Skip to main content

Advertisement

SpringerLink
Log in

Genetics of metabolic syndrome

  • Published:
Reviews in Endocrine and Metabolic Disorders Aims and scope Submit manuscript

Abstract

Metabolic syndrome (MetS) is a cluster of metabolic traits associated with an increased risk of cardiovascular disease and type 2 diabetes mellitus. Central obesity and insulin resistance are thought to play key roles in the pathogenesis of the MetS. The MetS has a significant genetic component, and therefore linkage analysis, candidate gene approach, and genome-wide association (GWA) studies have been applied in the search of gene variants for the MetS. A few variants have been identified, located mostly in or near genes regulating lipid metabolism. GWA studies for the individual components of the MetS have reported several loci having pleiotropic effects on multiple MetS-related traits. Genetic studies have provided so far only limited evidence for a common genetic background of the MetS. Epigenetic factors (DNA methylation and histone modification) are likely to play important roles in the pathogenesis of the MetS, and they might mediate the effects of environmental exposures on the risk of the MetS. Further research is needed to clarify the role of genetic variation and epigenetic mechanisms in the development of the MetS.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Abbreviations

BMI:

Body mass index

BP:

Blood pressure

EGIR:

European Group for the Study of Insulin Resistance

GWA:

Genome-wide association

HDL:

High density lipoprotein

IDF:

International Diabetes Federation

LDL:

Low density lipoprotein

MetS:

Metabolic syndrome

NCEP ATP III:

National Cholesterol Education Program Adult Treatment Panel III

SNP:

Single nucleotide polymorphism

TG:

Triglycerides

WC:

Waist circumference

WHO:

World Health Organization

WHR:

Waist-to-hip ratio

References

  1. Alberti KG, Zimmet PZ. Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 1998;15:539–53.

    Article  CAS  PubMed  Google Scholar 

  2. Balkau B, Charles MA. Comment on the provisional report from the WHO consultation. European Group for the Study of Insulin Resistance (EGIR). Diabet Med. 1999;16:442–3.

    Article  CAS  PubMed  Google Scholar 

  3. 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). JAMA. 2001;285:2486–97

  4. Grundy SM, Brewer HB, Cleeman JI, Smith SC, Lenfant D. for the Conference Participants. Definition of metabolic syndrome: report of the National, Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation. 2004;109:433–8.

    Article  PubMed  Google Scholar 

  5. Alberti KG, Zimmet P, Shaw J. IDF epidemiology task force consensus group. The metabolic syndrome–a new worldwide definition. Lancet. 2005;366:1059–62.

    Article  PubMed  Google Scholar 

  6. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. International diabetes federation task force on epidemiology and prevention; hational heart, lung, and blood institute; american heart association; world heart federation; international atherosclerosis society; international association for the study of obesity. 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. Circulation. 2009;120:1640–5.

    Article  CAS  PubMed  Google Scholar 

  7. Ilanne-Parikka P, Eriksson JG, Lindström J, Hämäläinen H, Keinänen-Kiukaanniemi S, Laakso M, et al. innish Diabetes Prevention Study Group. Prevalence of the metabolic syndrome and its components: findings from a Finnish general population sample and the Diabetes Prevention Study cohort. Diabetes Care. 2004;27:2135–40.

    Article  PubMed  Google Scholar 

  8. Athyros VG, Bouloukos VI, Pehlivanidis AN, Papageorgiou AA, Dionysopoulou SG, Symeonidis AN, et al. MetS-greece collaborative group. The prevalence of the metabolic syndrome in Greece: the MetS-greece multicentre study. Diabetes Obes Metab. 2005;7:397–405.

