Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

ACC 2024 Congress

Catch up on all the top stories and latest evidence in cardiology research with our ACC 2024 Congress hub page.
ADVANCED SEARCH
Log in
Top
Cardiovascular Diabetology
Published in: Cardiovascular Diabetology 1/2012

Open Access 01-12-2012 | Original investigation

Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study

Authors: Cécile M Povel, Jolanda MA Boer, N Charlotte Onland-Moret, Martijn ET Dollé, Edith JM Feskens, Yvonne T van der Schouw

Published in: Cardiovascular Diabetology | Issue 1/2012

Login to get access

Abstract

Background

Mechanisms involved in metabolic syndrome (MetS) development include insulin resistance, weight regulation, inflammation and lipid metabolism. Aim of this study is to investigate the association of single nucleotide polymorphisms (SNPs) involved in these mechanisms with MetS.

Methods

In a random sample of the EPIC-NL study (n = 1886), 38 SNPs associated with waist circumference, insulin resistance, triglycerides, HDL cholesterol and inflammation in genome wide association studies (GWAS) were selected from the 50K IBC array and one additional SNP was measured with KASPar chemistry. The five groups of SNPs, each belonging to one of the metabolic endpoints mentioned above, were associated with MetS and MetS-score using Goeman’s global test. For groups of SNPs significantly associated with the presence of MetS or MetS-score, further analyses were conducted.

Results

The group of waist circumference SNPs was associated with waist circumference (P=0.03) and presence of MetS (P=0.03). Furthermore, the group of SNPs related to insulin resistance was associated with MetS score (P<0.01), HDL cholesterol (P<0.01), triglycerides (P<0.01) and HbA1C (P=0.04). Subsequent analyses showed that MC4R rs17782312, involved in weight regulation, and IRS1 rs2943634, related to insulin resistance were associated with MetS (OR 1.16, 95%CI 1.02-1.32 and OR 0.88, 95% CI 0.79; 0.97, respectively). The groups of inflammation and lipid SNPs were neither associated with presence of MetS nor with MetS score.

