Alternative titles; symbols
Other entities represented in this entry:
SNOMEDCT: 237602007; ICD10CM: E88.810; ICD9CM: 277.7; DO: 14221;
Cytogenetic location: 3q27 Genomic coordinates (GRCh38): 3:183,000,001-188,200,000
| Location | Phenotype |
Phenotype MIM number |
Inheritance |
Phenotype mapping key |
|---|---|---|---|---|
| 3q27 | Abdominal obesity-metabolic syndrome 1 | 605552 | Autosomal dominant | 2 |
A clustering of abdominal obesity, high triglycerides, low levels of high density lipoprotein cholesterol (HDLC), high blood pressure, and elevated fasting glucose levels is sometimes called metabolic syndrome X (Reaven, 1988) or abdominal obesity-metabolic syndrome (Bjorntorp, 1991). The syndrome may affect nearly 1 in 4 U.S. adults and is considered a veritable epidemic (Ford et al., 2002). It is a major risk factor for both diabetes mellitus (see 125853 and Haffner et al., 1992) and cardiovascular disease (Isomaa et al., 2001). The etiology is complex, determined by the interplay of both genetic and environmental factors. The prevalence varies substantially among ethnic groups, with the highest rates in Mexican American women (Park et al., 2003). Other factors influencing the metabolic syndrome include age, smoking, alcohol, diet, and physical inactivity.
Genetic Heterogeneity of Abdominal Obesity-Metabolic Syndrome
AOMS2 (605572) has been mapped to chromosome 17p12. AOMS3 (615812) is caused by mutation in the DYRK1B gene (604556) on chromosome 19q13. AOMS4 (618620) is caused by mutation in the CELA2A gene (609443) on chromosome 1p36.
Esposito et al. (2003) tested the hypothesis that low serum IL10 (124092) concentrations associate with the metabolic syndrome in obese women. Compared with 50 matched nonobese women, the prevalence of the metabolic syndrome (3 or more of the following abnormalities: waist circumference greater than 88 cm; triglycerides greater than 1.69 mmol/liter; high density lipoprotein cholesterol less than 1.29 mmol/liter; blood pressure greater than 130/85 mm Hg; glucose greater than 6.1 mmol/liter) was higher in 50 obese women (52% vs 16%; P less than 0.01). As a group, obese women had higher circulating levels of IL6 (147620), C-reactive protein (123260), and IL10 than nonobese women. In both obese and nonobese women, IL10 levels were lower in those with than in women without the metabolic syndrome. These results showed that circulating levels of the antiinflammatory cytokine IL10 are elevated in obese women and that low IL10 levels are associated with the metabolic syndrome.
Huang et al. (2003) investigated the relationship between plasma adiponectin (605441) levels and blood pressures in 68 nondiabetic female adolescents, who were younger and had healthier metabolic profiles than subjects in previous studies. They found that systolic blood pressure was inversely related to plasma adiponectin levels independent of other variables of the metabolic syndrome and other risk factors of coronary artery disease.
Shulman and Mangelsdorf (2005) reviewed the role of retinoid X receptor heterodimers (see RXRA, 180245) in the metabolic syndrome. They suggested that the ability of RXR agonists to regulate target genes of multiple permissive partners implies that in vivo such compounds may have pharmacologic use as panagonists of several metabolically important pathways. The observation that liver-specific deletion of RXR in mice results in abnormalities in all metabolic pathways regulated by RXR heterodimers underscores the central, pleiotropic role of RXR. Although RXR agonists have therapeutic value and might offer enhanced potency through panactivation of permissive heterodimers, this advantage is likely to be offset by poor selectivity.
Among 512 Korean patients with ischemic stroke (see 601367), Bang et al. (2005) found a significant association between intracranial atherosclerotic stroke (143 patients) and components of the metabolic syndrome, compared to those with extracranial atherosclerotic stroke (77 patients) and those with nonatherosclerotic stroke (292 patients). The association was particularly strong with regard to hypertension, abdominal obesity, and HDL cholesterol levels.
As the initial step in identifying major genetic loci influencing these phenotypes, Kissebah et al. (2000) performed a genomewide scan by use of a 10-cM map in 2,209 individuals distributed over 507 nuclear Caucasian families. Pedigree-based analysis using a variance components linkage model demonstrated a quantitative trait locus (QTL) on chromosome 3q27 strongly linked to 6 traits (weight, waist circumference, leptin, insulin, insulin/glucose ratio, and hip circumference) representing these fundamental phenotypes (lod scores ranging from 2.4 to 3.5). This QTL exhibited possible epistatic interaction with a second QTL (605572) on chromosome 17p12 that is strongly linked to plasma leptin levels (lod = 5.0). Several candidate genes are located in both regions.