    Article  CAS  PubMed  Google Scholar 

  9. Ford ES. Prevalence of the metabolic syndrome in US populations. Endocrinol Metab Clin North Am. 2004;33:333–50.

    Article  PubMed  Google Scholar 

  10. Guallar-Castillón P, Pérez RF, López García E, León-Muñoz LM, Aguilera MT, Graciani A, Gutiérrez-Fisac JL, Banegas JR, Rodríguez-Artalejo F. Magnitude and Management of Metabolic Syndrome in Spain in 2008–2010: The ENRICA Study. Rev Esp Cardiol. 2014.

  11. Prasad DS, Kabir Z, Dash AK, Das BC. Prevalence and risk factors for metabolic syndrome in Asian Indians: A community study from urban Eastern India. J Cardiovasc Dis Res. 2012;3:204–11.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  12. Ford ES, Giles WH, Dietz WH. Prevalence of the metabolic syndrome among US adults: findings from the third National Health and Nutrition Examination Survey. JAMA. 2002;287:356–9.

    Article  PubMed  Google Scholar 

  13. Ford ES, Li C, Zhao G, Pearson WS, Mokdad AH. Prevalence of the metabolic syndrome among U.S. adolescents using the definition from the International Diabetes Federation. Diabetes Care. 2008;31:587–9.

    Article  PubMed  Google Scholar 

  14. McNeill AM, Rosamond WD, Girman CJ, Golden SH, Schmidt MI, East HE, et al. The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care. 2005;28:385–90.

    Article  PubMed  Google Scholar 

  15. Lakka HM, Laaksonen DE, Lakka TA, Niskanen LK, Kumpusalo E, Tuomilehto J, et al. The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men. JAMA. 2002;288:2709–16.

    Article  PubMed  Google Scholar 

  16. Hunt KJ, Resendez RG, Williams K, Haffner SM, Stern MP. San Antonio heart study. National cholesterol education program versus world health organization metabolic syndrome in relation to all-cause and cardiovascular mortality in the San Antonio heart study. Circulation. 2004;110:1251–7.

    Article  PubMed  Google Scholar 

  17. Ford ES, Schulze MB, Pischon T, Bergmann MM, Joost HG, Boeing H. Metabolic syndrome and risk of incident diabetes: findings from the european prospective investigation into cancer and nutrition-Potsdam study. Cardiovasc Diabetol. 2008;7:35.

    Article  PubMed Central  PubMed  Google Scholar 

  18. Ford ES. Risks for all-cause mortality, cardiovascular disease, and diabetes associated with the metabolic syndrome: a summary of the evidence. Diabetes Care. 2005;28:1769–78.

    Article  PubMed  Google Scholar 

  19. Gallagher EJ, Leroith D, Karnieli E. Insulin resistance in obesity as the underlying cause for the metabolic syndrome. Mt Sinai J Med. 2010;77:511–23.

    Article  PubMed  Google Scholar 

  20. Meigs JB, Rutter MK, Sullivan LM, Fox CS, D'Agostino Sr RB, Wilson PW. Impact of insulin resistance on risk of type 2 diabetes and cardiovascular disease in people with metabolic syndrome. Diabetes Care. 2007;30:1219–25.

    Article  CAS  PubMed  Google Scholar 

  21. Cheal KL, Abbasi F, Lamendola C, McLaughlin T, Reaven GM, Ford ES. Relationship to insulin resistance of the Adult Treatment Panel III diagnostic criteria for identification of the metabolic syndrome. Diabetes. 2004;53:1195–200.

    Article  CAS  PubMed  Google Scholar 

  22. Meigs JB, Wilson PW, Fox CS, Vasan RS, Nathan DM, Sullivan LM, et al. Body mass index, metabolic syndrome, and risk of type 2 diabetes or cardiovascular disease. J Clin Endocrinol Metab. 2006;91:2906–12.

    Article  CAS  PubMed  Google Scholar 

  23. Lin HF, Boden-Albala B, Juo SH, Park N, Rundek T, Sacco RL. Heritabilities of the metabolic syndrome and its components in the Northern Manhattan Family Study. Diabetologia. 2005;48:2006–12.

