. The basolateral membrane activity exchanges bicarbonate for chloride, thereby avoiding alkalization of the cytosol. K+ channels in the basolateral domain and Cl - channels in the apical ruffled border ensure dissipation of the electrogenic gradients generated by the vacuolar H+-ATPase The basolateral sodium pumps might be involved in secondary active transport of calcium and/or protons in association with a Na + /Ca 2+ exchanger and/or a Na+/H+ antiport. Genetic mutations in several of these components of the acidification and ion transport systems have been shown to be associated with osteopetrosis (defective bone resorption by osteoclasts) in humans and in mice.

 

The first process during bone matrix resorption is mobilization of the hydroxyapatite crystals by digestion of their link to collagen via the non-collagenous proteins and the low pH dissolves the hydroxyapatite crystals, exposing the bone matrix. Then the residual collagen fibers are digested by cathepsin K, now at optimal pH. The residues from this extracellular digestion are either internalized, or transported across the cell and released at the basolateral domain. Residues may also be released during periods of sealing zone relapse, as probably occurs during osteoclast motility, and possibly induced by a calcium sensor responding to the rise of extracellular calcium in the bone-resorbing compartment.

 

The regulation of bone resorption is mostly mediated by the action of hormones on stromal cells, osteoblasts and osteocytes. For example, PTH can stimulate osteoblastic production of M-CSF, RANKL, OPG or IL-6, which then act directly on the osteoclast (5,6).

 

Origin and Fate of the Osteoclast (6)

 

The osteoclast derives from cells in the mononuclear phagocyte lineage (Figure 5). Their differentiation requires the transcription factors PU-1 and MiTf at early stages, committing the precursors into the myeloid lineage. M-CSF is then required to engage the cells in the monocyte lineage and ensure their proliferation and the expression of the RANK receptor. At that stage, the cells require the presence of RANKL, a member of the TNF family of cytokines produced by stromal cells, to truly commit to the osteoclast lineage and progress in their differentiation program. This step also requires expression of TRAF6, NFκB, c-Fos and NFAT c1, all downstream effectors of RANK signaling. Although this differentiation occurs at the early promonocyte stage, monocytes and macrophages already committed to their own lineage might still be able to form osteoclasts under the right stimuli. Despite its mononuclear phagocytic origin, the osteoclast membrane express distinct markers: it is devoid of Fc and C 3 receptors, as well as of several other macrophage markers; like mononuclear phagocytes, however, the osteoclast is rich in nonspecific esterases, synthesizes lysozyme, and expresses CSF-1 receptors. Monoclonal antibodies have been produced that recognize osteoclasts but not macrophages. The osteoclast, unlike macrophages, also expresses, millions of copies of the RANK, calcitonin, and vitronectin (integrin avb3) receptors. Whether it expresses receptors for parathyroid hormone, estrogen, or vitamin D is still controversial. Dendritic cell-specific transmembrane protein (DC-STAMP) is currently considered to be the master regulator of osteoclastogenesis.  Knock out of DC-STAMP completely abrogates cell-cell fusion during osteoclastogenesis; osteoclasts isolated from DC-STAMP knock-out mice are mononucleated. (13) Another important factor involved in cell fusion is Pin 1, an enzyme that specifically recognizes the peptide bond between phosphorylated serine or threonine and proline.  Pin 1 regulates cell fusion during osteoclastogeneis by suppressing DC-STAMP. (14,15) Recent evidence suggest that the osteoclast undergoes apoptosis after a cycle of resorption, a process favored by estrogens, possibly explaining the increased bone resorption after gonadectomy or menopause.

Figure 5. Osteoclast Life Cycle. The osteoclast is derived from a mononuclear hematopoietic precursor cell which, upon activation, fuses with other precursors to form a multinucleated osteoclast. The osteoclast first attaches to the bone surface then commences resorption. After a cycle of bone resorption, the osteoclast undergoes apoptosis.

 

Relations to the Immune System (Osteoimmunology)

 

In the last few years it has been recognized that, in part due to the link between the osteoclast, macrophages and dendritic cells (all three belong to the same cell lineage), osteoclasts are regulated by and share regulatory mechanisms with cells of the immune system. For instance, T cells can produce locally RANKL, activating osteoclastogenesis. B cells may share a common precursor with and regulate osteoclast precursors. RANKL signaling and “immunoreceptor tyrosine-based activation motif” (ITAM) signals cooperate in osteoclastogenesis (16).

 

BONE REMODELING

 

Bone remodeling is the process by which bone is turned over; it is the result of the activity of the bone cells at the surfaces of bone, mainly the endosteal surface (which includes all trabecular surfaces). Remodeling is traditionally classified into two distinct types: Haversian remodeling within the cortical bone and endosteal remodeling along the trabecular bone surface. This distinction is more morphological than physiological because the Haversian surface is an extension of the endosteal surface and the cellular events during these two remodeling processes follow exactly the same sequence.

 

The Remodeling Sequence

 

Bone formation and bone resorption do not occur along the bone surface at random: they are coordinated as part of the turnover mechanism by which old bone is replaced by new bone, providing an opportunity to change the shape, architecture or density of the skeleton. In the normal adult skeleton, bone formation only occurs, for the most part, where bone resorption has already occurred. This basic principle of cellular activity at the remodeling site constitutes the Activation-Resorption-Reversal-Formation (ARRF) sequence (Figure 6).

Figure 6. The Bone Remodeling Sequence. The Activation-Resorption-Reversal-Formation cycle of bone remodeling as it occurs in trabecular bone. See text for details.

 

Under some signal, today considered to emanate from osteocytes, a locally acting factor released by lining cells, osteocytes, marrow cells, or in response to bone deformation or fatigue-related microfracture, a group of preosteoclasts are activated. These mononuclear cells attach to the bone via avb3 integrins and fuse to form a multi-nucleated osteoclast which will, in a definite area of the bone surface, resorb the bone matrix. After resorption of the bone, and osteoclast detachment, uncharacterized mononuclear cells cover the surface and a cement line is formed. The cement line marks the limit of bone resorption, and acts to cement together the old and the new bone. This is termed the reversal phase, and is followed by a period of bone formation. Preosteoblasts are activated, proliferate and differentiate into osteoblasts, which move onto the bone surface, forming an initial matrix (osteoid), which becomes mineralized after a time lag (the osteoid maturation period). The basic remodeling sequence is therefore Activation-Resorption-Formation; it is performed by a group of cells called the Basic Multicellular Unit (BMU). The complete remodeling cycle takes about 3 months in humans (Figure 7).

Figure 7. Bone Growth and Remodeling at the Growth Plate. The light micrograph demonstrates the zones of chondrocyte differentiation, as well as mineralization (black). The schematic representation shows the cellular events occurring at the growth plate in long bones. Note that bone formation in this process occurs by repeated Activation-Resorption-Formation cycles of bone remodeling beginning with the calcified cartilage matrix.

 

For decades, the reversal phase of the remodeling cycle was the least well understood.  It was recognized that during this phase, the resorption cavity was occupied by mononucleated cells, but the nature of these cells was unknown (17).  Recent work by Delaisse and colleagues (18) has definitively identified the reversal cells as belonging to the osteogenic lineage, expressing classic osteoblast markers: Runx2, ALP, and Col3. By applying immunocytochemistry and histomorphometry to femur and fibula samples harvested from teenagers and adults, these investigators have provided a much more complete picture of the temporal sequence of cellular events that occur between the start of resorption and the onset of formation.  In order to visualize the entire sequence of events, they analyzed longitudinal sections of evolving Haversian systems. They observed osteoclasts at two distinct locations: at the cutting cone (referred to as primary osteoclasts) and close to the reversal cells (referred to as secondary osteoclasts). The presence of secondary osteoclasts in the reversal phase suggests that bone resorption continues during this phase, which has been renamed the resorption-reversal phase. The authors have concluded that the primary osteoclasts are responsible for drilling the tunnel (initial resorption) and the secondary osteoclasts work to increase its diameter by radial resorption. This radial resorption was shown to be a major contributor to the overall amount of bone resorbed in each BMU. This new and more complete model of the resorption-reversal phase will lead to enhanced understanding of the delicate and all-important balance between resorption and formation (Figure 8).

 

Figure 8. Cartoon of a bone remodeling unit in cortical bone, showing the change in the designation of the reversal phase as a result of recent new findings. IR = initial resorption; RR = radial resorption; Og = osteoprogenitor cell; Oc = osteoclast. (17)

 

For many years it has been accepted that bone resorption and formation are coupled in the same way that bone matrix formation and calcification are linked. In other words, in the normal adult skeleton, the coupling of bone resorption and formation in remodeling results in equal levels of cellular activity so that bone turnover is balanced: the volume of bone resorbed is equal to the volume formed. This paradigm implies that, for example, a reduction in osteoblast activity would affect a similar reduction in osteoclast activity such that bone volume is maintained. Conversely, an increase in osteoclast activity should be compensated by an increase in osteoblasts and bone formation, resulting in a maintained bone mass with a high turnover, as in hyperparathyroidism for instance. Similarly, decreased osteoclast numbers or bone resorption activity should be associated with a decrease in bone formation, maintaining bone mass but with a decreased turnover rate.

 

Although this “coupling” may indeed function in most cases, there are multiple examples of dysfunctions, such as in osteoporosis or osteopetrosis for instance. It now appears that the number of osteoclasts rather than their strict activity is a key determinant of subsequent bone formation. This suggests that factors generated locally by the osteoclast, either directly or through resorption of the bone matrix, are capable of stimulating bone formation (19).

 

Haversian vs Endosteal Bone Remodeling

 

As previously mentioned, although cortical bone is anatomically different to trabecular bone, its remodeling occurs following the same sequence of events. The major difference is that while the average thickness of a trabecula is 150-200 microns, the average thickness of the cortex is of the order of 1-10 mm. There are no blood vessels in the trabeculae but the bone envelope system and the osteocyte network are able to carry out enough gaseous exchange, being always relatively close to the surface and the highly vascularized marrow. Consequently, bone remodeling in the trabecular bone will take place along the trabecular surface. On the other hand, the cortical bone itself needs to be vascularized. Blood vessels are first embedded during the histogenesis of cortical bone; the blood vessel and the bone which surrounds it is then called a primary osteon. Later, cortical bone remodeling will be initiated either along the surface of these vascular channels, or from the endosteal surface of the cortex. The remodeling process in cortical bone also follows the ARF sequence. Osteoclasts excavate a tunnel, creating a cutting cone. Again, there is a reversal phase, where mononuclear cells attach and lay down a cement line. Osteoblasts are then responsible for closing the cone, leaving a central canal, centered on blood vessels and surrounded by concentric bone lamellae. For mechanical reasons, all these Haversian systems are oriented along the longitudinal axis of the bone.

 

Bone Turnover and Skeletal Homeostasis

 

In a normal young adult, about 30% of the total skeletal mass is renewed every year (half-life = 20 months). In each remodeling unit, osteoclastic bone resorption lasts about 3 days, the reversal 14 days, and bone formation 70 days (total = 87 days). The linear bone formation rate is 0.5mm/day. During this process, about 0.01mm of bone is renewed in one given remodeling unit. Theoretically, with balanced matrix deposition and calcification as well as a balance between osteoclast and osteoblast activity, the amount of bone formed in each remodeling unit (and therefore in the total skeleton) equals the amount of bone which was previously resorbed. Thus, the total skeletal mass remains constant. This skeletal homeostasis relies upon a normal remodeling activity. The rate of activation of new remodeling units would then determine only the turnover rate.

 

SKELETAL DEVELOPMENT-HISTOGENESIS 

 

Bone development is achieved through the use of two distinct processes, intramembranous and endochondral bone formation. In the first, mesenchymal cells differentiate directly into osteoblasts whereas in the second mesenchymal cells differentiate into chondrocytes and it is only secondarily that osteoblasts appear and form bone around the cartilage model. Through a process that involves bone resorption by osteoclasts, vascular invasion and resorption of calcified cartilage, the cartilage model is progressively replaced by osteoblast-derived bone matrix. Bone is then remodeled through continuous cycles of bone resorption and formation, thereby allowing shape changes and adaptation to the local and systemic environment.

 

Intramembranous Ossification

 

During intramembranous ossification, a group of mesenchymal cells within a highly vascularized area of the embryonic connective tissue proliferates, forming early mesenchymal condensations within which cells differentiate directly into osteoblasts. Bone Morphogenetic Proteins, as well as FGFs appear to be essential in the process of mesenchymal cell condensation. The newly differentiated osteoblasts will synthesize a woven bone matrix, while at the periphery, mesenchymal cells continue to differentiate into osteoblasts. Blood vessels are incorporated between the woven bone trabeculae and will form the hematopoietic bone marrow. Later this woven bone will be remodeled through the classical remodeling process, resorbing woven bone and progressively replacing it with mature lamellar bone.

 

Endochondral Ossification

 

Development of long bones begins with the formation of a cartilage anlage (model) from a mesenchymal condensation, as in intramembranous ossification. (Figure 9). But here, under the influence of a different set of factors and local conditions, mesenchymal cells undergo division and differentiate into prechondroblasts and then into chondroblasts rather than directly into osteoblasts. These cells secrete the cartilaginous matrix, where the predominant collagen type is collagen type II. Like osteoblasts, the chondroblasts become progressively embedded within their own matrix, where they lie within lacunae, and they are then called chondrocytes. Unlike osteocytes however, chondrocytes continue to proliferate for some time, this being allowed in part by the gel-like consistency of cartilage. At the periphery of this cartilage (the perichondrium), the mesenchymal cells continue to proliferate and differentiate through appositional growth. Another type of growth is observed in the cartilage by cell proliferation and synthesis of new matrix between the chondrocytes (interstitial growth).

Figure 9. Duration and depth of the phases of the normal cancellous bone remodeling sequence, calculated from histomorphometric analysis of bone biopsy samples from young individuals (Adapted from: Eriksen EF, Axelrod DW, Melsen F. Bone Histomorphometry. Raven Press, New York, pp13-20, 1994).

 

Beginning in the center of the cartilage model, at what is to become the primary ossification center, chondrocytes continue to differentiate and become hypertrophic. During this process, hypertrophic cells deposit a mineralized matrix, where cartilage calcification is initiated by matrix vesicles. Once this matrix is calcified, it is partially resorbed by osteoclasts. After resorption and a reversal phase, osteoblasts differentiate in this area and form a layer of woven bone on top of the remaining cartilage. This woven bone will later be remodeled into lamellar bone.

 

Chondrocyte differentiation is regulated by a number of factors which have recently been described. The first factor shown to control chondrocyte differentiation was parathyroid hormone related peptide (PTHrP) acting on PTH receptors mostly found in prehypertrophic chondrocytes. This factor prolongs chondrocyte proliferation, and in PTHrP knockout mice, the main phenotype is bone shortening caused by premature chondrocyte hypertrophy. Targeted overexpression of PTHrP results in the opposite phenotype, with prolonged delay in chondrocyte maturation. PTHrP is part of a genetic signaling cascade, where not only is it regulated by factors expressed earlier in chondrocyte differentiation, such as Indian hedgehog (Ihh), but it also regulates chondrocyte differentiation itself, and alters gene expression in more mature chondrocytes. Other factors which regulate chondrocyte differentiation include the FGFs and bone morphogenetic proteins (BMPs). The transcription factors Runx2 and Sox9, together with the Wnt signaling pathway, control the commitment and differentiation within the chondrocytic lineage (20).

 

The embryonic cartilage is avascular. During its early development, a ring of woven bone is formed, the bone collar, at the periphery by intramembranous ossification in the future midshaft area under the perichondrium (which becomes periosteum). Following calcification of this woven bone, blood vessels, preceded by osteoclasts enter the primary ossification center, penetrate the bone collar and the calcified cartilage, to form the blood supply and allow seeding of the hematopoietic bone marrow. The osteoclast invasion and its concomitant wave of resorbing activity leads to the removal of the calcified cartilage and its replacement by woven bone in the primary spongiosa, as described above.

 

Secondary ossification centers begin to form at the epiphyseal ends of the cartilaginous model, and by a similar process, trabecular bone and a marrow space are formed. Between the primary and secondary ossification centers, epiphyseal cartilage (growth plates) remain until adulthood. The continued differentiation of chondrocytes, cartilage mineralization and subsequent remodeling cycles allow longitudinal bone growth to occur, such that as new bone is formed the bone will reach its final adult shape. There is, however, a progressive decrease in chondrocyte proliferation so that the growth plate becomes progressively thinner, allowing mineralization and resorption to catch up. It is at this point that the growth plates are completely remodeled and longitudinal growth is arrested.

 

The growth plate demonstrates, from the epiphyseal area to the diaphyseal area, the different stages of chondrocyte differentiation involved in endochondral bone formation (Figure 10). Firstly, a proliferative zone, where the chondroblasts divide actively, forming isogenous groups, and actively synthesizing the matrix. These cells become progressively larger, enlarging their lacunae in the pre-hypertrophic and hypertrophic zones. Lower in this area, the matrix of the longitudinal cartilage septa selectively calcifies (zone of provisional calcification). The chondrocytes become highly vacuolated and then die through programmed cell death (apoptosis). Once calcified, the cartilage matrix is resorbed, but only partially, by osteoclasts, leaving the calcified longitudinal septae and blood vessels appear in the zone of invasion. After resorption, osteoblasts differentiate and form a layer of woven bone on top of the cartilaginous remnants of the longitudinal septa. Thus, the first remodeling sequence is complete: the cartilage has been remodeled and replaced by woven bone. The resulting trabeculae are called the primary spongiosa. Still lower in the growth plate, this woven bone is subjected to further remodeling (a second ARF sequence) in which the woven bone and the cartilaginous remnants are replaced with lamellar bone, resulting in the mature trabecular bone called secondary spongiosum.

Figure 10. Bone Development. Schematic diagram showing the initial stages of endochondral ossification. Bone development begins with mesenchymal condensation to form a cartilage model of the bone to be formed. Following chondrocyte hypertrophy and cartilage matrix mineralization, osteoclast activity and vascularization result in the formation of the primary, and then secondary ossification centers. In mature adult bones, the growth plate is fully resorbed, so that one marrow cavity extends the full length of the bone. See text for details.

 

GROWTH IN BONE SHAPE AND DIAMETER (MODELING)

 

During longitudinal growth, and due to the fact that the midshaft is narrower than the metaphysis, the growth of a long bone progressively destroys the lower part of the metaphysis and transforms it into a diaphysis, a process accomplished by continuous resorption by osteoclasts beneath the periosteum.

In contrast, growth in the diameter of the metaphysis is the result of a deposition of new membranous bone beneath the periosteum that will continue throughout life. In this case, resorption does not immediately precede formation. Recently, more attention has been focusing on this type of bone formation inasmuch as periosteal bone formation seems to respond differently and/or independently from endosteal bone formation activity to different stimuli such as PTH or biomechanical loading. This is particularly important in the context of osteoporosis where it has been demonstrated that growth in diameter in the midshaft is a more important contributor to the decrease in the fracture risk than trabecular bone density and/or cortical thickness.

 

REFERENCES

 

  1. Fukumoto S, Martin TJ. Bone as an endocrine organ. Trends Endocrinol Metab. 2009 Jul;20(5):230-6.
  2. Zanatta LC, Boguszewski CL, Borba VZ, Kulak CA. Osteocalcin, energy and glucose metabolism. Arq Bras Endocrinol Metabol. 2014 Jul;58(5):444-51
  3. Ahmed LA, Shigdel R, Joakimsen RM, Eldevik OP, Eriksen EF, Ghasem-Zadeh A, Bala Y, Zebaze R, Seeman E, Bjørnerem Å. Measurement of cortical porosity of the proximal femur improves identification of women with nonvertebral fragility fractures. Osteoporos Int. 2015 Aug;26(8):2137-46.
  4. Robey P.G., Bone Matrix Proteoglycans and Glycoproteins, In Principles of Bone Biology, J.P. Bilezikian, L.G. Raisz and G.A. rodan Editors, Academic Press Publishers, Chapter 14, 225-238, 2002.
  5. Bonewald L.F., Transforming Growth Factor-β, In Principles of Bone Biology, J.P. Bilezikian, L.G. Raisz and G.A. rodan Editors, Academic Press Publishers, Chapter 49, 903-918, 2002.
  6. Harada S. and Rodan G.A., Control of osteoblast function and regulation of bone mass, Nature 423, 349-355, 2003.
  7. Baron R. and Rawadi G., Targeting the Wnt/β-catenin Pathway to Regulate Bone Formation in the Adult Skeleton, Endocrinology 148, 2635-43.
  8. Boyle W.J., Simonet W.S., Lacey D.L., Osteoclast differentiation and activation, Nature 423, 337 – 342, 2003.
  9. Asagiri M. and Takayanagi H., The molecular understanding of osteoclast differentiation, Bone, 40:251-264, 2007.
  10. Teitelbaum, S.L. & Ross, F.P., Genetic regulation of osteoclast development and function, Nature Reviews Genetics, 4, 638-649, 2003
  11. Bruzzaniti A. and Baron R. Molecular regulation of osteoclast activity. Rev. Endocr. Metab. Disord. 2007, 7:123-39.
  12. Destaing O., Saltel F., Geminard J.C., Jurdic P. and Bard F. Podosomes display actin turn-over and dynamic self-organization in osteoclasts expressing actin-GFP. Mol. Biol. Cell, 14, 407-416, 2003.
  13. Courtial N, Smink JJ, Kuvardina ON, Leutz A, Göthert JR, Lausen J. Tal1 regulates osteoclast differentiation through suppression of the master regulator of cell fusion DC-STAMP. FASEB J. 2012 Feb;26(2):523-32.
  14. Islam R, Bae HS, Yoon WJ, Woo KM, Baek JH, Kim HH, Uchida T, Ryoo HM. Pin1 regulates osteoclast fusion through suppression of the master regulator of cell fusion DC-STAMP. J Cell Physiol. 2014 Dec;229(12):2166-74.
  15. Islam R, Yoon WJ, Ryoo HM. Pin1, the Master Orchestrator of Bone Cell Differentiation. J Cell Physiol. 2017 Sep;232(9):2339-2347.
  16. Takayanagi H., Osteoimmunology: shared mechanisms and crosstalk between the immune and bone systems, Nature Reviews Immunology 7, 292 – 304, 2007.
  17. Dempster DW. Tethering Formation to Resorption: Reversal Revisited. J Bone Miner Res. 2017 Jul;32(7):1389-1390.
  18. Lassen NE, Andersen TL, Pløen GG, Søe K, Hauge EM, Harving S, Eschen GET, Delaisse JM. Coupling of Bone Resorption and Formation in Real Time: New Knowledge Gained From Human Haversian BMUs. J Bone Miner Res. 2017 Jul;32(7):1395-1405.
  19. Sims NA, Martin TJ. Coupling Signals between the Osteoclast and Osteoblast: How are Messages Transmitted between These Temporary Visitors to the Bone Surface? Front Endocrinol (Lausanne). 2015 Mar 24; 6:41.

20.. Kronenberg H.M., Developmental regulation of the growth plate, Nature 332-336, 2003.

 

 

Use of the Historial Weight Trajectory to Guide an Obesity-Focused Patient Encounter

ABSTRACT

 

Obesity is a complex and challenging disease to address by clinicians. Moreover, given the wide prevalence coupled with disease impact, every specialty in medicine will likely encounter many patients with obesity.  Thus, it becomes crucial for practitioners to obtain a thorough weight history from patients in order to identify potential triggers that influence weight gain trajectories and their relationships to development of disease co-morbidity and mortality. Obtaining a weight history from a patient can be approached systematically, similar to key elements of a history of present illness, as we will discuss. Furthermore, patient-drawn life-events graph or readily available electronic health records graphs can elucidate in visual context pertinent contributing factors to the etiology of obesity.  Oftentimes, biological, social, behavioral and psychological causes of weight gain can be elicited through the use of weight histories. In this chapter, we will also explore life-events graph more in detail as they can provide remarkable value to the overall assessment and plan of care (whether lifestyle intervention with additional ancillary support, pharmacological, surgical, or combination thereof) in the patient with obesity.

INTRODUCTION

 

Obesity adversely affects all organ systems in the human body and causes and/or exacerbates numerous medical disorders such as cardiovascular disease, diabetes, kidney disease, and cancers.  Today, the average adult weight has increased (1)with a disproportionate rightward skewing (2)of the body mass index (BMI) distribution curve (Figure 1) with a higher percentage of the population meeting criteria for Class 1 obesity or higher (>30 kg/m2) and more disease severity (Class 2 obesity or higher;  BMI >35 kg/m2).  In addition, the average waist circumference has increased across US adults since 1999 (3).  Increase in abdominal girth (>35 inches for women;  >40 inches for men), commonly called central or abdominal obesity, is a surrogate for visceral adiposity, which increases risk for the metabolic syndrome, inflammation and cardiovascular disease (4). 

Figure 1. Changing Shape of BMI Distribution Curve Over Time (2)

Obesity is defined as a pathologically elevated and defended body fat mass due to dysregulation of the pathways that determine energy balance. The complexity in these pathways, whether through biological, genetic, developmental, epigenetic, environmental, or behavioral factors, lead to substantial variability in the pathophysiological expression of both amount of unwanted weight gain experienced by an individual as well as the number and severity of co-morbid conditions (diabetes, hypertension, etc.) (5, 6, 7, 8, 9). 

 

In addition to the variability in phenotypic presentation of weight gain and fat distribution in obesity (10), individual responses to lifestyle, pharmacological, and surgical treatment are also heterogeneous.  Although most patients elicit an average response to a distinct type of treatment, some patients will have an above average response to the intervention, while in others the response may be sub-optimal, or they may not respond at all. A thorough weight history can help identify these targeted responders to specific treatment.   Thus, clinically applied and integrated understanding of the disease, its root causes and etiology within a thorough weight history can guide successful treatment.

 

THE OVERWEIGHT AND OBESITY-FOCUSED ENCOUNTER

 

History, Physical, and Laboratory Testing of the Patient who is Overweight or Has Obesity

 

The evaluation and diagnosis of a patient with obesity follows standard medical history, review of systems with a focus on weight-related complications, a review of potentially weight-promoting medications (11), a medical examination that characterizes the amount and distribution of weight as well as possible signs of secondary causes of unwanted weight gain, as well as relevant clinical laboratory tests.  In addition, the history of present illness includes a patient interview and generation of a chronological weight graph using the electronic health record (EHR), lifestyle patterns and preferences, and previous interventions (whether successful or unsuccessful). 

 

The physical exam should note the distribution of weight (especially truncal and abdominal) and areas of conspicuous absence of fat characteristic of lipodystrophies (12), both of which herald increased cardiometabolic risk; documentation of cardiac status looking for evidence of heart failure; abdominal palpation for hepatomegaly; identification of inflammatory or degenerative joint issues that may limit activity; and skin/neurological examinations to look for evidence of hypercortisolism (wide striae, proximal muscle weakness), hypothyroidism, hirsutism/acne in polycystic ovarian syndrome, acanthosis nigricans over extensor surfaces/neck/axilla, lipomas, and lipedema.  Laboratory evaluation at the initial visit should include a comprehensive metabolic panel, complete blood count, assessment of thyroid status, and cardiometabolic risk assessment including a lipid panel and A1c (Table 1). 

 

Identification of obesity-related co-morbidities during the patient encounter and lab testing may necessitate referral for further evaluation, such as non-invasive imaging or liver biopsy to establish non-alcoholic steatohepatitis, a sleep study to diagnose obstructive sleep apnea, or X-ray to assess osteoarthritis in weight-bearing joints.  Patients reporting low-level dyspnea on exertion or orthopnea should be considered for referral to a cardiologist for the possibility of cardiac ischemia or, an increasingly recognized disorder of severe obesity, heart failure with preserved ejection fraction (HFpEF).

 

Table 1.  Key Elements of an Obesity-Focused Encounter

History of Present Illness (HPI)

Weight History and timing to life events, developmental milestones (puberty, pregnancy, menopause), medication use, and injuries, surgeries, or illnesses.

Past Medical and Surgical History (PMH, PSH)

In addition to a general review, identification of obesity-associated comorbidities and procedures:  gastro-esophageal reflux, hypertension, HFpEF, asthma, OSA, OA, type 2 diabetes, CAD and PVD, menstrual irregularities/infertility/PCOS, bariatric surgery

Social History (SH)

Lifestyle, health practices, nutrition, physical activity, sleep, stressors, occupation, marital status

Family History

Parental obesity, cultural patterns, family eating patterns

Medications/Allergies

Weight-gain promoting medications

Physical Examination

BMI, waist circumference.  Distribution of body fat

Laboratory and Diagnostic Testing

Risk assessment:  comprehensive metabolic panel, complete blood count, 25-OH vitamin D, C-reactive protein, TSH, hemoglobin A1c, and lipid panel.  When indicated, screening for co-morbid conditions such as obstructive sleep apnea, non-alcoholic steatohepatitis, and PCOS

Assessment and Plan

Based on risks, complications, comorbid conditions and barriers to care

 

CLINICAL IMPORTANCE OF A WEIGHT TRAJECTORY

 

During the weight-focused portion of the history of present illness, it is important to document changes in the health that led the patient to seek medical attention overtime and establish a clear and chronological description of the sequential events, including weight gain or loss, leading up to the current visit (13, 14)(Table 2). 

 

Table 2.  Key Elements of an Obesity-Focused History of Present Illness (15)

Onset

Nadir and Maximum Weight (excluding pregnancy)

What was your highest and lowest weight?

What did you weigh in teenage years, college, 20s, 30s, 40s, 50s?

Nadir and Maximum Weight (excluding pregnancy)

What were your lowest and highest weights?

How did you achieve your lowest weight?

Precipitating Factors

What events in your life triggered weight gain (puberty, pregnancy, menopause, starting or stopping smoking, starting a new medication such as insulin or steroids)?

Quality of life

What is hardest to do at your current weight?

When did you feel your best?

Weight loss efforts

What did you try that helped you lose weight?

What interventions were successful for you?

Setting

In what context were you successful at your previous efforts? 

Why do you think those efforts worked?

Temporal Pattern

What is the nature of your weight loss and weight gain over time?

Do you ever weight cycle (yo-yo) or is it gradual or rapid over time?

 

Multiple studies have demonstrated that an upward weight trajectory can be predictive of future development of obesity, obesity-related comorbid conditions, disability, and mortality (16, 17, 18, 19, 20). Maximum BMI (compared to single baseline BMI measurement) in overweight or obesity categories coupled with 16 or more years of weight history is associated with an increased all-cause and cause-specific mortality including cardiovascular disease and coronary heart disease (21). 

 

As will be discussed below, temporal patterns of weight gain that raise concerns in a weight history might include (a) early adiposity rebound during infancy or early childhood years (22)(b) adolescent weight gain that most correlates with progression to severe adult obesity and related medical conditions (23), and  (c) excessive weight gain during pregnancy or menopause.  Other temporal associations with weight gain often not appreciated by patients or providers include that which accompanies smoking cessation(24), recovery from hyperthyroidism (25), initiation of now common medications for depression, anxiety, and pain management (e.g., beta-blockers,amitriptyline, gabapentin, others)(11), and the normal age-associated sarcopenia where skeletal muscle mass gradually declines and visceral fat preferentially increases (26).