The prevalences of coronary heart disease (CHD), type 2 diabetes (T2D; 125853), and the metabolic syndrome in Mauritius are among the highest in the world. Francke et al. (2001) conducted a genomewide scan in 99 independent families of northeastern Indian origin, each containing a proband with onset of CHD before 52 years of age and additional sibs with myocardial infarction or T2D. Multipoint linkage analysis revealed a locus for CHD on chromosome 16pter-p13 (lod = 3.06, P = 0.00017), which partially overlapped a high pressure peak. At the same locus, a nominal indication for linkage with T2D was found in 35 large T2D Pondicherian families of Indian origin. The authors also replicated the previously described locus on 3q27 for the metabolic syndrome and diabetes (Kissebah et al., 2000).
In a study of 1,094 female dizygotic twin pairs, Wilson et al. (2006) found suggestive linkage for central fat mass to 12q24 (lod score, 2.2); SNP analysis of 1,102 individuals selected from the twin cohort provided evidence for an association between central fat mass and SNPs in 2 genes located on chromosome 12q24, PLA2G1B (172410) and P2RX4 (600846), with p values of 0.0067 and 0.017, respectively.
Hotta et al. (2009) analyzed 336 SNPs in 85 obesity-related genes in 1,080 patients with metabolic syndrome and 528 controls and found 3 SNPs rs1545, rs1547, and rs2294901 in the MKKS gene (604896) that were significantly associated with the metabolic syndrome (p values of 3.3 to 4.3 x 10(-5); OR, 1.45 to 1.46). Analysis of 5 tagging SNPs in the MKKS gene (rs2294901, rs221667, rs6133922, rs6077785, and rs6108572) within 1 linkage disequilibrium block revealed a TGAAA haplotype that was protective against metabolic syndrome (p = 0.0074) and a CCGTT haplotype that was associated with susceptibility for the disorder (p = 0.00070). Hotta et al. (2009) suggested that genetic variation at the MKKS gene may influence the risk of metabolic syndrome.
McCarthy et al. (2003) surveyed 207 SNPs in 110 candidate genes among coronary artery disease patients, a population enriched for metabolic abnormalities. The number of abnormalities (0 to 5) was determined in 214 male and 91 female patients, and the association with each polymorphism evaluated by means of ordinal regression analysis. Polymorphisms in 8 genes were associated with metabolic syndrome in the whole population (P values ranging from 0.047 to 0.008): LDLR (606945), GBE1 (607839), IL1R1 (147810), TGFB1 (190180), IL6 (147620), COL5A2 (120190), SELE (131210), and LIPC (151670). Variants in 7 additional genes showed significant gene interaction by gender. Separate analyses in men and women revealed a strong association with a silent polymorphism in the gene encoding low density lipoprotein receptor-related protein-associated protein-1 (LRPAP1; 104225) among females (P = 0.0003), but not males (P = 0.292). Several other genes showed association only in females; only 1 gene, PRCP (176785), was significantly associated in men alone (P = 0.039).
Among 632 men, Robitaille et al. (2004) found increased frequency of the val162 allele of the leu162-to-val polymorphism in the PPARA gene (V162L; 170998.0001) among those with abdominal obesity, hypertriglyceridemia, high plasma apoB (107730), and low HDL plasma levels, which are components of the metabolic syndrome. The frequency of the V162 allele was approximately 10% in their group.
In a cohort of 716 German men genotyped for the I128T polymorphism of the MTP gene (157147.0009), Rubin et al. (2006) found that compared to wildtype homozygotes, carriers of the less common thr128 allele had significantly lower postprandial insulin levels, lower diastolic blood pressure, and a lower prevalence of impaired glucose metabolism and type 2 diabetes (125853). In a case-control study of 190 patients with type 2 diabetes and 380 controls, Rubin et al. (2006) observed a significantly lower incidence of type 2 diabetes in individuals with the thr128 genotype; the authors suggested that the rare allele of the MTP I128T polymorphism may be protective against impaired glucose tolerance, type 2 diabetes, and other parameters of the metabolic syndrome.
