Analysis of Metabolic Syndrome Components in >15 000 African Americans Identifies Pleiotropic Variants Results from the Population Architecture Using Genomics and Epidemiology Study

Circulation: Cardiovascular Genetics

Volumn 7, Issue 4, 2014, Pages 505-513

  Carty, Cara L ^a   Bhattacharjee, Samsiddhi ^b   Haessler, Jeff ^b   Cheng, Iona ^b   Hindorff, Lucia A ^b   Aroda, Vanita ^b   Carlson, Christopher S ^b   Hsu, Chun Nan ^b   Wilkens, Lynne ^b   Liu, Simin ^b   Selvin, Elizabeth ^b   Jackson, Rebecca ^b   North, Kari E ^b   Peters, Ulrike ^b   Pankow, James S ^b   Chatterjee, Nilanjan ^b   Kooperberg, Charles ^b  

^a Fred Hutchinson Cancer Research Center   (United States)

^b NONE

Author keywords

African continental ancestry group; Genetic pleiotropy; Genetic variation; High density lipoprotein cholesterol; Hispanic Americans; Hyperglycemia; Metabolic syndrome

Indexed keywords

ADULT; AFRICAN AMERICAN; ARTICLE; BLACK PERSON; CARDIOMETABOLIC RISK; FEMALE; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOMICS; HISPANIC; HUMAN; HYPERGLYCEMIA; HYPERTENSION; MAJOR CLINICAL STUDY; MALE; METABOLIC SYNDROME X; OBESITY; PLEIOTROPY; POPULATION GENETICS; PRIORITY JOURNAL; SINGLE NUCLEOTIDE POLYMORPHISM; TRANSLATIONAL RESEARCH; AGED; ALLELE; ANALYSIS; BLOOD; GENE LOCUS; GENETIC PREDISPOSITION; GENETIC VARIATION; GENETICS; GENOTYPE; GLUCOSE BLOOD LEVEL; META ANALYSIS; MIDDLE AGED; ODDS RATIO; PHENOTYPE;

APOA5 PROTEIN, HUMAN; APOLIPOPROTEIN A; APOLIPOPROTEIN C-I, HUMAN; APOLIPOPROTEIN C1; CETP PROTEIN, HUMAN; CHOLESTEROL ESTER TRANSFER PROTEIN; GLUCOSE BLOOD LEVEL; HIGH DENSITY LIPOPROTEIN CHOLESTEROL; LIPOPROTEIN LIPASE; LPL PROTEIN, HUMAN; TCF7L2 PROTEIN, HUMAN; TRANSCRIPTION FACTOR 7 LIKE 2;

AFRICAN AMERICANS; AGED; ALLELES; APOLIPOPROTEIN C-I; APOLIPOPROTEINS A; BLOOD GLUCOSE; CHOLESTEROL ESTER TRANSFER PROTEINS; CHOLESTEROL, HDL; FEMALE; GENETIC LOCI; GENETIC PLEIOTROPY; GENETIC PREDISPOSITION TO DISEASE; GENETIC VARIATION; GENOMICS; GENOTYPE; HISPANIC AMERICANS; HUMANS; LIPOPROTEIN LIPASE; MALE; METABOLIC SYNDROME X; MIDDLE AGED; ODDS RATIO; PHENOTYPE; POLYMORPHISM, SINGLE NUCLEOTIDE; TRANSCRIPTION FACTOR 7-LIKE 2 PROTEIN;

EID: 84925633812     PISSN: 1942325X     EISSN: 19423268     Source Type: Journal    
DOI: 10.1161/CIRCGENETICS.113.000386     Document Type: Article

References (46)

1. Ballantyne CM, Hoogeveen RC, McNeill AM, Heiss G, Schmidt MI, Duncan BB, et al. Metabolic syndrome risk for cardiovascular disease and diabetes in the ARIC study. Int J Obes (Lond). 2008;32(suppl 2):S21-S24
2. Sattar N, McConnachie A, Shaper AG, Blauw GJ, Buckley BM, de Craen AJ, et al. Can metabolic syndrome usefully predict cardiovascular disease and diabetes? Outcome data from two prospective studies. Lancet. 2008;371:1927-1935
3. 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;288:2709-2716
4. Alberti KG, Zimmet P, Shaw J; IDF Epidemiology Task Force Consensus Group. The metabolic syndrome-A new worldwide definition. Lancet. 2005;366:1059-1062
5. 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;287:356-359
6. Huang PL. A comprehensive definition for metabolic syndrome. Dis Model Mech. 2009;2:231-237
7. Eckel RH, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2005;365:1415-1428
8. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C; American Heart Association; National Heart, Lung, and Blood Institute. 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;109:433-438
9. Terán-García M, Bouchard C. Genetics of the metabolic syndrome. Appl Physiol Nutr Metab. 2007;32:89-114
10. Zabaneh D, Chambers JC, Elliott P, Scott J, Balding DJ, Kooner JS. Heritability and genetic correlations of insulin resistance and component phenotypes in Asian Indian families using a multivariate analysis. Diabetologia. 2009;52:2585-2589
11. Bhattacharjee S, Rajaraman P, Jacobs KB, Wheeler WA, Melin BS, Hartge P, et al; GliomaScan Consortium. A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits. Am J Hum Genet. 2012;90:821-835
12. Voight BF, Kang HM, Ding J, Palmer CD, Sidore C, Chines PS, et al. The metabochip, a custom genotyping array for genetic studies of metabolic, cardiovascular, and anthropometric traits. PLoS Genet. 2012;8:e1002793
13. Matise TC, Ambite JL, Buyske S, Carlson CS, Cole SA, Crawford DC, et al; PAGE Study. The Next PAGE in understanding complex traits: design for the analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study. Am J Epidemiol. 2011;174:849-859
14. The ARIC Investigators. The Atherosclerosis Risk in Communities (ARIC) Study: design and objectives. Am J Epidemiol. 1989;129:687-702
15. Anderson GL, Manson J, Wallace R, Lund B, Hall D, Davis S, et al. Implementation of the Women's Health Initiative study design. Ann Epidemiol. 2003;13(suppl 9):S5-17
16. The Women's Health Initiative Study Group. Design of the Women's Health Initiative clinical trial and observational study. Control Clin Trials. 1998;19:61-109
17. 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;120:1640-1645
18. Genuth S, Alberti KG, Bennett P, Buse J, Defronzo R, Kahn R, et al; Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care. 2003;26:3160-3167
19. Buyske S, Wu Y, Carty CL, Cheng I, Assimes TL, Dumitrescu L, et al. Evaluation of the metabochip genotyping array in African Americans and implications for fine mapping of GWAS-identified loci: the PAGE study. PLoS One. 2012;7:e35651
20. Liu EY, Buyske S, Aragaki AK, Peters U, Boerwinkle E, Carlson C, et al. Genotype imputation of Metabochip SNPs using a study-specific reference panel of ~4,000 haplotypes in African Americans from the Women's Health Initiative. Genet Epidemiol. 2012;36:107-117
21. Patterson N, Price AL, Reich D. Population structure and eigenanalysis. PLoS Genet. 2006;2:e190
22. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904-909
23. R Development Core Team. A language and environment for statistical computing. 2008
24. Berglund G, Elmstähl S, Janzon L, Larsson SA. The Malmo Diet and Cancer Study. Design and feasibility. J Intern Med. 1993;233:45-51
25. Kahn R. Metabolic syndrome-what is the clinical usefulness? Lancet. 2008;371:1892-1893
26. Monda KL, North KE, Hunt SC, Rao DC, Province MA, Kraja AT. The genetics of obesity and the metabolic syndrome. Endocr Metab Immune Disord Drug Targets. 2010;10:86-108
27. Park YW, Zhu S, Palaniappan L, Heshka S, Carnethon MR, Heymsfield SB. The metabolic syndrome: prevalence and associated risk factor findings in the US population from the Third National Health and Nutrition Examination Survey, 1988-1994. Arch Intern Med. 2003;163:427-436
28. Joy T, Hegele RA. Genetics of metabolic syndrome: is there a role for phenomics? Curr Atheroscler Rep. 2008;10:201-208
29. 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;5:242-249
30. Zabaneh D, Balding DJ. A genome-wide association study of the metabolic syndrome in Indian Asian men. PLoS One. 2010;5:e11961
31. 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;60:1329-1339
32. Ng MC, Saxena R, Li J, Palmer ND, Dimitrov L, Xu J, et al. Transferability and fine mapping of type 2 diabetes loci in African Americans: the Candidate Gene Association Resource Plus Study. Diabetes. 2013;62:965-976
33. 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
34. Coram MA, Duan Q, Hoffmann TJ, Thornton T, Knowles JW, Johnson NA, et al. Genome-wide characterization of shared and distinct genetic components that influence blood lipid levels in ethnically diverse human populations. Am J Hum Genet. 2013;92:904-916
35. Orho-Melander M, Melander O, Guiducci C, Perez-Martinez P, Corella D, Roos C, et al. Common missense variant in the glucokinase regulatory protein gene is associated with increased plasma triglyceride and C-reactive protein but lower fasting glucose concentrations. Diabetes. 2008;57:3112-3121
36. Sparsø T, Andersen G, Nielsen T, Burgdorf KS, Gjesing AP, Nielsen AL, et al. The GCKR rs780094 polymorphism is associated with elevated fasting serum triacylglycerol, reduced fasting and OGTT-related insulinaemia, and reduced risk of type 2 diabetes. Diabetologia. 2008;51:70-75
37. Aulchenko YS, Ripatti S, Lindqvist I, Boomsma D, Heid IM, Pramstaller PP, et al; ENGAGE Consortium. Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts. Nat Genet. 2009;41:47-55
38. Smith EN, Chen W, Kähönen M, Kettunen J, Lehtimäki T, Peltonen L, et al. Longitudinal genome-wide association of cardiovascular disease risk factors in the Bogalusa heart study. PLoS Genet. 2010;6:e1001094
39. Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikäinen LP, et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet. 2012;44:269-276
40. Zemunik T, Boban M, Lauc G, Jankovic S, Rotim K, Vatavuk Z, et al. Genome-wide association study of biochemical traits in Korcula Island, Croatia. Croat Med J. 2009;50:23-33
41. Zeggini E, Weedon MN, Lindgren CM, Frayling TM, Elliott KS, Lango H, et al; Wellcome Trust Case Control Consortium (WTCCC). Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes. Science. 2007;316:1336-1341
42. Park YM, Province MA, Gao X, Feitosa M, Wu J, Ma D, et al. Longitudinal trends in the association of metabolic syndrome with 550 k singlenucleotide polymorphisms in the Framingham Heart Study. BMC Proc. 2009;3 Suppl 7:S116
43. Robinson WS. Ecological correlations and the behavior of individuals. Am Sociol Rev. 1950;15:351-357
44. Solovieff N, Cotsapas C, Lee PH, Purcell SM, Smoller JW. Pleiotropy in complex traits: challenges and strategies. Nat Rev Genet. 2013;14:483-495
45. Dumitrescu L, Carty CL, Taylor K, Schumacher FR, Hindorff LA, Ambite JL, et al. Genetic determinants of lipid traits in diverse populations from the population architecture using genomics and epidemiology (PAGE) study. PLoS Genet. 2011;7:e1002138
46. Sivakumaran S, Agakov F, Theodoratou E, Prendergast JG, Zgaga L, Manolio T, et al. Abundant pleiotropy in human complex diseases and traits. Am J Hum Genet. 2011;89:607-618.