Abstract
To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 234-244 |
| Number of pages | 11 |
| Journal | Nature Genetics |
| Volume | 46 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2014 |
Bibliographical note
Funding Information:Funding for the research undertaken in this study has been received from the following: the Canadian Institutes of Health Research; the European Commission (ENGAGE FP7 HEALTH-F4-2007-201413); the Medical Research Council UK (G0601261); the Mexico Convocatoria (SSA/IMMS/ISSSTE-CONACYT 2012-2, clave 150352, IMSS R-2011-785-018 and CONACYT Salud-2007-C01-71068); the US National Institutes of Health (DK062370, HG000376, DK085584, DK085545, DK073541 and DK085501); and the Wellcome Trust (WT098017, WT090532, WT090367, WT098381, WT081682 and WT085475). We acknowledge the many colleagues who contributed to collection and phenotypic characterization of the clinical samples and the genotyping and analysis of the GWAS data, full details of which are provided in the contributing consortia papers5,11,13,15. We also thank those individuals who agreed to participate in this study.