Love-Gregory et al. (2008) evaluated 36 tag SNPs across the CD36 gene (173510) in 2,020 African American individuals from the HyperGEN study and identified 5 SNPs that were associated with increased odds for metabolic syndrome (p = 0.0027 to 0.03; odds ratio, 1.3 to 1.4). In contrast, the coding SNP rs3211938 (173510.0002), which resulted in CD36 deficiency in a homozygous individual, was associated with protection against the metabolic syndrome, as well as increased HDL cholesterol and decreased triglycerides. Fifteen additional SNPs were associated with HDLC (p = 0.0028 to 0.044). Love-Gregory et al. (2008) concluded that CD36 variants may impact metabolic syndrome-related pathophysiology and HDL metabolism.
Associations with Waist-to-Hip Ratio
In 2,238 middle-aged (40-59 years old) and older (60-79 years old) Japanese individuals, Okura et al. (2003) analyzed the relationship between the estrogen receptor-alpha (ESR1; 133430) polymorphisms PvuII and XbaI and anthropometric variables, fat mass, and percentage fat mass. They found that middle-aged women with XbaI AG or GG genotypes had significantly greater BMI, fat mass, percentage fat mass, and waist-to-hip ratio (WHR) than those with the AA genotype. Conversely, waist size and fat mass were lower in older women with the GG genotype. Okura et al. (2003) concluded that the XbaI polymorphism, particularly the GG genotype, may contribute to the development of abdominal obesity in middle-aged women, but may decrease the whole-body and abdominal fat tissue of older women.
Kim et al. (2004) examined the effects of the pro12-to-ala polymorphism of the PPARG2 gene (P12A; 601487.0002) on body fat distribution and other obesity-related parameters in 1,051 Korean females. Body weight, fat mass, fat percentage, BMI, and WHR were significantly higher in individuals with the PA or AA genotype than those with PP. Among overweight individuals (BMI greater than 25), PA/AA was associated with significantly higher abdominal subcutaneous fat, abdominal visceral fat, and subcutaneous upper and lower thigh fat; there was no association in individuals with a BMI less than 25. Kim et al. (2004) suggested that the PPARG2 PA/AA genotype is associated with increased subcutaneous and visceral fat areas in overweight Korean females.
Ukkola et al. (2005) studied the impact of SNPs in the PTPN1 gene (176885) on body fat distribution in 502 white and 276 black individuals. White individuals with the GG genotype at the IVS6+82G-A SNP had significantly higher percentages of body fat, sums of 8 skinfold measurements, and highest amounts of subcutaneous fat on the extremities than those with AA or AG genotypes; however, the trunk-to-extremity skinfold ratio, adjusted for age, sex, and fat mass, was lower in GG than AA or AG individuals.
Baker et al. (2005) tested for association between 3 SNPs in the noncoding region of the POMC gene (176830) and obesity phenotypes in 1,428 members of 248 families originally ascertained for essential hypertension. There was significant association between genotypes at the 8246C-T (rs1042571) and 1032C-G (rs1009388) SNPs and WHR corrected for age, sex, smoking, exercise, alcohol consumption, and BMI: each T or G allele was associated with a 0.2-SD higher WHR in a codominant fashion. Baker et al. (2005) concluded that genetic variants at the POMC locus influence body fat distribution.
Masuzaki et al. (2001) created transgenic mice overexpressing 11-beta-hydroxysteroid dehydrogenase type 1 (600713) selectively in adipose tissue to an extent similar to that found in adipose tissue from obese humans. These mice had increased adipose levels of corticosterone and developed visceral obesity that was exaggerated by a high-fat diet. The mice also exhibited pronounced insulin-resistant diabetes, hyperlipidemia, and, surprisingly, hyperphagia despite hyperleptinemia. Increased adipocyte 11-beta-hydroxysteroid type 1 activity may be a common molecular etiology for visceral obesity and the metabolic syndrome.
Vartanian et al. (2006) found that Neil1 (608844) knockout mice were born at expected mendelian ratios and the phenotype of Neil1 -/- pups was normal through the first 4 to 6 months of life. At about 7 months, however, male Neil1 -/- mice developed severe obesity, and female Neil1 -/- mice were modestly overweight. Mutant mice also showed dyslipidemia, fatty liver disease, and a tendency to develop hyperinsulinemia, similar to metabolic syndrome in humans. Histologic studies showed significant kidney vacuolization, and mitochondrial DNA from Neil1 -/- mice showed increased levels of steady-state DNA damage and deletions, compared to wildtype controls.