    Article  PubMed Central  PubMed  Google Scholar 

  24. Bellia A, Giardina E, Lauro D, Tesauro M, Di Fede G, Cusumano G, et al. “The Linosa Study”: epidemiological and heritability data of the metabolic syndrome in a Caucasian genetic isolate. Nutr Metab Cardiovasc Dis. 2009;19:455–61.

    Article  CAS  PubMed  Google Scholar 

  25. Carmelli D, Cardon LR, Fabsitz R. Clustering of hypertension, diabetes, and obesity in adult male twins: same genes or same environments? Am J Hum Genet. 1994;55:566–73.

    CAS  PubMed Central  PubMed  Google Scholar 

  26. Edwards KL, Newman B, Mayer E, Selby JV, Krauss RM, Austin MA. Heritability of factors of the insulin resistance syndrome in women twins. Genet Epidemiol. 1997;14:241–53.

    Article  CAS  PubMed  Google Scholar 

  27. Kissebah AH, Sonnenberg GE, Myklebust J, Goldstein M, Broman K, James RG, et al. Quantitative trait loci on chromosomes 3 and 17 influence phenotypes of the metabolic syndrome. Proc Natl Acad Sci U S A. 2000;97:14478–83.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  28. Loos RJ, Katzmarzyk PT, Rao DC, Rice T, Leon AS, Skinner JS, et al. HERITAGE Family Study. Genome-wide linkage scan for the metabolic syndrome in the HERITAGE Family Study. J Clin Endocrinol Metab. 2003;88:5935–43.

    Article  CAS  PubMed  Google Scholar 

  29. Tang W, Miller MB, Rich SS, North KE, Pankow JS, Borecki IB, et al. National Heart, Lung, and Blood Institute Family Heart Study. Linkage analysis of a composite factor for the multiple metabolic syndrome: the National Heart, Lung, and Blood Institute Family Heart Study. Diabetes. 2003;52:2840–7.

    Article  CAS  PubMed  Google Scholar 

  30. Edwards KL, Hutter CM, Wan JY, Kim H, Monks SA. Genome-wide linkage scan for the metabolic syndrome: the GENNID study. Obesity (Silver Spring). 2008;16:1596–601.

    Article  CAS  Google Scholar 

  31. Zabaneh D, Balding DJ. A genome-wide association study of the metabolic syndrome in Indian Asian men. PLoS One. 2010;5:e11961.

    Article  PubMed Central  PubMed  Google Scholar 

  32. Kraja AT, Vaidya D, Pankow JS, Goodarzi MO, Assimes TL, Kullo IJ, et al. A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium. Diabetes. 2011;60:1329–39.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  33. Kristiansson K, Perola M, Tikkanen E, Kettunen J, Surakka I, Havulinna AS, et al. Genome-wide screen for metabolic syndrome susceptibility Loci reveals strong lipid gene contribution but no evidence for common genetic basis for clustering of metabolic syndrome traits. Circ Cardiovasc Genet. 2012;5:242–9.

    Article  PubMed Central  PubMed  Google Scholar 

  34. Avery CL, He Q, North KE, Ambite JL, Boerwinkle E, Fornage M, et al. A phenomics-based strategy identifies loci on APOC1, BRAP, and PLCG1 associated with metabolic syndrome phenotype domains. PLoS Genet. 2011;7:e1002322.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  35. Fall T, Ingelsson E. Genome-wide association studies of obesity and metabolic syndrome. Mol Cell Endocrinol. 2014;382:740–57.

    Article  CAS  PubMed  Google Scholar 

  36. Global Lipids Genetics Consortium, Willer CJ, Schmidt EM, Sengupta S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45:1274–83.

    Article  CAS  PubMed  Google Scholar 

  37. Kilpeläinen TO, Zillikens MC, Stančáková A, et al. Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile. Nat Genet. 2011;43:753–60.