 

Early Growth, Childhood, and Puberty

 

Timing of excessive body weight gain during one’s life is also a predictor of future disease severity.  Of note, early and rapid weight gain during youth is predictive of co-morbidities later in life and these patients might often experience a more steeply inclined weight trajectory into later stages of adulthood (18).  During the ages of 2-6 years, children have a lower adiposity and are usually at their nadir weight (Figure 2).  Early adiposity rebound (as denoted by the red dotted line weight trajectory) during this period is a risk factor for childhood obesity and can be visualized on the BMI for-age and gender appropriate growth charts, typically expressed in percentile for age and sex (27).  Furthermore, early adiposity rebound in infancy (less than one year of age) should elicit concerns in regards to syndromic or non-syndromic causes of obesity (i.e. genetic or congenital syndromes; Figure 2).  Of note, monogenetic obesity syndromes, such as melanocortin-4-receptor gene mutation MC4R that has been implicated in 1-6% of early-onset severe obesity, are very rare (22, 28, 29). However, cardinal features such as rapid weight gain from early infancy, development of severe obesity (>97thBMI percentile) at early ages (usually <3 years of age), persistent food-seeking behavior, parental consanguinity, and tall stature/increased growth velocity should prompt screening for genetic obesity.

Figure 2. BMI Percentile Growth Chart

Weight gain during adolescent development period correlates very highly with progression to severe adult obesity.  The adolescent stage is a time of critical pubertal development when body composition and fat distribution changes.  Adolescent obesity can affect timing of puberty (early vs. delayed) (30).  During normal pubertal development and growth, males acquire greater fat-free and skeletal muscle mass, whereas females attain higher fat mass (31).    

Figure 3. Schematic Depiction of Abnormal BMI Percentile Growth Curves for Adolescents with Severe Obesity. Greater than or equal to the 95th BMI percentile correspond to cut-offs for pediatric obesity. Other important considerations that determine therapeutic criteria are if the adolescent’s trajectory falls at or above 120th% and 140th% the 95th BMI percentile for age/gender (see Table 3).

Most patients who experience unwanted excess weight gain in childhood and adolescence develop obesity-related disease pathologies that, when severe, often require pharmacologic intervention and/or bariatric surgery. Early identification, management, and treatment are recommended as there is evidence that chances for weight-loss maintenance long-term are greater at this age than in older patients (see Endotext Chapter on Pediatrics) (32).  Currently there are six FDA-approved anti-obesity medications available, of which phentermine and orlistat are approved for age >16 years and >12 years respectively (32).  Use of anti-obesity pharmacotherapy in adolescents with severe obesity (>95thBMI percentile plus the presence of obesity-related comorbidity or >120thof 95thBMI percentile) has been recently proposed (32).  Furthermore, vertical sleeve gastrectomy and Roux-en-Y metabolic and bariatric surgery procedures are available options for adolescents with severe obesity (>120thof 95thBMI percentile plus obesity-related comorbidity or BMI >140thof 95thBMI percentile) (33). 

 

Table 3. Available Therapeutic Options Based on BMI Percentile Cut Offs of Weight Trajectory in Adolescent Patients with Severe Obesity

BMI percentile as per CDC growth chart

>95th BMI percentile

>120th of the 95thBMI percentile

>140th of the 95thBMI percentile

Intensive lifestyle intervention

Anti-obesity medication

With comorbidity

Adolescent bariatric metabolic surgery

 

With comorbidity

 

Pregnancy, Breast Feeding, and Menopausal Transition

 

Pregnancy and menopause can be a time when women’s weights and body composition may become permanently altered under the influence of dramatic shifts in sex steroid levels.  Excessive weight gain during pregnancy can result in epigenetic changes in the developing fetus leading to adult-onset chronic disease such as diabetes, cardiovascular disease and obesity (22, 23, 24).  Furthermore, maternal obesity and excessive gestational weight gain have been linked to maternal-fetal complications such as increased risk of C-sections, preeclampsia, shoulder dystocia, and macrosomia in the infant (25). Data from large population-based epidemiological studies have shown that roughly 50% of women after pregnancy will return to their pre-pregnancy weight, but the other 50% will retain extra weight, with a third of all pregnant women shifting a BMI category (normal to overweight or obesity) (26, 27).

 

The post-partum period following delivery of the newborn infant is indeed a vulnerable time for weight retention.  Moreover, the relationship between breastfeeding practices and postpartum weight changes is largely unclear due to the difficulties examining breastfeeding and weight management in observational research and confounding variables (34, 35).  Breastfeeding overall has other notable health benefits to the infant, including atopy, cognitive development, bone health, and maternal-infant attachment (36). 

 

Weight gain during midlife is common, and about two-thirds of women ages 40 to 59 and nearly three-quarters of women older than 60 are overweight (BMI greater than 25 kg/m2). On average, midlife women gain 1.5 pounds (0.7 kg) per year (37).  Thus, it is not surprising that menopause is often depicted as a weight-gain trigger on a patient’s life-event graph, especially in older women who gain weight after a period of weight maintenance.  Towards midlife, women undergo redistribution of body composition with increase in total body fat and enhanced inclination toward central abdominal visceral adiposity (38).  Excess body weight during menopause leads to elevated cardiovascular (39)and metabolic risk, including insulin resistance and Type 2 diabetes mellitus (40, 41). Early or late-onset menopause (with final menstrual cycle age <45 years or age >55 years respectively) compared to age 46-55 years is associated with increased risk of Type 2 diabetes mellitus[HR 1.04, 95% CI 0.99, 1.09 and HR 1.08, 95% CI 1.01, 1.14, respectively](42).  Having an underlying hysterectomy or an oophorectomy increases risk of diabetes further (RR 1.17, 95% CI 1.07-1.29) compared to peri-/post-menopausal women (43).

 

CASE LESSONS IN PATIENT-GENERATED WEIGHT GRAPHS (44)

 

While in the clinic, having a patient submit his/her own drawing of weight graph accomplishes two-fold goals.  First, it provides a template on which weight inflections in the patient’s life can be potentially identified with causative or contributory life events, medical conditions, and medications, and secondly, it provides a platform to guide the clinical discussion in regards to appropriate goal setting and best approaches to help him/her achieve as close to a healthy weight range as possible. 

 

Impact of Medications

 

The patient in Figure 4 experienced steroid-induced weight gain that is a very common iatrogenic cause of obesity.  Exploring reasons for why this patient was initiated on steroids and communication with other specialists in regards to switch over to another non-steroid dependent medication, if available, might mitigate the weight gain and prove to be a successful weight management strategy. Similar effects prompting discussions of alternative approaches may also be seen by other commonly prescribed medications, including some birth control methods (e.g., Depo-Provera), beta-blockers, amitriptyline, gabapentin, pregabalin, thiazolidinediones, and insulin). 

Figure 4. Life Graph Showing Effects of Repeated Exposures to Steroids on Weight for Chronic Inflammatory Arthritis.

Effects of Situational Life Changes That Impact Weight

 

In Figure 5, the patient’s weight was at its nadir during college years until graduation.  Subsequently, marriage and job change were aforementioned social factors contributing to weight gain. In addition, pregnancy and menopause were identified biological associations with upward weight trajectory overtime.  Psychological stressors further augmented weight gain over time. Resilience to major life stressors (marriage, divorce, loss of spouse, unemployment, death of a loved one, major illness or injury, moving/relocation) does not commonly occur and can precipitate psychosocial disorders such as anxiety, depression and alcoholism (45, 46).

Figure 5. Life Graph Showing Effects of Several Situational Life Changes that Impact Weight.

Figure 6. Life Graph Showing Effect of a Single Traumatic Incident (such as Motor Vehicle Accident in this Case) on Weight

In Figure 6 above, the patient had a stable weight prior to a traumatic incident that elicited changes in physical function leading to immobility and sedentary behaviors. Identification of this specific event contributing to upward weight trajectory in the patient helped tailor the treatment strategy toward physical therapy, rehabilitation and a customized exercise prescription to mitigate the weight gain.

 

Identification of Response to Weight Loss Interventions:  Importance of Identifying Lifetime Max

 

Below are examples of weight graphs taken from the electronic health record (47, 48).

In Figure 7, the patient gained over 40 pounds through exposure to various antipsychotic medications for the treatment of her bipolar disorder. The downward shift in her weight graph occurred after treatment with metformin 500mg once daily (to mitigate antipsychotic medication induced weight gain (49)) and phentermine to ultimately lose weight. If certain medications are critical and cannot be switched over to a weight-mitigating alternative, as is often the case in patients requiring anti-psychotic medications, anti-obesity medications (48)and in severe obesity, bariatric surgery, can often reverse the weight gain. 

Figure 7. Life Graph Showing the Effects of Antipsychotic Medications on Weight and Effective Therapeutic Intervention with Anti-Obesity Medications

In Figure 8, the first blue arrow shows the time of initial visit when the patient had started to gain weight due to multifactorial etiology (strong family history of obesity, maladaptive stress related to work, poor nutritional habits), followed by initiation of anti-obesity medicine therapy and intensive lifestyle intervention (phentermine; 2ndblue arrow).  Subsequently, the patient developed side effects and phentermine monotherapy was discontinued (3rdblue arrow).  Several other anti-obesity pharmacological options were trialed (4thblue arrow); however, the patient did not respond.  Ultimately, the patient underwent bariatric surgery (Roux-en-Y gastric bypass (RYGB)) to achieve successful weight loss response. 

 

Obesity has a multifactorial etiology leading to wide variability in its presentation.  Understanding causation and association of weight gain promoting factors in a patient’s life can help elucidate appropriate treatment strategies.  Furthermore, initial non-response to anti-obesity medication does not indicate that the medication is ineffective overall; rather it may not be targeting the pathophysiological pathways involved in metabolic dysregulaton in the individual patient and an alternative anti-obesity medication or combination should be trialed for synergistic or additive weight loss effects. In this patient’s case, other anti-obesity medications were prescribed due to initial side effects on phentermine monotherapy.

Figure 8. The Life Events Graph Depicts the Response to Treatment and Strategies for Further Intervention.

Identification of Weight Regain after Successful Weight Loss:  Importance of Prompt Intervention

Figure 9. Life Graph Showing Effect of Weight Loss Program Intervention Overtime with Weight Regain.

Figure 9 shows the life-events graph of a 55-year-old patient with a history of hypertension, obstructive sleep apnea and severe obesity (BMI 41.8 kg/m2, 293.5 lbs.). The patient lost 95

pounds over a 1.5-year period through self-monitoring using an electronic smart phone tracking application, 1800 kcal/day intake, and an increase in physical activity as tolerated.  However, after 1.5 years of successful weight loss, despite continued intensive lifestyle changes in the absence of other potential weight gain triggers, he experienced weight regain over the next 3 years. Weight regain after a period of caloric restriction is physiologic as long-term persistence of metabolic adaptation occurs and hunger and satiety signals resist weight loss (50).  It is a prime time to initiate anti-obesity pharmacotherapy at this critical stage after weight maintenance to help sustain the weight loss and prevent weight regain. In this patient, starting an anti-obesity medication after 1.5 years when weight gain had started to occur would be recommended.     

 

Figure 10. Life Graph Showing a Patient Status Post Gastric-Bypass Surgery with Weight Regain Following Situational Life Transitions (Marriage, Birth of Child).

Figure 11. Life Graph Showing Weight Loss in a Patient After Bariatric Surgery Followed by Weight Regain Subsequent to High Job-Related Stress and Retirement.

 

CONCLUSIONS

 

Eliciting an obesity-focused medical history is important for the care of the patient who is overweight or has obesity.  In addition to identifying obesity-related co-morbid conditions by means of a thorough history, physical, and appropriate laboratory work up, we illustrated, through the use of described life-events and electronic health record weight graphs, the clinical relevance of documenting weight trajectories in the management of a patient with obesity.  Creating a representation of a patient’s weight trajectory and fluctuations over time can help guide the clinical discussion in regards to potentially modifiable influences on a patient’s weight.  These include identifying causative medical conditions or culprit medications that promote weight gain, associating weight gain with known life-transitions that increase a patient’s risk for becoming overweight or obese (e.g., puberty, pregnancy, menopause), help patients to re-commit to improved lifestyle choices, assess an individual’s responsiveness to recommended therapies, and help with timing for when initiating combinations of therapies (either weight loss medications in combination or adding on following weight loss surgery).       

 

REFERENCES

 

  1. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA2012;307:491-497.
  2. Penman AD, Johnson WD. The changing shape of the body mass index distribution curve in the population: implications for public health policy to reduce the prevalence of adult obesity. Prev Chronic Dis2006;3:A74.
  3. Fryar CD, Kruszon-Moran D, Gu Q, Ogden CL. Mean Body Weight, Height, Waist Circumference, and Body Mass Index Among Adults: United States, 1999-2000 Through 2015-2016. Natl Health Stat Report2018:1-16.
  4. Ritchie SA, Connell JM. The link between abdominal obesity, metabolic syndrome and cardiovascular disease. Nutr Metab Cardiovasc Dis2007;17:319-326.
  5. Bessler M, Daud A, DiGiorgi MF, Schrope BA, Inabnet WB, Davis DG. Frequency distribution of weight loss percentage after gastric bypass and adjustable gastric banding. Surg Obes Relat Dis2008;4:486-491.
  6. Gardner CD. Tailoring dietary approaches for weight loss. Int J Obes Suppl2012;2:S11-S15.
  7. Smith SR, Prosser WA, Donahue DJ, Morgan ME, Anderson CM, Shanahan WR, et al.Lorcaserin (APD356), a selective 5-HT(2C) agonist, reduces body weight in obese men and women. Obesity (Silver Spring)2009;17:494-503.
  8. Hatoum IJ, Greenawalt DM, Cotsapas C, Reitman ML, Daly MJ, Kaplan LM. Heritability of the weight loss response to gastric bypass surgery. J Clin Endocrinol Metab2011;96:E1630-1633.
  9. Buford TW, Roberts MD, Church TS. Toward exercise as personalized medicine. Sports Med2013;43:157-165.
  10. Srivastava G, Apovian CM. Current pharmacotherapy for obesity. Nat Rev Endocrinol2018;14:12-24.
  11. Verhaegen AA, Van Gaal LF. Drugs That Affect Body Weight, Body Fat Distribution, and Metabolism. In: Feingold KR, Anawalt, B., Boyce, A., Chrousos, G., Dungan, K., Grossman, A., Hershman, J. M., Kaltsas, G., Koch, C., Kopp, P., Korbonits, M., McLachlan, R., Morley, J. E., New, M., Perreault, L., Purnell, J., Rebar, R., Singer, F., Trence, D. L., Vinik, A., Wilson, D. P. (ed). Endotext [Internet]. MDText.com, Inc.; 2000-: South Dartmouth (MA) 2019 Feb 11.
  12. Akinci B, Sahinoz, M., and Oral, E. Lipodystrophy Syndromes: Presentation and Treatment. In: Feingold KR, Anawalt, B., Boyce ,A., Chrousos, G., Dungan, K., Grossman, A., Hershman, J. M., Kaltsas, G., Koch, C., Kopp, P., Korbonits, M., McLachlan, R., Morley, J. E., New, M., Perreault, L., Purnell, J., Rebar, R., Singer, F., Trence, D. L., Vinik, A., Wilson, D. (ed). Endotext [Internet]. MDText.com, Inc.; 2000-. South Dartmouth (MA), 2018 Apr 24.
  13. Adler HM. The history of the present illness as treatment: who's listening, and why does it matter? J Am Board Fam Pract1997;10:28-35.
  14. Redelmeier DA, Schull MJ, Hux JE, Tu JV, Ferris LE. Problems for clinical judgement: 1. Eliciting an insightful history of present illness. CMAJ2001;164:647-651.
  15. Kushner R, 'Taking a Weight History – Using Mnemonics to Learn a Missing Skill in Medical Education', MedEdPublish, 6, [4], 46, https://doi.org/10.15694/mep.2017.000215.
  16. Malhotra R, Ostbye T, Riley CM, Finkelstein EA. Young adult weight trajectories through midlife by body mass category. Obesity (Silver Spring)2013;21:1923-1934.
  17. Stokes A, Ni Y, Preston SH. Prevalence and Trends in Lifetime Obesity in the U.S., 1988-2014. Am J Prev Med2017;53:567-575.
  18. Zheng Y, Manson JE, Yuan C, Liang MH, Grodstein F, Stampfer MJ, et al.Associations of Weight Gain From Early to Middle Adulthood With Major Health Outcomes Later in Life. JAMA2017;318:255-269.
  19. Zheng Y, Song M, Manson JE, Giovannucci EL, Hu FB. Group-Based Trajectory of Body Shape From Ages 5 to 55 Years and Cardiometabolic Disease Risk in 2 US Cohorts. Am J Epidemiol2017;186:1246-1255.
  20. Petrick JL, Kelly SP, Liao LM, Freedman ND, Graubard BI, Cook MB. Body weight trajectories and risk of oesophageal and gastric cardia adenocarcinomas: a pooled analysis of NIH-AARP and PLCO Studies.Br J Cancer2017;116:951-959.
  21. Yu E, Ley SH, Manson JE, Willett W, Satija A, Hu FB, et al.Weight History and All-Cause and Cause-Specific Mortality in Three Prospective Cohort Studies. Ann Intern Med2017;166:613-620.
  22. Farooqi IS, O'Rahilly S. The Genetics of Obesity in Humans. In: Feingold KR, Anawalt, B., Boyce A3, Chrousos, G., Dungan, K., Grossman, A., Hershman, J. M., Kaltsas, G., Koch, C., Kopp, P., Korbonits, M., McLachlan, R., Morley, J. E., New, M., Perreault, L., Purnell, J., Rebar, R., Singer, F., Trence, D. L., Vinik, A., Wilson, D. P. (ed). Endotext [Internet]. MDText.com, Inc.; 2000-: South Dartmouth (MA), 2017 Dec 23.
  23. Twig G, Yaniv G, Levine H, Leiba A, Goldberger N, Derazne E, et al.Body-Mass Index in 2.3 Million Adolescents and Cardiovascular Death in Adulthood. N Engl J Med2016;374:2430-2440.
  24. Bush T, Lovejoy JC, Deprey M, Carpenter KM. The effect of tobacco cessation on weight gain, obesity, and diabetes risk. Obesity (Silver Spring)2016;24:1834-1841.
  25. Schneider DF, Nookala R, Jaraczewski TJ, Chen H, Solorzano CC, Sippel RS. Thyroidectomy as primary treatment optimizes body mass index in patients with hyperthyroidism. Ann Surg Oncol2014;21:2303-2309.
  26. Choi KM. Sarcopenia and sarcopenic obesity.Korean J Intern Med2016;31:1054-1060.
  27. Rolland-Cachera MF, Peneau S. Growth trajectories associated with adult obesity. World Rev Nutr Diet2013;106:127-134.
  28. Oswal A, Yeo GS. The leptin melanocortin pathway and the control of body weight: lessons from human and murine genetics.Obes Rev2007;8:293-306.
  29. Doulla M, McIntyre AD, Hegele RA, Gallego PH. A novel MC4R mutation associated with childhood-onset obesity: A case report. Paediatr Child Health2014;19:515-518.
  30. Lee JM, Wasserman R, Kaciroti N, Gebremariam A, Steffes J, Dowshen S, et al.Timing of Puberty in Overweight Versus Obese Boys. Pediatrics2016;137:e20150164.
  31. Loomba-Albrecht LA, Styne DM. Effect of puberty on body composition. Curr Opin Endocrinol Diabetes Obes2009;16:10-15.
  32. Srivastava G, Fox CK, Kelly AS, Jastreboff AM, Browne AF, Browne NT, et al.Clinical Considerations Regarding the Use of Obesity Pharmacotherapy in Adolescents with Obesity. Obesity (Silver Spring)2019;27:190-204.
  33. Pratt JSA, Browne A, Browne NT, Bruzoni M, Cohen M, Desai A, et al.ASMBS pediatric metabolic and bariatric surgery guidelines, 2018. Surg Obes Relat Dis2018;14:882-901.
  34. Neville CE, McKinley MC, Holmes VA, Spence D, Woodside JV. The effectiveness of weight management interventions in breastfeeding women--a systematic review and critical evaluation. Birth2014;41:223-236.
  35. Neville CE, McKinley MC, Holmes VA, Spence D, Woodside JV. The relationship between breastfeeding and postpartum weight change--a systematic review and critical evaluation. Int J Obes (Lond)2014;38:577-590.
  36. Lucas A. Scientific Evidence for Breastfeeding. Nestle Nutr Inst Workshop Ser2019;90:1-12.
  37. Kapoor E, Collazo-Clavell ML, Faubion SS. Weight Gain in Women at Midlife: A Concise Review of the Pathophysiology and Strategies for Management. Mayo Clin Proc2017;92:1552-1558.
  38. Kozakowski J, Gietka-Czernel M, Leszczynska D, Majos A. Obesity in menopause - our negligence or an unfortunate inevitability? Prz Menopauzalny2017;16:61-65.
  39. Ramezani Tehrani F, Behboudi-Gandevani S, Ghanbarian A, Azizi F. Effect of menopause on cardiovascular disease and its risk factors: a 9-year follow-up study. Climacteric2014;17:164-172.
  40. Davis SR, Castelo-Branco C, Chedraui P, Lumsden MA, Nappi RE, Shah D, et al.Understanding weight gain at menopause. Climacteric2012;15:419-429.
  41. Senechal M, Arguin H, Bouchard DR, Carpentier AC, Ardilouze JL, Dionne IJ, et al.Weight gain since menopause and its associations with weight loss maintenance in obese postmenopausal women. Clin Interv Aging2011;6:221-225.
  42. LeBlanc ES, Kapphahn K, Hedlin H, Desai M, Parikh NI, Liu S, et al.Reproductive history and risk of type 2 diabetes mellitus in postmenopausal women: findings from the Women's Health Initiative. Menopause2017;24:64-72.
  43. Pandeya N, Huxley RR, Chung HF, Dobson AJ, Kuh D, Hardy R, et al.Female reproductive history and risk of type 2 diabetes: A prospective analysis of 126 721 women. Diabetes Obes Metab2018;20:2103-2112.
  44. Kushner RF, Ryan DH. Assessment and lifestyle management of patients with obesity: clinical recommendations from systematic reviews. JAMA2014;312:943-952.
  45. Infurna FJ, Luthar SS. Resilience to Major Life Stressors Is Not as Common as Thought. Perspect Psychol Sci2016;11:175-194.
  46. Just-Ostergaard E, Mortensen EL, Flensborg-Madsen T. Major life events and risk of alcohol use disorders: a prospective cohort study. Addiction2018;113:25-33.
  47. Jensen MD, Ryan DH, Apovian CM, Ard JD, Comuzzie AG, Donato KA, et al.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. J Am Coll Cardiol2014;63:2985-3023.
  48. Apovian CM, Aronne LJ, Bessesen DH, McDonnell ME, Murad MH, Pagotto U, et al.Pharmacological management of obesity: an endocrine Society clinical practice guideline. J Clin Endocrinol Metab2015;100:342-362.
  49. Hendrick V, Dasher R, Gitlin M, Parsi M. Minimizing weight gain for patients taking antipsychotic medications: The potential role for early use of metformin. Ann Clin Psychiatry2017;29:120-124.
  50. Sumithran P, Prendergast LA, Delbridge E, Purcell K, Shulkes A, Kriketos A, et al.Long-term persistence of hormonal adaptations to weight loss. N Engl J Med2011;365:1597-1604.
  51. Srivastava G, Buffington C. A Specialized Medical Management Program to Address Post-operative Weight Regain in Bariatric Patients. Obes Surg2018.

 

Diabetes Mellitus After Solid Organ Transplantation

ABSTRACT

Posttransplantation diabetes mellitus (PTDM), also known as New Onset Diabetes After Transplantation, is a common and important complication following solid organ transplantation.  PTDM may arise from both transplant-related and traditional risk factors and has variably been reported to be associated with decreased patient and graft survival and other adverse outcomes including increased cardiovascular disease risk, infection, and graft rejection. This chapter presents an overview of the nomenclature change for diabetes developing after transplantation, the diagnostic criteria for PTDM, its incidence after solid organ transplantation, risk factors, and its associated adverse effects. Screening for PTDM including pretransplant evaluation and early detection in the posttransplant period, and the unique aspects of diabetes management in the context of organ transplantation are also presented. 

NOMENCLATURES AND DIAGNOSIS OF POSTTRANSPLANTATION DIABETES MELLITUS: HISTORICAL PERSPECTIVES 

Nomenclatures

Posttransplantation diabetes mellitus (PTDM) was first described in kidney transplant recipients in 1964 (1). It was subsequently recognized as a complication of kidney transplantation in the 1970s. Over the years, PTDM has undergone changes in nomenclatures including steroid diabetes, posttransplantation diabetes mellitus (PTDM), new onset diabetes mellitus (NODM), transplant-associated hyperglycemia (TAH), and new onset diabetes after transplantation (NODAT) (2, 3, 4, 5, 6). In 2014, the International Expert Panel consisting of transplant nephrologists, diabetologists, and clinical scientists recommended changing the terminology NODAT back to PTDM, excluding transient posttransplantation hyperglycemia (7). Utilizing the term NODAT is thought to be misleading because it seemingly excludes patients with pretransplant diabetes. Pre-existing diabetes is often undiagnosed because of the effect of chronic kidney disease on insulin metabolism and clearance, and the lack of effective pretransplant screening. The term PTDM will be utilized for the remainder of this chapter.

Diagnosis

Historically, PTDM has been variably defined as having random glucose levels greater than 200 mg/dL, fasting glucose levels greater than 140 mg/dL, or the need for insulin or oral hypoglycemic agents in the posttransplant period (8). In 2003 the International Expert panel consisting of leaders from both the transplant and diabetes fields suggested that the definition and diagnosis of diabetes and impaired glucose tolerance should be based on the definition and diagnosis described by the World Health Organizations (9). In 2011, the American Diabetes Association (ADA) incorporated hemoglobin A1C (HbA1C) > 6.5% as a diagnostic criterion for diabetes mellitus in the general population based on the observed association between HbA1C level and the risk for future development of retinopathy (10). In 2014, the International Expert Panel recommended expanding screening tests for PTDM using postprandial glucose monitoring and HbA1C. However, HbA1C test is not recommended early after transplantation (arbitrarily defined as within 45 days after transplantation) because of potential confounding factors (7). A normal HbA1C does not exclude the diagnosis of PTDM in the presence of early posttransplant anemia and/or dynamic kidney allograft function. In a small single-center study consisting of 30 diabetic patients with CKD stage 3 b and 4, treatment with intravenous iron and erythropoietin stimulating agent (ESA) has been shown to result in a fall in A1C independent of glycemic changes (11). It is speculated that the fall in A1C level associated with either treatment is due to the formation of new erythrocytes in the circulation (causing a change in the proportion of young to old red blood cells), and an alteration in the red-cell glycation rates. A similar study in the transplant setting is lacking and warrants further exploration because intravenous iron and ESA therapy are commonly administered in the early posttransplant period. Although not widely used in clinical practice, oral glucose tolerance (OGTT) remains the gold standard for diagnosing PTDM. It should be noted that the algorithmic approach to the screening and diagnosis of PTDM is largely based on published kidney transplantation literature. Similar studies in the settings of liver, heart, and lung transplants are lacking. However, it is speculated that the principles are relevant to all forms of solid organ transplantation (7). The ADA criteria for prediabetes and diabetes are shown in Figure 1.

Figure 1. The American Diabetes Association diagnostic criteria for prediabetes and diabetes. 1Results must be confirmed by repeat testing. HbA1C, hemoglobin A1C; NGSP, National Glycohemoglobin Standardization Program

INCIDENCE

PTDM has been reported to occur in 4% to 25% of kidney transplant recipients, 2.5% to 25% of liver transplant recipients, 4% to 40% of heart transplant recipients, and 30% to 35% of lung transplant recipients (9, 12-15). Higher incidences have also been reported. The variation in the reported incidence may be due in part to the prior lack of a standard definition, the presence of both modifiable and non-modifiable risks factors, the type of organ transplants, and the duration of follow up (e.g. in one retrospective cohort study of 415 liver transplant recipients, PTDM occurred in 34.7%, 46.9%, and 56.2% of patients at 1, 3, and 5 year follow-up, respectively). In one study half of PTDM cases developed by 6 months and 75% by 12 months (15).

RISK FACTORS FOR PTDM

PTDM may arise from both transplant-related and traditional risk factors. The diabetogenic effect of various immunosuppressive agents have been well-described. Corticosteroids may reduce peripheral insulin sensitivity, inhibit pancreatic production/secretion, and increase hepatic gluconeogenesis. The calcineurin inhibitors tacrolimus and cyclosporine decrease insulin secretion and synthesis. Sirolimus increases peripheral insulin resistance and impairs pancreatic beta-cell response. The antimetabolites azathioprine and mycophenolic acid derivatives (mycophenolate mofetil and mycophenolate sodium) are not diabetogenic. Belatacept is a humanized fusion protein that inhibits the costimulatory pathway. Its use in kidney transplant recipients has not been shown to increase PTDM risk. Transplant patients may have improved appetite and a more liberal diet which can lead to obesity.

Risk factors for PTDM can be loosely categorized into those that are non-modifiable, potentially modifiable, and modifiable (8, 16-22). Solid organ transplant recipients with specific end-organ diagnosis such as end-stage kidney disease due to polycystic kidney disease, end stage liver disease due to hepatitis C infection, or end stage lung disease due to cystic fibrosis have been reported to be at increased risk for PTDM compared with those without such diagnosis (20). Suggested risk factors for the development of PTDM are presented in Figure 2. A more extensive discussion of the studies evaluating PTDM risk factors is beyond the scope of this chapter. Interested readers are referred to reference Pham and colleagues (8). 

 

Figure 2. Risk factors for Posttransplantation Diabetes Mellitus.

1Curative therapy for chronic hepatitis C can be achieved with interferon-free direct acting antiviral-based regimen. Stable transplant recipients with HCV viremia by PCR should be referred to Hepatology for treatment. In HCV-positive kidney transplant candidate with a living donor, pretransplant treatment of HCV infection should be considered

2 Posttransplant CMV prophylaxis is preferred over preemptive therapy after heart and lung transplant. Either prophylaxis or preemptive therapy is recommended after kidney or liver transplant recipients. However, for programs or patients who are unable to meet the stringent logistic requirements required with preemptive therapy, prophylaxis therapy is recommended (23)

3Persistent hypomagnesemia can occasionally be seen despite aggressive replacement therapy because of ongoing calcineurin inhibitor-induced urinary magnesium wasting 

4Manipulation of immunosuppression should be weighed against the risk of acute rejection

PPAR, peroxisome proliferators activated receptor; IGT, impaired glucose tolerance; IFG, impaired fasting glucose 

 

IMPACT OF PTDM ON OUTCOMES AFTER TRANSPLANTATION

Studies evaluating the association between PTDM and morbidity and mortality have yielded mixed results (17, 24-29). 

PTDM After Kidney Transplantation 

In an analysis of the United States Renal Data System consisting of more than 11,000 kidney transplant recipients, Kasiske et al. demonstrated that PTDM was associated with a strong, independent predictor of mortality (p < 0.0001), graft failure (p < 0.0001), and death-censored graft failure (p < 0.0001) (17). A single-center study consisting of more than 700 kidney transplant recipients similarly demonstrated worse 10-year actuarial patient survival among patients with PTDM compared with those without PTDM (26). In contrast, a retrospective analysis of the UNOS/OPTN database (n > 37,000) failed to demonstrate the negative impact of PTDM on transplant survival or cardiovascular mortality during a median follow up of 548 days (27). However, the study results were considered inconclusive because of the wide confidence intervals and relatively short duration of follow-up. Studies with longer-term follow-up demonstrated similar 5- and 10-year graft survival rates among patients with PTDM and those without PTDM (26).

