TY - JOUR T1 - A bivariate genome-wide approach to metabolic syndrome: STAMPEED consortium. JF - Diabetes Y1 - 2011 A1 - Kraja, Aldi T A1 - Vaidya, Dhananjay A1 - Pankow, James S A1 - Goodarzi, Mark O A1 - Assimes, Themistocles L A1 - Kullo, Iftikhar J A1 - Sovio, Ulla A1 - Mathias, Rasika A A1 - Sun, Yan V A1 - Franceschini, Nora A1 - Absher, Devin A1 - Li, Guo A1 - Zhang, Qunyuan A1 - Feitosa, Mary F A1 - Glazer, Nicole L A1 - Haritunians, Talin A1 - Hartikainen, Anna-Liisa A1 - Knowles, Joshua W A1 - North, Kari E A1 - Iribarren, Carlos A1 - Kral, Brian A1 - Yanek, Lisa A1 - O'Reilly, Paul F A1 - McCarthy, Mark I A1 - Jaquish, Cashell A1 - Couper, David J A1 - Chakravarti, Aravinda A1 - Psaty, Bruce M A1 - Becker, Lewis C A1 - Province, Michael A A1 - Boerwinkle, Eric A1 - Quertermous, Thomas A1 - Palotie, Leena A1 - Jarvelin, Marjo-Riitta A1 - Becker, Diane M A1 - Kardia, Sharon L R A1 - Rotter, Jerome I A1 - Chen, Yii-Der Ida A1 - Borecki, Ingrid B KW - Adult KW - Aged KW - Female KW - Genetic Predisposition to Disease KW - Genome-Wide Association Study KW - Genotype KW - Humans KW - Male KW - Meta-Analysis as Topic KW - Metabolic Syndrome KW - Middle Aged KW - Phenotype KW - Polymorphism, Single Nucleotide AB -

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.

VL - 60 IS - 4 U1 - http://www.ncbi.nlm.nih.gov/pubmed/21386085?dopt=Abstract ER -