Conclusions

In this study we found support for the hypothesis that weight regulation and insulin metabolism are involved in MetS development. MC4R rs17782312 and IRS1 rs2943634 may explain part of the genetic variation in MetS.
Appendix
Available only for authorised users
Literature
1.
Eckel RH, Grundy SM, Zimmet PZ: The metabolic syndrome. Lancet. 2005, 365 (9468): 1415-1428. 10.1016/S0140-6736(05)66378-7.CrossRefPubMed
2.
Hotamisligil GS: Inflammation and metabolic disorders. Nature. 2006, 444 (7121): 860-867. 10.1038/nature05485.CrossRefPubMed
3.
Sutherland JP, McKinley B, Eckel RH: The metabolic syndrome and inflammation. Metab Syndr Relat Disord. 2004, 2 (2): 82-104. 10.1089/met.2004.2.82.CrossRefPubMed
4.
Povel CM, Boer JMA, Reiling E, Feskens EJM: Genetic variants and the metabolic syndrome: a systematic review. Obes Rev. 2011, 12 (11): 952-967. 10.1111/j.1467-789X.2011.00907.x.CrossRefPubMed
5.
Kraja AT, Vaidya D, Pankow JS, Goodarzi MO, Assimes TL, Kullo IJ, Sovio U, Mathias RA, Sun YV, Franceschini N, et al: A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium. Diabetes. 2011, 60 (4): 1329-1339. 10.2337/db10-1011.PubMedCentralCrossRefPubMed
6.
Bosy-Westphal A, Onur S, Geisler C, Wolf A, Korth O, Pfeufferm M, Schrezenmeir J, Krawczak M, Muller MJ: Common familial influences on clustering of metabolic syndrome traits with central obesity and insulin resistance: the Kiel obesity prevention study. Int J Obes (Lond). 2007, 31 (5): 784-790.
7.
Goeman JJ, van de Geer SA, de Kort F, van Houwelingen HC: A global test for groups of genes: testing association with a clinical outcome. Bioinformatics. 2004, 20 (1): 93-99. 10.1093/bioinformatics/btg382.CrossRefPubMed
8.
Beulens JW, Monninkhof EM, Verschuren WM, van der Schouw YT, Smit J, Ocke MC, Jansen EH, van Dieren S, Grobbee DE, Peeters PH, et al: Cohort profile: the EPIC-NL study. Int J Epidemiol. 2010, 39 (5): 1170-1178. 10.1093/ije/dyp217.CrossRefPubMed
9.
Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, Gordon DJ, Krauss RM, Savage PJ, Smith SC, et al: Diagnosis and management of the metabolic syndrome. An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Executive summary. Cardiol Rev. 2005, 13 (6): 322-327.PubMed
10.
American Diabetes Association: Standards of medical care in diabetes–2010. Diabetes. 2010, 33 (Suppl 1): S11-S61.
11.
American Diabetes Association: Diagnosis and classification of diabetes mellitus. Diabetes. 2010, 33 (Suppl 1): S62-S69.
12.
Keating BJ, Tischfield S, Murray SS, Bhangale T, Price TS, Glessner JT, Galver L, Barrett JC, Grant SF, Farlow DN, et al: Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies. PLoS One. 2008, 3 (10): e3583-10.1371/journal.pone.0003583.PubMedCentralCrossRefPubMed
13.
Bauer F, Elbers CC, Adan RA, Loos RJ, Onland-Moret NC, Grobbee DE, van Vliet-Ostaptchouk JV, Wijmenga C, van der Schouw YT: Obesity genes identified in genome-wide association studies are associated with adiposity measures and potentially with nutrient-specific food preference. Am J Clin Nutr. 2009, 90 (4): 951-959. 10.3945/ajcn.2009.27781.CrossRefPubMed
14.
Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, Wheeler E, Glazer NL, Bouatia-Naji N, Gloyn AL, et al: New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat. 2010, 42 (2): 105-116. 10.1038/ng.520.
15.
Rung J, Cauchi S, Albrechtsen A, Shen L, Rocheleau G, Cavalcanti-Proenca C, Bacot F, Balkau B, Belisle A, Borch-Johnsen K, et al: Genetic variant near IRS1 is associated with type 2 diabetes, insulin resistance and hyperinsulinemia. Nat Genet. 2009, 41 (10): 1110-1115. 10.1038/ng.443. Epub 2009 Sep 1116CrossRefPubMed
16.
Lindgren CM, Heid IM, Randall JC, Lamina C, Steinthorsdottir V, Qi L, Speliotes EK, Thorleifsson G, Willer CJ, Herrera BM, et al: Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution. PLoS Genet. 2009, 5 (6): e1000508-10.1371/journal.pgen.1000508.PubMedCentralCrossRefPubMed