 

PTDM After Liver Transplantation

 

Retrospective analysis of the UNOS/OPTN database consisting of > 13,000 liver transplant recipients demonstrated that the presence of both PTDM and acute rejection at 1-year posttransplant but not PTDM alone was associated with higher overall graft failure and mortality risk (29). However, it should be noted that UNOS database did not distinguish transient posttransplantation hyperglycemia from established PTDM. A single-center retrospective cohort study (n=994) compared the incidence of major cardiovascular events (MCE) among four groups of liver transplant recipients 1) without diabetes (39%), 2) with pre-existing diabetes (24%), 3) with transient PTDM (16%), and 4) with sustained PTDM (20%). Sustained PTDM was found to be associated with a significant increase in mortality risk and a doubling of major cardiovascular events at a median follow up of 54.7 months (sub-distribution HR 1.95, 95% CI 1.20–3.18). A greater than threefold increased risk of death was observed among those who experienced MCE (sustained PTDM was defined as PTDM for at least 6 months after transplant). MCE was defined as a composite of cardiac arrest, fatal and nonfatal myocardial infarction, ischemic stroke, and symptomatic peripheral artery disease requiring a revascularization intervention) (30). In a retrospective cohort study of 415 adult liver transplant recipients, PTDM was found to be associated with higher rejection rates (31.9% vs. 21.8%, respectively; p=0.055) and a trend towards worse patient survival compared with no-PTDM at 5 year follow up (72.5% vs. 77.2%, respectively; p=0.460) (15).

PTDM After Heart Transplantation 

Meta-analysis of observational studies in heart transplant recipients demonstrated that pre-existing diabetes was associated with a 37% increase in mortality risk (HR 1.37, CI 1.15-1.62) (31). Studies on the impact of PTDM on outcomes after heart transplantation are lacking. In one single-center South Korean study consisting of 391 isolated heart transplant recipients 1) without diabetes (n=257), 2) with pre-existing diabetes (n=46), and 3) with PTDM (n=88), the risk of death was found to be twofold higher among transplant recipients with pre-existing as well as posttransplantation diabetes compared with their non-diabetic counterparts (32).   

PTDM After Lung Transplantation 

The 27th International Society for Heart and Lung Transplantation Registry consisting of more than 32,000 lung transplant recipients demonstrated that pre-existing diabetes was associated with a 21% increase in 5-year mortality risk (RR 1.21, p=0.0023) (33). Limited studies suggest that PTDM similarly adversely affects survival among lung transplant recipients. In a single-center prospective observational Australian study consisting of 210 patients who underwent their first single, bilateral or heart-lung transplant between 2010-2013, hyperglycemia in both the early and late posttransplant periods (defined as first 4 months and beyond 4 months) was found to be associated with increased mortality risk. Of 210 patients, 80 had no DM, and 90 had persistent DM. Patients with pre-existing DM (n=45) and PTDM (n=45) were classified together as “persistent DM”. In the whole cohort, each 18 mg/dL increase in mean fasting blood glucose (FBG) and random blood glucose and each 1% increase in mean A1C were associated with 18% (p=0.006), 38% (p< 0.001), and 46% (p=0.002) increase in mortality risk, respectively (median follow up of 3 years). Of interest, random blood glucose correlated with mortality in both the persistent DM and no DM groups (35%, p=0.012 and 109%, p=0.041, respectively). It was concluded that glycemic control strongly correlated with survival after lung transplant (34). The same group of investigators previously demonstrated that DM conferred a nearly fourfold increase in mortality risk compared with no DM. When patients were classified into subgroups including 1) no diabetes, 2) pre-existing DM, 3) PTDM, 4) DM diagnosed within 2 weeks of death, and 5) DM developing after transplant but death within 90 days of transplant, pre-existing DM and PTDM were associated with a 65% (p=0.003) and a 90% (p< 0.001) increase in mortality risk, respectively (35). 

Although studies on the impact of PTDM on outcomes after non-renal solid organ transplantation remain limited, it is tempted to speculate that PTDM adversely affects survival among recipients of various solid organ transplants. Patients with PTDM may also develop many of the complications associated with diabetes similar to that observed in the general population.  In a study of 4105 patients with PTDM, one or more diabetic complications arose in 58% including ketoacidosis (8%), hyperosmolarity (3%), renal complications (31%), ophthalmic complications (8%), neurological complications (16%), peripheral circulatory disorders (4%), and hypoglycemia/shock (7%).  These complications occurred within a mean of 500-600 days of developing PTDM, indicating an accelerated pace for the development of complications (28). Moreover, PTDM patients had an increased rate of infections and sepsis compared with their non-diabetic counterparts (24).

DETECTION OF PTDM

Pretransplant Baseline Evaluation

Pretransplant Evaluation should include history of hyperglycemia, prediabetes, diabetes, and risk factors for PTDM including family history and hepatitis C virus.  The 2004 International Consensus Guidelines suggest that a pretransplant baseline evaluation should include a complete medical and family history, including documentation of glucose history (36). Those with risk factors for metabolic syndrome can be screened further with laboratory testing.  Patients with evidence of risk factors can be counseled of their risk for PTDM.  Those with evidence of prediabetes can be counseled of lifestyle modifications including dietary modifications, thirty minutes of moderate intensity physical activity, and overall five to ten percent weight reduction (37).  In HCV-positive kidney transplant candidates with a living donor, pretransplant treatment of HCV infection should be considered. With the advent of the interferon-free direct acting antiviral-based regimen, treatment of hepatitis C in the post-transplant period is a reasonable alternative in selected prospective kidney transplant candidates without a living donor due to a considerably shorter waiting time for a deceased HCV-positive donor kidney (38). The choice of an immunosuppressive regimen should be tailored to each individual patient, weighing the risk of acute rejection against that for PTDM.

Early Detection of PTDM After Transplantation

New onset perioperative hyperglycemia is common and may develop in the context of high dose corticosteroid or as a consequence of posttransplant stress hyperglycemia, or both. Limited studies suggest that posttransplant stress hyperglycemia is an independent risk factor for subsequent diabetes (39). The 2014 International Consensus guidelines on PTDM screening is shown in Figure 3 (7). The expert panel suggested that patients with early posttransplant hyperglycemia (defined as hyperglycemia before 45 days after transplantation) should not be diagnosed as PTDM.

Figure 3. The 2014 International Consensus Guidelines on the Screening, Diagnosis, and Management of Early Posttransplant Hyperglycemia and PTDM.1

1Although recommendations from the Expert Panel are largely based on published kidney transplantation literature, the principles are likely relevant to all forms of solid organ transplantation.

2HbA1C alone < 365 days may underestimate PTDM and require corroborating.

At the authors’ institution, fasting and premeal home glucose monitoring is routinely recommended for patients with new-onset posttransplantation hyperglycemia particularly those requiring insulin therapy in the immediate posttransplantation period. Nonetheless, it should be noted that monitoring a 2-hour postprandial blood glucose may be a better indicator of diabetes and its control, particularly in steroid-treated patients. Clinically stable patients with persistent posttransplantation hyperglycemia for > 3 months should be screened for PTDM using HbA1C test. Although evidence-based screening guidelines for the early detection of PTDM are lacking, obtaining baseline A1C at 3 months after transplant, then at 6 months, 9 months, 12 months, and annually thereafter seems reasonable. If screening A1C is in the prediabetic range, patients should be counseled on dietary and lifestyle modification and A1C monitored every 3 months. While OGTT remains the gold standard for diagnosing PTDM, there remains insufficient evidence to recommend OGTT for all kidney transplant recipients (7). In addition, screening all patients with OGTT may be impractical in clinical practice and should be individualized and reserved for those with multiple risk factors (opinion-based) (38, 40). 

PREVENTION AND MANAGEMENT OF PTDM 

Non-Pharmacological Preventive and Management Strategies

Studies in the general population demonstrated that lifestyle modification promoting reduced fat/energy diet, daily moderate intensity physical activity, and modest weight loss reduce the incidence of type 2 diabetes (41). Similar studies in the context of solid organ transplantation are lacking. In a small single center study consisting of 25 kidney transplant recipients with impaired glucose tolerance, reversal to normal glucose tolerance with lifestyle modification was observed in 13 patients after a median of 9 months with only one patient progressing to PTDM (42). Small single-center studies showed that posttransplant weight gain is associated with persistent PTDM (43). Pre- and post- transplant lifestyle modification including dietary changes with the guidance of a dietitian and regular moderate cardiovascular activity aiming at increasing muscle mass while decreasing fat mass has been suggested to decrease the incidence of PTDM (39). Whether active lifestyle modification has a favorable effect on glycemic control in kidney transplant recipients remains speculative and awaits results of an ongoing prospective, randomized controlled trial comparing the glycemic benefits of active versus passive lifestyle intervention. Patients randomized to the former group receive active lifestyle modification intervention including dietician referral, cognitive behavior therapy, weight loss advice, and enrollment in graded exercise program. In the passive lifestyle intervention group, patients are counselled in clinic about the risks of glucose intolerance and are given leaflets outlining lifestyle modification including healthy eating, exercise and the importance of weight loss. However, there will be no dietician referral, psychosocial intervention or focused exercise or weight loss monitoring program (NCT02233491).

Pharmacological Preventive and Management Strategies

In the immediate posttransplant period, the pancreatic β-cells are exposed to multiple hyperglycemic stressors including the transplant surgery itself, high-dose corticosteroids, and the introduction of cyclosporine or tacrolimus immunosuppression therapy. In a randomized controlled trial, Hecking et al. demonstrated that early basal insulin therapy following detection of early posttransplantation hyperglycemia (defined as < 3 weeks) reduced the subsequent odds of developing PTDM within the first year after transplantation by 73% (44). It is conceivable that early basal insulin therapy decreases PTDM through insulin-mediated protection of pancreatic beta-cells (44-45). However, the routine recommendation of early initiation of insulin therapy in the prevention of PTDM development awaits results of randomized controlled clinical trials (ITP-NODAT, clinicaltrials.org: NTC01683331 and NCT03507829 –recruitment completed. Study results are pending at the time of this writing). The glucose threshold for starting insulin therapy remains to be defined.

Insulin tapering or withdrawal and transitioning to non-insulin-based regimen can be considered after the first 1-3 month after transplant when insulin requirement is less than 15-20 units a day (opinion-based). The choice of individual agents should be based on the potential advantages and disadvantages of different classes of agents at the discretion of the clinicians (Figure 4).

Figure 4. The potential advantages and disadvantages of various classes of antihyperglycemic agents

1KDIGO guidelines: Reduce dose if estimated glomerular filtration rate (eGFR) < 45 cc/min/1.73 m2. Discontinue if eGFR < 30 cc/min/1.73m2

2From Parekh TM, Raji M, Lin YL, et al. Hypoglycemia after antimicrobial drug prescription for older patients using sulfonylureas. JAMA Intern Med. 2014;174(10):1605-1612.

3Contraindicated in patients with personal history or family history of thyroid cancer or multiple endocrine neoplasia (MEN) type 2.

4Sitagliptin may prolong QT interval particularly when used with cyclosporine.

 

Modification of Immunosuppression

 

Although clinical trials comparing the incidence of PTDM in cyclosporine versus tacrolimus-treated patients have yielded variable results, tacrolimus has more consistently been shown to have a greater diabetogenic effect than cyclosporine (38). Modification of immunosuppression including cyclosporine to tacrolimus conversion therapy or steroid avoidance or withdrawal has variably been shown to improve glycemic control (8, 46-49). However, manipulation of immunosuppression is not without immunological risk. In a meta-analysis of controlled clinical trials to assess the safety and efficacy of early steroid withdrawal or avoidance, Pascual et al. showed that steroid avoidance or steroid withdrawal after a few days reduced PTDM incidence among cyclosporine but not tacrolimus-treated kidney transplant recipients (50). However, among cyclosporine-treated patients, acute rejection episodes were more frequently observed in steroid avoidance compared with conventional steroid treated groups. The same group of investigators demonstrated no significant beneficial effect of late steroid withdrawal (3 to 6 months after transplantation) on the incidence of PTDM (51). In the current era of immunosuppression, the beneficial effect of steroid avoidance or withdrawal on the incidence of PTDM has been questioned by experts in the field because rapid steroid taper and the use of lower target cyclosporine and tacrolimus levels are now common practice (7). The use of tacrolimus and mTOR inhibitor combination therapy may increase PTDM risk and should probably be avoided. Nonetheless, low dose calcineurin inhibitor (cyclosporine or tacrolimus) and mTOR inhibitor combination therapy seems justifiable in transplant recipients with a history of malignancies (such as skin cancers, renal cell carcinoma, or Kaposi sarcoma). Due to the lack of well-defined guidelines, modification of immunosuppression to alleviate the incidence of PTDM should be tailored to each individual patient. Reduction in immunosuppression should be weighed against the risk of acute rejection.

Management of Established PTDM in the Late Posttransplant Period

Although there may be differences in the pathogenesis and presentation of PTDM compared to type 2 diabetes mellitus, management of established PTDM in the late posttransplant period should follow the conventional approach and clinical guidelines as established by well-recognized organizations.  The American Diabetes Association and European Association for the Study of Diabetes generally recommend a HbA1c target of < 7% (52). Lifestyle modifications including weight reduction, dietary changes, and regular moderate cardiovascular activity should be employed. If glycemic control does not reach therapeutic targets, medical management with oral antidiabetic agents and ultimately insulin can be initiated.

 

Metformin has not been widely used in the setting of transplantation due to the concern for lactic acidosis in the presence of dynamic kidney allograft function particularly in the early posttransplant period. In contrast, the potential beneficial effects of metformin including weight neutral or weight loss, cardioprotection, and lack of significant drug-drug interactions renders metformin an attractive treatment option for solid organ transplant recipients. Further clinical trials to assess the risk and benefit ratio of metformin are needed before it can be endorsed as the antihyperglycemic agent of choice in PTDM (7). At the time of this writing, there has been only one randomized clinical trial assessing the efficacy of metformin in the prevention of PTDM in kidney transplant recipients –The Transplantation and Diabetes (Transdiab) study (53). The Transdiab study is an ongoing single-center, open label, randomized controlled trial designed to assess the feasibility, gastrointestinal tolerability, and efficacy of metformin in patients with posttransplantation impaired glucose tolerance. The latter is diagnosed using a 2-hour oral glucose tolerance test in the 4-12 weeks after transplant. Eligible patients with IFG are randomized to standard of care or standard of care and metformin 500 mg twice daily. The efficacy of metformin is assessed by measuring fasting blood glucose and A1C at 3, 6, 9, and 12-month follow up.

Experimental studies suggest that sulfonylureas are associated with β-cell apoptosis and β-cell exhaustion (54), raising theoretical concern about their use in PTDM, particularly in the early posttransplant period. In contrast, the anti-hyperglycemic dipeptidyl peptidase-4 inhibitor (DPP-4) inhibitors have been shown to preserve pancreatic beta-cell function in diabetic animal models (55, 56). Early clinical studies suggest that DPP-4 inhibitors are safe and effective in the treatment of PTDM in kidney transplant recipients (57-59). In a single-center study consisting of 71 stable kidney transplant recipients with PTDM newly diagnosed by an oral glucose tolerance test, Haidinger et al. demonstrated that patients treated with vildagliptin at baseline had significantly reduced HbA1C levels at 3, 6,12, and 18 months, whereas no improvement in glycemic control was observed among their sulfonylurea-treated counterparts (58). In a randomized controlled trial comparing vildagliptin with placebo in the treatment of PTDM, the same group of investigators demonstrated that treatment with vildagliptin significantly improved A1C levels within 3 months compared with placebo (60). Systematic review and meta-analysis of five studies demonstrated that DDP-4 inhibitors had a favorable glycemic effect (assessed by A1C) compared with either placebo or oral anti-hyperglycemic agent (A1C= -0.993, p=0.001) at 6-month follow-up. No significant changes in eGFR or tacrolimus levels were observed in DDP-4 inhibitor-treated patients (61). 

Studies evaluating the safety and efficacy of DDP-4 inhibitors in non-renal solid organ transplant recipients remain lacking. In a small retrospective study of 30 stable heart transplant recipients with type 2 diabetes, vildagliptin was found to significantly reduce A1C level compared with their control counterparts. [mean A1C in the vildagliptin-treated patients was 7.4% ± 0.7% before versus 6.8% ± 0.8% after 8 months of therapy (P = 0.002 vs baseline). Mean A1C levels at baseline and at 8-month follow up in the control group were 7.0% ± 0.7% versus 7.3% ± 1.2%, respectively (P = 0.21)] (62). No statistically significant changes in body weight, total cholesterol or triglyceride levels were seen in vildagliptin-treated patients. Furthermore, no significant changes in immunosuppressive drug levels or dosages were observed in either group. Whether vildagliptin is safe and effective in the treatment of PTDM after orthotopic heart transplantation remains to be studied.

GLP-1 agonist therapy may confer a weight-loss benefit, counteracting the weight gain commonly seen in the setting of hyperglycemia and steroid therapy after transplantation (63, 64).  

The new sodium-glucose cotransporter type 2 (SGLT2) inhibitor has been shown to increase urinary glucose excretion and improve hyperglycemia in type 2 diabetes. An experimental animal model of tacrolimus-induced diabetes demonstrated that empagliflozin improves hyperglycemia and suppressed the tacrolimus-induced twofold increase in the expression of SGLT2 receptors (65). Furthermore, empagliflozin was found to have a direct protective effect on tacrolimus-induced renal injury. This study suggests that a SGLT2 inhibitor is a suitable therapeutic option for transplant recipients with tacrolimus-induced PTDM. Nonetheless, it should be noted that SGLT2 has been reported to be associated with increased risk for urinary tract infections and genital candidiasis, potentially limiting its use in the immunosuppressed transplant population. The use of SGLT2 inhibitors in the transplant setting cannot be recommended until safety data are available. The empagliflozin in renal transplant recipients (EMPA-RenalTx) is an ongoing single-center, prospective, placebo-controlled, double blind randomized study evaluating the safety and efficacy of empagliflozin in the treatment of PTDM (NCT03157414).  

Evidence-based studies recommending one antihyperglycemic agent over the other in the context of transplantation are currently lacking. An incretin-based regimen appears safe and effective in kidney transplant recipients. Nonetheless, the choice of individual agents should be based on the potential advantages and disadvantages of different classes of agents (Figure 4). Failure to achieve glycemic control despite multiple antihyperglycemic agent combination therapy generally requires initiation of insulin therapy. The 2014 international consensus guidelines on the screening, diagnosis, and management of early posttransplant hyperglycemia and PTDM is shown in Figure 1. The authors’ suggested protocol for screening, diagnosis, and management of early posttransplantation hyperglycemia and PTDM is shown in Figure 5 (practice varies among centers).

Figure 5. Screening and management of PTDM (opinion-based)

 

SUMMARY

 

PTDM is a common complication after solid organ transplantation and has variably been reported to be associated with increased morbidity and mortality. Risk stratification, intervention to minimize risk and early diagnosis may alleviate the incidence of PTDM and improve outcomes following solid organ transplantation. The 2014 International Consensus Guidelines suggest expanding screening tests for PTDM using postprandial glucose monitoring and HbA1C test. However, the latter should be used with caution in the early posttransplant period. A normal HbA1C does not exclude the diagnosis of PTDM in the presence of early posttransplant anemia and/or dynamic kidney allograft function. Whether intravenous iron therapy and/or the use of erythropoietin stimulating agent result in falsely low A1C levels remains to be studied. The routine recommendation of early initiation of insulin therapy in patients with new onset hyperglycemia during the first posttransplantation week to preserve β-cell function and progression to overt PTDM awaits results of randomized clinical trials. Management of established late PTDM should follow the conventional approach and guidelines established for the general population. When lifestyle modification fails to achieve glycemic control, medical intervention is often necessary. The choice of one antihyperglycemic agent over the other should be based on the potential advantages and disadvantages of individual agents. The use of metformin in the setting of solid organ transplantation should be individualized. Incretin-based regimen appears safe and effective in kidney transplant recipients. Similar to the general population, insulin therapy should be considered in individuals with suboptimal glycemic control despite multiple antihyperglycemic agent combination therapy.

REFERENCES

 

  1. Starlz TE. Experience in renal transplantation. Philadelphia: Saunders 1964:111.
  2. Gunnarsson R, Arner P, Lundgren G, et al. Steroid diabetes after renal transplantation. A preliminary report. Scan Urol Nephrol Suppl 1977; 42:191-194.
  3. Araki M, Flechner SM, Ismail HR, et al. Posttransplant diabetes mellitus in kidney transplant recipients receiving calcineurin or mTOR inhibitor drugs. Transplantation 2006; 81(3): 335-341.
  4. Crutchlow MF, Bloom RD. Transplant-associated hyperglycemia: a new look at an old problem. Clin J Am Soc Nephrol 2007; 2(2):343-355.
  5. Bloom RD, Crutchlow MF. New-onset diabetes mellitus in the kidney recipients: diagnosis and management strategies. Clinical J Am Soc Nephrol 2008; 3: S38-48.
  6. Pham PT, Pham PVC, Lipshutz G. New onset diabetes mellitus after solid organ transplantation. Endocrinol Metab Clin North Am 2007; 36(4): 873-890.
  7. Sharif A, Hecking M, de Vries AP, et al. Proceedings from an international consensus meeting on posttransplantation diabetes mellitus: recommendations and future directions.  Am J Transplant. 2014; 14(9):1992-2000.
  8. Pham PT, Pham PM, Pham SV, Pham PA, Pham PC. New onset diabetes after transplantation (NODAT): an overview.  Diabetes Metab Syndr Obes. 2011; 4:175-86.
  9. Davidson J, Wilkinson AH, Dantal J, et al. New-onset diabetes after transplantation: 2003 International Consensus Guidelines. Transplantation. 2003;7: SS3–SS24.
  10. American Diabetes Association. Standards of Medical Care in Diabetes 2011. Diabetes Care 2011; 34: S11.
  11. Ng JMCooke MBhandari S, et al. The effect of iron and erythropoietin treatment on the A1C of patients with diabetes and chronic kidney disease. Diabetes Care 2010; 33(11): 2310-2313.
  12. Baid S, Cosimi AB, Farrell ML, et al. Posttransplant diabetes mellitus in liver transplant recipients: risk factors, temporal relationship with hepatitis C virus allograft hepatitis, and impact on mortality. Transplantation. 2001; 72:1066–1072.
  13. Knobler H, Stagnaro-Green A, Wallenstein S, et al. Higher incidence of diabetes in liver transplant recipients with hepatitis C. J Clin Gastroenterol. 1998; 26:30–33.
  14. Ye X, KuoH-T, Sampaio MS, Jiang Y, Bunnapradist S. Risk factors for the development of new-onset diabetes mellitus after transplant in adult lung transplant recipients. Clin Transplant. 2010; DOI 10. 1111:1–7.
  15. Lieber SRLee RAJiang Y, et al. The Impact of Post-Transplant Diabetes Mellitus on Liver Transplant Outcomes. Clin Transplant.2019 Mar 29: e13554. doi: 10.1111/ctr.13554. [Epub ahead of print].
  16. Cosio FG, Pesavento TE, Osei K, et al. Posttransplant diabetes mellitus: increasing incidence in renal allograft recipients transplanted in recent years. Kid Int 2001; 59(2): 732-737.
  17. Kasiske BL, Snyder JJ, Gilbertson D, et al. Diabetes mellitus after kidney transplantation in the United States. Am J transplant 2003;3(2): 178-185.
  18. Martinez-Castelao A, Hernandez MD, Pascual J, et al. Detection and treatment of post kidney transplant hyperglycemia: a Spanish multicenter cross-sectional study. Transplant Proc 2005;37: 3813-3816.
  19. Quaglia M1, Terrazzino S, Musetti C, et al. The Role of TCF7L2 rs7903146 in Diabetes After Kidney Transplant: Results From a Single-Center Cohort and Meta-Analysis of the Literature. Transplantation 2016; 100(8): 1750-1758.
  20. Jenssen T, Hartmann A. Post-transplant diabetes mellitus in patients with solid organ transplants. Nat Rev Endocrinol 2019; 15(3): 172-188.
  21. Elens L, Sombogaard F, Hesselink D, et al. Single-nucleotide polymorphism in P450 oxidoreductase and peroxisome proliferator-activated receptor are associated with the development of new onset diabetes after transplantation in kidney transplant recipients treated with tacrolimus. Pharmacogenet Genomics. 2013; 23:649-657 (21)
  22. El Essawy B, Kandeel F. Pre, peri and posttransplant diabetes mellitus. Current opinion Nephrol Hypertens. 2018; 28: 47-57 (22)
  23. Kotton CN, Kumar D, Caliendo AM, et al. The Transplantation Society International CMV Consensus Group. The Third International Consensus Guidelines on the Management of Cytomegalovirus in Solid-organ Transplantation. Transplantation. 2018 Jun;102(6):900-931.
  24. Boudreaux JP, McHugh L, Canafax DM, et al. The impact of cyclosporine and combination immunosuppression on the incidence of post transplant diabetes in renal allograft recipients. Transplantation. 1987;44(3):376–381.
  25. Ojo AO. Cardiovascular complications after renal transplantation and their prevention. Transplantation. 2006;82(5):603–611.
  26. Joss N, Staatz CE, Thomson AH, et al. Predictors of new onset diabetes after renal transplantation 2007;21(1): 136-143.
  27. Kuo H-T, Sampaio MS, Vincenti F, et al. Associations of pretransplant diabetes mellitus, New-Onset Diabetes Mellitus after Transplant, and acute rejection with transplant outcomes: an analysis of the Organ Procurement and Transplant Network/United Network for Organ Sharing (OPTN/UNOS) database. 2010;56(6): 1026-1028.
  28. Burroughs TE, Swindle J, Takemoto S, et al.  Diabetic complications associated with new-onset diabetes mellitus in renal transplant recipients. Transplantation. 2007;83(8):1027.
  29. Kuo HT, Lum E, Martin P, et al. Effect of diabetes and acute rejection on liver transplant outcomes, an analysis of the OPTN/UNOS database. Liver Transpl 2016; 22(16): 796-804
  30. Roccaro GA, Goldberg DS, Hwang WT, et al. Sustained posttransplantation diabetes is associated with long-term major cardiovascular events following liver transplantation. Am J Transplant 2018; 18(1): 207-215
  31. ForoutanF, Alba AC, Guyatt G, et al. Predictors of 1-year mortality in heart transplant recipients: a systematic review and meta-analysis. Heart. 2018 Jan;104(2):151-160.
  32. Kim HJ, Jung SH, Kim JJ et al. New-onset diabetes mellitus after heart transplantation: incidence, risk factors, and impact on clinical outcome. Circ J 2017; 806-814
  33. Christie JD, Edwards LB, Kucheryavaya AY, et al. The registry of the international society of heart and lung transplantation: twenty-seventh official adult transplant report 2010. J Heart Lung Transplant 2010; 1105-1118
  34. Hackman KL, Snell GI, Bach LA. Poor glycemic control is associated with decreased survival in lung transplant recipients. Transplantation 2017; 2200-2205
  35. Hackman KL, Bailey MJ, Snell GI. Diabetes is a major risk factor for mortality after lung transplant. Am J Transplant 2014; 14: 438-445
  36. Wilkinson AH, Davidson J, Dotta F, et al. Guidelines for the treatment and management of new-onset diabetes after transplantation. Clin Transplant. 2005; 19:291–298.
  37. Nathan DM, Davidson MB, DeFronzo RA, et al. Impaired fasting glucose and impaired glucose tolerance. Diabetes Care 2007; 30:753.
  38. Pham PT, Pham SV, Lee M, et al. Evaluation of the potential kidney transplant candidates. In: Pham PT, Pham PC. Quick Guide to Kidney Transplantation: From Initial Evaluation to Long-Term Post-Transplant Care. First Edition. Lippincott, Williams and Wilkins 2019; pp 40-58.
  39. Chakkera HA, Weil EJ, Pham PT, et al. Can new-onset diabetes after kidney transplant be prevented? Diabetes Care 2013; 36: 1406-1412.
  40. Pham PT, Edling KL, Chakkera HA, et al. Screening strategies and predictive diagnostic tools for the development of new-onset diabetes mellitus after transplantation: an overview.  Diabetes Metab Syndr Obes. 2012; 5:379-87.
  41. Knowler WC, Barrett-Connor E, Fowler SE, et al. Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. N Engl J Med 2002; 346: 393-403.
  42. Sharif A, Moore R, Baboolal K. Influence of lifestyle modification in renal transplant recipients with postprandial hyperglycemia. Transplantation 2008; 85: 353-358.
  43. Kim Y, Kim JR, Choi H, et al. Patients with persistent new-onset diabetes after transplantation have greater weight gain after kidney transplantation.  J Korean Med Sci. 2013 Oct;28(10):1431-4.
  44. Hecking M, Haidinger M, Doller D, et al. Early basal insulin therapy decreases new-onset diabetes after transplantation. J Am Soc Nephrol 2012; 23: 739-749.
  45. Hecking M, Werzowa J, Haidinger M, et al. Novel views on new-onset diabetes after transplantation: development, prevention and treatment.  Nephrol Dial Transplant. 2013 Mar;28(3):550-66.
  46. Heisel O, Heisel R, Balshaw R, et al. New onset diabetes in patients receiving calcineurin inhibitors: a systematic review and meta-analysis. Am J Transplant 2004; 4(4): 583-595.
  47. Vincenti F, Friman S, Scheuermann E, et al. Results of an international, randomized trial comparing glucose metabolism disorders and outcome with cyclosporine versus tacrolimus.  Am J Transplant. 2007 Jun;7(6):1506-14.
  48. Rathi M, Rajkumar V, Rao N, et al. Conversion from tacrolimus to cyclosporine in patients with new-onset diabetes after renal transplant: an open-label randomized prospective pilot study.  Transplant Proc. 2015 May;47(4):1158-61.
  49. Wissing KM, Abramowicz D, Weekers L, et al. Prospective randomized study of conversion from tacrolimus to cyclosporine A to improve glucose metabolism in patients with posttransplant diabetes mellitus after renal transplantation. Am J Transplant. 2018;18(7):1726-1734.
  50. Pascual J, Royuela A, Galeano C, et al. Very early steroid withdrawal or avoidance for kidney transplant recipients: A systematic review. Nephroll Dial Transplant 2012; 27: 825-832.
  51. Pascual J, Galeano C, Royuela A, et al. A systematic review on steroid withdrawal between 3 and 6 months after kidney transplantation. Transplantation 2010; 90: 343-349.
  52. Nathan DM, Buse JB, Davidson MB, et al. Medical management of hyperglycemia in type 2 diabetes: a consensus algorithm for the initiation and adjustment of therapy: a consensus statement of the American Diabetes Association and the European Association for the Study of Diabetes.  Diabetes Care. 2009;32(1):193.
  53. Alnasrallah B, Pilmore H, Manley P. Protocol for a pilot randomized controlled trial of metformin in pre-diabetes after kidney transplantation: the transplantation and diabetes (Transdiab) study. BMJ Open 2017; 7, e016813
  54. Maedler K, Carr RD, Bosco D, et al. Sulfonylurea induced beta-cell apoptosis in cultured human islets. The J of Clin End and Metab 2005; 90: 501-506.
  55. Mu J, Petrov A, Eiermann GJ, Woods J, et al. Inhibition of DPP-4 with sitagliptin improves glycemic control and restores islet cell mass and function in a rodent model of type 2 diabetes. Eur J Pharmacol 2009; 623(1-3): 148-154.
  56. Cho JM, Jang HW, Cheon H, et al. A novel dipeptidyl peptidase IV inhibitor DA-1229 ameliorates streptozocin-induced diabetes by increasing β-cell replication and neogenesis. Diabetes Res Clin Pract 2011; 91(1): 72-79.
  57. Halden TAS, Asberg A, Vik K, et al. Short-term efficacy and safety of sitagliptin treatment in long-term stable renal recipients with new-onset diabetes after transplantation. Nephrol Dial Transplant 2014; 14: 115-123.
  58. Haidinger M, Werzowa J, Hecking M, et al. Efficacy and safety of vildagliptin in new-onset diabetes after kidney transplantation. A randomized, double-blind, placebo-controlled trial. Am J Transplant 2014; 14: 115-123
  59. Boerner BPMiles CDShivaswamy V. Efficacy and safety of sitagliptin for the treatment of new-onset diabetes after renal transplantation. Int J Endocrinol.2014;2014:617638. doi: 10.1155/2014/617638. Epub 2014 Apr 10.
  60. Werzowa J, Hecking M, Haidinger M, et al. Vildagliptin and pioglitazone in patients with impaired glucose tolerance after kidney transplantation: a randomized, placebo-controlled clinical trial. Transplantation 2013; 95(3): 456-462.
  61. Abdelaziz TSAli AY1, Fatthy M. Efficacy and safety of Dipeptidyl Peptidase-4 Inhibitors in kidney transplant recipients with Post-transplant diabetes mellitus (PTDM)-a systematic review and Meta-Analysis. Curr Diabetes Rev.2019 Mar 21. doi: 10.2174/1573399815666190321144310. [Epub ahead of print]
  62. Gueler IMueller SHelmschrott M, et al. Effects of vildagliptin (Galvus®) therapy in patients with type 2 diabetes mellitus after heart transplantation. Drug Des Devel Ther.2013 Apr 8;7:297-303.
  63. Pinelli NR, Patel A, Salinitri FD. Coadministration of liraglutide with tacrolimus in kidney transplant recipients: a case series. Diabetes Care. 2013 Oct;36(10): e171-172.
  64. Sadhu ARSchwartz SSHerman ME. The rationale for use of incretins in the management of New Onset Diabetes after Transplantation (NODAT). Endocr Pract.2015 Jul;21(7):814-822.
  65. Jin JJin LLuo K, et al. Effect of Empagliflozin on Tacrolimus-Induced Pancreas Islet Dysfunction and Renal Injury. Am J Transplant.2017;17(10):2601-2616.