    Article  PubMed Central  PubMed  Google Scholar 

  38. Dupuis J, Langenberg C, Prokopenko I, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet. 2010;42:105–16.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  39. Saxena R, Hivert MF, Langenberg C, et al. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet. 2010;42:142–8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  40. Diabetes Genetics Initiative of Broad Institute of Harvard and MIT, Lund University, andartis Institutes of BioMedical Research, Saxena R, et al. Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels. Science. 2007;316:1331–6.

    Article  CAS  PubMed  Google Scholar 

  41. Willer CJ, Sanna S, Jackson AU, et al. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet. 2008;40:161–9.

    Article  CAS  PubMed  Google Scholar 

  42. Stančáková A, Paananen J, Soininen P, Kangas AJ, Bonnycastle LL, Morken MA, et al. Effects of 34 risk loci for type 2 diabetes or hyperglycemia on lipoprotein subclasses and their composition in 6,580 nondiabetic Finnish men. Diabetes. 2011;60:1608–16.

    Article  PubMed Central  PubMed  Google Scholar 

  43. Speliotes EK, Yerges-Armstrong LM, Wu J, et al. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits. PLoS Genet. 2011;7:e1001324.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  44. Frayling TM, Timpson NJ, Weedon MN, Zeggini E, Freathy RM, Lindgren CM, et al. A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity. Science. 2007;316:889–94.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  45. Chambers JC, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, et al. Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet. 2008;40:716–8.

    Article  CAS  PubMed  Google Scholar 

  46. Do R, Bailey SD, Desbiens K, Belisle A, Montpetit A, Bouchard C, et al. Genetic variants of FTO influence adiposity, insulin sensitivity, leptin levels, and resting metabolic rate in the Quebec Family Study. Diabetes. 2008;57:1147–50.

    Article  CAS  PubMed  Google Scholar 

  47. Morris AP, Voight BF, Teslovich TM, et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet. 2012;44:981–90.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  48. Heid IM, Jackson AU, Randall JC, et al. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution. Nat Genet. 2010;42:949–60.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  49. Kooner JS, Saleheen D, Sim X, et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat Genet. 2011;43:984–9.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  50. Scott RA, Lagou V, Welch RP, et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet. 2012;44:991–1005.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  51. Zeggini E, Scott LJ, Saxena R, et al. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes. Nat Genet. 2008;40:638–45.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  52. Steinthorsdottir V, Thorleifsson G, Reynisdottir I, et al. A variant in CDKAL1 influences insulin response and risk of type 2 diabetes. Nat Genet. 2007;39:770–5.

    Article  CAS  PubMed  Google Scholar 

  53. Wen W, Cho YS, Zheng W, et al. Meta-analysis identifies common variants associated with body mass index in east Asians. Nat Genet. 2012;44:307–11.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  54. Speliotes EK, Willer CJ, Berndt SI, et al. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet. 2010;42:937–48.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  55. Bi M, Kao WH, Boerwinkle E, Hoogeveen RC, Rasmussen-Torvik LJ, Astor BC, et al. Association of rs780094 in GCKR with metabolic traits and incident diabetes and cardiovascular disease: the ARIC Study. PLoS One. 2010;5:e11690.

    Article  PubMed Central  PubMed  Google Scholar 

  56. Povel CM, Boer JM, Onland-Moret NC, Dollé ME, Feskens EJ, van der Schouw YT. Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study. Cardiovasc Diabetol. 2012;11:133.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  57. Dušátková L, Zamrazilová H, Sedláčková B, Včelák J, Hlavatý P, Aldhoon Hainerová I, et al. Association of obesity susceptibility gene variants with metabolic syndrome and related traits in 1,443 czech adolescents. Folia Biol (Praha). 2013;59:123–33.

    Google Scholar 

  58. Yang CW, Li CI, Liu CS, Bau DT, Lin CH, Lin WY, et al. The joint effect of cigarette smoking and polymorphisms on LRP5, LEPR, near MC4R and SH2B1 genes on metabolic syndrome susceptibility in Taiwan. Mol Biol Rep. 2013;40:525–33.