17.
Elliott P, Chambers JC, Zhang W, Clarke R, Hopewell JC, Peden JF, Erdmann J, Braund P, Engert JC, Bennett D, et al: Genetic Loci associated with C-reactive protein levels and risk of coronary heart disease. JAMA. 2009, 302 (1): 37-48. 10.1001/jama.2009.954.PubMedCentralCrossRefPubMed
18.
Richards JB, Waterworth D, O’Rahilly S, Hivert MF, Loos RJ, Perry JR, Tanaka T, Timpson NJ, Semple RK, Soranzo N, et al: A genome-wide association study reveals variants in ARL15 that influence adiponectin levels. PLoS Genet. 2009, 5 (12): e1000768-10.1371/journal.pgen.1000768.PubMedCentralCrossRefPubMed
19.
He M, Cornelis MC, Kraft P, van Dam RM, Sun Q, Laurie CC, Mirel DB, Chasman DI, Ridker PM, Hunter DJ, et al: Genome-wide association study identifies variants at the IL18-BCO2 locus associated with interleukin-18 levels. Arterioscler. 2010, 30 (4): 885-890. 10.1161/ATVBAHA.109.199422.CrossRef
20.
Ridker PM, Pare G, Parker A, Zee RY, Danik JS, Buring JE, Kwiatkowski D, Cook NR, Miletich JP, Chasman DI: Loci related to metabolic-syndrome pathways including LEPR,HNF1A, IL6R, and GCKR associate with plasma C-reactive protein: the Women’s Genome Health Study. Am J Hum Genet. 2008, 82 (5): 1185-1192. 10.1016/j.ajhg.2008.03.015. Epub 2008 Apr 1124PubMedCentralCrossRefPubMed
21.
Waterworth DM, Ricketts SL, Song K, Chen L, Zhao JH, Ripatti S, Aulchenko YS, Zhang W, Yuan X, Lim N, et al: Genetic variants influencing circulating lipid levels and risk of coronary artery disease. Arterioscler Thromb Vasc Biol. 2010, 30 (11): 2264-2276. 10.1161/ATVBAHA.109.201020.PubMedCentralCrossRefPubMed
22.
Sabatti C, Service SK, Hartikainen AL, Pouta A, Ripatti S, Brodsky J, Jones CG, Zaitlen NA, Varilo T, Kaakinen M, et al: Genome-wide association analysis of metabolic traits in a birth cohort from a founder population. Nat Genet. 2009, 41 (1): 35-46. 10.1038/ng.271.PubMedCentralCrossRefPubMed
23.
Kathiresan S, Melander O, Guiducci C, Surti A, Burtt NP, Rieder MJ, Cooper GM, Roos C, Voight BF, Havulinna AS, et al: Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nat Genet. 2008, 40 (2): 189-197. 10.1038/ng.75.PubMedCentralCrossRefPubMed
24.
Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, Heath SC, Timpson NJ, Najjar SS, Stringham HM, et al: Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet. 2008, 40 (2): 161-169. 10.1038/ng.76.CrossRefPubMed
25.
Wallace C, Newhouse SJ, Braund P, Zhang F, Tobin M, Falchi M, Ahmadi K, Dobson RJ, Marcano AC, Hajat C, et al: Genome-wide association study identifies genes for biomarkers of cardiovascular disease: serum urate and dyslipidemia. Am J Hum Genet. 2008, 82 (1): 139-149. 10.1016/j.ajhg.2007.11.001.PubMedCentralCrossRefPubMed
26.
Kathiresan S, Willer CJ, Peloso GM, Demissie S, Musunuru K, Schadt EE, Kaplan L, Bennett D, Li Y, Tanaka T, et al: Common variants at 30 loci contribute to polygenic dyslipidemia. Nat Genet. 2009, 41 (1): 56-65. 10.1038/ng.291.PubMedCentralCrossRefPubMed
27.
Aulchenko YS, Ripatti S, Lindqvist I, Boomsma D, Heid IM, Pramstaller PP, Penninx BW, Janssens AC, Wilson JF, Spector T, et al: Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet. 2009, 41 (1): 47-55. 10.1038/ng.269.PubMedCentralCrossRefPubMed
28.
Ridker PM, Pare G, Parker AN, Zee RY, Miletich JP, Chasman DI: Polymorphism in the CETP gene region, HDL cholesterol, and risk of future myocardial infarction: Genomewide analysis among 18 245 initially healthy women from the Women’s Genome Health Study. Circ Cardiovasc Genet. 2009, 2 (1): 26-33. 10.1161/CIRCGENETICS.108.817304.PubMedCentralCrossRefPubMed
29.
