Abstract
Metabolic syndrome (MetS) is the commonly observed clustering of obesity, hypertension, dyslipidemia, and insulin resistance. The components of MetS occur together more often than expected by chance and display significant heritability. Investigations into monogenic diseases that model features of the common MetS have uncovered responsible genes. Genome-wide association studies (GWAS) of the components of the MetS have been enormously successful. Meta-analysis of public GWAS data and risk-score analysis are revealing the role of common single-nucleotide polymorphism genotypes in MetS pathophysiology. A pleotropic polygenic architecture underlies MetS, making it a fascinating complex trait. Research will continue to uncover how metabolic pathways interact to form the MetS and its subsequent risk for atherosclerosis and diabetes.
Keywords
Metabolic syndrome, obesity, hypertension, dyslipidemia, insulin resistance, heritability, GWAS
Chapter Outline
Introduction 47
Defining Metabolic Syndrome 48
Pathophysiology of Metabolic Syndrome 48
Heritability of Metabolic Syndrome 50
Monogenic Models of Metabolic Syndrome 51
Genetics of Common Metabolic Syndrome 55
Linkage Analysis 55
Candidate Gene-Association Studies 55
Genome-Wide Association Studies 56
Risk-Score Analysis 58
Finding the Missing Heritability 58
The “Thrifty-Gene” Hypothesis 59
Clinical Implications to Genetic Findings in Metabolic Syndrome 60
Conclusion 60
Acknowledgments 60
References
Introduction
The clustering of several metabolic abnormalities, including dyslipidemia (elevated serum triglycerides and depressed high-density lipoprotein (HDL) cholesterol), dysglycemia, hypertension, and central obesity, has been termed the metabolic syndrome (MetS). The term syndrome, originating from Greek literally meaning “running together,” refers to a set of signs or symptoms occurring together where the underlying pathophysiology leading to the concurrence is unknown. Several lines of evidence suggest that a MetS definition is important both clinically and as a research tool, though some controversy exists regarding the importance of a MetS diagnosis compared to the sum of the risk factors independently, for prediction of the development of diabetes and atherosclerotic cardiovascular disease. Nonetheless, it is clinically apparent that these risk factors occur together more often than one would expect if they were independent processes, and a fivefold increased risk of diabetes and twofold increased risk for cardiovascular disease are observed with a diagnosis of MetS . In addition, in patients with an extreme perturbation of one of the components of MetS, as observed in lipodystrophy or monogenic obesity, disruption of the other components almost inevitably follows. The common form of MetS is a classic complex genetic trait involving the interaction of a multitude of genetic and environmental factors, and genetic investigations into MetS may yield insights into the responsible mechanisms.
Defining Metabolic Syndrome
At least six different organizations have published criteria for MetS diagnosis, but a recent consensus statement of stakeholders has unified the definition for clinical use, as well as for epidemiological and basic research studies . The debate over the criteria for MetS has largely revolved around whether elevated abdominal obesity should be a mandatory component, and what the threshold for continuous variables should be. The revised definition includes five criteria, three of which must be met for a diagnosis ( Table 4.1 ). The criteria include elevated waist circumference, triglycerides, blood pressure, fasting glucose, and depressed HDL cholesterol. Differences in baseline waist circumference observed between the sexes and ethnicities have also been a concern, and sex- and ethnicity-specific guidelines have been specified .
| Metabolic Syndrome Component | Threshold for Criteria |
|---|---|
| Waist circumference | >80 cm in women; >94 cm in men |
| HDL cholesterol | <1.0 mmol/L |
| Triglycerides | ≥1.7 mmol/L or drug therapy for high triglycerides a |
| Blood pressure | SBP ≥130 mmHg or DBP ≥85 mmHg or drug therapy for hypertension |
| Fasting glucose | ≥5.5 mmol/L or drug therapy for elevated glucose |
a Fibrates and nicotinic acid are the most commonly used triglyceride lowering therapies.
Regardless of the definition used, MetS is a common diagnosis. Data from the Third National Health and Nutrition Examination Survey, which used the National Cholesterol Education Program Adult Treatment Panel III MetS criteria, found the prevalence of MetS to be 24% in the United States . Using the International Diabetes Foundation MetS definition, in a large study including >26,000 participants from 52 countries, the average MetS prevalence was 16.8% . Due to its high prevalence, an improvement to our understanding of MetS could yield large benefits to public health.