 

 

Hypertriglyceridemia: Pathophysiology, Role of Genetics, Consequences, and Treatment

ABSTRACT

 

Hypertriglyceridemia (HTG) can result from a variety of causes. Mild to moderate HTG occurs commonly as part of the metabolic syndrome, can be the result of multiple genetic mutations in an individual or family, and can be secondary to several diseases and drugs. Severe HTG with plasma triglyceride (TG) levels >1000-1500 mg/dL can result from 3 groups of conditions: (1) rare mutations in the lipoprotein lipase (LPL) complex, where it is termed the familial chylomicronemia syndrome (FCS), (2) the co-existence of genetic and secondary forms of HTG, termed the multifactorial chylomicronemia syndrome (MFCS), which is a much more common cause of severe HTG, and (3) familial partial lipodystrophy (FPLD).  Mild to moderate HTG is associated with an increased risk of premature cardiovascular disease (CVD), while severe HTG can lead to pancreatitis and other features of the chylomicronemia syndrome, as well as an increased risk of premature CVD. Appropriate management of the patient with HTG requires knowledge of the likely cause of the HTG, in order to prevent itscomplications.

 

ABBREVIATIONS USED

 

HTG – hypertriglyceridemia

TG - triglyceride

FCS – familial chylomicronemia syndrome

MFCS – multifactorial chylomicronemia syndrome

FPLD – familial partial lipodystrophy

FFA – free fatty acids

LPL – lipoprotein lipase

ANGPTL – angiopoietin-like protein

CVD – cardiovascular disease

FCHL – familial combined hyperlipidemia

 

PHYSIOLOGY

 

A detailed overview of lipoprotein physiology is provided in the chapter on Lipoprotein Metabolism (1).  Here we will briefly review some aspects the metabolism of the triglyceride (TG)-rich lipoproteins (VLDL and chylomicrons) of particular relevance to this chapter.

 

Secretion of TG-rich Lipoproteins Into Plasma

 

TGs are transported through plasma as very low-density lipoproteins (VLDL), which transport TGs primarily made in the liver, and as chylomicrons, which transport dietary (exogenous) fat.  VLDL secretion by the liver is regulated in several ways.  Each VLDL particle has one apoB100 molecule, making apoB100 availability a key determinant of the number of VLDL particles, and hence, TG secretion by the liver.  In addition to one molecule of apoB-100, each VLDL particle contains multiple copies of other apolipoproteins, together with varied amounts of TGs, cholesteryl esters and phospholipids.  The extent of TG synthesis is in part determined by the flux of free fatty acids (FFA) to the liver.  The addition of TG to the developing VLDL particle in the endoplasmic reticulum is mediated by the enzyme microsomal triglyceride transfer protein (MTP).  The pool of apoB100 in the liver is not typically regulated by its level of synthesis, which is relatively constant, but by its level of degradation, which can occur in several proteolytic pathways (2).   Insulin also plays a role in the regulation of VLDL secretion -  it decreases hepatic VLDL production by limiting fatty acid influx into the liver, decreases the stability of, and promotes the posttranslational degradation of apoB100 (3).  Recent studies have shown that apoC-III, an apolipoprotein thought to primarily play a role in inhibiting TG removal (see below), also is involved in the assembly and secretion of VLDL (4). VLDL particles (containing apoB100) also increase in plasma in the postprandial state as well as chylomicrons that contain apoB48 (5).

 

Consumption of dietary fat results in the formation of chylomicrons by enterocytes.  Fatty acids and monoacylglycerols that result from digestion of dietary TGs by acid and pancreatic lipases are transported into enterocytes by mechanisms that are not completely understood.  In the enterocyte, monoacylglycerol and fatty acids are resynthesized into TGs by the action of the enzymes acyl-coenzyme A: monoacylglycerol acyltransferase and acyl-coenzyme A: diacylglycerol acyltransferase 1 and 2. The resulting TGs are packaged with apoB48 to form chylomicrons, a process also mediated by MTP (6).   Chylomicrons then pass into the thoracic duct from where they enter plasma and acquire additional apolipoproteins.  Of particular relevance to their clearance from plasma is the acquisition of apoC-II and apoC-III. 

 

Catabolism of the TG-rich Lipoproteins

 

TGs in both VLDL and chylomicrons are hydrolyzed by the lipoprotein lipase (LPL) complex.  LPL is synthesized by several tissues, including adipose tissue, skeletal muscle and cardiac myocytes.  After secretion by adipocytes, the enzyme is transported by glycosylphosphatidylinositol-anchored high-density lipoprotein–binding protein 1 (GPIHBP1) to the luminal side of the capillary endothelium, where it becomes tethered to glycosaminoglycans (GAGs).  This pool of LPL is referred to as “functional LPL”, since it is available to hydrolyze TGs in both VLDL and chylomicrons.  LPL can be liberated from these GAG binding sites by heparin injection. Several other proteins, reviewed in (7), regulate LPL activity. These include apoC-II, which activates LPL, and apoC-III, which inhibits LPL in addition to its effect on VLDL secretion alluded to earlier.  Both are produced by the liver and are present on TG-rich lipoproteins.  ApoC-III also inhibits the turnover of TG-rich lipoproteins through a hepatic clearance mechanism involving the LDL receptor/LDL receptor-related protein 1 (LDLR/LRP1) axis (8).  ApoE also is present on the TG-rich lipoproteins and plays an important role in the uptake and clearance of the remnants of the TG-rich lipoproteins that result from hydrolysis of TGs in these lipoproteins.  Other activators of LPL include apoA-IV (9), apoA-V (10-12)and lipase maturation factor 1 (LMF1) (13,14).  In addition, several members of the angiopoeitin-like (ANGPTL) protein family play a role in regulating LPL activity.  ANGPTL3 is produced by the liver and is an endocrine regulator by inhibiting LPL in peripheral tissues (7,15,16).  ANGPTL4 is produced in several tissues (7), where it inhibits LPL in a paracrine fashion (7,17).  Both ANPGTL3 and ANGPTL4 retard the clearance of the TG-rich lipoproteins (7).

 

The core TGs in VLDL and chylomicrons are hydrolyzed by apoC-II activated LPL; FFA thus formed are taken up by adipocytes and reincorporated into TGs for storage, or in skeletal and cardiac muscle, utilized for energy.  Hydrolysis of chylomicron- and VLDL-TG results in TG-poor, cholesteryl ester and apoE-enriched particles called chylomicron and VLDL remnants, respectively, which under physiological conditions are removed by the liver by binding to LDL receptors, LDL receptor related protein, and cell surface proteoglycans (12,18). Hepatic TG lipase and apoA-V also are involved in the remnant clearance process (10-12,19,20).

 

It is important to appreciate that the clearance of TGs from plasma is saturable when plasma TGs exceed ~500-700 mg/dL (21).  Once removal mechanisms are saturated, additional chylomicrons and VLDL entering plasma cannot readily be removed and hence accumulate.  As a result, plasma TGs can increase dramatically, resulting in very high levels and the accumulation of chylomicrons in plasma obtained after an overnight fast. 

 

NORMAL RANGE FOR PLASMA TRIGLYCERIDES AND DEFINITION OF HYPERTRIGLYCERIDEMIA

 

Statistical Determination of a Normal Range

 

Normal ranges often are defined by statistical upper limits (e.g., >95thpercentile or >2SD from the mean) for a normal local population.   However, it is important to appreciate that TGs increase with age (22), differ between males and females (23), and that their distribution within populations is heavily skewed to the right (24,25).  Because of this skewed distribution, logarithmic transformation is required to establish statistical normal ranges.  A more rational approach might be to define normal as a level below which complications do not occur. 

 

Normal Range Based on Risk of Complications of HTG

 

Use of such an approach to the establishment of a normal range for plasma TG concentrations requires a detailed knowledge of the morbidities associated with elevated TG levels.  The major complications of hypertriglyceridemia (HTG) are (1) increased risk of cardiovascular disease (CVD) and (2) acute pancreatitis.  These consequences of HTG are discussed in detail later in this chapter.  As will become evident, these two complications occur at different levels of TGs, the risk of pancreatitis occurring at much higher TG levels than the risk of premature CVD.  Moreover, the cause of the HTG can be an important determinant of risk.  Equivalent TG levels may not confer equal risk of CVD in different genetic and secondary forms of HTG.  Rather, the specific form of the HTG, associated lipid and lipoprotein abnormalities, and other CVD risk factors may be more important determinants of CVD risk than the TG level per se.  Thus, establishing a normal range is actually more complicated than simply applying statistical approaches.

 

Normal Range According to Guidelines

 

Despite these concerns regarding establishment of an upper limit of normal for TGs, most guidelines define values for HTG, often without a strong biological rationale.  Definitions for the diagnosis of HTG provided in several guidelines are shown in Table 1.   

 

Cut points for HTG were first defined by the National Cholesterol Education Program Adult Treatment Panel (NCEP-ATP). The term moderate HTG has been used more recently by the Endocrine Society (26)for TG levels between 200 to 999 mg/dL, severe HTG for 1000 to 1999 mg/dL  and very severe HTG for values >2000 mg/dL.  Hegele et al have proposed a simplified classification of HTG(27).  Based on genetic data, they divide HTG into two states: severe (TG concentration >10 mmol/L or 885 mg/dL), which is more likely to have a monogenic component; and mild-to-moderate (TG concentration 2-10 mmol/L, or 175-885 mg/dL).  Rare autosomal recessive monogenic HTG usually results from large-effect mutations in six different genes.  Mild-to-moderate HTG is typically multigenic and results from the cumulative burden of common and rare variants in more than 30 genes, as quantified by genetic risk scores.  All genetic forms can be exacerbated by non-genetic factors.

 

Table 1. Definition of Hypertriglyceridemia According to Various Clinical Guidelines

Guideline

Classification

Triglyceride Levels

NCEP/ ATP III (28)

American Heart Association (29)

National Lipid Association (30)

 

Normal

Borderline-high TGs

High TGs

Very high TGs

<150 mg/dL (< 1.7 mmol/L)

150-199 mg/dL (1.7-2.3 mmol/L)

200-499 mg/dL (2.3-5.6 mmol/L)

≥500 mg/dL (≥5.6 mmol/L)

The Endocrine Society (31)

Normal

Mild HTG

Moderate HTG

Severe HTG

Very severe HTG

<150 mg/dL (< 1.7 mmol/L)

150-199 mg/dL (1.7-2.3 mmol/L)

200-999 mg/dL (2.3-11.2 mmol/L)

1000-1999 mg/dL (11.2-22.4 mmol/L)

≥2000 mg/dL (≥22.4 mmol/L)

European Society of Cardiology/European Atherosclerosis Society (32)

Normal

Mild-moderate HTG

Severe HTG

<1.7 mmol/L (<150mg/dL)

1.7<10mmol/L (150-880 mg/dL)

> 10 mmol/L (> 880mg/dL)

Hegele (27)

Normal

Mild to moderate

Severe

<2.0 mmol/L (<175 mg/dL)

2.0-10 mmol/L (175- 885 mg/dL)

>10 mmol/dL (>885 mg/dL)

 

In summary, establishing a precise definition of what constitutes abnormal TG values is fraught with difficulty. Evaluation of plasma TG values in the individual patient should be interpreted in the light of these considerations. For example, an acceptable level for the prevention of pancreatitis is likely to be quite different from that at which CVD risk might be increased.  The impact of HTG on CVD risk needs to be evaluated in the context of the family history of premature CVD, associated abnormalities of lipids and lipoproteins, and other CVD risk factors, particularly those associated with the metabolic syndrome (see later).

 

CAUSES OF HYPERTRIGLYCERIDEMIA

 

In general, HTG has been classified as primary, when a genetic or familial basis is suspected, or secondary, where other conditions that raise TG levels can be identified.  However, this classification may be overly simplistic. It has become clear in the past decade that the spectrum of plasma TG levels, ranging from mild elevation to very severe HTG, is modulated by a multitude of genes working in concert with non-genetic secondary and environmental contributors  Thus, in the vast majority of individuals, mutations in multiple genes with interaction from non-genetic factors result in altered TG-rich lipoprotein synthesis and catabolism and subsequent HTG.

 

Historical perspective

 

Phenotypic heterogeneity among patients with HTG has been historically defined by qualitative and quantitative differences in plasma lipoproteins. In the pre-genomic era, the Fredrickson classification of hyperlipoproteinemia was based on electrophoretic patterns of lipoprotein fractions (33).  This classification included 6 phenotypes, five of which included HTG in their definition. The phenotypes are distinguished based on the specific class or classes of accumulated TG-rich lipoprotein particles, including chylomicrons, VLDL and VLDL-remnants. However, this classification system is dated, has neither improved clinical or scientific insight, and therefore does not find wide use at this time (27).

 

In 1973, Goldstein and colleagues characterized a variable pattern of lipid abnormalities in families of survivors of myocardial infarction that they termed familial combined hyperlipidemia (FCHL) (34).  At the same time, this phenotype of mixed or combined hyperlipidemia was observed in another cohort, where it was called multiple-type familial hyperlipoproteinemia (35).  Affected family members can present with hypercholesterolemia alone, HTG alone, or with elevations in both TGs and LDL.  This pattern was estimated to have a population prevalence of 1-2% (36), making it the most common inherited form of dyslipidemia.

 

In the aforementioned study, a pattern of isolated HTG, historically called familial HTG (FHTG) also was described (34).  This condition was characterized by increased TG synthesis, with secretion of normal numbers of large TG-enriched VLDL particles (37), elevated VLDL levels, but normal levels of LDL and HDL cholesterol (38).  FHTG did not appear to be associated with an increased risk of premature CVD in an early study (39), but baseline TG levels predicted subsequent CVD mortality after 20 years of follow up among relatives in families classified as having FHTG (40),(41).  

 

FCHL and FHTG were initially thought to be monogenic disorders (34).  However, more recent genetic characterization of individuals with familial forms of HTG indicates that these are not disorders associated with variation within a single gene, but rather polymorphisms in multiple genes associated with HTG, as detailed below.  Therefore, classification of FCHL and FHTG is potentially misleading.  Nevertheless, it is important to note that FCHL as originally described is associated with a very high prevalence of premature CVD (39,40,42).  Thus, identifying clinical “FCHL” or combined hyperlipidemia, albeit not a monogenic disorder, is useful for CVD prevention in individuals and their affected family members (43).

 

Current Concepts: Genetic Forms of Hypertriglyceridemia

 

Hypertriglyceridemia alone or with associated lipid or lipoprotein abnormities such as elevated levels of low density lipoproteins (LDL) or reduced levels of high density lipoprotein cholesterol (HDL-C), tends to cluster in families (27).  It is now evident that clinically relevant abnormalities of plasma TG levels appear to require a polygenic foundation of common or rare genetic variants(27).  Common small-effect gene variants confer a background predisposition that interact with rare large-effect heterozygous variantsin genes that govern synthesis or catabolism of TG-rich lipoproteins, or nongenetic secondary factors, leading to the expression of a more severe TG phenotype (44).  Recently, the most prevalent genetic feature underlying severe HTG was shown to be the polygenic accumulation of common (rather than rare) variants—more specifically, the accumulation of TG-raising alleles across multiple SNP loci (45).

 

Genetic characterization of individuals originally classified as FCHL and FHTG indicates that these are not simple disorders associated with variation within a single gene (46).  Common variants in TG loci associate not only with TG but also with HDL-C and LDL-C levels.  What was historically termed FHTG appears to be the foundation of all hypertriglyceridemic states; it results from presence of common and rare genetic variants that increase susceptibility to development of HTG.  An excess of polygenic common LDL-C-raising alleles in the genomes of individuals who already carry a burden of polygenic HTG susceptibility can produce a combined hyperlipidemia phenotype with increased LDL-C and TG (historically referred to as “FCHL”).

 

Genome wide association studies (GWAS) have identified SNPs in at least 45 loci associated with plasma TG levels, affecting TGs alone or in combination with other lipoproteins (47,48).  Certain common variants in several genes are strongly associated with susceptibility to HTG.  One chromosomal locus that has been consistently linked to HTG is 1q21–23 (49).  Linkage to several FCHL traits has been observed, including apoB, plasma TG and cholesterol levels (50).  The apoA1/C3/A4/A5 gene cluster, which associates with TG levels and LDL particle size, is an important modifier gene present at the 1q21–23 locus that has been linked with FCHL and its related traits in several but not all studies (51).     Another commonly linked gene is the ubiquitous transcription factor upstream stimulatory factor 1 (USF1), which has numerous target genes, including several related to lipid and glucose metabolism (52).  Determining how genetic variance in USF1 contributes to the cause and phenotype of combined hyperlipidemia has thus far remained elusive.

 

Some of the currently known gene associations in combined hyperlipidemia are listed in Table 2 and a detailed review of gene associations is available (49).  In general, implicated genes are primarily those involved in VLDL production, catabolism and adipose tissue function.  These include hormone sensitive lipase (LIPC), which enables lipolysis of TG-rich lipoproteins, although its association with FCHL has been inconsistent (53-55), dysfunctional variants of LPL (56-61), adipose TG lipase (PNPLA2) (62)and the Pro446Leu variant of the glucokinase regulator gene (GCKR) that results in increased hepatic gluconeogenesis and reduced beta-oxidation (63).   

 

In summary, lipid disorders historically classified as FCHL and FHTG on clinical grounds are complex, genetically heterogeneous disorders.  Because they are a consequence of interaction between multiple susceptibility genes and lifestyle factors, it has been suggested by some that individuals with moderate HTG should be considered as a single group without distinction, irrespective of concomitant lipoprotein disturbances(27).  Because of the complexity of these disorders, routine genetic testing is not recommended.

 

Table 2. Selected Genes with Roles in Familial Combined Hyperlipidemia (FCHL)

Locus

Gene

Gene name

Protein function

Genes linked to VLDL overproduction

2p23

GCKR

Glucokinase (hexokinase 4) regulator

Inhibitor of glucokinase in liver

1q22-q23

USF1

Upstream transcription factor 1

Transcription factor that regulates many genes involved in lipid metabolism

Genes with involvement in TG metabolism and clearance

11q23-24

APOA-I, APOC-III, APOA-IV, APOA-V

Apo A-I,

apoC-III,

apoA-IV,

apoA-V

ApoA-1- cholesterol efflux;

ApoC-III- inhibitor of LPL and HL;

apoA-V- lipoprotein catabolism?

8p22

LPL

Lipoprotein lipase

TG hydrolysis in heart, muscle, adipose

15q21-23

HL

Hepatic lipase

TG hydrolysis in liver

7

SLC25A40

Solute carrier family 25 member 40

Mitochondrial membrane transport

Genes involved in adipose dysfunction

1q22-q23

USF1

Upstream transcription factor 1

Transcription factor that regulates many genes involved in lipid metabolism

19q13

LIPE

Hormone sensitive lipase

In WAT, hydrolyzes TG to FFA

 Adapted from reference (49).

 

Pathogenesis of Genetic Forms of HTG

 

Genetic forms of HTG without other lipoprotein disturbances (i.e., pure HTG) are characterized by increased TG synthesis, where normal numbers of large TG-enriched VLDL particles are secreted (37,64-66).  Reduced TG clearance also has been observed in some individuals (65-67).  Affected people have elevated VLDL levels, but normal levels of LDL, and are generally asymptomatic unless clinical CVD or severe HTG develops. 

 

A variety of metabolic defects that differ among families are associated with the combined hyperlipidemia phenotype. The characteristic lipoprotein abnormalities are increased apoB levels and increased number of small dense LDL particles (38), a phenotype similar to that seen in the metabolic syndrome and type 2 diabetes (68).  These primary defects occur due to 1) hepatic overproduction of VLDL particles (37)due to increased apoB synthesis in the setting of disordered adipose metabolism (69,70), insulin resistance (37,71-73)and liver fat accumulation, and, 2) impaired clearance of apoB containing particles (74,75).   Increased VLDL secretion results in an elevated plasma apoB and HTG (71).  Long residence time of VLDL particles favors the formation of small dense LDL (74).  An abundance of small dense LDL particles traditionally is associated with the presence of HTG; however, these LDL characteristics remain even after correction of the HTG by treatment with fibrates (76,77).

 

In addition to apo B abnormalities, other lipoprotein disturbances include abnormal expression of apoA-II, apoC-III, and PCSK9.  VLDL-TG levels in combined hyperlipidemia are modulated by apoA-II and apoC-III (78).  Plasma PCSK9 levels are higher in these patients, and levels correlate with TG and apo B levels (79).

 

Visceral adiposity appears to be an important determinant of insulin resistance, which occurs commonly in subjects with both isolated HTG (80)and combined hyperlipidemia (80-84).  Other abnormalities that have been reported in clinical FCHL include impaired lipolysis due to decreased cyclic AMP dependent signaling (69,84),  abnormal adipocyte TG turnover (85), fatty liver (86), increased arterial stiffness (87)and increased carotid intimal-medial thickness (88). 

 

In all of the phenotypes described above, severe HTG can occur when secondary causes of HTG such as untreated diabetes, marked weight gain or use of TG-raising drugs are present concurrently, leading to the Multifactorial Chylomicronemia Syndrome (MFCS), described later (89).

 

Diagnosis

 

Because of the heterogeneity of genetic forms of HTG, it has been suggested that individuals with moderate HTG be considered as a single group, irrespective of concomitant lipoprotein disturbances.  However, there is utility in making a clinical diagnosis of “FCHL”, since it identifies individuals and families atmarkedly increased risk for developing premature CVD, who likely would benefit from lipid-lowering therapy (90).  Variation in the phenotype both within and between individuals can makes diagnosis challenging (91,92).  The most consistent lipoprotein abnormality is an elevated apoB level in combination with elevated TGs (91).  ApoB levels > 90th percentile and small, dense LDL particles (93)can occur independent of central obesity (94), although assessment of LDL particle size and/or density is not routinely done in clinical practice.  Individuals with combined hyperlipidemia frequently have other CVD risk factors such as visceral adiposity, insulin resistance, impaired glucose tolerance and hypertension, i.e., features of the metabolic syndrome (see later).  Premature CVD in a male family member under age 55 and female family member under age 65 (28)is often present in families. CVD occurs in 11–14% of individuals with a combined hyperlipidemia phenotype and increases CVD risk in first- and second-degree relatives of affected individuals by up to 5-fold (95,96).  Conventional CVD risk assessment algorithms can underestimate absolute CVD risk in these because they do not account for family history of premature CVD. Obtaining a detailed family history is critical and assessment of plasma lipids from family members may be helpful in CV risk stratification in patients with elevated TGs, with or without a personal or family history of clinical CAD.  The presence of normal apoB levels may help distinguish other genetic forms of HTG from FCHL, where apoB levels tend to be higher (38,91). The presence of features of the metabolic syndrome also is useful in risk stratification.  In the population-based Family Heart Study, a large part of the CVD risk was accounted for by features of the metabolic syndrome, which was highly prevalent in subjects with HTG (80).  These observations suggest that identification of the metabolic syndrome may add benefit in risk stratifying patients with HTG.  Moreover, appropriate identification of individuals with genetic forms of HTG is important, since they are prone to development of marked HTG and resultant TG-induced pancreatitis if they develop concomitant secondary forms of HTG, including from alcohol and several drugs (see later).

 

Hypertriglyceridemia as a Component of the Metabolic Syndrome

 

HTG may also be present as part of the metabolic syndrome independent of a genetic form of HTG. The metabolic syndrome defines a cluster of risk factors that is associated with an increased risk of developing premature CVD (97,98).  One of the most widely used definitions for the diagnosis of the metabolic syndrome is from the NCEP ATP-III panel, which requires the presence of 3 of more of the following (28): central or abdominal obesity (measured by waist circumference ≥ 35 inches in women and ≥40 inches in men); TGs ≥ 150 mg/dL; HDL cholesterol <40 mg/dL in men and <50 mg/dL in women; blood pressure ≥130/85 mm Hg; and fasting glucose ≥100 mg/dL 2.  Several other features of the metabolic syndrome not included in this definition are insulin resistance, hypercoagulability, and the presence of inflammatory markers such as elevated levels of C-reactive protein (99).  It is estimated that up to one quarter to one third of the US population could have the metabolic syndrome (100), which constitutes a major risk for CVD in this country.  Després and colleagues have coined the term “hypertriglyceridemic waist” to describe patients with HTG and central obesity who are at increased risk of developing CVD (101).  There is likely to be considerable overlap between these individuals and those classified as having the metabolic syndrome, although HTG is a requirement for being classified as having a “hypertriglyceridemic waist”.

 

The mechanism by which plasma TG levels are increased as part of the metabolic syndrome may relate to insulin resistance, since the presence of hepatic insulin resistance is believed to prevent the physiological effect of insulin in lowering VLDL secretion (102-104).  Overproduction of TG by the insulin resistant liver also is likely to be playing a major role in the pathogenesis of the HTG associated with type 2 diabetes (103).   However, diabetes also leads to a defect in adipose tissue LPL that may take as long as 3 months to correct (105).  The relationship between obesity and HTG also is complex.  Obesity can generally be divided into two major categories - metabolically unhealthy and metabolically healthy (or less unhealthy) obesity (106,107).  The former category occurs as part of the metabolic syndrome, the latter not so (108).  An important feature of the HTG that occurs as part of the metabolic syndrome, including that seen in diabetes, is that it is accompanied by the accumulation of a preponderance of small, dense LDL particles, LDL-C levels that are usually high normal or normal, and abnormalities in HDL-C and HDL composition.  The latter is characterized by low levels of HDL2and a reduction in the ratio of apoA-I/A-II (38).  This constellation of lipid and lipoprotein abnormalities has been termed diabetic dyslipidemia (109), but a similar lipoprotein pattern is characteristic of the metabolic syndrome (110). 

 

Remnant Removal Disease (Dysbetalipoproteinemia)

 

Remnant removal disease, dysbetalipoproteinemia or type III hyperlipoproteinemia, is a rare autosomal recessive disorder that can present with elevated TG levels.  This disorder is characterized by the accumulation of remnant lipoproteins.

 

PATHOGENESIS AND GENETICS

 

Remnant removal disease requires homozygosity for the apoE2 genotype or a rare heterozygosity for a dysfunctional mutation in the apoE gene, which results in impaired hepatic uptake of apoE-containing lipoproteins (46). Three common isoforms of apoE occur in humans, apoE2, apoE3, and apoE4 (111).  Each differs in isoelectric point by one charge unit, apoE4 being the most basic isoform and apoE2 the most acidic.  ApoE3 (Cys112àArg158) is the commonest isoform. ApoE2 (Arg158àCys) and apoE4 (Cys112àArg) differ from apoE3 by single amino acid substitutions at positions 158 and 112, respectively (112).  In the majority of cases, remnant removal disease is associated with the E2/E2 genotype and therefore an autosomal recessive disorder. The prevalence of apoE2 homozygosity in Caucasian populations is estimated to be about 1% (113).  While the apoE2 genotype is inherited in a recessive manner, rarer apoE variants such as apoE3-Leiden (114)and apoE2 (Lys1463Gln) that also can cause remnant accumulation are dominantly inherited (115). 

 

In the absence of additional genetic, hormonal, or environmental factors, remnants do not accumulate to a degree sufficient to cause hyperlipidemia in apoE2 homozygotes; in fact, hypolipidemia is commonly seen in this situation.  Remnant accumulation results when the E2/2 genotype is accompanied by a second genetic or acquired defect that causes overproduction of VLDL such as obesity or diabetes (116)(117,118), a decrease in remnant clearance, or a reduction in LDL receptor activity (e.g., hypothyroidism (119)).  Thus, full phenotypic expression requires the presence of other environmental or genetic factors (120).  In these circumstances, the reduced uptake of remnant lipoproteins by the liver results in reduced conversion of VLDL and intermediate density lipoproteins to LDL, with subsequent accumulation of remnant lipoproteins (121,122), hence the term remnant removal disease.

 

DIAGNOSIS

 

Patients with remnant removal disease have roughly equivalent elevations in plasma cholesterol and TGs. The disease rarely manifests before adulthood, and in some individuals never manifests clinically.  It is more common in men than in women, where expression seldom occurs before menopause, since estrogen has a protective effect in women who are apoE2 homozygotes (113).   Palmar xanthomas (Figure 1), orange lipid deposits in the palmar or plantar creases, are pathognomonic of remnant removal disease but are not always present (123). Tuberoeruptive xanthomas can be found at pressure sites on the elbows, knees and buttocks. The presence of remnant removal disease should be suspected when total cholesterol and TG levels range from 300 to 1000 mg/dL and are roughly equal in magnitude. VLDL particles are cholesterol- enriched, which can be determined by isolation of VLDL by ultracentrifugation and by the demonstration of beta migrating VLDL on electrophoresis.  A VLDL-cholesterol/plasma TG ratio of <0.30 is usually observed (124).  A low apoB/total cholesterol ratio of <0.33 also can be helpful in making the diagnosis (125). The diagnosis of remnant removal disease should be confirmed by demonstrating the presence of the E2/E2 genotype.If the genotype result is not E2/E2, an autosomal dominant variant of APOE should be suspected. There is a high prevalence of premature coronary artery disease (126-128)and peripheral arterial disease (129,130).  Occasionally severe HTG and an increased risk of pancreatitis can develop in the presence of a concomitant secondary form of HTG or TG-raising drugs.

Figure 1. Palmar Xanthomas: Note the orange-yellow discoloration confined to the palmar creases.

Secondary Forms of HTG

 

These are described in greater detail in the chapters on Secondary Disorders of Lipid and Lipoprotein Metabolism (131-134).  However, in the section where we describe MFCS we will briefly touch on some aspects of secondary forms of HTG, since they assume importance in the pathogenesis of the severe HTG seen in the MFCS, where they often co-exist in individuals with genetic forms of HTG.  In our experience, the commonest secondary forms of HTG that interact with genetic forms of HTG are type 2 diabetes (usually as part of the metabolic syndrome), alcohol, the use of TG-raising drugs, and chronic kidney disease (CKD)(89,135,136). 