Teslovich TM, Musunuru K, Smith AV, Edmondson AC, Stylianou IM, Koseki M, Pirruccello JP, Ripatti S, Chasman DI, Willer CJ, et al: Biological, clinical and population relevance of 95 loci for blood lipids. Nature. 2010, 466 (7307): 707-713. 10.1038/nature09270.PubMedCentralCrossRefPubMed
30.
Heid IM, Vollmert C, Kronenberg F, Huth C, Ankerst DP, Luchner A, Hinney A, Bronner G, Wichmann HE, Illig T, et al: Association of the MC4R V103I polymorphism with the metabolic syndrome: the KORA Study. Obesity (Silver Spring). 2008, 16 (2): 369-376. 10.1038/oby.2007.21.CrossRef
31.
Butler AA, Cone RD: The melanocortin receptors: lessons from knockout models. Neuropeptides. 2002, 36 (2–3): 77-84.CrossRefPubMed
32.
Chambers J, Elliott P, Zabaneh D, Zhang W, Li Y, Froguel P, Balding D, Scott J, Kooner JS: Common genetic variation near MC4R is associated with waist circumference and insulin resistance. Nat Genet. 2008, 40 (6): 716-718. 10.1038/ng.156.CrossRefPubMed
33.
Freathy RM, Timpson NJ, Lawlor DA, Pouta A, Ben-Shlomo Y, Ruokonen A, Ebrahim S, Shields B, Zeggini E, Weedon MN, et al: Common variation in the FTO gene alters diabetes-related metabolic traits to the extent expected given its effect on BMI. Diabetes. 2008, 57 (5): 1419-1426. 10.2337/db07-1466.PubMedCentralCrossRefPubMed
34.
Borai A, Livingstone C, Abdelaal F, Bawazeer A, Keti V, Ferns G: The relationship between glycosylated haemoglobin (HbA1c) and measures of insulin resistance across a range of glucose tolerance. Scand J Clin Lab Invest. 2011, 71 (2): 168-172.PubMed
35.
Abe H, Yamada N, Kamata K, Kuwaki T, Shimada M, Osuga J, Shionoiri F, Yahagi N, Kadowaki T, Tamemoto H, et al: Hypertension, hypertriglyceridemia, and impaired endothelium-dependent vascular relaxation in mice lacking insulin receptor substrate-1. J Clin Invest. 1998, 101 (8): 1784-1788. 10.1172/JCI1594.PubMedCentralCrossRefPubMed
36.
Kilpelainen TO, Zillikens MC, Stancakova A, Finucane FM, Ried JS, Langenberg C, Zhang W, Beckmann JS, Luan J, Vandenput L, et al: Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile. Nat Genet. 2011, 43 (8): 753-760. 710.1038/ng.1866.PubMedCentralCrossRefPubMed
37.
Vassy JL, Shrader P, Yang Q, Liu T, Yesupriya A, Chang MH, Dowling NF, Ned RM, Dupuis J, Florez JC, et al: Genetic associations with metabolic syndrome and its quantitative traits by race/ethnicity in the United States. Metab Syndr Relat Disord. 2011, 9 (6): 475-482. 10.1089/met.2011.0021.PubMedCentralCrossRefPubMed
38.
Sjogren M, Lyssenko V, Jonsson A, Berglund G, Nilsson P, Groop L, Orho-Melander M: The search for putative unifying genetic factors for components of the metabolic syndrome. Diabetologia. 2008, 51 (12): 2242-2251. 10.1007/s00125-008-1151-4.CrossRefPubMed
39.
Tonjes A, Scholz M, Loeffler M, Stumvoll M: Association of Pro12Ala polymorphism in peroxisome proliferator-activated receptor gamma with Pre-diabetic phenotypes: meta-analysis of 57 studies on nondiabetic individuals. Diabetes Care. 2006, 29 (11): 2489-2497. 10.2337/dc06-0513.CrossRefPubMed
40.
Passaro A, Dalla Nora E, Marcello C, Di Vece F, Morieri ML, Sanz JM, Bosi C, Fellin R, Zuliani G: PPARgamma Pro12Ala and ACE ID polymorphisms are associated with BMI and fat distribution, but not metabolic syndrome. Cardiovasc Diabetol. 2011, 10: 112-10.1186/1475-2840-10-112.PubMedCentralCrossRefPubMed
41.
Chasman DI, Pare G, Mora S, Hopewell JC, Peloso G, Clarke R, Cupples LA, Hamsten A, Kathiresan S, Malarstig A, et al: Forty-three loci associated with plasma lipoprotein size, concentration, and cholesterol content in genome-wide analysis. PLoS Genet. 2009, 5 (11): e1000730-10.1371/journal.pgen.1000730.PubMedCentralCrossRefPubMed
42.
Timpson NJ, Lawlor DA, Harbord RM, Gaunt TR, Day IN, Palmer LJ, Hattersley AT, Ebrahim S, Lowe GD, Rumley A, et al: C-reactive protein and its role in metabolic syndrome: mendelian randomisation study. Lancet. 2005, 366 (9501): 1954-1959. 10.1016/S0140-6736(05)67786-0.CrossRefPubMed