    Article  CAS  PubMed  Google Scholar 

  59. Heid IM, Vollmert C, Kronenberg F, Huth C, Ankerst DP, Luchner A, et al. Association of the MC4R V103I polymorphism with the metabolic syndrome: the KORA Study. Obesity (Silver Spring). 2008;16:369–76.

    Article  CAS  Google Scholar 

  60. Kawajiri T, Osaki Y, Kishimoto T. Association of gene polymorphism of the fat mass and obesity associated gene with metabolic syndrome: a retrospective cohort study in Japanese workers. Yonago Acta Med. 2012;55:29–40.

    CAS  PubMed Central  PubMed  Google Scholar 

  61. Hotta K, Kitamoto T, Kitamoto A, Mizusawa S, Matsuo T, Nakata Y, et al. Association of variations in the FTO, SCG3 and MTMR9 genes with metabolic syndrome in a Japanese population. J Hum Genet. 2011;56:647–51.

    Article  CAS  PubMed  Google Scholar 

  62. Wang T, Huang Y, Xiao XH, Wang DM, Diao CM, Zhang F, et al. The association between common genetic variation in the FTO gene and metabolic syndrome in Han Chinese. Chin Med J (Engl). 2010;123:1852–8.

    CAS  Google Scholar 

  63. Attaoua R. Ait El Mkadem S, Lautier C, Kaouache S, Renard E, Brun JF, Fedou C, Gris JC, Bringer J, Grigorescu F. Association of the FTO gene with obesity and the metabolic syndrome is independent of the IRS-2 gene in the female population of Southern France. Diabetes Metab. 2009;35:476–83.

    Article  CAS  PubMed  Google Scholar 

  64. Al-Attar SA, Pollex RL, Ban MR, Young TK, Bjerregaard P, Anand SS, et al. Association between the FTO rs9939609 polymorphism and the metabolic syndrome in a non-Caucasian multi-ethnic sample. Cardiovasc Diabetol. 2008;7:5.

    Article  PubMed Central  PubMed  Google Scholar 

  65. Zhou D, Liu H, Zhou M, Wang S, Zhang J, Liao L, et al. Common variant (rs9939609) in the FTO gene is associated with metabolic syndrome. Mol Biol Rep. 2012;39:6555–61.

    Article  CAS  PubMed  Google Scholar 

  66. Wang H, Dong S, Xu H, Qian J, Yang J. Genetic variants in FTO associated with metabolic syndrome: a meta- and gene-based analysis. Mol Biol Rep. 2012;39:5691–8.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  67. Miyaki K, Oo T, Song Y, Lwin H, Tomita Y, Hoshino H, et al. Association of a cyclin-dependent kinase 5 regulatory subunit-associated protein 1-like 1 (CDKAL1) polymorphism with elevated hemoglobin A1(c) levels and the prevalence of metabolic syndrome in Japanese men: interaction with dietary energy intake. Am J Epidemiol. 2010;172:985–91.

    Article  PubMed  Google Scholar 

  68. Gerken T, Girard CA, Tung YC, Webby CJ, Saudek V, Hewitson KS, et al. The obesity-associated FTO gene encodes a 2-oxoglutarate-dependent nucleic acid demethylase. Science. 2007;318:1469–72.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  69. Fischer J, Koch L, Emmerling C, Vierkotten J, Peters T, Brüning JC, et al. Inactivation of the Fto gene protects from obesity. Nature. 2009;458:894–8.

    Article  CAS  PubMed  Google Scholar 

  70. Church C, Moir L, McMurray F, Girard C, Banks GT, Teboul L, et al. Overexpression of Fto leads to increased food intake and results in obesity. Nat Genet. 2010;42:1086–92.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  71. Tschritter O, Preissl H, Yokoyama Y, Machicao F, Häring HU, Fritsche A. Variation in the FTO gene locus is associated with cerebrocortical insulin resistance in humans. Diabetologia. 2007;50:2602–3.

    Article  CAS  PubMed  Google Scholar 

  72. Butler AA, Cone RD. The melanocortin receptors: lessons from knockout models. Neuropeptides. 2002;36:77–84.

    Article  CAS  PubMed  Google Scholar 

  73. Tamemoto H, Kadowaki T, Tobe K, Yagi T, Sakura H, Hayakawa T, et al. Insulin resistance and growth retardation in mice lacking insulin receptor substrate-1. Nature. 1994;372:182–6.

    Article  CAS  PubMed  Google Scholar 

  74. Wolffe AP, Guschin D. Review: chromatin structural features and targets that regulate transcription. J Struct Biol. 2000;129:102–22.

    Article  CAS  PubMed  Google Scholar 

  75. Dabelea D, Hanson RL, Lindsay RS, Pettitt DJ, Imperatore G, Gabir MM, et al. Intrauterine exposure to diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes. 2000;49:2208–11.

    Article  CAS  PubMed  Google Scholar 

  76. Nilsson E,sson PA, Perfilyev A, Volkov P, Pedersen M, Svensson MK, Poulsen P, Ribel-Madsen R, Pedersen NL, Almgren P, Fadista J, Rönn T, Klarlund-Pedersen B, Scheele C, Vaag A, Ling C. Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes. Diabetes. 2014; doi:10.2337/db13-1459.

  77. Dayeh T, Volkov P, Salö S, Hall E, Nilsson E, Olsson AH, et al. Genome-wide DNA methylation analysis of human pancreatic islets from type 2 diabetic and non-diabetic donors identifies candidate genes that influence insulin secretion. PLoS Genet. 2014;10:e1004160.

    Article  PubMed Central  PubMed  Google Scholar 

  78. Toperoff G, Aran D, Kark JD, Rosenberg M, Dubnikov T, Nissan B, et al. Genome-wide survey reveals predisposing diabetes type 2-related DNA methylation variations in human peripheral blood. Hum Mol Genet. 2012;21:371–83.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  79. Zhang Y, Kent 2nd JW, Lee A, Cerjak D, Ali O, Diasio R, et al. Fatty acid binding protein 3 (fabp3) is associated with insulin, lipids and cardiovascular phenotypes of the metabolic syndrome through epigenetic modifications in a Northern European family population. BMC Med Genomics. 2013;6:9.

    Article  PubMed Central  PubMed  Google Scholar 

  80. Milagro FI, Gómez-Abellán P, Campión J. tínez JA, Ordovás JM, Garaulet M. CLOCK, PER2 and BMAL1 DNA methylation: association with obesity and metabolic syndrome characteristics and monounsaturated fat intake. Chronobiol Int. 2012;29:1180–94.

    Article  CAS  PubMed  Google Scholar 

  81. Rottiers V, Näär AM. MicroRNAs in metabolism and metabolic disorders. Nat Rev Mol Cell Biol. 2012;13:239–50.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  82. Ge Q, Brichard S, Yi X, Li Q. microRNAs as a new mechanism regulating adipose tissue inflammation in obesity and as a novel therapeutic strategy in the metabolic syndrome. J Immunol Res. 2014;2014:987285

Download references

Conflict of interest

The authors declare that they have no conflict of interest.

Author information

Authors and Affiliations

  1. Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland

    Alena Stančáková

  2. Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland

    Markku Laakso

Authors
  1. Alena Stančáková
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Markku Laakso
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Markku Laakso.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Stančáková, A., Laakso, M. Genetics of metabolic syndrome. Rev Endocr Metab Disord 15, 243–252 (2014). https://doi.org/10.1007/s11154-014-9293-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11154-014-9293-9

Keywords

Search

Navigation