 

Severe Hypertriglyceridemia and the Chylomicronemia Syndrome

 

In the late 1960s Fredrickson, Levy and Lees (33)classified HTG into types dependent on the pattern of lipoproteins on paper electrophoresis and the presence or absence of chylomicrons in fasting plasma.  They recognized that acute pancreatitis and eruptive xanthomata occurred in the presence of chylomicronemia that accumulate in what they termed Type I and Type V hyperlipoproteinemia.  Chylomicrons are present in the post-prandial state, and usually are present in fasting plasma when TG levels exceed 1000 mg/dL, but absent in fasting plasma below that value (137).  The term chylomicronemia syndrome was first used to describe a constellation of clinical findings such as abdominal pain, acute pancreatitis, eruptive xanthoma and lipemia retinalis that occurred in association with very high TG levels (138).   Three groups of conditions can lead to severe HTG and clinical manifestations of the chylomicronemia syndrome; (1) familial chylomicronemia syndrome (FCS) due to mutations in the LPL complex, (2) multifactorial chylomicronemia syndrome (MFCS), in which genetic and secondary forms of HTG nearly always co-exist, and (3) familial partial lipodystrophy (FPLD).

 

FAMILIAL CHYLOMICRONEMIA SYNDROME (FCS)

 

FCS resulting from a monogenic disorder is very rare, with an estimated prevalence of about 1 in 1,000,000 (139).  It usually is due to mutations in one or more genes of the LPL complex that affect chylomicron catabolism.  The most common gene affected in FCS is LPL itself, in which patients are homozygous or compound heterozygous for two defective LPL alleles.  Over 180 mutations that result in LPL deficiency have been described with some clustered mutations due to founder effects (140-143).  Loss of function mutations account for over 90% of cases (139).  Many are missense mutations, some in catalytically important sites and some in regions that predispose to instability of the homodimeric structure of LPL required for enzyme activity (144).  However, many common LPL gene variants have been described that have no clinical phenotype (145).  Mutations in the APOC2 gene, which encodes apoC-II, an activator of LPL, is another cause of FCS.  Mutations have been described in several families (146,147).

 

FCS can be due to homozygous mutations in other components of the LPL complex such as GPIHBP1, apoA-V, and LMF1 (Table 3), each of which plays an important role in determining LPL function (148).  The lipoprotein phenotype in these mimics that seen that in classical LPL deficiency. Loss of function mutations in GPIHBP1, which directs transendothelial LPL transport and helps anchor chylomicrons to the endothelial surface near LPL, thereby providing a platform for lipolysis, has been described in several families (139).  Autoantibodies to GPIHBP1 also can lead to chylomicronemia (149).  A small number of individuals with homozygous mutations in apo A-V, which stabilizes  the lipoprotein–enzyme complex thereby enhancing lipolysis (10), have been described (150).  Mutations in LMF1, an endoplasmic reticulum chaperone protein required for post-translational activation of LPL, have been identified in 2 patients (151).

 

These disorders usually present in childhood or early adolescence with very high TG levels and features of the chylomicronemia syndrome, although it can present in adulthood (143). Clinical findings include eruptive xanthomas, lipemia retinalis and hepatosplenomegaly, and a predisposition to acute pancreatitis, a serious condition that can result in the systemic inflammatory response syndrome, multi-organ failure, and death.

 

Table 3. Rare Genetic Disorders Affecting the LPL Complex

Disorder

Inheritance

Incidence

Lipid Phenotype

Underlying Defect

Clinical Features

LPL deficiency

Autosomal Recessive

1 in 1,000,000

Marked HTG/ chylomicronemia in infancy or childhood

Very low or absent LPL activity; circulating inhibitor of LPL

Hepato-splenomegaly; severe chylomicronemia

Apo C-II deficiency

Autosomal Recessive

Rare

Marked HTG/ chylomicronemia in infancy or childhood

Absent Apo C-II

Hepato-splenomegaly; severe chylomicronemia

Apo A-V mutation

Unknown

Rare

Marked HTG/ chylomicronemia later in adulthood

Defective or absent Apo A-V

Chylomicronemia

GPIHBP1 mutation

Unknown

Rare

Marked HTG/ chylomicronemia in adulthood

Defective or absent GPIHBP1

Chylomicronemia

LFM1 mutation

Unknown

Rare

Marked HTG/ chylomicronemia in adulthood

Defective of absent LFM1

Chylomicronemia

 Adapted from Ref (139)

 

MULTIFACTORIAL CHYLOMICRONEMIA SYNDROME (MFCS)

 

The prevalence of MFCS is much higher than FCS (140).  Most, if not all, patients with MFCS have a genetic form of moderate HTG co-existing with one or more secondary forms of HTG (152,153).   The most common secondary cause of HTG in the past was undiagnosed or untreated diabetes (89), although earlier detection of diabetes may be making the association of marked hyperglycemia of untreated diabetes with very severe HTG less common.  More recently, MFCS commonly results from the addition of specific drugs in patients with an underlying genetic form of HTG (26).  These include beta-adrenergic blocking agents (selective and non-selective) and/or diuretics (thiazides and loop-diuretics such as furosemide) used for hypertension, retinoid therapy for acne, oral estrogen therapy for menopause or birth control, selective estrogen receptor modulators (particularly raloxifene) for osteoporosis or breast cancer, protease inhibitors for HIV/AIDS, atypical anti-psychotic drugs, alcohol, and possibly sertraline (140).  Rarer causes of very severe HTG include autoimmune disease (sometimes with LPL- or GPIHBP1- specific antibodies), asparaginase therapy for acute lymphoblastic leukemia (154), (155)and bexarotene, a RXR agonist used in the treatment of cutaneous T cell lymphoma (156).  In addition, weight regain following successful weight loss has been associated with increasing TG levels (26,140).  These patients almost always have relatives with genetic forms of HTG, whose TG levels are considerably lower than the index patient with severe HTG, in whom secondary forms of HTG also are present (89). 

 

Table 4. Secondary Causes that Can Contribute to Severe HTG

Conditions

Hypothyroidism

Uncontrolled diabetes

Pregnancy

Nephrotic syndrome

Chronic Renal Failure

Acute hepatitis

Weight regain after weight loss

Sepsis

Autoimmune chylomicronemia

            Systemic lupus erythematosis

            Anti-LPL antibodies

Rare Genetic Causes

Glycogen storage disorders

Lipodystrophies

            Congenital- generalized or partial

            Acquired- HIV, autoimmune

Drugs

Alcohol

Beta blockers

Diuretics

Oral estrogens

Selective estrogen reuptake modulators - tamoxifen, raloxifene

Androgens

Glucocorticoids

Atypical anti-psychotics

Sertraline

Bile acid resins

Sirolimus, tacrolimus

Cyclosporine

RXR agonists -bexarotene, isotretinoin

HIV Protease inhibitors

L- asparaginase

Alpha-interferon

Propofol

Lipid emulsions

 

Following correction of treatable secondary forms of HTG in the MFCS, TG levels usually decrease to the moderately elevated levels seen in their affected relatives (152,153).  Johansen and Hegele have reported several single nucleotide polymorphisms that account for about 20% of the TG elevation in individuals with very severe HTG.  How the many common genetic variants that have small effects in patients with severe HTG (157)(see earlier) relate to the co-existence of familial and secondary forms of HTG, which in our experience is the usual cause of MFCS, is unknown.  Perhaps an additional single nucleotide variant is required in addition to the genetic and secondary forms of HTG in order to develop TG levels above 2000 mg/dL (158).

 

FAMILIAL PARTIAL LIPODYSTROPHY (FPLD)

 

The lipodystrophies are a group of heterogeneous inherited or acquired disorders that are characterized by selective loss of body fat and HTG(159)and are reviewed elsewhere in the chapter on Lipodystrophies (160).  Loss of fat can be either localizedto small discrete areas, in some cases partialwith loss from extremities, or generalizedwith fat loss from nearly the entire body. Inherited lipodystrophies, while rare, can be autosomal dominant or recessive.  Some forms manifest at birth, while others become evident later in life.

 

Partial or generalized lipodystrophic disorders frequently are associated with significant metabolic derangements associated with severe insulin resistance, including HTG.  The extent of fat loss sometimes determines the severity of metabolic complications(161).  HTG is a common accompaniment of many lipodystrophies, often in conjunction with low HDL-C levels.  Potential mechanisms for the development of HTG relate to decreased storage capacity of fat in adipose tissue, with increased hepatic VLDL synthesis and delayed clearance (161). 

 

Genetics

 

Several genes have been implicated in the manifestation of various forms including LMNA, PPARG, LIPE, CIDEC (162). In the Dunnigan form, the most commonly identified genetic variant of FPLD, the commonest mutations are in the LMNAgene (159).  No specific genetic defect has been identified in Köbberling’s FPLD, although recent evidence suggests a heavy polygenic burden in these individuals (163,164).

 

Diagnosis

 

Congenital generalized lipodystrophy (CGL) is a rare autosomal recessive disorder in which near total absence of subcutaneous adipose tissue is evident from birth.  HTG and hepatic steatosis are evident at a young age and are often difficult to control. Severe HTG, often associated with eruptive xanthoma and recurrent pancreatitis, can occur in patients with CGL. The prevalence of HTG in case series of CGL patients is over 70% (161,165).  Plasma TGs are normal or slightly increased during early childhood, with severe HTG manifesting at puberty along with onset of diabetes mellitus. 

 

Familial partial lipodystrophies (FPLD) are complex metabolic disorders that are often not recognized clinically (166).  Partial lipodystrophies are characterized by partial loss of adipose tissue and significant metabolic derangements.  The Dunnigan variety of FPLD (FPLD type 2) is a rare autosomal dominant disorder in which fat loss mostly involves the extremities and the trunk.  Onset of fat loss in the buttocks and extremities occurs at puberty or late adolescence, with gain of fat to the face and neck. Acanthosis nigricans, muscle hypertrophy, phlebomegaly (prominent veins), and eruptive xanthomata can be observed. Metabolic dysfunction including diabetes, which is often very insulin resistant, and HTG often severe and difficult to treat, can occur.  Myopathy, cardiomyopathy, and/or conduction system abnormalities can occur (167).  CVD risk also is increased (168,169).

 

The Köbberling variety is believed to be less frequent (159,168), likely because common mutations leading to this phenotype have not yet been elucidated.   In our experience, the diagnosis of the Köbberling form of partial lipodystrophy is frequently missed, since individuals with this disorder have many clinical features in common with the metabolic syndrome, including central obesity, diabetes, hypertension and HTG, which tends to be worse than in the Dunnigan form of FPLD (164).  However, unlike the metabolic syndrome, they have very little subcutaneous adipose tissues in their extremities.  A prominent ledge of fat above the gluteal area, and upper arm over the deltoid and upper triceps can be observed by careful examination of the legs, arms and buttocks (170), below which adipose tissue disappears (Figure 2).

Figure 2. Diagnostic buttock shelf below which subcutaneous fat is absent in Köbberling lipodystrophy.

A subscapular/calf skinfold ratio >3.5 was found to be a good diagnostic index for this condition (164)   Since examination of the buttocks is not routinely performed during outpatient visits, this disorder is frequently missed and underdiagnosed.  Extremities can be very lean and muscular with phlebomegaly and absent subcutaneous fat.  Because patients with the Köbberling variety FPLD selectively lose subcutaneous fat on their limbs, but not on their abdomen or face, they can present with a Cushingoid appearance.  In the absence of genetic markers, the diagnosis of Köbberling’s lipodystrophy can only be made on clinical grounds. 

 

Some lipodystrophies, where fat loss appears to be proportionate to loss of total and lean body mass, do not result in dyslipidemia.  Elevated TG levels have been reported in patients with atypical progeroid syndrome due to LMNA mutations (171,172).   Of the acquired lipodystrophies, the HIV-associated form usually is characterized by more moderate HTG.  HIV-associated lipodystrophy occurs in patients receiving protease inhibitor containing highly active anti-retroviral therapy regimens (173).  Fat loss occurs in the face, buttocks and extremities.

 

CONSEQUENCES OF HYPERTRIGLYCERIDEMIA

 

Increased Risk of Cardiovascular Disease

 

EPIDEMIOLOGY

 

HTG has long been known to be a risk factor for CVD (29,174-177), which has been reconfirmed in meta-analyses (41).  However, HTG also is frequently associated with low levels of HDL-cholesterol and an accumulation of remnants of the TG-rich lipoproteins, both known risk factors for CVD.  When adjusted for both HDL-C and non-HDL-C, which contains both remnants of the TG-rich lipoproteins and LDL, the association of TGs with CVD risk remained significant, although somewhat attenuated (23).  Postprandial TGs are elevated throughout the day in subjects with HTG, and postprandial TG-rich lipoproteins and their remnants also have been hypothesized to be important in the pathogenesis of atherosclerosis (177).   It is therefore of interest that non-fasting TGs also has been associated with CVD risk (177-179), despite non-fasting TGs being quite variable.  However, unlike the situation with elevated LDL levels, the magnitude of the TG elevation does not appear to correlate with the extent of CVD risk.  In particular, very severe HTG per se does not always appear to confer increased CVD risk, possibly because the chylomicrons that accumulate are too large to enter the arterial intima (180,181). 

 

TRIGLYCERIDES IN THE PATHOGENESIS OF CVD

 

Although chylomicrons may be too large to enter the arterial intima, apoE-and cholesterol-enriched remnants of the TG-rich lipoproteins can enter with ease (179)where they can bind to vascular proteoglycans, similar to LDL (182,183).  Modification of these retained lipoproteins by either oxidative damage or enzyme digestion of some of the lipid components can liberate toxic by-products, which have been hypothesized to play a role in atherogenesis by facilitating local injury, generation of adhesion molecule, and cytokine expression and inflammation (183).  Remnants of the TG-rich lipoproteins also can be taken up by macrophages leading to the formation of foam cells, an important component of atherosclerotic plaques.  HTG also is associated with a preponderance of small, dense LDL, particles, reduced levels of HDL-C, and in the metabolic syndrome, with abnormalities of HDL composition (see earlier).  Small, dense LDL can traverse the endothelial barrier more easily than large, buoyant LDL particles (184), are retained more avidly than large, buoyant LDL (185), and also are more readily oxidized (186,187), all of which may facilitate atherogenesis.  HDL particles in some hypertriglyceridemic states, e.g., in association with the metabolic syndrome, might be dysfunctional with respect to their cholesterol efflux, anti-inflammatory and anti-oxidant properties. Moreover, a hypercoagulable state has been reported in association with both HTG and the metabolic syndrome (110).  Thus, HTG might accelerate atherosclerosis by several mechanisms, all of which could increase CVD risk.

 

GENETICS OF TRIGLYCERIDES AND CARDIOVASCULAR DISEASE

 

Recent human genetic studies have provided important insight into the contribution of TGs to CVD.  Several genetic approaches, including candidate gene sequencing, GWAS of common DNA sequence variants, and genetic analysis of TG phenotypes have unraveled new proteins and gene variants involved in plasma TG regulation (188).  Some genetic variants that influence TG levels appear to be associated with increased CVD risk even after adjusting for their effects on other lipid traits (189).  GWAS have identified common noncoding variants of the LPL gene locus associated with TG and CVD risk (190,191).  A common gain-of-function mutation in the LPL gene, S447X (10% allele frequency), is associated with reduced TG levels and reduced risk of CVD (192)and an LPL variant associated with reduced TG and apoB levels was associated with reduced CVD similar to LDL-C lowering variants, suggesting that the clinical benefit of lowering triglyceride and LDL-C levels may be proportional to the absolute change in apoB (193).  Conversely, several loss-of-function LPL variants linked with elevated TG levels are associated with increased CVD risk (194).  Variants in the TRIB1 locus have been associated with LDL, HDL-C and TG levels (191), hepatic steatosis (195)and coronary artery disease (196).  Mutations that disrupt APOC3 gene function and reduce plasma apoC-III concentration are associated with lower TG levels and decreased risk of clinical CVD (197,198).  In contrast, carriers of rare mutations in APOA5, encoding apoA-V, an activator of LPL, are associated with elevated TGs and with increased risk of myocardial infarction (199,200).  Loss of function variants in ANGPTL4 that had lower TG levels also were associated with reduced CVD risk (201,202).  Thus, exciting new human genetics findings have causally implicated TG and TG-rich lipoproteins in the development of CVD risk.  In particular, the LPL pathway and its reciprocal regulators apoC-III and apoA-V appear to have an important influence on atherosclerotic CVD risk.

 

Pancreatitis and Other Features of the Chylomicronemia Syndrome

 

The chylomicronemia syndrome describes a constellation of findings that occur with severe elevations of plasma TG levels.  Although there is some lack of consensus as to what constitutes severe HTG, values >1000-1500 mg/dL are generally classified as severe, while values in the 500-1000 mg/dL range are classified as moderate (203).  The most serious consequences of the chylomicronemia syndrome is acute pancreatitis, which often is recurrent.  Atherosclerotic CVD also can occur as part of the chylomicronemia syndrome in individuals with MFCS and FPLD.

 

PANCREATITIS IN THE CHYLOMICRONEMIA SYNDROME

 

Individuals with both FCS and MFCS often present with acute pancreatitis, which can be recurrent. Pancreatitis due to very severe HTG also may occur during infusion of lipid emulsions for parenteral feeding (204)or with use of the anesthetic agent propofol, which is infused in a 10% fat emulsion (205).  Severe HTG also can result in pancreatitis in a subset of women with HTG during pregnancy, particularly the third trimester (206).

 

The pancreatitis that occurs with severe HTG often is recurrent. With long term multiple episodes of acute, recurrent pancreatitis, exocrine pancreatic insufficiency or insulin deficient secondary diabetes may occur.  Abdominal pain also may be the result of rapid expansion of the liver by fat, since fatty liver occurs commonly in all forms of severe HTG (207).  In a prospective study of patients admitted with acute pancreatitis, the distribution of plasma TGs was bimodal when measured at the peak of the pain (152,153).  TG levels less than 880 mg/dL were associated with gall bladder disease and chronic alcoholism, while those above 2000 mg/dL were associated with the simultaneous presence of familial and secondary forms of HTG.  It has been suggested that individuals become prone to the development of TG-induced pancreatitis at TG values between 1500-2000 mg/dL (208).  TG-induced pancreatitis has been reported with TG levels lower than 2000 mg/dL(209,210),  although in our experience this usually occurs when patients with severe HTG stopped eating some time prior to the blood draw. The frequency of severe HTG leading to acute pancreatitis varies widely form about 6-20% of subjects, possibly related to the type of patient presenting to different type of medical centers (211,212).  Moreover, the pancreatitis often is recurrent if HTG is not appreciated to be the cause and if TG levels are not adequately controlled (143).  The effect of TG level on the cumulative incidence of acute pancreatitis in >3000 HTG subjects followed for >10 years, showed a stepwise increase in the cumulative incidence of pancreatitis as levels rose from 1000-1999 mg/dL through 2000-2999 to >3000 mg/dL, with diabetes and obesity being major contributing factors in the magnitude of TG elevation (213).  A meta-analysis of observational studies suggests that TG-induced pancreatitis has worse outcomes that pancreatitis from other causes, with an approximate doubling of renal and respiratory failure, a nearly 4-fold increase of shock and a near doubling of mortality (214).  

 

MECHANISM OF CHYLOMICRON-INDUCED PANCREATITIS

 

The mechanism by which very severe HTG leads to pancreatitis remains speculative. Suggested mechanisms include the local liberation of FFA from TGs and lysophosphatidylcholine from phosphatidycholine when pancreatic lipase encounters very high levels of TG-rich lipoproteins in the pancreatic capillaries (215).   High local concentrations of FFA overwhelm the binding capacity of albumin with resultant aggregation into micellar structures with detergent properties.  Both FFA and lysophosphatidylcholine have been shown to cause chemical pancreatitis when infused into pancreatic arteries in animal models (216-218). This leads to local liberation of more lipase, resulting in a vicious cycle (216,219).  It also has been hypothesized that increased plasma viscosity due to the presence of increased numbers of chylomicrons in the pancreatic microcirculation contributes to the development of pancreatitis (220).  There also is recent evidence of gene associations in TG-induced pancreatitis; in a Chinese cohort with HTG, a CFTR variant and TNF alpha promoter polymorphism were found to be independent risk factors for developing pancreatitis (221), while another study found an increased frequency of apoE4 (222).

 

DIAGNOSIS OF CHYLOMICRON-INDUCED PANCREATITIS

 

The diagnosis of HTG-associated pancreatitis can be made by the presence of severely elevated TG levels in a patient with acute pancreatitis.   Falsely low serum amylase levels can be encountered due to assay interference by the TG-rich lipoproteins (223).  Pseudohyponatremia due to the presence of large numbers of TG-rich lipoproteins in plasma can be seen with very high TG levels.  Interference with liver transaminase assays may also occur, giving spuriously high values making it difficult to exclude alcoholic liver disease (223).

 

OTHER CLINICAL FEATURES SEEN IN INDIVIDUALS WITH CHYLOMICRONEMIA

 

With chronic chylomicronemia, patients may also develop eruptive xanthomata (Figure 3). Xanthomas represent an inflammatory response to the deposition of chylomicron-associated lipids in tissues and are yellow-red papules that usually appear on the buttocks, back and extensor surfaces of the upper limbs.  Histologically, these lesions contain lipid laden foamy macrophages (224).  

Figure 3. Eruptive Xanthomas. The commonest site is on the buttocks. The lesions are popular with an erythematous base. They often are itchy.

Lipemia retinalis, where the retinal vessels take on a whitish hue with pallor of the optic fundus and retina can be observed with very high TG levels (Figure 4).  There is no associated visual impairment.  

Figure 4. Lipemia retinalis. Note the pale color of the retinal vessels.

Acute recent memory loss and mental fogginess (138)can also occasionally be seen, but has not been extensively studied.  Symptoms such as fatigue, blurred vision, dysesthesias, and transient ischemic attacks have been suggested to be related to hyperviscosity resulting from high TG levels (225,226).  Hepatosplenomegaly is frequently present in FCS due to macrophage infiltration in response to the chylomicron accumulation.  Fatty liver is a common finding on imaging in both FCS and MFCS.

 

CARDIOVASCULAR DISEASE IN THE CHYLOMIRONEMIA SYNDROME

 

As described earlier, chylomicrons have been considered to be too large to penetrate the vascular endothelium and play a role in atherogenesis (178), although  remnants of the TG-rich lipoproteins may be atherogenic (178,227-230).  The incidence of CVD is low in individuals with FCS (231), although premature atherosclerosis has been documented in well characterized subjects with this disorder (232).  However, CVD risk clearly is increased in many patients with MFCS, although the exact frequency remains unclear.  The frequency of CVD outcomes does not appear to relate to the magnitude of the TG elevations (213).   It is not surprising that CVD is increased in MFCS considering the association between TGs and CVD that has been documented in many studies (reviewed in (177,233,234)).  Many subjects develop severe HTG due to the co-existence of polygenic mutations that result in mild to moderate HTG (27)with secondary causes of HTG.  Residual HTG due to these genetic disorders persists even after severely elevated TG levels have been reduced by treatment of the secondary forms of HTG and treatment of the HTG per se.  Moreover, many patients with the MFCS have other CVD risk factors such as diabetes, reduced levels of HDL-C, and hypertension, the latter resulting in use of diuretics and beta-blockers, which play a role in raising their TGs to levels at which chylomicrons accumulate due to saturation of clearance mechanisms. Therefore, strategies to prevent CVD need to be undertaken once the TGs have been lowered to a level where pancreatitis is unlikely to recur.  This is particularly true in cases where a presumptive clinical diagnosis of FCHL can be made by the presence of premature CVD in multiple family members.  In such cases, statin therapy and lifestyle changes aimed at reducing the risk of CVD should be undertaken in addition to strategies to maintain reduced TG levels.

 

MANAGEMENT OF HYPERTRIGLYCERIDEMIA

 

Management of HTG by lifestyle and pharmacological means is discussed in detail in the chapters on Lifestyle Changes and Triglyceride Lowering and HDL Increasing Drugs (235,236).  However, in this section we will make a few points specifically relevant to this chapter. 

 

Cardiovascular Disease Prevention

 

CVD risk in HTG is modulated by the presence of several other factors, including other lipoprotein abnormalities, other CVD risk factors, and family history, with some families with HTG appearing to have a greater risk of CVD than others (40).  Factors that might favor more aggressive therapy to reduce CVD risk (either for primary or secondary prevention) include the presence of a strongly positive family history of premature CVD (assuming sufficient family members are available to evaluate), elevated apoB and decreased apoA-I levels, and the presence of features of the metabolic syndrome and other CVD risk factors.  Many of these individuals would be those carrying a clinical diagnosis of FCHL, as described earlier.

 

The best clinical trial data currently available for the prevention of CVD in patients with HTG demonstrate that statins are likely to confer the most benefit, even though their primary mode of action is not to reduce plasma TGs, nor are they very effective in so doing (237).  Based on the results of the IMPROVE-IT trial (238), the addition of ezetimibe may be of additional benefit.

 

The role of TG lowering by pharmacological means remains somewhat controversial, but there is consensus that the presence of HTG imparts residual risk after LDL has been adequately lowered with statins.  Fibrates, which are PPAR-α agonists, are effective in lowering plasma TG levels. Several studies have failed to demonstrate a benefit of fibrates on CVD events, either alone or in combination with statins.  However, participants in these studies were not confined to individuals with HTG.  Nonetheless, post-hoc analysis showed that subgroups of subjects who had HTG had a significant reduction of CVD events (239-242).  In addition, the Action to Control Cardiovascular Risk in Diabetes (ACCORD)-LIPID trial, which was confined to subjects with diabetes, showed a similar outcome in the subgroups with HTG, although the trial was negative for all subjects (240).  Unfortunately, no fibrate studies to date have focused solely on subjects with HTG, although a clinical trial, Pemafibrate to Reduce Cardiovascular OutcoMes by Reducing Triglycerides IN patiENts With diabeTes (PROMINENT - ClinicalTrials.gov Identifier: NCT03071692), using a novel selective peroxisome proliferator-activated receptor α modulator, pemafibrate, that possesses unique PPARα activity and selectivity (243), is currently being performed in individuals with HTG and diabetes. 

 

The role of omega-3 (n-3) fatty acids in CVD prevention in HTG also is controversial.  A meta-analysis of 10 randomized trials involving ~78,000 patients did not show a beneficial effect on CVD events in subjects that received n–3 fatty acids supplements (244).  ASCEND (A Study of Cardiovascular Events in Diabetes), also failed to demonstrate a beneficial effect of low dose n–3 fatty acids in patients with type 2 diabetes (245).  Moreover, the Vitamin D and Omega-3 Trial (VITAL) primary-prevention trial in a large number of participants also failed to show a lower incidence of the CVD outcomes in the n-3 fatty acid limb of the trial (246).  However, the recent Cardiovascular Events with Icosapent Ethyl–Intervention Trial (REDUCE-IT), confined to high-risk patients with elevated TG levels who had been receiving effective statin therapy, demonstrated a surprising 25% lower risk in subjects who received a high dose of icosapent ethyl, a highly purified form of eicosapentaenoic (EPA) acid than in those receiving placebo (247).  Interestingly, the reduction in CVD events was greater than the reduction in TG levels and did not correlate with either baseline or on trial TGs, raising the question of whether the benefit in CVD protection resulted from some effects of the agent other than on plasma TG.  Nonetheless, the results of REDUCE-IT are similar to those seen in the earlier Japan EPA Lipid Intervention Study (JELIS), an open-label trial that reported a lower dose of EPA led a similar reduction in major adverse CVD in high risk subjects on therapy (248).  Many of the negative trials used a low dose of n-3-fatty acid (e.g., 1 g/day), in contrast the positive trials that used higher doses JELIS (1.8 EPA g/day) and REDUCE-IT (4 icosapent ethyl g/day)  It may be that the dose of omega-3-fatty acid makes a difference. It also is possible that EPA has effects that are not shared by the other main n-3 fatty acid, docosahexaenoic acid.  Hopefully the ongoing STRENGTH (Statin Residual Risk Reduction With Epanova in High Cardiovascular Risk Patients with Hypertriglyceridemia) trial of another n–3 fatty acid will help shed light on the role of n-3 fatty acids on CVD prevention in patients with residual hypertriglyceridemia. 

 

Treatment of Severe HTG that Accompanies the Chylomicronemia Syndrome

 

Therapeutic approaches to the three major causes of the chylomicronemia syndrome (MFCS, FCS and FPLD) differ considerably.  Therefore, each will be considered separately.

 

FAMILIAL CHYLOMICRONEMIA SYNDROME (FCS) 

 

Consumption of even small amounts of fat can lead to severe HTG in FCS due to the absence of functional LPL. Infants with FCS presenting with abdominal pain or failure to thrive require discontinuation of breast feeding with replacement by very low-fat formula feeding to decrease TG levels and symptoms.  In children and adults with FCS, dietary fat calories should be severely restricted to control the severe HTG and abdominal pain.  This translates to about 5% to 10% of total daily calories, which is a major burden for these patients (249).  Medium-chain TGs, which are taken up directly by the liver after absorption and do not enter plasma as chylomicrons via the thoracic duct, are a potential alternate fat source for these patients.  While n-3 fatty acids lower plasma TGs in MFCS, they can aggravate the severe HTG of FCS and therefore are contraindicated in FCS (250,251).  Fibrates also do not appear to be beneficial in FCS (207).  There are limited studies showing that orlistat might be beneficial in patients with FCS (252,253).  Alcohol, oral contraceptives, and other TG-elevating drugs (see Table 4) can exacerbate severe HTG and precipitate acute pancreatitis in FCS.  Successful pregnancies in patients with FCS have become more common of late (254,255).

 

Alipogene tiparvovec, an adeno-associated virus LPL gene therapy, is no longer available.  It resulted in a significant improvement of postprandial chylomicron metabolism in patients with FCS (256), although fasting TG levels only fell by about 40% and subsequently returned towards baseline (257).  Retrospective long-term follow up suggests that alipogene tiparvovec was associated with a lower frequency and severity of pancreatitis events, although the numbers were small (258).  More recently, weekly subcutaneous injection of an antisense oligonucleotide inhibitor of apoC-III transcription resulted in substantial reductions in plasma TGs in three well characterized FCS patients who had no functional LPL (259), an approach that holds promise for the future treatment of FCS patients.

 

MULTIFACTORIAL CHYLOMICRONEMIA SYNDROME (MFCS)

 

To prevent pancreatitis in MFCS, the goal is to maintain TG levels below the threshold for pancreatitis, preferably <500 mg/dL.  This requires reversal of secondary cause of HTG, such as treatment of poorly-controlled or undiagnosed diabetes, substitution of lipid neutral antihypertensive agents such as ACE inhibitors, ARBs, calcium channel inhibitors, or alpha blockers for beta-adrenergic blockers and diuretics for the treatment of hypertension, and discontinuation of other TG-raising drugs (table 4) where possible.  Alcohol intake should be limited or eliminated, since even small amounts of alcohol can substantially raise TG levels in individuals with baseline HTG.  Attention should be paid to avoid rebound weight gain that commonly occurs after successful weight loss.  Oral estrogens should be substituted by transdermal or vaginal preparations, which raise plasma TGs to a lesser extent than oral estrogens (260,261).  Residual HTG should be treated with fibrates (262), which together with management of the secondary disorder or disorders, usually reduces TG levels to below the threshold for developing pancreatitis.  Other agents that can be used to lower TGs alone or in combination with fibrates, include n-3 fatty acids, high-dose statins and niacin.  Although lifestyle measures and weight loss might be of value, caution needs to be exerted, since in our experience rapid weight regain after successful weight loss can be associated with rebound severe HTG. Bariatric surgery also has been used to reduce severe HTG in refractory patients (263).  Antisense oligonucleotides against apoC-III, which have been shown to lower TGs in patients with severe HTG not due to FCS (264), may have a role to play in the future the management of severe HTG in patients with MFCS. 