43.
Rafiq S, Melzer D, Weedon MN, Lango H, Saxena R, Scott LJ, Palmer CN, Morris AD, McCarthy MI, Ferrucci L, et al: Gene variants influencing measures of inflammation or predisposing to autoimmune and inflammatory diseases are not associated with the risk of type 2 diabetes. Diabetologia. 2008, 51 (12): 2205-2213. 10.1007/s00125-008-1160-3.PubMedCentralCrossRefPubMed
44.
Davey Smith G, Ebrahim S: ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?. Int J Epidemiol. 2003, 32 (1): 1-22. 10.1093/ije/dyg070.CrossRef
45.
Yoshiuchi I: Evidence of selection at insulin receptor substrate-1 gene loci. Acta Diabetol. 2012, 15: 15.
46.
Heard-Costa N, Zillikens MC, Monda KL, Johansson A, Harris TB, Fu M, Haritunians T, Feitosa MF, Aspelund T, Eiriksdottir G, et al: NRXN3 is a novel locus for waist circumference: a genome-wide association study from the CHARGE Consortium. PLoS Genet. 2009, 5 (6): e1000539-10.1371/journal.pgen.1000539.PubMedCentralCrossRefPubMed
47.
Dehghan A, Dupuis J, Barbalic M, Bis JC, Eiriksdottir G, Lu C, Pellikka N, Wallaschofski H, Kettunen J, Henneman P, et al: Meta-analysis of genome-wide association studies in >80 000 subjects identifies multiple loci for C-reactive protein levels. Circulation. 2011, 123 (7): 731-738. 10.1161/CIRCULATIONAHA.110.948570.PubMedCentralCrossRefPubMed
48.
Jee SH, Sull JW, Lee JE, Shin C, Park J, Kimm H, Cho EY, Shin ES, Yun JE, Park JW, et al: Adiponectin concentrations: a genome-wide association study. Am J Hum Genet. 2010, 87 (4): 545-552. 10.1016/j.ajhg.2010.09.004.PubMedCentralCrossRefPubMed
49.
Kooner JS, Chambers JC, Aguilar-Salinas CA, Hinds DA, Hyde CL, Warnes GR, Gomez Perez FJ, Frazer KA, Elliott P, Scott J, et al: Genome-wide scan identifies variation in MLXIPL associated with plasma triglycerides. Nat Genet. 2008, 40 (2): 149-151. 10.1038/ng.2007.61.CrossRefPubMed
50.
Pollin TI, Damcott CM, Shen H, Ott SH, Shelton J, Horenstein RB, Post W, McLenithan JC, Bielak LF, Peyser PA, et al: A null mutation in human APOC3 confers a favorable plasma lipid profile and apparent cardioprotection. Science. 2008, 322 (5908): 1702-1705. 10.1126/science.1161524.PubMedCentralCrossRefPubMed
Metadata
Title
Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study
Authors
Cécile M Povel
Jolanda MA Boer
N Charlotte Onland-Moret
Martijn ET Dollé
Edith JM Feskens
Yvonne T van der Schouw
Publication date
01-12-2012
Publisher
BioMed Central
Published in
Cardiovascular Diabetology / Issue 1/2012
Electronic ISSN: 1475-2840
DOI
https://doi.org/10.1186/1475-2840-11-133

Other articles of this Issue 1/2012

Cardiovascular Diabetology 1/2012 Go to the issue

Study protocol

Detecting DNA synthesis of neointimal formation after catheter balloon injury in GK and in Wistar rats: using 5-ethynyl-2'-deoxyuridine

Original investigation

ROCK inhibitor fasudil attenuated high glucose-induced MCP-1 and VCAM-1 expression and monocyte-endothelial cell adhesion

Review

Mammalian target of rapamycin signaling in diabetic cardiovascular disease

Review

Acute and chronic animal models for the evaluation of anti-diabetic agents

Original investigation

Previous gestational diabetes is independently associated with increased carotid intima-media thickness, similarly to metabolic syndrome – a case control study

Original investigation

Zinc-induced cardiomyocyte relaxation in a rat model of hyperglycemia is independent of myosin isoform

ACC 2024 Congress Coverage

Cardiology Video

Highlights from the ACC 2024 Congress

Watch now

Watch official videos from the ACC congress summarizing key highlights from the last year in heart failure, cardiomyopathies, valvular disease, pulmonary vascular disease, and pediatric cardiology.

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits