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Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study

Jia Y. Wan, Deborah L. Goodman, Emileigh L. Willems, Alexis R. Freedland, Trina M. Norden-Krichmar, Stephanie A. Santorico, Karen L. Edwards, Eric Boerwinkle, John Buse, Ralph DeFronzo,
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Published: 1 June 2021
Diabetology & Metabolic Syndrome , Volume 13, pp 1-15; doi:10.1186/s13098-021-00670-3

Abstract: Background To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. Methods Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina’s Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping. Results Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects. Conclusions This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.
Keywords: Metabolic syndrome / Genetic epidemiology / Family studies / Quantitative trait loci / Linkage

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