 

FAMILIAL PARTIAL LIPODYSTROPHY (FPLD)

 

The severe HTG that accompanies FPLD can be very resistant to treatment and can lead to recurrent episodes of acute pancreatitis (170).  Fibrates and n-3 fatty acids sometimes but not always lower TGs sufficiently to reduce the risk of pancreatitis.  Treatment of diabetes, which often is very insulin resistant, may help.  If TG levels remain very elevated, addition of n-3 fatty acids, thiazolidinediones or cautious, selective use of GLP-1 receptor analogs may improve both TG levels and glycemic control in some patients, although these strategies are based on anecdotal rather than being evidence based.  Leptin administration appears to be helpful in congenital total lipodystrophy and in some FPLD patients with low leptin levels (265).  Because serum leptin levels are normal or high in the Köbberling variety of FPLD (164,170); there is little rationale for its use in this form of lipodystrophy.  In the future, use of antisense oligonucleotides to apoC-III or ANGPTL 3 inhibition (266)might prove to be of value.  Since ANGPTL3 inhibition also lowers LDL cholesterol and HDL cholesterol, and loss of function mutations of ANGPTL3 have been associated with a reduced risk of atherosclerosis (267), ANPTL3 inhibition might prove to be of value in the prevention of CVD in addition to prevention of TG-induced pancreatitis.

 

Prevention of and Treatment TG-induced Pancreatitis

 

Because of the low frequency of FCS, MFCS and FPLD, and because only some patients with these disorders develop pancreatitis, large random controlled clinical trials are difficult to perform and unlikely to be undertaken in the foreseeable future. Therefore, therapeutic decisions need to be based on less stringent criteria than might otherwise be desirable. However, keeping TG levels <500 mg/dL should prevent the onset of TG-induced pancreatitis (203,262,268). 

 

The clinical presentation of HTG-induced pancreatitis is similar to that from other causes of acute pancreatitis and can be preceded by episodic nausea, epigastric pain radiating through to the back and increasing heart-burn. Individuals may present without severe elevation in pancreatic enzymes (269).  Its management is similar to the management of non-TG induced pancreatitis, which includes cessation of all oral intake, fluid resuscitation, and management of metabolic abnormalities.  Lipid emulsions for parenteral feeding should be avoided since their use will further delay clearance and exacerbate the HTG. TGs fall rapidly with discontinuation of oral intake. The use of plasmapheresis to acutely lower TGs is controversial.  Although recommended by some (270,271), the current evidence for the benefit of use of plasmapheresis is limited to small uncontrolled anecdotal series (272)from which no firm conclusion can be made regarding its use in acute TG-induced pancreatitis (273).  TG levels fall rapidly with cessation of oral intakeand use of non-lipid-containing intravenous fluids.  Additionally, plasmapheresis requires a specialized center and only temporarily improves TG levels without addressing the underlying cause (139).  Therefore, we do not recommend its routine use in this situation unless clinical circumstances necessitate plasmapheresis such as severe acute necrotizing pancreatitis (274)or possibly pregnancy (275).  Heparin will liberate LPL into plasma from its endothelial binding sites and hence rapidly lowers TGs (276).  However, it also can cause rebound HTG due to rapid degradation of released LPL (277)and increase the risk of hemorrhagic pancreatitis.  Therefore, the use of heparin is not recommended (278).  The rationale for the use of an IV insulin infusion of regular insulin (in conjunction with IV glucose administration as needed) is that it can activate LPL and enhance clearance of TG-rich lipoproteins (279).  Its use in TG--induced pancreatitis without diabetes has been reported in several case reports (280-284), but it is unclear whether similar changes would have occurred simply by restricting oral intake without the use of insulin.  In a study of chylomicronemia with uncontrolled diabetes, insulin infusion lowered TGs more rapidly than plasmapheresis (285).

 

After TG lowering in the setting of acute pancreatitis, it is essential to determine both the primary and secondary causes of the severe HTG that precipitated the acute pancreatitis.  Continued management of any secondary form of HTG, as well as lifestyle and drug therapy to maintain low TG levels is required to prevent recurrent pancreatitis.  If fasting plasma TG levels remain above 1000 mg/dL after treating or removing the precipitating causes of the severe HTG, life-long therapy with fibrates or n-3 fatty acids, as described earlier, might be considered for patients with both MCFS and FPDL.  Limited evidence suggests that orlistat, a gastrointestinal lipase inhibitor that decreases absorption of ingested fat, thereby reducing intestinal chylomicron synthesis, may be of benefit in reducing TG levels when used in conjunction with fibrate therapy (286,287).  TG and glucose control can be particularly challenging in individuals with some forms of FPLD.

 

REFERENCES

 