Pathophysiology of Metabolic Syndrome
The inciting factors in the development of MetS are abdominal obesity and insulin resistance ( Fig. 4.1 ). The accumulation of visceral fat, typically caused by overnutrition and physical inactivity, results in the release of free fatty acids leading to lipotoxicity and insulin resistance , and eventually hyperinsulinemia and hyperglycemia . Insulin has numerous molecular effects beyond glucose homeostasis including upregulation of amino acid uptake and protein synthesis, activation of lipoprotein lipase, and inhibition of very low-density lipoprotein secretion . Abundance of fatty acids and diacylglycerol within skeletal muscle inhibits insulin signaling and reduces its ability to transport and utilize glucose . Visceral fat accumulation creates a dysregulation of adipokine secretion, specifically hyposecretion of adiponectin and hypersecretion of both leptin ( LEP ) and proinflammatory cytokines (such as tumor necrosis factor alpha and interleukin-6 ( IL6 )), each of which may contribute to the MetS pathophysiology. Genetic analysis supports a causal role for adiponectin, which is secreted by adipocytes, in the pathogenesis of MetS . In response to hyperinsulinemia and hyperglycemia, the liver secretes C-reactive protein and prothrombotic molecules such as fibrinogen and plasminogen activator inhibitor-1 . Clearly, MetS is a complicated phenotype involving a complex network of causative and associated biochemical players, disentangling their relationships to further our understanding and develop novel therapeutics is thus a difficult task.
Heritability of Metabolic Syndrome
Strong evidence exists for the heritability of both MetS and its components arising from studies of twins, families, and more recently using population-based cohorts. In a study of 2508 pairs of American male twins, the MetS concordance between monozygotic pairs was 31.6% compared to 6.3% for dizygotic twins . In 1942, Korean twin pairs and their families, significant heritability of both MetS (51%–60%), and all of its components (46%–77%) were observed . Among 803 individuals from 89 Caribbean–Hispanic families, the heritability of a MetS diagnosis was 24%, with significant heritability for lipid/glucose/obesity (44%) and hypertension (20%) components . In a study of 1277 Omani Arab individuals in 5 large consanguineous families, a large degree of heritability was observed for MetS (38%), while the heritability of the MetS components ranged from 38% to 63% . Study of family members in the African American Jackson Heart Study yielded a MetS heritability of 32%, with higher heritability estimates for waist circumference (45%), HDL (43%), and triglycerides (42%), but lower estimates for systolic blood pressure (SBP), diastolic blood pressure, and fasting blood glucose (16%, 15%, and 14%, respectively) . Finally, studying the Framingham Heart Study and Atherosclerosis Risk in Communities populations, the estimates for MetS component heritability were 34% for body mass index (BMI), 28% for waist-to-hip ratio, 47% for triglycerides, 48% for HDL, and 30% for SBP .
Variation in the reported heritability of MetS and its components is likely partially due to differences in ethnicity, variation in environmental exposures between family members, and the statistical techniques employed. Based upon the demonstrated heritability of MetS and its components, investigations to identify responsible genetic variants have been undertaken using both linkage analysis and association mapping strategies, the results of which are discussed in this chapter.
Monogenic Models of Metabolic Syndrome
Monogenic diseases, also termed Mendelian diseases, are the result of a single genetic mutation, and thus have high penetrance, follow Mendelian inheritance patterns, and include small or nonexistent environmental components . Contrarily, in complex diseases such as MetS, there is no apparent inheritance pattern, many genetic loci are involved, and there are large environmental components. In the last 30 years, the genetic basis of several monogenic diseases that include multiple components of MetS has been discovered, garnering insight into potential mechanisms of MetS, despite being responsible for a very small proportion of MetS in the population.
Since monogenic disorders segregate through families, linkage analysis of severely affected families followed by sequencing of genes within the identified region has discovered the responsible genetic variant for many monogenic models of MetS. Whole exome studies, in which the transcribed portion of the genome is sequenced, have already been successful identifying variants responsible for Mendelian disorders which are monogenic models for MetS. With the increasing availability of next-generation sequencing technologies, including whole exome and whole genome sequencing, our ability to identify rare genetic variants responsible for monogenic models of MetS will continue to improve.