Lam et al. (2007) found that intracerebroventricular administration of glucose in rats lowered circulating triglycerides through the inhibition of VLDL secretion by the liver. The effect of glucose required its conversion to lactate, leading to activation of ATP-sensitive potassium channels and to decreased hepatic Scd1 (604031) activity. These central effects of glucose, but not those of lactate, were rapidly lost in diet-induced obese rats. Lam et al. (2007) suggested that a defect in brain glucose sensing might play a critical role in the etiology of the metabolic syndrome.
Biddinger et al. (2008) generated liver-specific Insr (147670)-knockout (LIRKO) mice and observed a marked predisposition to cholesterol gallstone formation, with all of the LIRKO mice developing gallstones after 12 weeks on a lithogenic diet. This predisposition was due to at least 2 distinct mechanisms: disinhibition of the Foxo1 gene (136533), which increased expression of the biliary cholesterol transporters Abcg5 (605459) and Abcg8 (605460), resulting in an increase in biliary cholesterol secretion; and decreased expression of the bile acid synthetic enzymes, particularly Cyp7b1 (603711), which produced partial resistance to the farnesoid X receptor (NR1H4; 603826), leading to a lithogenic bile salt profile. The authors concluded that hepatic insulin resistance provides the link between the metabolic syndrome and increased cholesterol gallstone susceptibility.
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Kim, K. S., Choi, S. M., Shin, S. U., Yang, H. S., Yoon, Y. Effects of peroxisome proliferator-activated receptor-gamma-2 pro12ala polymorphism on body fat distribution in female Korean subjects. Metabolism 53: 1538-1543, 2004. [PubMed: 15562396] [Full Text: https://doi.org/10.1016/j.metabol.2004.06.019]
Kissebah, A. H., Sonnenberg, G. E., Myklebust, J., Goldstein, M., Broman, K., James, R. G., Marks, J. A., Krakower, G. R., Jacob, H. J., Weber, J., Martin, L., Blangero, J., Comuzzie, A. G. Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc. Nat. Acad. Sci. 97: 14478-14483, 2000. [PubMed: 11121050] [Full Text: https://doi.org/10.1073/pnas.97.26.14478]
Lam, T. K. T., Gutierrez-Juarez, R., Pocai, A., Bhanot, S., Tso, P., Schwartz, G. J., Rossetti, L. Brain glucose metabolism controls the hepatic secretion of triglyceride-rich lipoproteins. Nature Med. 13: 171-180, 2007. [PubMed: 17273170] [Full Text: https://doi.org/10.1038/nm1540]
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McCarthy, J. J., Meyer, J., Moliterno, D. J., Newby, L. K., Rogers, W. J., Topol, E. J. Evidence for substantial effect modification by gender in a large-scale genetic association study of the metabolic syndrome among coronary heart disease patients. Hum. Genet. 114: 87-98, 2003. [PubMed: 14557872] [Full Text: https://doi.org/10.1007/s00439-003-1026-1]
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Reaven, G. M. Role of insulin resistance in human disease. Diabetes 37: 1595-1607, 1988. [PubMed: 3056758] [Full Text: https://doi.org/10.2337/diab.37.12.1595]
Robitaille, J., Brouillette, C., Houde, A., Lemieux, S., Perusse, L., Tchernof, A., Gaudet, D., Vohl, M.-C. Association between the PPAR-alpha-L162V polymorphism and components of the metabolic syndrome. J. Hum. Genet. 49: 482-489, 2004. [PubMed: 15309680] [Full Text: https://doi.org/10.1007/s10038-004-0177-9]
Rubin, D., Helwig, U., Pfeuffer, M., Schreiber, S., Boeing, H., Fisher, E., Pfeiffer, A., Freitag-Wolf, S., Foelsch, U. R., Doering, F., Schrezenmeir, J. A common functional exon polymorphism in the microsomal triglyceride transfer protein gene is associated with type 2 diabetes, impaired glucose metabolism and insulin levels. J. Hum. Genet. 51: 567-574, 2006. [PubMed: 16721486] [Full Text: https://doi.org/10.1007/s10038-006-0400-y]
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Wilson, S. G., Adam, G., Langdown, M., Reneland, R., Braun, A., Andrew, T., Surdulescu, G. L., Norberg, M., Dudbridge, F., Reed, P. W., Sambrook, P. N., Kleyn, P. W., Spector, T. D. Linkage and potential association of obesity-related phenotypes with two genes on chromosome 12q24 in a female dizygous twin cohort. Europ. J. Hum. Genet. 14: 340-348, 2006. [PubMed: 16391564] [Full Text: https://doi.org/10.1038/sj.ejhg.5201551]