  1. Feingold KR, Grunfeld C. Introduction to Lipids and Lipoproteins. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2018.
  2. Fisher EA. The degradation of apolipoprotein B100: multiple opportunities to regulate VLDL triglyceride production by different proteolytic pathways. Biochim Biophys Acta2012; 1821:778-781
  3. Sundaram M, Yao Z. Recent progress in understanding protein and lipid factors affecting hepatic VLDL assembly and secretion. Nutrition & metabolism2010; 7:35
  4. Yao Z. Human apolipoprotein C-III - a new intrahepatic protein factor promoting assembly and secretion of very low density lipoproteins. Cardiovascular & hematological disorders drug targets2012; 12:133-140
  5. Schneeman BO, Kotite L, Todd KM, Havel RJ. Relationships between the responses of triglyceride-rich lipoproteins in blood plasma containing apolipoproteins B-48 and B-100 to a fat-containing meal in normolipidemic humans. Proc Natl Acad Sci U S A1993; 90:2069-2073
  6. Kindel T, Lee DM, Tso P. The mechanism of the formation and secretion of chylomicrons. Atheroscler Suppl2010; 11:11-16
  7. Kersten S. Physiological regulation of lipoprotein lipase. Biochim Biophys Acta2014; 1841:919-933
  8. Gordts PL, Nock R, Son NH, Ramms B, Lew I, Gonzales JC, Thacker BE, Basu D, Lee RG, Mullick AE, Graham MJ, Goldberg IJ, Crooke RM, Witztum JL, Esko JD. ApoC-III inhibits clearance of triglyceride-rich lipoproteins through LDL family receptors. J Clin Invest2016; 126:2855-2866
  9. Goldberg IJ, Scheraldi CA, Yacoub LK, Saxena U, Bisgaier CL. Lipoprotein ApoC-II activation of lipoprotein lipase. Modulation by apolipoprotein A-IV. J Biol Chem1990; 265:4266-4272
  10. Nilsson SK, Heeren J, Olivecrona G, Merkel M. Apolipoprotein A-V; a potent triglyceride reducer. Atherosclerosis2011; 219:15-21
  11. Priore Oliva C, Pisciotta L, Li Volti G, Sambataro MP, Cantafora A, Bellocchio A, Catapano A, Tarugi P, Bertolini S, Calandra S. Inherited apolipoprotein A-V deficiency in severe hypertriglyceridemia. Arterioscler Thromb Vasc Biol2005; 25:411-417
  12. Gonzales JC, Gordts PL, Foley EM, Esko JD. Apolipoproteins E and AV mediate lipoprotein clearance by hepatic proteoglycans. J Clin Invest2013; 123:2742-2751
  13. Kroupa O, Vorrsjo E, Stienstra R, Mattijssen F, Nilsson SK, Sukonina V, Kersten S, Olivecrona G, Olivecrona T. Linking nutritional regulation of Angptl4, Gpihbp1, and Lmf1 to lipoprotein lipase activity in rodent adipose tissue. BMC Physiol2012; 12:13
  14. Lamiquiz-Moneo I, Bea AM, Mateo-Gallego R, Baila-Rueda L, Cenarro A, Pocovi M, Civeira F, de Castro-Oros I. [Identification of variants in LMF1 gene associated with primary hypertriglyceridemia]. Clin Investig Arterioscler2015;
  15. Inukai K, Nakashima Y, Watanabe M, Kurihara S, Awata T, Katagiri H, Oka Y, Katayama S. ANGPTL3 is increased in both insulin-deficient and -resistant diabetic states. Biochem Biophys Res Commun2004; 317:1075-1079
  16. Shimamura M, Matsuda M, Ando Y, Koishi R, Yasumo H, Furukawa H, Shimomura I. Leptin and insulin down-regulate angiopoietin-like protein 3, a plasma triglyceride-increasing factor. Biochem Biophys Res Commun2004; 322:1080-1085
  17. Koster A, Chao YB, Mosior M, Ford A, Gonzalez-DeWhitt PA, Hale JE, Li D, Qiu Y, Fraser CC, Yang DD, Heuer JG, Jaskunas SR, Eacho P. Transgenic angiopoietin-like (angptl)4 overexpression and targeted disruption of angptl4 and angptl3: regulation of triglyceride metabolism. Endocrinology2005; 146:4943-4950
  18. Foley EM, Gordts PL, Stanford KI, Gonzales JC, Lawrence R, Stoddard N, Esko JD. Hepatic remnant lipoprotein clearance by heparan sulfate proteoglycans and low-density lipoprotein receptors depend on dietary conditions in mice. Arterioscler Thromb Vasc Biol2013; 33:2065-2074
  19. Crawford SE, Borensztajn J. Plasma clearance and liver uptake of chylomicron remnants generated by hepatic lipase lipolysis: evidence for a lactoferrin-sensitive and apolipoprotein E-independent pathway. J Lipid Res1999; 40:797-805
  20. Dichek HL, Johnson SM, Akeefe H, Lo GT, Sage E, Yap CE, Mahley RW. Hepatic lipase overexpression lowers remnant and LDL levels by a noncatalytic mechanism in LDL receptor-deficient mice. J Lipid Res2001; 42:201-210
  21. Brunzell JD, Hazzard WR, Porte D, Jr., Bierman EL. Evidence for a common saturable triglyceride removal mechanism for chylomicrons and very low density lipoproteins in man. J Clin Invest1973; 52:1578-1585
  22. Greenfield MS, Kraemer F, Tobey T, Reaven G. Effect of age on plasma triglyceride concentrations in man. Metabolism1980; 29:1095-1099
  23. Hokanson JE, Austin MA. Plasma triglyceride level is a risk factor for cardiovascular disease independent of high-density lipoprotein cholesterol level: a meta-analysis of population-based prospective studies. J Cardiovasc Risk1996; 3:213-219
  24. Asplund-Carlson A, Carlson LA. Studies in hypertriglyceridaemia. 1. Serum triglyceride distribution and its correlates in randomly selected Swedish middle-aged men. J Intern Med1994; 236:57-64
  25. Johansen CT, Kathiresan S, Hegele RA. Genetic determinants of plasma triglycerides. J Lipid Res2011; 52:189-206
  26. Berglund L, Brunzell JD, Goldberg AC, Goldberg IJ, Sacks F, Murad MH, Stalenhoef AF. Evaluation and treatment of hypertriglyceridemia: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab2012; 97:2969-2989
  27. Hegele RA, Ginsberg HN, Chapman MJ, Nordestgaard BG, Kuivenhoven JA, Averna M, Boren J, Bruckert E, Catapano AL, Descamps OS, Hovingh GK, Humphries SE, Kovanen PT, Masana L, Pajukanta P, Parhofer KG, Raal FJ, Ray KK, Santos RD, Stalenhoef AF, Stroes E, Taskinen MR, Tybjaerg-Hansen A, Watts GF, Wiklund O, European Atherosclerosis Society Consensus P. The polygenic nature of hypertriglyceridaemia: implications for definition, diagnosis, and management. Lancet Diabetes Endocrinol2014; 2:655-666
  28. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of The Third Report of The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, And Treatment of High Blood Cholesterol In Adults (Adult Treatment Panel III). JAMA2001; 285:2486-2497
  29. Miller M, Stone NJ, Ballantyne C, Bittner V, Criqui MH, Ginsberg HN, Goldberg AC, Howard WJ, Jacobson MS, Kris-Etherton PM, Lennie TA, Levi M, Mazzone T, Pennathur S, American Heart Association Clinical Lipidology T, Prevention Committee of the Council on Nutrition PA, Metabolism, Council on Arteriosclerosis T, Vascular B, Council on Cardiovascular N, Council on the Kidney in Cardiovascular D. Triglycerides and cardiovascular disease: a scientific statement from the American Heart Association. Circulation2011; 123:2292-2333
  30. Jacobson TA, Ito MK, Maki KC, Orringer CE, Bays HE, Jones PH, McKenney JM, Grundy SM, Gill EA, Wild RA, Wilson DP, Brown WV. National lipid association recommendations for patient-centered management of dyslipidemia: part 1--full report. J Clin Lipidol2015; 9:129-169
  31. Berglund L, Brunzell JD, Goldberg AC, Goldberg IJ, Sacks F, Murad MH, Stalenhoef AF, Endocrine s. Evaluation and treatment of hypertriglyceridemia: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab2012; 97:2969-2989
  32. Authors/Task Force Members:, Catapano AL, Graham I, De Backer G, Wiklund O, Chapman MJ, Drexel H, Hoes AW, Jennings CS, Landmesser U, Pedersen TR, Reiner Z, Riccardi G, Taskinen MR, Tokgozoglu L, Verschuren WM, Vlachopoulos C, Wood DA, Zamorano JL. 2016 ESC/EAS Guidelines for the Management of Dyslipidaemias: The Task Force for the Management of Dyslipidaemias of the European Society of Cardiology (ESC) and European Atherosclerosis Society (EAS) Developed with the special contribution of the European Assocciation for Cardiovascular Prevention & Rehabilitation (EACPR). Atherosclerosis2016; 253:281-344
  33. Fredrickson D, Levy R, Lees R. Fat transport and lipoproteins - an integrated approach to mechanisms and disorders. N Engl J Med1967; 276:32,94,148,215,273
  34. Goldstein JL, Schrott HG, Hazzard WR, Bierman EL, Motulsky AG. Hyperlipidemia in coronary heart disease. II. Genetic analysis of lipid levels in 176 families and delineation of a new inherited disorder, combined hyperlipidemia. J Clin Invest1973; 52:1544-1568
  35. Nikkila EA, Aro A. Family study of serum lipids and lipoproteins in coronary heart-disease. Lancet1973; 1:954-959
  36. Brunzell JD. Clinical practice. Hypertriglyceridemia. N Engl J Med2007; 357:1009-1017
  37. Chait A, Albers JJ, Brunzell JD. Very low density lipoprotein overproduction in genetic forms of hypertriglyceridemia. Eur J Clin Invest1980; 10:17-22
  38. Brunzell JD, Albers JJ, Chait A, Grundy SM, Groszek E, McDonald GB. Plasma lipoproteins in familial combined hyperlipidemia and monogenic familial hypertriglyceridemia. J Lipid Res1983; 24:147-155
  39. Brunzell JD, Schrott HG, Motulsky AG, Bierman EL. Myocardial infarction in the familial forms of hypertriglyceridemia. Metabolism1976; 25:313-320
  40. Austin MA, McKnight B, Edwards KL, Bradley CM, McNeely MJ, Psaty BM, Brunzell JD, Motulsky AG. Cardiovascular disease mortality in familial forms of hypertriglyceridemia: A 20-year prospective study. Circulation2000; 101:2777-2782
  41. Hokanson JE, Austin MA. Plasma triglyceride level is a risk factor for cardiovascular disease independent of high-density lipoprotein cholesterol level: a meta- analysis of population-based prospective studies. J Cardiovasc Risk1996; 3:213-219
  42. McNeely M, Edwards K, Marcovina S, Brunzell J, Motulsky A, Austin M. Lipoprotein and apolipoprotein abnormalities in familial combined hyperlipidemia: a 20-year prospective study. Atherosclerosis2001; 159:417-481
  43. van Greevenbroek MM, Stalenhoef AF, de Graaf J, Brouwers MC. Familial combined hyperlipidemia: from molecular insights to tailored therapy. Curr Opin Lipidol2014; 25:176-182
  44. Lewis GF, Xiao C, Hegele RA. Hypertriglyceridemia in the genomic era: a new paradigm. Endocr Rev2015; 36:131-147
  45. Dron JS, Wang J, Cao H, McIntyre AD, Iacocca MA, Menard JR, Movsesyan I, Malloy MJ, Pullinger CR, Kane JP, Hegele RA. Severe hypertriglyceridemia is primarily polygenic. J Clin Lipidol2019; 13:80-88
  46. Johansen CT, Wang J, Lanktree MB, McIntyre AD, Ban MR, Martins RA, Kennedy BA, Hassell RG, Visser ME, Schwartz SM, Voight BF, Elosua R, Salomaa V, O'Donnell CJ, Dallinga-Thie GM, Anand SS, Yusuf S, Huff MW, Kathiresan S, Cao H, Hegele RA. An increased burden of common and rare lipid-associated risk alleles contributes to the phenotypic spectrum of hypertriglyceridemia. Arterioscler Thromb Vasc Biol2011; 31:1916-1926
  47. Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Do R, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkila K, Hypponen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikainen LP, Magnusson PKE, Mangino M, Mihailov E, Montasser ME, Muller-Nurasyid M, Nolte IM, O'Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney ASF, Doring A, Elliott P, Epstein SE, Ingi Eyjolfsson G, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJP, Khaw KT, Kim E, Klopp N, Komulainen P, Kumari M, Langenberg C, Lehtimaki T, Lin SY, Lindstrom J, Loos RJF, Mach F, McArdle WL, Meisinger C, Mitchell BD, Muller G, Nagaraja R, Narisu N, Nieminen TVM, Nsubuga RN, Olafsson I, Ong KK, Palotie A, Papamarkou T, Pomilla C, Pouta A, Rader DJ, Reilly MP, Ridker PM, Rivadeneira F, Rudan I, Ruokonen A, Samani N, Scharnagl H, Seeley J, Silander K, Stancakova A, Stirrups K, Swift AJ, Tiret L, Uitterlinden AG, van Pelt LJ, Vedantam S, Wainwright N, Wijmenga C, Wild SH, Willemsen G, Wilsgaard T, Wilson JF, Young EH, Zhao JH, Adair LS, Arveiler D, Assimes TL, Bandinelli S, Bennett F, Bochud M, Boehm BO, Boomsma DI, Borecki IB, Bornstein SR, Bovet P, Burnier M, Campbell H, Chakravarti A, Chambers JC, Chen YI, Collins FS, Cooper RS, Danesh J, Dedoussis G, de Faire U, Feranil AB, Ferrieres J, Ferrucci L, Freimer NB, Gieger C, Groop LC, Gudnason V, Gyllensten U, Hamsten A, Harris TB, Hingorani A, Hirschhorn JN, Hofman A, Hovingh GK, Hsiung CA, Humphries SE, Hunt SC, Hveem K, Iribarren C, Jarvelin MR, Jula A, Kahonen M, Kaprio J, Kesaniemi A, Kivimaki M, Kooner JS, Koudstaal PJ, Krauss RM, Kuh D, Kuusisto J, Kyvik KO, Laakso M, Lakka TA, Lind L, Lindgren CM, Martin NG, Marz W, McCarthy MI, McKenzie CA, Meneton P, Metspalu A, Moilanen L, Morris AD, Munroe PB, Njolstad I, Pedersen NL, Power C, Pramstaller PP, Price JF, Psaty BM, Quertermous T, Rauramaa R, Saleheen D, Salomaa V, Sanghera DK, Saramies J, Schwarz PEH, Sheu WH, Shuldiner AR, Siegbahn A, Spector TD, Stefansson K, Strachan DP, Tayo BO, Tremoli E, Tuomilehto J, Uusitupa M, van Duijn CM, Vollenweider P, Wallentin L, Wareham NJ, Whitfield JB, Wolffenbuttel BHR, Ordovas JM, Boerwinkle E, Palmer CNA, Thorsteinsdottir U, Chasman DI, Rotter JI, Franks PW, Ripatti S, Cupples LA, Sandhu MS, Rich SS, Boehnke M, Deloukas P, Kathiresan S, Mohlke KL, Ingelsson E, Abecasis GR, Global Lipids Genetics C. Discovery and refinement of loci associated with lipid levels. Nat Genet2013; 45:1274-1283
  48. Ripatti P, Ramo JT, Soderlund S, Surakka I, Matikainen N, Pirinen M, Pajukanta P, Sarin AP, Service SK, Laurila PP, Ehnholm C, Salomaa V, Wilson RK, Palotie A, Freimer NB, Taskinen MR, Ripatti S. The Contribution of GWAS Loci in Familial Dyslipidemias. PLoS Genet2016; 12:e1006078
  49. Brouwers MC, van Greevenbroek MM, Stehouwer CD, de Graaf J, Stalenhoef AF. The genetics of familial combined hyperlipidaemia. Nat Rev Endocrinol2012; 8:352-362
  50. Pajukanta P, Nuotio I, Terwilliger JD, Porkka KV, Ylitalo K, Pihlajamaki J, Suomalainen AJ, Syvanen AC, Lehtimaki T, Viikari JS, Laakso M, Taskinen MR, Ehnholm C, Peltonen L. Linkage of familial combined hyperlipidaemia to chromosome 1q21-q23. Nat Genet1998; 18:369-373
  51. Mar R, Pajukanta P, Allayee H, Groenendijk M, Dallinga-Thie G, Krauss RM, Sinsheimer JS, Cantor RM, de Bruin TW, Lusis AJ. Association of the APOLIPOPROTEIN A1/C3/A4/A5 gene cluster with triglyceride levels and LDL particle size in familial combined hyperlipidemia. Circ Res2004; 94:993-999
  52. Suviolahti E, Lilja HE, Pajukanta P. Unraveling the complex genetics of familial combined hyperlipidemia. Ann Med2006; 38:337-351
  53. Pihlajamaki J, Valve R, Karjalainen L, Karhapaa P, Vauhkonen I, Laakso M. The hormone sensitive lipase gene in familial combined hyperlipidemia and insulin resistance. Eur J Clin Invest2001; 31:302-308
  54. Pajukanta P, Porkka KV, Antikainen M, Taskinen MR, Perola M, Murtomaki-Repo S, Ehnholm S, Nuotio I, Suurinkeroinen L, Lahdenkari AT, Syvanen AC, Viikari JS, Ehnholm C, Peltonen L. No evidence of linkage between familial combined hyperlipidemia and genes encoding lipolytic enzymes in Finnish families. Arterioscler Thromb Vasc Biol1997; 17:841-850
  55. Hoffer MJ, Snieder H, Bredie SJ, Demacker PN, Kastelein JJ, Frants RR, Stalenhoef AF. The V73M mutation in the hepatic lipase gene is associated with elevated cholesterol levels in four Dutch pedigrees with familial combined hyperlipidemia. Atherosclerosis2000; 151:443-450
  56. Yang WS, Nevin DN, Peng R, Brunzell JD, Deeb SS. A mutation in the promoter of the lipoprotein lipase gene in a patient with familial combined hyperlipidemia and low LDL activity. Proc Natl Acad Sci USA1995; 92:4462-4466
  57. Yang WS, Nevin DN, Iwasaki L, Peng R, Brown BG, Brunzell JD, Deeb SS. Regulatory mutations in the human lipoprotein lipase gene in patients with familial combined hyperlipidemia and coronary artery disease. J Lipid Res1996; 37:2627-2637
  58. Reymer PW, Groenemeyer BE, Gagne E, Miao L, Appelman EE, Seidel JC, Kromhout D, Bijvoet SM, van de Oever K, Bruin T, et al. A frequently occurring mutation in the lipoprotein lipase gene (Asn291Ser) contributes to the expression of familial combined hyperlipidemia. Hum Mol Genet1995; 4:1543-1549
  59. Gagne E, Genest J, Jr., Zhang H, Clark LA, Hayden MR. Analysis of DNA changes in the LPL gene in patients with familial combined hyperlipidemia. Arterioscler Thromb1994; 14:1250-1257
  60. Hoffer MJV, Bredie SJH, Boomsma D, Reymer PWA, Kastelein JJP, deKnijff P, Demacker PNM, Stalenhoef AFH, Havekes LM, Frants RR. The lipoprotein lipase (Asn291Ser) mutation is associated with elevated lipid levels in families with familial combined hyperlipidemia. Atherosclerosis1995; 119:159-167
  61. Nevin DN, Brunzell JD, Deeb SS. The LPL gene in individuals with familial combined hyperlipidemia and decreased LPL activity. Arterioscler Thromb1994; 14:869-873
  62. Nanni L, Quagliarini F, Megiorni F, Montali A, Minicocci I, Campagna F, Pizzuti A, Arca M. Genetic variants in adipose triglyceride lipase influence lipid levels in familial combined hyperlipidemia. Atherosclerosis2010; 213:206-211
  63. Weissglas-Volkov D, Aguilar-Salinas CA, Sinsheimer JS, Riba L, Huertas-Vazquez A, Ordonez-Sanchez ML, Rodriguez-Guillen R, Cantor RM, Tusie-Luna T, Pajukanta P. Investigation of variants identified in caucasian genome-wide association studies for plasma high-density lipoprotein cholesterol and triglycerides levels in Mexican dyslipidemic study samples. Circ Cardiovasc Genet2010; 3:31-38
  64. Eaton RP, Allen RC, Schade DS. Overproduction of a kinetic subclass of VLDL-apoB, and direct catabolism of VLDL-apoB in human endogenous hypertriglyceridemia: an analytical model solution of tracer data. J Lipid Res1983; 24:1291-1303
  65. Grundy SM, Mok HYI, Zech L, Steinberg D, Berman M. Transport of very low density lipoprotein triglycerides in varying degrees of obesity and hypertriglyceridemia. J Clin Invest1979; 63:1274-1283
  66. Beil U, Grundy SM, Crouse JR, Zech L. Triglyceride and cholesterol metabolism in primary hypertriglyceridemia. Arteriosclerosis1982; 2:44-57
  67. Sigurdsson G, Nicoll A, Lewis B. Metabolism of very low density lipoproteins in hyperlipidaemia: studies of apolipoprotein B kinetics in man. Eur J Clin Invest1976; 6:167-177
  68. Ayyobi AF, Brunzell JD. Lipoprotein distribution in the metabolic syndrome, type 2 diabetes mellitus, and familial combined hyperlipidemia. Am J Cardiol2003; 92:27J-33J
  69. Reynisdottir S, Eriksson M, Angelin B, Arner P. Impaired activation of adipocyte lipolysis in familial combined hyperlipidemia. J Clin Invest1995; 95:2161-2169
  70. Reynisdottir S, Angelin B, Langin D, Lithell H, Eriksson M, Holm C, Arner P. Adipose tissue lipoprotein lipase and hormone-sensitive lipase. Contrasting findings in familial combined hyperlipidemia and insulin resistance syndrome. Arterioscler Thromb Vasc Biol1997; 17:2287-2292
  71. Venkatesan S, Cullen P, Pacy P, Halliday D, Scott J. Stable isotopes show a direct relation between VLDL apoB overproduction and serum triglyceride levels and indicate a metabolically and biochemically coherent basis for familial combined hyperlipidemia. Arterioscler Thromb1993; 13:1110-1118
  72. Aitman T, Godsland I, Farren B, Crook D, Wong H, Scott J. Defects of insulin action on fatty acid and carbohydrate metabolism in familial combined hyperlipidemia. Arterioscler Thromb Vasc Biol1997; 17:748-754
  73. Janus ED, Nicoll AM, Turner PR, Magill P, Lewis B. Kinetic bases of the primary hyperlipidemias:Studies of apolipoprotein B turnover in genetically defined subjects. Eur J Clin Invest1980; 10:161-172
  74. Berneis KK, Krauss RM. Metabolic origins and clinical significance of LDL heterogeneity. J Lipid Res2002; 43:1363-1379
  75. Cabezas MC, de Bruin TW, Jansen H, Kock LA, Kortlandt W, Erkelens DW. Impaired chylomicron remnant clearance in familial combined hyperlipidemia. Arterioscler Thromb1993; 13:804-814
  76. Hokanson JE, Austin MA, Zambon A, Brunzell JD. Plasma triglyceride and LDL heterogeneity in familial combined hyperlipidemia. Arterioscler Thromb1993; 13:427-434
  77. Hokanson JE, Krauss RM, Albers JJ, Austin MA, Brunzell JD. LDL physical and chemical properties in familial combined hyperlipidemia. Arterioscler Thromb Vasc Biol1995; 15:452-459
  78. Cruz-Bautista I, Mehta R, Cabiedes J, Garcia-Ulloa C, Guillen-Pineda LE, Almeda-Valdes P, Cuevas-Ramos D, Aguilar-Salinas CA. Determinants of VLDL composition and apo B-containing particles in familial combined hyperlipidemia. Clin Chim Acta2015; 438:160-165
  79. Brouwers MC, van Greevenbroek MM. Lipid metabolism: the significance of plasma proprotein convertase subtilisin kexin type 9 in the elucidation of complex lipid disorders. Curr Opin Lipidol2011; 22:317-318
  80. Hopkins PN, Heiss G, Ellison RC, Province MA, Pankow JS, Eckfeldt JH, Hunt SC. Coronary artery disease risk in familial combined hyperlipidemia and familial hypertriglyceridemia: a case-control comparison from the National Heart, Lung, and Blood Institute Family Heart Study. Circulation2003; 108:519-523
  81. Purnell JQ, Kahn SE, Schwartz RS, Brunzell JD. Relationship of insulin sensitivity and ApoB levels to intra-abdominal fat in subjects with familial combined hyperlipidemia. Arterioscler Thromb Vasc Biol2001; 21:567-572
  82. Ascaso J, Lorente R, Merchante A, Real J, Priego A, Carmena R. Insulin resistance in patients wtih familial combined hyperlipidemia and coronary artery disease. Am J Cardiol1997; 80:1481-1487
  83. Castro Cabezas M, de Bruin T, de Valk H, Shoulders C, Jansen H, Willem Erkelens D. Impaired fatty acid metabolism in familial combined hyperlipidemia: a mechanism associating hepatic apolipoprotein B overproduction and insulin resistance. J Clin Invest1993; 92:160-168
  84. van der Kallen C, Voors-Pette C, Bouwman F, Keizer H, Lu J, van de Hulst R, Bianchi R, Janssen M-J, Keulen E, Boeckx W, Rotter J, de Bruin T. Evidence of insulin resistant lipid metabolism in adipose tissue in familial combined hyperlipidemia, but not type 2 diabetes mellitus. Atherosclerosis2002; 164:337-346
  85. Arner P, Bernard S, Salehpour M, Possnert G, Liebl J, Steier P, Buchholz BA, Eriksson M, Arner E, Hauner H, Skurk T, Ryden M, Frayn KN, Spalding KL. Dynamics of human adipose lipid turnover in health and metabolic disease. Nature2011; 478:110-113
  86. Brouwers MC, Bilderbeek-Beckers MA, Georgieva AM, van der Kallen CJ, van Greevenbroek MM, de Bruin TW. Fatty liver is an integral feature of familial combined hyperlipidaemia: relationship with fat distribution and plasma lipids. Clin Sci (Lond)2007; 112:123-130
  87. Brouwers MC, Reesink KD, van Greevenbroek MM, Meinders JM, van der Kallen CJ, Schaper N, Hoeks AP, Stehouwer CD. Increased arterial stiffness in familial combined hyperlipidemia. J Hypertens2009; 27:1009-1016
  88. Keulen ET, Kruijshoop M, Schaper NC, Hoeks AP, de Bruin TW. Increased intima-media thickness in familial combined hyperlipidemia associated with apolipoprotein B. Arterioscler Thromb Vasc Biol2002; 22:283-288
  89. Chait A, Brunzell JD. Severe hypertriglyceridemia:Role of familial and acquired disorders. Metabolism1983; 32:209-214
  90. Luijten J, van Greevenbroek MMJ, Schaper NC, Meex SJR, van der Steen C, Meijer LJ, de Boer D, de Graaf J, Stehouwer CDA, Brouwers M. Incidence of cardiovascular disease in familial combined hyperlipidemia: A 15-year follow-up study. Atherosclerosis2019; 280:1-6
  91. Veerkamp MJ, de Graaf J, Hendriks JC, Demacker PN, Stalenhoef AF. Nomogram to diagnose familial combined hyperlipidemia on the basis of results of a 5-year follow-up study. Circulation2004; 109:2980-2985
  92. Veerkamp MJ, de Graaf J, Bredie SJ, Hendriks JC, Demacker PN, Stalenhoef AF. Diagnosis of familial combined hyperlipidemia based on lipid phenotype expression in 32 families: results of a 5-year follow-up study. Arterioscler Thromb Vasc Biol2002; 22:274-282
  93. Ayyobi AF, McGladdery SH, McNeely MJ, Austin MA, Motulsky AG, Brunzell JD. Small, dense LDL and elevated apolipoprotein B are the common characteristics for the three major lipid phenotypes of familial combined hyperlipidemia. Arterioscler Thromb Vasc Biol2003; 23:1289-1294
  94. Purnell JQ, Kahn, Steven E., Schwartz, Robert S., Brunzell, John D. Relationship of insulin sensitivity and apoB levels to intra-abdominal fat in subjects with familial combined hyperlipidemia. Arterioscler Thromb Vasc Biol2001; 21:567-572
  95. Voors-Pette C, de Bruin TW. Excess coronary heart disease in Familial Combined Hyperlipidemia, in relation to genetic factors and central obesity. Atherosclerosis2001; 157:481-489
  96. Genest JJ, Jr., Martin-Munley SS, McNamara JR, Ordovas JM, Jenner J, Myers RH, Silberman SR, Wilson PW, Salem DN, Schaefer EJ. Familial lipoprotein disorders in patients with premature coronary artery disease. Circulation1992; 85:2025-2033
  97. Eckel RH, Alberti KG, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet2010; 375:181-183
  98. Ninomiya JK, L'Italien G, Criqui MH, Whyte JL, Gamst A, Chen RS. Association of the metabolic syndrome with history of myocardial infarction and stroke in the Third National Health and Nutrition Examination Survey. Circulation2004; 109:42-46
  99. Sutherland JP, McKinley B, Eckel RH. The metabolic syndrome and inflammation. Metab Syndr Relat Disord2004; 2:82-104
  100. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC, Jr., International Diabetes Federation Task Force on E, Prevention, Hational Heart L, Blood I, American Heart A, World Heart F, International Atherosclerosis S, International Association for the Study of O. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation2009; 120:1640-1645
  101. Lemieux I, Pascot A, Couillard C, Lamarche B, Tchernof A, Almeras N, Bergeron J, Gaudet D, Tremblay G, Prud'homme D, Nadeau A, Despres JP. Hypertriglyceridemic waist: A marker of the atherogenic metabolic triad (hyperinsulinemia; hyperapolipoprotein B; small, dense LDL) in men? Circulation2000; 102:179-184
  102. Choi SH, Ginsberg HN. Increased very low density lipoprotein (VLDL) secretion, hepatic steatosis, and insulin resistance. Trends Endocrinol Metab2011; 22:353-363
  103. Ginsberg HN, Zhang YL, Hernandez-Ono A. Regulation of plasma triglycerides in insulin resistance and diabetes. Archives of medical research2005; 36:232-240
  104. Adiels M, Westerbacka J, Soro-Paavonen A, Hakkinen AM, Vehkavaara S, Caslake MJ, Packard C, Olofsson SO, Yki-Jarvinen H, Taskinen MR, Boren J. Acute suppression of VLDL1 secretion rate by insulin is associated with hepatic fat content and insulin resistance. Diabetologia2007; 50:2356-2365
  105. Brunzell JD, Porte D, Jr., Bierman EL. Abnormal lipoprotein lipase mediated plasma triglyceride removal in untreated diabetes mellitus associated with hypertriglyceridemia. Metabolism1979; 28:897-903
  106. Ruderman NB, Schneider SH, Berchtold P. The "metabolically-obese," normal-weight individual. Am J Clin Nutr1981; 34:1617-1621
  107. Phillips CM. Metabolically healthy obesity: definitions, determinants and clinical implications. Rev Endocr Metab Disord2013; 14:219-227
  108. Hamer M, Stamatakis E. Metabolically healthy obesity and risk of all-cause and cardiovascular disease mortality. J Clin Endocrinol Metab2012; 97:2482-2488
  109. Chahil TJ, Ginsberg HN. Diabetic dyslipidemia. Endocrinol Metab Clin North Am2006; 35:491-510, vii-viii
  110. Cornier MA, Dabelea D, Hernandez TL, Lindstrom RC, Steig AJ, Stob NR, Van Pelt RE, Wang H, Eckel RH. The metabolic syndrome. Endocr Rev2008; 29:777-822
  111. Siest G, Pillot T, Regis-Bailly A, Leininger-Muller B, Steinmetz J, Galteau MM, Visvikis S. Apolipoprotein E: an important gene and protein to follow in laboratory medicine. Clin Chem1995; 41:1068-1086
  112. Weisgraber KH, Rall SC, Jr., Mahley RW. Human E apoprotein heterogeneity. Cysteine-arginine interchanges in the amino acid sequence of the apo-E isoforms. J Biol Chem1981; 256:9077-9083
  113. Smelt AH, de Beer F. Apolipoprotein E and familial dysbetalipoproteinemia: clinical, biochemical, and genetic aspects. Semin Vasc Med2004; 4:249-257
  114. Dong LM, Innerarity TL, Arnold KS, Newhouse YM, Weisgraber KH. The carboxyl terminus in apolipoprotein E2 and the seven amino acid repeat in apolipoprotein E-Leiden: role in receptor-binding activity. J Lipid Res1998; 39:1173-1180
  115. Mahley RW, Huang Y, Rall SC, Jr. Pathogenesis of type III hyperlipoproteinemia (dysbetalipoproteinemia). Questions, quandaries, and paradoxes. J Lipid Res1999; 40:1933-1949
  116. Mahley RW, Rall SC, Jr. Type III hyperlipoproteinemia (dysbetalipoproteinemia):The role of apolipoprotein E in normal and abnormal lipoprotein metabolism. In: Scriver CR, Beaudet AL, Sly WS, Valle D, eds. The Metabolic Basis of Inherited Disease. New York: McGraw-Hill; 1989:1195.
  117. Brummer D, Evans D, Berg D, Greten H, Beisiegel U, Mann WA. Expression of type III hyperlipoproteinemia in patients homozygous for apolipoprotein E-2 is modulated by lipoprotein lipase and postprandial hyperinsulinemia. J Mol Med (Berl)1998; 76:355-364
  118. Koopal C, Marais AD, Visseren FL. Familial dysbetalipoproteinemia: an underdiagnosed lipid disorder. Curr Opin Endocrinol Diabetes Obes2017; 24:133-139
  119. Feussner G, Ziegler R. Expression of type III hyperlipoproteinaemia in a subject with secondary hypothyroidism bearing the apolipoprotein E2/2 phenotype. J Intern Med1991; 230:183-186
  120. Breslow JL, Zannis VI, SanGiacomo TR, Third JL, Tracy T, Glueck CJ. Studies of familial type III hyperlipoproteinemia using as a genetic marker the apoE phenotype E2/2. J Lipid Res1982; 23:1224-1235
  121. Chait A, Brunzell JD, Albers JJ, Hazzard WR. Type-III Hyperlipoproteinaemia ("remnant removal disease"). Insight into the pathogenetic mechanism. Lancet1977; 1:1176-1178
  122. Chait A, Hazzard WR, Albers JJ, Kushwaha RP, Brunzell JD. Impaired very low density lipoprotein and triglyceride removal in broad beta disease: comparison with endogenous hypertriglyceridemia. Metabolism1978; 27:1055-1066
  123. Rothschild M, Duhon G, Riaz R, Jetty V, Goldenberg N, Glueck CJ, Wang P. Pathognomonic Palmar Crease Xanthomas of Apolipoprotein E2 Homozygosity-Familial Dysbetalipoproteinemia. JAMA Dermatol2016; 152:1275-1276
  124. Albers JJ, Warnick GR, Hazzard WR. Type III hyperlipoproteinemia: a comparative study of current diagnostic techniques. Clin Chim Acta1977; 75:193-204
  125. Blom DJ, O'Neill FH, Marais AD. Screening for dysbetalipoproteinemia by plasma cholesterol and apolipoprotein B concentrations. Clin Chem2005; 51:904-907
  126. Morganroth J, Levy RI, Fredrickson DS. The biochemical, clinical, and genetic features of type III hyperlipoproteinemia. Ann Intern Med1975; 82:158-174
  127. Havel RJ, Kane JP. Primary dysbetalipoproteinemia:Predominancy of a specific apoprotein species in triglyceride-rich lipoproteins. Proc Natl Acad Sci USA1973; 70:2015
  128. Koopal C, Retterstol K, Sjouke B, Hovingh GK, Ros E, de Graaf J, Dullaart RP, Bertolini S, Visseren FL. Vascular risk factors, vascular disease, lipids and lipid targets in patients with familial dysbetalipoproteinemia: a European cross-sectional study. Atherosclerosis2015; 240:90-97
  129. Mahley R, Rall S. Type III Hyperlipoproteinemia (Dysbetalipoproteinemia): The Role of Apolipoprotein E in Normal and Abnormal Lipoprotein Metabolism. In: Scriver C, Beaudet A, Sly W, Valle D, eds. The Metabolic & Molecular Bases of Inherited Disease. Vol 119. 8th ed. New York: McGraw-Hill; 2001:2835-2862.
  130. Koopal C, Geerlings MI, Muller M, de Borst GJ, Algra A, van der Graaf Y, Visseren FL, Group SS. The relation between apolipoprotein E (APOE) genotype and peripheral artery disease in patients at high risk for cardiovascular disease. Atherosclerosis2016; 246:187-192
  131. Herink M, Ito MK. Medication Induced Changes in Lipid and Lipoproteins. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2000.
  132. Feingold KR, Grunfeld C. The Effect of Inflammation and Infection on Lipids and Lipoproteins. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2018.
  133. Feingold KR, Grunfeld C. Obesity and Dyslipidemia. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2018.
  134. Feingold K, Brinton EA, Grunfeld C. The Effect of Endocrine Disorders on Lipids and Lipoproteins. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2017.
  135. Chait A. Secondary hyperlipidemia. J Clin Pathol1973; 26:68-71
  136. Chait A, Brunzell JD. Acquired hyperlipidemia (secondary dyslipoproteinemia). Endocrinol Metab Clin North Am1990; 19:259-278
  137. Brunzell JD, Bierman EL. Chylomicronemia syndrome.Interaction of genetic and acquired hypertriglyceridemia. Med Clin North Am1982; 66:455-468
  138. Chait A, Robertson HT, Brunzell JD. Chylomicronemia syndrome in diabetes mellitus. Diabetes Care1981; 4:343-348
  139. Brahm AJ, Hegele RA. Chylomicronaemia-current diagnosis and future therapies. Nat Rev Endocrinol2015;
  140. Brunzell J, Deeb S. Familial lipoprotein lipase deficiency, apo CII deficiency, and hepatic lipase deficiency. In: Scriver C, Beaudet A, Sly W, Vale D, eds. The Metabolic and Molecular Basis of Inherited Disease. Vol II. 8th ed. New York: McGraw-Hill Book Co.; 2001:2789-2816.
  141. Rahalkar AR, Giffen F, Har B, Ho J, Morrison KM, Hill J, Wang J, Hegele RA, Joy T. Novel LPL mutations associated with lipoprotein lipase deficiency: two case reports and a literature review. Can J Physiol Pharmacol2009; 87:151-160
  142. Martin-Campos JM, Julve J, Roig R, Martinez S, Errico TL, Martinez-Couselo S, Escola-Gil JC, Mendez-Gonzalez J, Blanco-Vaca F. Molecular analysis of chylomicronemia in a clinical laboratory setting: diagnosis of 13 cases of lipoprotein lipase deficiency. Clin Chim Acta2014; 429:61-68
  143. Blom DJ, O'Dea L, Digenio A, Alexander VJ, Karwatowska-Prokopczuk E, Williams KR, Hemphill L, Muniz-Grijalvo O, Santos RD, Baum S, Witztum JL. Characterizing familial chylomicronemia syndrome: Baseline data of the APPROACH study. J Clin Lipidol2018; 12:1234-1243 e1235
  144. Peterson J, Ayyobi AF, Ma Y, Henderson H, Reina M, Deeb SS, Santamarina-Fojo S, Hayden MR, Brunzell JD. Structural and functional consequences of missense mutations in exon 5 of the lipoprotein lipase gene. J Lipid Res2002; 43:398-406
  145. Nickerson DA, Taylor SL, Weiss KM, Clark AG, Hutchinson RG, Stengard J, Salomaa V, Vartiainen E, Boerwinkle E, Sing CF. DNA sequence diversity in a 9.7-kb region of the human lipoprotein lipase gene. Nat Genet1998; 19:233-240
  146. Breckenridge WC, Little JA, Steiner G, Chow A, Poapst M. Hypertriglyceridemia associated with deficiency of apolipoprotein C-II. N Engl J Med1978; 298:1265
  147. Rabacchi C, Pisciotta L, Cefalu AB, Noto D, Fresa R, Tarugi P, Averna M, Bertolini S, Calandra S. Spectrum of mutations of the LPL gene identified in Italy in patients with severe hypertriglyceridemia. Atherosclerosis2015; 241:79-86
  148. Surendran RP, Visser ME, Heemelaar S, Wang J, Peter J, Defesche JC, Kuivenhoven JA, Hosseini M, Peterfy M, Kastelein JJ, Johansen CT, Hegele RA, Stroes ES, Dallinga-Thie GM. Mutations in LPL, APOC2, APOA5, GPIHBP1 and LMF1 in patients with severe hypertriglyceridaemia. J Intern Med2012; 272:185-196
  149. Kristensen KK, Midtgaard SR, Mysling S, Kovrov O, Hansen LB, Skar-Gislinge N, Beigneux AP, Kragelund BB, Olivecrona G, Young SG, Jorgensen TJD, Fong LG, Ploug M. A disordered acidic domain in GPIHBP1 harboring a sulfated tyrosine regulates lipoprotein lipase. Proc Natl Acad Sci U S A2018; 115:E6020-E6029
  150. Calandra S, Priore Oliva C, Tarugi P, Bertolini S. APOA5 and triglyceride metabolism, lesson from human APOA5 deficiency. Curr Opin Lipidol2006; 17:122-127
  151. Peterfy M. Lipase maturation factor 1: a lipase chaperone involved in lipid metabolism. Biochim Biophys Acta2012; 1821:790-794
  152. Brunzell JD, Schrott HG. The interaction of familial and secondary causes of hypertriglyceridemia:Role in pancreatitis. Trans Assoc Am Physicians1973; 86:245-254
  153. Brunzell JD, Schrott HG. The interaction of familial and secondary causes of hypertriglyceridemia: role in pancreatitis. J Clin Lipidol2012; 6:409-412
  154. Parsons SK, Skapek SX, Neufeld EJ, Kuhlman C, Young ML, Donnelly M, Brunzell JD, Otvos JD, Sallan SE, Rifai N. Asparaginase-associated lipid abnormalities in children with acute lymphoblastic leukemia. Blood1997; 89:1886-1895
  155. Tozuka M, Yamauchi K, Hidaka H, Nakabayashi T, Okumura N, Katsuyama T. Characterization of hypertriglyceridemia induced by L-asparaginase therapy for acute lymphoblastic leukemia and malignant lymphoma. Ann Clin Lab Sci1997; 27:351-357
  156. Yadav D, Pitchumoni CS. Issues in hyperlipidemic pancreatitis. Journal of clinical gastroenterology2003; 36:54-62
  157. Johansen CT, Hegele RA. Allelic and phenotypic spectrum of plasma triglycerides. Biochim Biophys Acta2012; 1821:833-842
  158. Rosenthal E RJ, Cosslin DR, Burt A, Brunzell JD, Motulsky AG, Nickerson DA Wijsman EM, Jarvik GP. Exome Sequencing Project NHLBI GO ESP. Joint linkage and association analysis with exome sequence data implicates SLC25A40 in hypertriglyceridemia. . Am J Hum Genet 2014:In press
  159. Garg A. Clinical review#: Lipodystrophies: genetic and acquired body fat disorders. J Clin Endocrinol Metab2011; 96:3313-3325
  160. Akinci B, Sahinoz M, Oral E. Lipodystrophy Syndromes: Presentation and Treatment. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2017.
  161. Simha V, Garg A. Inherited lipodystrophies and hypertriglyceridemia. Curr Opin Lipidol2009; 20:300-308
  162. Lightbourne M, Brown RJ. Genetics of Lipodystrophy. Endocrinol Metab Clin North Am2017; 46:539-554
  163. Lotta LA, Gulati P, Day FR, Payne F, Ongen H, van de Bunt M, Gaulton KJ, Eicher JD, Sharp SJ, Luan J, De Lucia Rolfe E, Stewart ID, Wheeler E, Willems SM, Adams C, Yaghootkar H, Consortium EP-I, Cambridge FC, Forouhi NG, Khaw KT, Johnson AD, Semple RK, Frayling T, Perry JR, Dermitzakis E, McCarthy MI, Barroso I, Wareham NJ, Savage DB, Langenberg C, O'Rahilly S, Scott RA. Integrative genomic analysis implicates limited peripheral adipose storage capacity in the pathogenesis of human insulin resistance. Nat Genet2017; 49:17-26
  164. Guillin-Amarelle C, Sanchez-Iglesias S, Castro-Pais A, Rodriguez-Canete L, Ordonez-Mayan L, Pazos M, Gonzalez-Mendez B, Rodriguez-Garcia S, Casanueva FF, Fernandez-Marmiesse A, Araujo-Vilar D. Type 1 familial partial lipodystrophy: understanding the Kobberling syndrome. Endocrine2016; 54:411-421
  165. Agarwal AK, Garg A. A novel heterozygous mutation in peroxisome proliferator-activated receptor-gamma gene in a patient with familial partial lipodystrophy. J Clin Endocrinol Metab2002; 87:408-411
  166. Ajluni N, Meral R, Neidert AH, Brady GF, Buras E, McKenna B, DiPaola F, Chenevert TL, Horowitz JF, Buggs-Saxton C, Rupani AR, Thomas PE, Tayeh MK, Innis JW, Omary MB, Conjeevaram H, Oral EA. Spectrum of disease associated with partial lipodystrophy: lessons from a trial cohort. Clin Endocrinol (Oxf)2017; 86:698-707
  167. Subramanyam L, Simha V, Garg A. Overlapping syndrome with familial partial lipodystrophy, Dunnigan variety and cardiomyopathy due to amino-terminal heterozygous missense lamin A/C mutations. Clin Genet2010; 78:66-73
  168. Hussain I, Garg A. Lipodystrophy Syndromes. Endocrinol Metab Clin North Am2016; 45:783-797
  169. Hussain I, Patni N, Garg A. Lipodystrophies, dyslipidaemias and atherosclerotic cardiovascular disease. Pathology2019; 51:202-212
  170. Herbst KL, Tannock LR, Deeb SS, Purnell JQ, Brunzell JD, Chait A. Kobberling type of familial partial lipodystrophy: an underrecognized syndrome. Diabetes Care2003; 26:1819-1824
  171. Jacob KN, Baptista F, dos Santos HG, Oshima J, Agarwal AK, Garg A. Phenotypic heterogeneity in body fat distribution in patients with atypical Werner's syndrome due to heterozygous Arg133Leu lamin A/C mutation. J Clin Endocrinol Metab2005; 90:6699-6706
  172. Garg A, Subramanyam L, Agarwal AK, Simha V, Levine B, D'Apice MR, Novelli G, Crow Y. Atypical progeroid syndrome due to heterozygous missense LMNA mutations. J Clin Endocrinol Metab2009; 94:4971-4983
  173. Calvo M, Martinez E. Update on metabolic issues in HIV patients. Curr Opin HIV AIDS2014; 9:332-339
  174. Castelli WP. The triglyceride issue: a view from Framingham. Am Heart J1986; 112:432-437
  175. Harchaoui KE, Visser ME, Kastelein JJ, Stroes ES, Dallinga-Thie GM. Triglycerides and cardiovascular risk. Curr Cardiol Rev2009; 5:216-222
  176. Langsted A, Freiberg JJ, Tybjaerg-Hansen A, Schnohr P, Jensen GB, Nordestgaard BG. Nonfasting cholesterol and triglycerides and association with risk of myocardial infarction and total mortality: the Copenhagen City Heart Study with 31 years of follow-up. J Intern Med2011; 270:65-75
  177. Nordestgaard BG, Varbo A. Triglycerides and cardiovascular disease. Lancet2014; 384:626-635
  178. Zilversmit DB. Atherogenesis:A postprandial phenomenon. Circulation1979; 60:473-485
  179. Zilversmit DB. Atherogenic nature of triglycerides, postprandial lipidemia, and triglyceride-rich remnant lipoproteins. Clin Chem1995; 41:153-158
  180. Nordestgaard BG, Zilversmit DB. Large lipoproteins are excluded from the arterial wall in diabetic cholesterol-fed rabbits. J Lipid Res1988; 29:1491-1500
  181. Nordestgaard BG, Stender S, Kjeldsen K. Reduced atherogenesis in cholesterol-fed diabetic rabbits. Giant lipoproteins do not enter the arterial wall. Arteriosclerosis1988; 8:421-428
  182. Williams KJ, Tabas I. The response-to-retention hypothesis of early atherogenesis. Arterioscler Thromb Vasc Biol1995; 15:551-561
  183. Williams KJ, Tabas I. The response-to-retention hypothesis of atherogenesis reinforced. Curr Opin Lipidol1998; 9:471-474
  184. Krauss RM. Dense low density lipoproteins and coronary artery disease. Am J Cardiol1995; 75:53B-57B
  185. Olin-Lewis K, Krauss RM, La Belle M, Blanche PJ, Barrett PH, Wight TN, Chait A. ApoC-III content of apoB-containing lipoproteins is associated with binding to the vascular proteoglycan biglycan. J Lipid Res2002; 43:1969-1977
  186. Chait A, Brazg RL, Tribble DL, Krauss RM. Susceptibility of small, dense low density lipoproteins to oxidative modification in subjects with the atherogenic lipoprotein phenotype, pattern B. Am J Med1993; 94:350-356
  187. Tribble DL, van den Berg J, Motchnik PA, Ames BN, Lewis DM, Chait A, Krauss RM. Oxidative susceptibility of LDL density subfractions is related to their ubiquinol-10 and à-tocopherol content. Proc Natl Acad Sci USA1994; 91:1183-1187
  188. Rosenson RS, Davidson MH, Hirsh BJ, Kathiresan S, Gaudet D. Genetics and causality of triglyceride-rich lipoproteins in atherosclerotic cardiovascular disease. J Am Coll Cardiol2014; 64:2525-2540
  189. Do R, Willer CJ, Schmidt EM, Sengupta S, Gao C, Peloso GM, Gustafsson S, Kanoni S, Ganna A, Chen J, Buchkovich ML, Mora S, Beckmann JS, Bragg-Gresham JL, Chang HY, Demirkan A, Den Hertog HM, Donnelly LA, Ehret GB, Esko T, Feitosa MF, Ferreira T, Fischer K, Fontanillas P, Fraser RM, Freitag DF, Gurdasani D, Heikkila K, Hypponen E, Isaacs A, Jackson AU, Johansson A, Johnson T, Kaakinen M, Kettunen J, Kleber ME, Li X, Luan J, Lyytikainen LP, Magnusson PK, Mangino M, Mihailov E, Montasser ME, Muller-Nurasyid M, Nolte IM, O'Connell JR, Palmer CD, Perola M, Petersen AK, Sanna S, Saxena R, Service SK, Shah S, Shungin D, Sidore C, Song C, Strawbridge RJ, Surakka I, Tanaka T, Teslovich TM, Thorleifsson G, Van den Herik EG, Voight BF, Volcik KA, Waite LL, Wong A, Wu Y, Zhang W, Absher D, Asiki G, Barroso I, Been LF, Bolton JL, Bonnycastle LL, Brambilla P, Burnett MS, Cesana G, Dimitriou M, Doney AS, Doring A, Elliott P, Epstein SE, Eyjolfsson GI, Gigante B, Goodarzi MO, Grallert H, Gravito ML, Groves CJ, Hallmans G, Hartikainen AL, Hayward C, Hernandez D, Hicks AA, Holm H, Hung YJ, Illig T, Jones MR, Kaleebu P, Kastelein JJ, Khaw KT, Kim E, Klopp N, Komulainen P, Kumari M, Langenberg C, Lehtimaki T, Lin SY, Lindstrom J, Loos RJ, Mach F, McArdle WL, Meisinger C, Mitchell BD, Muller G, Nagaraja R, Narisu N, Nieminen TV, Nsubuga RN, Olafsson I, Ong KK, Palotie A, Papamarkou T, Pomilla C, Pouta A, Rader DJ, Reilly MP, Ridker PM, Rivadeneira F, Rudan I, Ruokonen A, Samani N, Scharnagl H, Seeley J, Silander K, Stancakova A, Stirrups K, Swift AJ, Tiret L, Uitterlinden AG, van Pelt LJ, Vedantam S, Wainwright N, Wijmenga C, Wild SH, Willemsen G, Wilsgaard T, Wilson JF, Young EH, Zhao JH, Adair LS, Arveiler D, Assimes TL, Bandinelli S, Bennett F, Bochud M, Boehm BO, Boomsma DI, Borecki IB, Bornstein SR, Bovet P, Burnier M, Campbell H, Chakravarti A, Chambers JC, Chen YD, Collins FS, Cooper RS, Danesh J, Dedoussis G, de Faire U, Feranil AB, Ferrieres J, Ferrucci L, Freimer NB, Gieger C, Groop LC, Gudnason V, Gyllensten U, Hamsten A, Harris TB, Hingorani A, Hirschhorn JN, Hofman A, Hovingh GK, Hsiung CA, Humphries SE, Hunt SC, Hveem K, Iribarren C, Jarvelin MR, Jula A, Kahonen M, Kaprio J, Kesaniemi A, Kivimaki M, Kooner JS, Koudstaal PJ, Krauss RM, Kuh D, Kuusisto J, Kyvik KO, Laakso M, Lakka TA, Lind L, Lindgren CM, Martin NG, Marz W, McCarthy MI, McKenzie CA, Meneton P, Metspalu A, Moilanen L, Morris AD, Munroe PB, Njolstad I, Pedersen NL, Power C, Pramstaller PP, Price JF, Psaty BM, Quertermous T, Rauramaa R, Saleheen D, Salomaa V, Sanghera DK, Saramies J, Schwarz PE, Sheu WH, Shuldiner AR, Siegbahn A, Spector TD, Stefansson K, Strachan DP, Tayo BO, Tremoli E, Tuomilehto J, Uusitupa M, van Duijn CM, Vollenweider P, Wallentin L, Wareham NJ, Whitfield JB, Wolffenbuttel BH, Altshuler D, Ordovas JM, Boerwinkle E, Palmer CN, Thorsteinsdottir U, Chasman DI, Rotter JI, Franks PW, Ripatti S, Cupples LA, Sandhu MS, Rich SS, Boehnke M, Deloukas P, Mohlke KL, Ingelsson E, Abecasis GR, Daly MJ, Neale BM, Kathiresan S. Common variants associated with plasma triglycerides and risk for coronary artery disease. Nat Genet2013; 45:1345-1352
  190. Waterworth DM, Ricketts SL, Song K, Chen L, Zhao JH, Ripatti S, Aulchenko YS, Zhang W, Yuan X, Lim N, Luan J, Ashford S, Wheeler E, Young EH, Hadley D, Thompson JR, Braund PS, Johnson T, Struchalin M, Surakka I, Luben R, Khaw KT, Rodwell SA, Loos RJ, Boekholdt SM, Inouye M, Deloukas P, Elliott P, Schlessinger D, Sanna S, Scuteri A, Jackson A, Mohlke KL, Tuomilehto J, Roberts R, Stewart A, Kesaniemi YA, Mahley RW, Grundy SM, Wellcome Trust Case Control C, McArdle W, Cardon L, Waeber G, Vollenweider P, Chambers JC, Boehnke M, Abecasis GR, Salomaa V, Jarvelin MR, Ruokonen A, Barroso I, Epstein SE, Hakonarson HH, Rader DJ, Reilly MP, Witteman JC, Hall AS, Samani NJ, Strachan DP, Barter P, van Duijn CM, Kooner JS, Peltonen L, Wareham NJ, McPherson R, Mooser V, Sandhu MS. Genetic variants influencing circulating lipid levels and risk of coronary artery disease. Arterioscler Thromb Vasc Biol2010; 30:2264-2276
  191. Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, Johansen CT, Fouchier SW, Isaacs A, Peloso GM, Barbalic M, Ricketts SL, Bis JC, Aulchenko YS, Thorleifsson G, Feitosa MF, Chambers J, Orho-Melander M, Melander O, Johnson T, Li X, Guo X, Li M, Shin Cho Y, Jin Go M, Jin Kim Y, Lee JY, Park T, Kim K, Sim X, Twee-Hee Ong R, Croteau-Chonka DC, Lange LA, Smith JD, Song K, Hua Zhao J, Yuan X, Luan J, Lamina C, Ziegler A, Zhang W, Zee RY, Wright AF, Witteman JC, Wilson JF, Willemsen G, Wichmann HE, Whitfield JB, Waterworth DM, Wareham NJ, Waeber G, Vollenweider P, Voight BF, Vitart V, Uitterlinden AG, Uda M, Tuomilehto J, Thompson JR, Tanaka T, Surakka I, Stringham HM, Spector TD, Soranzo N, Smit JH, Sinisalo J, Silander K, Sijbrands EJ, Scuteri A, Scott J, Schlessinger D, Sanna S, Salomaa V, Saharinen J, Sabatti C, Ruokonen A, Rudan I, Rose LM, Roberts R, Rieder M, Psaty BM, Pramstaller PP, Pichler I, Perola M, Penninx BW, Pedersen NL, Pattaro C, Parker AN, Pare G, Oostra BA, O'Donnell CJ, Nieminen MS, Nickerson DA, Montgomery GW, Meitinger T, McPherson R, McCarthy MI, McArdle W, Masson D, Martin NG, Marroni F, Mangino M, Magnusson PK, Lucas G, Luben R, Loos RJ, Lokki ML, Lettre G, Langenberg C, Launer LJ, Lakatta EG, Laaksonen R, Kyvik KO, Kronenberg F, Konig IR, Khaw KT, Kaprio J, Kaplan LM, Johansson A, Jarvelin MR, Janssens AC, Ingelsson E, Igl W, Kees Hovingh G, Hottenga JJ, Hofman A, Hicks AA, Hengstenberg C, Heid IM, Hayward C, Havulinna AS, Hastie ND, Harris TB, Haritunians T, Hall AS, Gyllensten U, Guiducci C, Groop LC, Gonzalez E, Gieger C, Freimer NB, Ferrucci L, Erdmann J, Elliott P, Ejebe KG, Doring A, Dominiczak AF, Demissie S, Deloukas P, de Geus EJ, de Faire U, Crawford G, Collins FS, Chen YD, Caulfield MJ, Campbell H, Burtt NP, Bonnycastle LL, Boomsma DI, Boekholdt SM, Bergman RN, Barroso I, Bandinelli S, Ballantyne CM, Assimes TL, Quertermous T, Altshuler D, Seielstad M, Wong TY, Tai ES, Feranil AB, Kuzawa CW, Adair LS, Taylor HA, Jr., Borecki IB, Gabriel SB, Wilson JG, Holm H, Thorsteinsdottir U, Gudnason V, Krauss RM, Mohlke KL, Ordovas JM, Munroe PB, Kooner JS, Tall AR, Hegele RA, Kastelein JJ, Schadt EE, Rotter JI, Boerwinkle E, Strachan DP, Mooser V, Stefansson K, Reilly MP, Samani NJ, Schunkert H, Cupples LA, Sandhu MS, Ridker PM, Rader DJ, van Duijn CM, Peltonen L, Abecasis GR, Boehnke M, Kathiresan S. Biological, clinical and population relevance of 95 loci for blood lipids. Nature2010; 466:707-713
  192. Rip J, Nierman MC, Ross CJ, Jukema JW, Hayden MR, Kastelein JJ, Stroes ES, Kuivenhoven JA. Lipoprotein lipase S447X: a naturally occurring gain-of-function mutation. Arterioscler Thromb Vasc Biol2006; 26:1236-1245
  193. Ference BA, Kastelein JJP, Ray KK, Ginsberg HN, Chapman MJ, Packard CJ, Laufs U, Oliver-Williams C, Wood AM, Butterworth AS, Di Angelantonio E, Danesh J, Nicholls SJ, Bhatt DL, Sabatine MS, Catapano AL. Association of Triglyceride-Lowering LPL Variants and LDL-C-Lowering LDLR Variants With Risk of Coronary Heart Disease. JAMA2019; 321:364-373
  194. Pimstone SN, Gagne SE, Gagne C, Lupien PJ, Gaudet D, Williams RR, Kotze M, Reymer PW, Defesche JC, Kastelein JJ, et al. Mutations in the gene for lipoprotein lipase. A cause for low HDL cholesterol levels in individuals heterozygous for familial hypercholesterolemia. Arterioscler Thromb Vasc Biol1995; 15:1704-1712
  195. Burkhardt R, Toh SA, Lagor WR, Birkeland A, Levin M, Li X, Robblee M, Fedorov VD, Yamamoto M, Satoh T, Akira S, Kathiresan S, Breslow JL, Rader DJ. Trib1 is a lipid- and myocardial infarction-associated gene that regulates hepatic lipogenesis and VLDL production in mice. J Clin Invest2010; 120:4410-4414
  196. Douvris A, Soubeyrand S, Naing T, Martinuk A, Nikpay M, Williams A, Buick J, Yauk C, McPherson R. Functional analysis of the TRIB1 associated locus linked to plasma triglycerides and coronary artery disease. J Am Heart Assoc2014; 3:e000884
  197. TG and HDL Working Group of the Exome Sequencing Project, National Heart, Lung, and Blood Institute, Crosby J, Peloso GM, Auer PL, Crosslin DR, Stitziel NO, Lange LA, Lu Y, Tang ZZ, Zhang H, Hindy G, Masca N, Stirrups K, Kanoni S, Do R, Jun G, Hu Y, Kang HM, Xue C, Goel A, Farrall M, Duga S, Merlini PA, Asselta R, Girelli D, Olivieri O, Martinelli N, Yin W, Reilly D, Speliotes E, Fox CS, Hveem K, Holmen OL, Nikpay M, Farlow DN, Assimes TL, Franceschini N, Robinson J, North KE, Martin LW, DePristo M, Gupta N, Escher SA, Jansson JH, Van Zuydam N, Palmer CN, Wareham N, Koch W, Meitinger T, Peters A, Lieb W, Erbel R, Konig IR, Kruppa J, Degenhardt F, Gottesman O, Bottinger EP, O'Donnell CJ, Psaty BM, Ballantyne CM, Abecasis G, Ordovas JM, Melander O, Watkins H, Orho-Melander M, Ardissino D, Loos RJ, McPherson R, Willer CJ, Erdmann J, Hall AS, Samani NJ, Deloukas P, Schunkert H, Wilson JG, Kooperberg C, Rich SS, Tracy RP, Lin DY, Altshuler D, Gabriel S, Nickerson DA, Jarvik GP, Cupples LA, Reiner AP, Boerwinkle E, Kathiresan S. Loss-of-function mutations in APOC3, triglycerides, and coronary disease. N Engl J Med2014; 371:22-31
  198. Jorgensen AB, Frikke-Schmidt R, Nordestgaard BG, Tybjaerg-Hansen A. Loss-of-function mutations in APOC3 and risk of ischemic vascular disease. N Engl J Med2014; 371:32-41
  199. Soufi M, Sattler AM, Kurt B, Schaefer JR. Mutation screening of the APOA5 gene in subjects with coronary artery disease. J Investig Med2012; 60:1015-1019
  200. Do R, Stitziel NO, Won HH, Jorgensen AB, Duga S, Angelica Merlini P, Kiezun A, Farrall M, Goel A, Zuk O, Guella I, Asselta R, Lange LA, Peloso GM, Auer PL, Project NES, Girelli D, Martinelli N, Farlow DN, DePristo MA, Roberts R, Stewart AF, Saleheen D, Danesh J, Epstein SE, Sivapalaratnam S, Hovingh GK, Kastelein JJ, Samani NJ, Schunkert H, Erdmann J, Shah SH, Kraus WE, Davies R, Nikpay M, Johansen CT, Wang J, Hegele RA, Hechter E, Marz W, Kleber ME, Huang J, Johnson AD, Li M, Burke GL, Gross M, Liu Y, Assimes TL, Heiss G, Lange EM, Folsom AR, Taylor HA, Olivieri O, Hamsten A, Clarke R, Reilly DF, Yin W, Rivas MA, Donnelly P, Rossouw JE, Psaty BM, Herrington DM, Wilson JG, Rich SS, Bamshad MJ, Tracy RP, Cupples LA, Rader DJ, Reilly MP, Spertus JA, Cresci S, Hartiala J, Tang WH, Hazen SL, Allayee H, Reiner AP, Carlson CS, Kooperberg C, Jackson RD, Boerwinkle E, Lander ES, Schwartz SM, Siscovick DS, McPherson R, Tybjaerg-Hansen A, Abecasis GR, Watkins H, Nickerson DA, Ardissino D, Sunyaev SR, O'Donnell CJ, Altshuler D, Gabriel S, Kathiresan S. Exome sequencing identifies rare LDLR and APOA5 alleles conferring risk for myocardial infarction. Nature2015; 518:102-106
  201. Dewey FE, Gusarova V, O'Dushlaine C, Gottesman O, Trejos J, Hunt C, Van Hout CV, Habegger L, Buckler D, Lai KM, Leader JB, Murray MF, Ritchie MD, Kirchner HL, Ledbetter DH, Penn J, Lopez A, Borecki IB, Overton JD, Reid JG, Carey DJ, Murphy AJ, Yancopoulos GD, Baras A, Gromada J, Shuldiner AR. Inactivating Variants in ANGPTL4 and Risk of Coronary Artery Disease. N Engl J Med2016; 374:1123-1133
  202. Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators,, Stitziel NO, Stirrups KE, Masca NG, Erdmann J, Ferrario PG, Konig IR, Weeke PE, Webb TR, Auer PL, Schick UM, Lu Y, Zhang H, Dube MP, Goel A, Farrall M, Peloso GM, Won HH, Do R, van Iperen E, Kanoni S, Kruppa J, Mahajan A, Scott RA, Willenberg C, Braund PS, van Capelleveen JC, Doney AS, Donnelly LA, Asselta R, Merlini PA, Duga S, Marziliano N, Denny JC, Shaffer CM, El-Mokhtari NE, Franke A, Gottesman O, Heilmann S, Hengstenberg C, Hoffman P, Holmen OL, Hveem K, Jansson JH, Jockel KH, Kessler T, Kriebel J, Laugwitz KL, Marouli E, Martinelli N, McCarthy MI, Van Zuydam NR, Meisinger C, Esko T, Mihailov E, Escher SA, Alver M, Moebus S, Morris AD, Muller-Nurasyid M, Nikpay M, Olivieri O, Lemieux Perreault LP, AlQarawi A, Robertson NR, Akinsanya KO, Reilly DF, Vogt TF, Yin W, Asselbergs FW, Kooperberg C, Jackson RD, Stahl E, Strauch K, Varga TV, Waldenberger M, Zeng L, Kraja AT, Liu C, Ehret GB, Newton-Cheh C, Chasman DI, Chowdhury R, Ferrario M, Ford I, Jukema JW, Kee F, Kuulasmaa K, Nordestgaard BG, Perola M, Saleheen D, Sattar N, Surendran P, Tregouet D, Young R, Howson JM, Butterworth AS, Danesh J, Ardissino D, Bottinger EP, Erbel R, Franks PW, Girelli D, Hall AS, Hovingh GK, Kastrati A, Lieb W, Meitinger T, Kraus WE, Shah SH, McPherson R, Orho-Melander M, Melander O, Metspalu A, Palmer CN, Peters A, Rader D, Reilly MP, Loos RJ, Reiner AP, Roden DM, Tardif JC, Thompson JR, Wareham NJ, Watkins H, Willer CJ, Kathiresan S, Deloukas P, Samani NJ, Schunkert H. Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease. N Engl J Med2016; 374:1134-1144
  203. Brown WV, Brunzell JD, Eckel RH, Stone NJ. Severe hypertriglyceridemia. J Clin Lipidol2012; 6:397-408
  204. Mirtallo JM, Dasta JF, Kleinschmidt KC, Varon J. State of the art review: Intravenous fat emulsions: Current applications, safety profile, and clinical implications. The Annals of pharmacotherapy2010; 44:688-700
  205. Devaud JC, Berger MM, Pannatier A, Marques-Vidal P, Tappy L, Rodondi N, Chiolero R, Voirol P. Hypertriglyceridemia: a potential side effect of propofol sedation in critical illness. Intensive Care Med2012; 38:1990-1998
  206. Goldberg AS, Hegele RA. Severe hypertriglyceridemia in pregnancy. J Clin Endocrinol Metab2012; 97:2589-2596
  207. Brunzell JD DS. Familial lipoprotein lipase deficiency, apo CII deficiency and hepatic lipase deficiency. The Metabolic and Molecular Basis of Inherited Disease, 8th editionNew York: McGraw-Hill Book Co.; 2001:2789-2816.
  208. Brunzell JD. Lipoprotein lipase deficiency and other causes of the chylomicronemia syndrome. In: Scriver CR, Beuadel AL, Sly WS, Valle D, eds. The Metabolic Basis of Inherited Disease. Vol 6th. New York: McGraw-Hill; 1989:1165-1180.
  209. Tremblay K, Methot J, Brisson D, Gaudet D. Etiology and risk of lactescent plasma and severe hypertriglyceridemia. J Clin Lipidol2011; 5:37-44
  210. Lloret Linares C, Pelletier AL, Czernichow S, Vergnaud AC, Bonnefont-Rousselot D, Levy P, Ruszniewski P, Bruckert E. Acute pancreatitis in a cohort of 129 patients referred for severe hypertriglyceridemia. Pancreas2008; 37:13-12
  211. Cameron JL, Capuzzi DM, Zuidema GD, Margolis S. Acute pancreatitis with hyperlipidemia:The incidence of lipid abnormalities in acute pancreatitis. Ann Surg1973; 177:483-489
  212. Farmer RG, Winkelman EI, Brown HB, Lewis LA. Hyperlipoproteinemia and pancreatitis. Am J Med1973; 54:161-165
  213. Zafrir B, Jubran A, Hijazi R, Shapira C. Clinical features and outcomes of severe, very severe, and extreme hypertriglyceridemia in a regional health service. J Clin Lipidol2018; 12:928-936
  214. Wang Q, Wang G, Qiu Z, He X, Liu C. Elevated Serum Triglycerides in the Prognostic Assessment of Acute Pancreatitis: A Systematic Review and Meta-Analysis of Observational Studies. Journal of clinical gastroenterology2017; 51:586-593
  215. Havel RJ. Pathogenesis, differentiation and management of hypertriglyceridemia. Adv Intern Med1969; 15:117-154
  216. Yang F, Wang Y, Sternfeld L, Rodriguez JA, Ross C, Hayden MR, Carriere F, Liu G, Schulz I. The role of free fatty acids, pancreatic lipase and Ca+ signalling in injury of isolated acinar cells and pancreatitis model in lipoprotein lipase-deficient mice. Acta Physiol (Oxf)2009; 195:13-28
  217. Tsuang W, Navaneethan U, Ruiz L, Palascak JB, Gelrud A. Hypertriglyceridemic pancreatitis: presentation and management. The American journal of gastroenterology2009; 104:984-991
  218. Valdivielso P, Ramirez-Bueno A, Ewald N. Current knowledge of hypertriglyceridemic pancreatitis. Eur J Intern Med2014; 25:689-694
  219. Saharia P, Margolis S, Zuidema GD, Cameron JL. Acute pancreatitis with hyperlipemia: studies with an isolated perfused canine pancreas. Surgery1977; 82:60-67
  220. Seplowitz AH, Chien S, Smith FR. Effects of lipoproteins on plasma viscosity. Atherosclerosis1981; 38:89-95
  221. Chang YT, Chang MC, Su TC, Liang PC, Su YN, Kuo CH, Wei SC, Wong JM. Association of cystic fibrosis transmembrane conductance regulator (CFTR) mutation/variant/haplotype and tumor necrosis factor (TNF) promoter polymorphism in hyperlipidemic pancreatitis. Clin Chem2008; 54:131-138
  222. Ivanova R, Puerta S, Garrido A, Cueto I, Ferro A, Ariza MJ, Cobos A, Gonzalez-Santos P, Valdivielso P. Triglyceride levels and apolipoprotein E polymorphism in patients with acute pancreatitis. Hepatobiliary Pancreat Dis Int2012; 11:96-101
  223. Durrington P. Dyslipidaemia. Lancet2003; 362:717-731
  224. Parker F, Bagdade JD, Odland GF, Bierman EL. Evidence for the chylomicron origin of lipids accumulating in diabetic eruptive xanthomas:A correlative lipid biochemical, histochemical and electron microscopic study. J Clin Invest1970; 49:2172-2187
  225. Rosenson RS, Shott S, Lu L, Tangney CC. Hypertriglyceridemia and other factors associated with plasma viscosity. Am J Med2001; 110:488-492
  226. Inokuchi R, Matsumoto A, Azihara R, Sato H, Kumada Y, Yokoyama H, Okada M, Ishida T, Nakamura K, Nakajima S, Yahagi N, Shinohara K. Hypertriglyceridemia as a possible cause of coma: a case report. J Med Case Rep2012; 6:412
  227. Nordestgaard BG, Wootton R, Lewis B. Selective retention of VLDL, IDL, and LDL in the arterial intima of genetically hyperlipidemic rabbits in vivo. Molecular size as a determinant of fractional loss from the intima-inner media. Arterioscler Thromb Vasc Biol1995; 15:534-542
  228. Norata GD, Grigore L, Raselli S, Redaelli L, Hamsten A, Maggi F, Eriksson P, Catapano AL. Post-prandial endothelial dysfunction in hypertriglyceridemic subjects: molecular mechanisms and gene expression studies. Atherosclerosis2007; 193:321-327
  229. Malloy MJ, Kane JP. A risk factor for atherosclerosis: triglyceride-rich lipoproteins. Adv Intern Med2001; 47:111-136
  230. Mamo JC, Proctor SD, Smith D. Retention of chylomicron remnants by arterial tissue; importance of an efficient clearance mechanism from plasma. Atherosclerosis1998; 141 Suppl 1:S63-69
  231. Havel RJ, Gordon RS, Jr. Idiopathic hyperlipemia: metabolic studies in an affected family. J Clin Invest1960; 39:1777-1790
  232. Benlian P, De Gennes JL, Foubert L, Zhang H, Gagne SE, Hayden M. Premature atherosclerosis in patients with familial chylomicronemia caused by mutations in the lipoprotein lipase gene. N Engl J Med1996; 335:848-854
  233. Austin MA, Hokanson JE. Epidemiology of triglycerides, small dense low-density lipoprotein, and lipoprotein(a) as risk factors for coronary heart disease. Med Clin North Am1994; 78:99-115
  234. Goldberg IJ, Eckel RH, McPherson R. Triglycerides and heart disease: still a hypothesis? Arterioscler Thromb Vasc Biol2011; 31:1716-1725
  235. Feingold KR, Grunfeld C. Triglyceride Lowering Drugs. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2018.
  236. Enkhmaa B, Surampudi P, Anuurad E, Berglund L. Lifestyle Changes: Effect of Diet, Exercise, Functional Food, and Obesity Treatment on Lipids and Lipoproteins. In: Feingold KR, Anawalt B, Boyce A, Chrousos G, Dungan K, Grossman A, Hershman JM, Kaltsas G, Koch C, Kopp P, Korbonits M, McLachlan R, Morley JE, New M, Perreault L, Purnell J, Rebar R, Singer F, Trence DL, Vinik A, Wilson DP, eds. Endotext. South Dartmouth (MA)2018.
  237. Scandinavian Simvastatin Survival Study Group. Randomized trial of cholesterol lowering in 4444 patients with coronary heart disease: The Scandinavian Simvastatin Survival Study (4S). Lancet1994; 344:1383-1389
  238. Cannon CP, Blazing MA, Giugliano RP, McCagg A, White JA, Theroux P, Darius H, Lewis BS, Ophuis TO, Jukema JW, De Ferrari GM, Ruzyllo W, De Lucca P, Im K, Bohula EA, Reist C, Wiviott SD, Tershakovec AM, Musliner TA, Braunwald E, Califf RM, Investigators I-I. Ezetimibe Added to Statin Therapy after Acute Coronary Syndromes. N Engl J Med2015;
  239. Koskinen P, Mänttäri M, Manninen V, Huttunen J, Heinonon O. Coronary heart disease incidence in NIDDM patients in the Helsinki Heart Study. Diab Care1992; 15:825-829
  240. ACCORD Study Group, Ginsberg HN, Elam MB, Lovato LC, Crouse JR, 3rd, Leiter LA, Linz P, Friedewald WT, Buse JB, Gerstein HC, Probstfield J, Grimm RH, Ismail-Beigi F, Bigger JT, Goff DC, Jr., Cushman WC, Simons-Morton DG, Byington RP. Effects of combination lipid therapy in type 2 diabetes mellitus. N Engl J Med2010; 362:1563-1574
  241. Keech A, Simes RJ, Barter P, Best J, Scott R, Taskinen MR, Forder P, Pillai A, Davis T, Glasziou P, Drury P, Kesaniemi YA, Sullivan D, Hunt D, Colman P, d'Emden M, Whiting M, Ehnholm C, Laakso M, investigators Fs. Effects of long-term fenofibrate therapy on cardiovascular events in 9795 people with type 2 diabetes mellitus (the FIELD study): randomised controlled trial. Lancet2005; 366:1849-1861
  242. Bezafibrate Infarction Prevention Study. Secondary prevention by raising HDL cholesterol and reducing triglycerides in patients with coronary artery disease. Circulation2000; 102:21-27
  243. Camejo G. Phase 2 clinical trials with K-877 (pemafibrate): A promising selective PPAR-alpha modulator for treatment of combined dyslipidemia. Atherosclerosis2017; 261:163-164
  244. Aung T, Halsey J, Kromhout D, Gerstein HC, Marchioli R, Tavazzi L, Geleijnse JM, Rauch B, Ness A, Galan P, Chew EY, Bosch J, Collins R, Lewington S, Armitage J, Clarke R, Omega-3 Treatment Trialists C. Associations of Omega-3 Fatty Acid Supplement Use With Cardiovascular Disease Risks: Meta-analysis of 10 Trials Involving 77917 Individuals. JAMA Cardiol2018; 3:225-234
  245. ASCEND Study Collaborative Group, Bowman L, Mafham M, Wallendszus K, Stevens W, Buck G, Barton J, Murphy K, Aung T, Haynes R, Cox J, Murawska A, Young A, Lay M, Chen F, Sammons E, Waters E, Adler A, Bodansky J, Farmer A, McPherson R, Neil A, Simpson D, Peto R, Baigent C, Collins R, Parish S, Armitage J. Effects of n-3 Fatty Acid Supplements in Diabetes Mellitus. N Engl J Med2018; 379:1540-1550
  246. Manson JE, Cook NR, Lee IM, Christen W, Bassuk SS, Mora S, Gibson H, Albert CM, Gordon D, Copeland T, D'Agostino D, Friedenberg G, Ridge C, Bubes V, Giovannucci EL, Willett WC, Buring JE, Group VR. Marine n-3 Fatty Acids and Prevention of Cardiovascular Disease and Cancer. N Engl J Med2018;
  247. Bhatt DL, Steg PG, Miller M, Brinton EA, Jacobson TA, Ketchum SB, Doyle RT, Jr., Juliano RA, Jiao L, Granowitz C, Tardif JC, Ballantyne CM, Investigators R-I. Cardiovascular Risk Reduction with Icosapent Ethyl for Hypertriglyceridemia. N Engl J Med2018;
  248. Yokoyama M, Origasa H, Matsuzaki M, Matsuzawa Y, Saito Y, Ishikawa Y, Oikawa S, Sasaki J, Hishida H, Itakura H, Kita T, Kitabatake A, Nakaya N, Sakata T, Shimada K, Shirato K, Japan EPAlisI. Effects of eicosapentaenoic acid on major coronary events in hypercholesterolaemic patients (JELIS): a randomised open-label, blinded endpoint analysis. Lancet2007; 369:1090-1098
  249. Davidson M, Stevenson M, Hsieh A, Ahmad Z, Crowson C, Witztum JL. The burden of familial chylomicronemia syndrome: interim results from the IN-FOCUS study. Expert Rev Cardiovasc Ther2017; 15:415-423
  250. Rouis M, Dugi KA, Previato L, Patterson AP, Brunzell JD, Brewer HB, Santamarina-Fojo S. Therapeutic response to medium-chain triglycerides and omega-3 fatty acids in a patient with the familial chylomicronemia syndrome. Arterioscler Thromb Vasc Biol1997; 17:1400-1406
  251. Brunzell JD. Familial Lipoprotein Lipase Deficiency. GeneReviews at GeneTests: Medical Genetics Information Resource. Seattle: University of Washington; 2011:1997-2010.
  252. Patni N, Quittner C, Garg A. Orlistat Therapy for Children With Type 1 Hyperlipoproteinemia: A Randomized Clinical Trial. J Clin Endocrinol Metab2018; 103:2403-2407
  253. Blackett P, Tryggestad J, Krishnan S, Li S, Xu W, Alaupovic P, Quiroga C, Copeland K. Lipoprotein abnormalities in compound heterozygous lipoprotein lipase deficiency after treatment with a low-fat diet and orlistat. J Clin Lipidol2013; 7:132-139
  254. Tsai EC, Brown JA, Veldee MY, Anderson GJ, Chait A, Brunzell JD. Potential of essential fatty acid deficiency with extremely low fat diet in lipoprotein lipase deficiency during pregnancy: A case report. BMC pregnancy and childbirth2004; 4:27
  255. Al-Shali K, Wang J, Fellows F, Huff MW, Wolfe BM, Hegele RA. Successful pregnancy outcome in a patient with severe chylomicronemia due to compound heterozygosity for mutant lipoprotein lipase. Clin Biochem2002; 35:125-130
  256. Carpentier AC, Frisch F, Labbe SM, Gagnon R, de Wal J, Greentree S, Petry H, Twisk J, Brisson D, Gaudet D. Effect of alipogene tiparvovec (AAV1-LPL(S447X)) on postprandial chylomicron metabolism in lipoprotein lipase-deficient patients. J Clin Endocrinol Metab2012; 97:1635-1644
  257. Gaudet D, Methot J, Dery S, Brisson D, Essiembre C, Tremblay G, Tremblay K, de Wal J, Twisk J, van den Bulk N, Sier-Ferreira V, van Deventer S. Efficacy and long-term safety of alipogene tiparvovec (AAV1-LPLS447X) gene therapy for lipoprotein lipase deficiency: an open-label trial. Gene Ther2013; 20:361-369
  258. Gaudet D, Stroes ES, Methot J, Brisson D, Tremblay K, Bernelot Moens SJ, Iotti G, Rastelletti I, Ardigo D, Corzo D, Meyer C, Andersen M, Ruszniewski P, Deakin M, Bruno MJ. Long-Term Retrospective Analysis of Gene Therapy with Alipogene Tiparvovec and Its Effect on Lipoprotein Lipase Deficiency-Induced Pancreatitis. Hum Gene Ther2016; 27:916-925
  259. Gaudet D, Brisson D, Tremblay K, Alexander VJ, Singleton W, Hughes SG, Geary RS, Baker BF, Graham MJ, Crooke RM, Witztum JL. Targeting APOC3 in the familial chylomicronemia syndrome. N Engl J Med2014; 371:2200-2206
  260. Sanada M, Tsuda M, Kodama I, Sakashita T, Nakagawa H, Ohama K. Substitution of transdermal estradiol during oral estrogen-progestin therapy in postmenopausal women: effects on hypertriglyceridemia. Menopause2004; 11:331-336
  261. Hemelaar M, van der Mooren MJ, Mijatovic V, Bouman AA, Schijf CP, Kroeks MV, Franke HR, Kenemans P. Oral, more than transdermal, estrogen therapy improves lipids and lipoprotein(a) in postmenopausal women: a randomized, placebo-controlled study. Menopause2003; 10:550-558
  262. Capell WH, Eckel RH. Treatment of hypertriglyceridemia. Curr Diab Rep2006; 6:230-240
  263. Hsu SY, Lee WJ, Chong K, Ser KH, Tsou JJ. Laparoscopic bariatric surgery for the treatment of severe hypertriglyceridemia. Asian J Surg2015; 38:96-101
  264. Gaudet D, Alexander VJ, Baker BF, Brisson D, Tremblay K, Singleton W, Geary RS, Hughes SG, Viney NJ, Graham MJ, Crooke RM, Witztum JL, Brunzell JD, Kastelein JJ. Antisense Inhibition of Apolipoprotein C-III in Patients with Hypertriglyceridemia. N Engl J Med2015; 373:438-447
  265. Diker-Cohen T, Cochran E, Gorden P, Brown RJ. Partial and generalized lipodystrophy: comparison of baseline characteristics and response to metreleptin. J Clin Endocrinol Metab2015; 100:1802-1810
  266. Graham MJ, Lee RG, Brandt TA, Tai LJ, Fu W, Peralta R, Yu R, Hurh E, Paz E, McEvoy BW, Baker BF, Pham NC, Digenio A, Hughes SG, Geary RS, Witztum JL, Crooke RM, Tsimikas S. Cardiovascular and Metabolic Effects of ANGPTL3 Antisense Oligonucleotides. N Engl J Med2017; 377:222-232
  267. Stitziel NO, Khera AV, Wang X, Bierhals AJ, Vourakis AC, Sperry AE, Natarajan P, Klarin D, Emdin CA, Zekavat SM, Nomura A, Erdmann J, Schunkert H, Samani NJ, Kraus WE, Shah SH, Yu B, Boerwinkle E, Rader DJ, Gupta N, Frossard PM, Rasheed A, Danesh J, Lander ES, Gabriel S, Saleheen D, Musunuru K, Kathiresan S, Promis, Myocardial Infarction Genetics Consortium I. ANGPTL3 Deficiency and Protection Against Coronary Artery Disease. J Am Coll Cardiol2017; 69:2054-2063
  268. Chaudhry R, Viljoen A, Wierzbicki AS. Pharmacological treatment options for severe hypertriglyceridemia and familial chylomicronemia syndrome. Expert Rev Clin Pharmacol2018; 11:589-598
  269. Yuan G, Al-Shali KZ, Hegele RA. Hypertriglyceridemia: its etiology, effects and treatment. CMAJ2007; 176:1113-1120
  270. Szczepiorkowski ZM, Winters JL, Bandarenko N, Kim HC, Linenberger ML, Marques MB, Sarode R, Schwartz J, Weinstein R, Shaz BH, Apheresis Applications Committee of the American Society for A. Guidelines on the use of therapeutic apheresis in clinical practice--evidence-based approach from the Apheresis Applications Committee of the American Society for Apheresis. J Clin Apher2010; 25:83-177
  271. Stefanutti C, Julius U. Treatment of primary hypertriglyceridemia states - General approach and the role of extracorporeal methods. Atheroscler Suppl2015; 18:85-94
  272. Furuya T, Komatsu M, Takahashi K, Hashimoto N, Hashizume T, Wajima N, Kubota M, Itoh S, Soeno T, Suzuki K, Enzan K, Matsuo S. Plasma exchange for hypertriglyceridemic acute necrotizing pancreatitis: report of two cases. Ther Apher2002; 6:454-458
  273. Click B, Ketchum AM, Turner R, Whitcomb DC, Papachristou GI, Yadav D. The role of apheresis in hypertriglyceridemia-induced acute pancreatitis: A systematic review. Pancreatology2015; 15:313-320
  274. Koutroumpakis E, Slivka A, Furlan A, Dasyam AK, Dudekula A, Greer JB, Whitcomb DC, Yadav D, Papachristou GI. Management and outcomes of acute pancreatitis patients over the last decade: A US tertiary-center experience. Pancreatology2017; 17:32-40
  275. Huang C, Liu J, Lu Y, Fan J, Wang X, Liu J, Zhang W, Zeng Y. Clinical features and treatment of hypertriglyceridemia-induced acute pancreatitis during pregnancy: A retrospective study. J Clin Apher2016; 31:571-578
  276. Whayne TF, Jr., Felts JM. Activation of lipoprotein lipase. Effects of rat serum lipoprotein fractions and heparin. Circ Res1970; 27:941-951
  277. Weintraub M, Rassin T, Eisenberg S, Ringel Y, Grosskopf I, Iaina A, Charach G, Liron M, Rubinstein A. Continuous intravenous heparin administration in humans causes a decrease in serum lipolytic activity and accumulation of chylomicrons in circulation. J Lipid Res1994; 35:229-238
  278. Whayne TF, Jr. Concerns about heparin therapy for hypertriglyceridemia. Arch Intern Med2010; 170:108-109; author reply 109
  279. Goldberg IJ. Lipoprotein lipase and lipolysis: central roles in lipoprotein metabolism and atherogenesis. J Lipid Res1996; 37:693-707
  280. Aryal MR, Mainali NR, Gupta S, Singla M. Acute pancreatitis owing to very high triglyceride levels treated with insulin and heparin infusion. BMJ Case Rep2013; 2013
  281. Khan AS, Latif SU, Eloubeidi MA. Controversies in the etiologies of acute pancreatitis. JOP2010; 11:545-552
  282. Coskun A, Erkan N, Yakan S, Yildirim M, Carti E, Ucar D, Oymaci E. Treatment of hypertriglyceridemia-induced acute pancreatitis with insulin. Prz Gastroenterol2015; 10:18-22
  283. Mikhail N, Trivedi K, Page C, Wali S, Cope D. Treatment of severe hypertriglyceridemia in nondiabetic patients with insulin. Am J Emerg Med2005; 23:415-417
  284. Jabbar MA, Zuhri-Yafi MI, Larrea J. Insulin therapy for a non-diabetic patient with severe hypertriglyceridemia. J Am Coll Nutr1998; 17:458-461
  285. Thuzar M, Shenoy VV, Malabu UH, Schrale R, Sangla KS. Extreme hypertriglyceridemia managed with insulin. J Clin Lipidol2014; 8:630-634
  286. Wierzbicki AS, Reynolds TM, Crook MA. Usefulness of Orlistat in the treatment of severe hypertriglyceridemia. Am J Cardiol2002; 89:229-231
  287. Tolentino MC, Ferenczi A, Ronen L, Poretsky L. Combination of gemfibrozil and orlistat for treatment of combined hyperlipidemia with predominant hypertriglyceridemia. Endocr Pract2002; 8:208-212