Lipodystrophy
Lipodystrophy is a heterogeneous group of disorders characterized by selective or generalized atrophy of anatomical adipose tissue stores ( Table 4.2 ). Loss of the ability to retain excess lipids in “classical” adipose tissue stores leads to the overdevelopment of ectopic fat stores such as within and around skeletal muscle, heart, liver, pancreas and kidneys, and within the arterial wall presenting as atherosclerosis. In patients with congenital generalized lipodystrophy, an absence of adipose tissue is noted in early infancy. In familial partial lipodystrophy (FPLD), patients have normal fat distribution during childhood, but during or shortly after puberty, there is a progressive and gradual loss of subcutaneous adipose tissue of the extremities, a triggering event for the development of the other components of MetS including extreme insulin resistance, dyslipidemia, and hypertension.
| Disease | OMIM No. |
|---|---|
| Generalized Lipodystrophy | |
| Congenital generalized lipodystrophy (CGL) (Berardinelli–Seip) | |
| CGL1— AGPAT2 | 608594 |
| CGL2— BSCL2 | 269700 |
| CGL3— CAV1 , PTRF | 612526 |
| FOS | 164810 |
| PCYT1A | 123695 |
| Partial Lipodystrophy | |
| Familial partial lipodystrophy (FPLD) | |
| FPLD2 (Dunnigan)— LMNA | 151660 |
| FPLD3— PPARG | 604367 |
| FPLD4— PLIN1 | 170290 |
| FPLD5— CIDEC | 615238 |
| Partial lipodystrophy with congenital cataracts, neurodegeneration— CAV1 | 606721 |
| Partial lipodystrophy associated with AKT2 mutations | 164731 |
| Acquired partial lipodystrophy (APL) (Barraquer–Simmons) | |
| APL—some cases associated with LMNB2 mutations | 608709 |
| Syndromes that Include Lipodystrophy as a Component | |
| Mandibuloacral dysplasia (MAD) | |
| MADA— LMNA | 248370 |
| MADB— ZMPSTE24 | 608612 |
| SHORT syndrome— PIK3R1 | 269880 |
| Hutchinson–Gilford progeria syndrome (HGPS)— LMNA | 176670 |
| Werner syndrome (WRN)— RECQL2 , LMNA | 277700 |
| Autoinflammation, lipodystrophy and dermatosis (ALDD)— PSMB8 | 256040 |
| Mandibular hypoplasia, deafness, progeroid lipodystrophy— POLD1 | 615381 |
A total of 16 genes have been identified to contain mutations causative of at least one form of lipodystrophy, with four genes recently identified with whole exome sequencing approaches: PIK3R1 , POLD1 , PIK3R1 , and PCYT1A ( Table 4.2 ). The two most commonly mutated genes causing lipodystrophy are nuclear lamin A/C ( LMNA) and peroxisome proliferator-activated receptor γ ( PPARG ). Over 200 mutations have been identified in LMNA , causing 13 different diseases together termed laminopathies: FPLD, Emery–Dreifuss muscular dystrophy, limb-girdle muscular dystrophy type 1B, dilated cardiomyopathy type 1A, Charcot–Marie–Tooth, Hutchinson–Gilford progeria syndrome, atypical Werner syndrome, and a range of overlapping syndromes ( www.hgmd.cf.ac.uk ). LMNA encodes an intermediate filament protein vital for the structural integrity of the nuclear envelope, transcriptional regulation, nuclear pore functioning, and heterochromatin organization. However, it remains unknown how the mutations observed in LMNA specifically cause the observed phenotypes.
PPARG was selected as a candidate for sequencing in FPLD patients due to its important role as a ligand-inducible transcription factor regulating adipogenesis, and the repartitioning of fat stores observed in patients taking the thiazolidinedione class of drugs, which are agonists for PPARG. Sequencing of PPARG resulted in the discovery of causative mutations . Through functional studies, different PPARG mutations were observed to work through both a dominant negative mechanism, in which the mutant receptor is able to inhibit the action of the wild-type receptor , and a haploinsufficiency mechanism, in which the 50% reduction in wild-type expression was sufficient to create the phenotype .
Monogenic Diseases of Obesity and Insulin Resistance
Over 20 genes have been implicated in rare monogenic diseases that include extreme obesity and/or insulin resistance that could provide insight into more common forms of MetS ( Table 4.3 ). The most common monogenic cause of extreme obesity is mutations in melanocortin receptor 4 ( MC4R ) (OMIM: 155541), accounting for approximately 4% of extremely obese individuals . MC4R is primarily expressed in the brain and is thought to impact obesity through central effects on appetite and satiety . Proopiomelanocortin (POMC) (OMIM: 176830) is a precursor protein for multiple biologically active peptide hormones, including but not limited to adrenocorticotropic hormone, β-liptropin, β-endorphin, and α-, β-, and γ-melanocyte-stimulating hormone, which bind with varying affinity to five homologous melanocortin receptors, including MC4R . Pomc − / − mice develop obesity and abnormal pigmentation , and complete loss-of-function mutations in the POMC were first described in patients with hypocortisolism, red hair, and early-onset extreme obesity . Melanocortin signaling has also been implicated in modulating both blood pressure and lipid metabolism, independent of weight and insulin signaling, indicating a potentially greater role for MC4R and POMC in MetS .
