Consistent Directions of Effect for Established Type 2 Diabetes Risk Variants Across Populations: The Population Architecture using Genomics and Epidemiology (PAGE) Consortium

Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, USA.
Diabetes (Impact Factor: 8.1). 04/2012; 61(6):1642-7. DOI: 10.2337/db11-1296
Source: PubMed


Common genetic risk variants for type 2 diabetes (T2D) have primarily been identified in populations of European and Asian ancestry. We tested whether the direction of association with 20 T2D risk variants generalizes across six major racial/ethnic groups in the U.S. as part of the Population Architecture using Genomics and Epidemiology Consortium (16,235 diabetes case and 46,122 control subjects of European American, African American, Hispanic, East Asian, American Indian, and Native Hawaiian ancestry). The percentage of positive (odds ratio [OR] >1 for putative risk allele) associations ranged from 69% in American Indians to 100% in European Americans. Of the nine variants where we observed significant heterogeneity of effect by racial/ethnic group (P(heterogeneity) < 0.05), eight were positively associated with risk (OR >1) in at least five groups. The marked directional consistency of association observed for most genetic variants across populations implies a shared functional common variant in each region. Fine-mapping of all loci will be required to reveal markers of risk that are important within and across populations.

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    • "The SNPs included in the study are CDKN2A/B (rs10811661), NOTCH (rs10923931), HHEX-IDE (rs111875), CDC123/CAMK1D (rs12779790), SLC30A8 (rs13266634), PPARG (rs1801282), KCNQ1 (rs2237895), IGFBP2 (rs4402960), ADAMTS9 (rs4607103), CDKAL1 (rs4712523), THADA (rs7578597), TCFL2 (rs7903146), TSPAN8-LGRS (rs7961581), FTO (rs8050136), and JAZF1 (rs864745). All SNPs were previously associated with T2D (as of early 2009) in candidate gene and genome-wide association studies and were subsequently analyzed for single-SNP associations with T2D in a large meta-analysis by the PAGE study [22]. The 15 SNPs tested for gene–environment interactions were either accessed from existing data in the Genetic NHANES database or directly genotyped by EAGLE, one of the four large population-based studies of the PAGE I network, by using Sequenom or Illumina BeadXpress. "
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    ABSTRACT: Background Both environmental and genetic factors impact type 2 diabetes (T2D). To identify such modifiers, we genotyped 15 T2D-associated variants from genome-wide association studies (GWAS) in 6,414 non-Hispanic whites, 3,073 non-Hispanic blacks, and 3,633 Mexican American participants from the National Health and Nutrition Examination Surveys (NHANES) and evaluated interactions between these variants and carbohydrate intake and fiber intake. Results We calculated a genetic risk score (GRS) with the 15 SNPs. The odds ratio for T2D with each GRS point was 1.10 (95% CI: 1.05-1.14) for non-Hispanic whites, 1.07 (95% CI: 1.02-1.13) for non-Hispanic blacks, and 1.11 (95% CI: 1.06-1.17) for Mexican Americans. We identified two gene-carbohydrate interactions (P < 0.05) in non-Hispanic whites (with CDKAL1 rs471253 and FTO rs8050136), two in non-Hispanic blacks (with IGFBP2 rs4402960 and THADA rs7578597), and two in Mexican Americans (with NOTCH2 rs1092398 and TSPAN8-LGRS rs7961581). We found three gene-fiber interactions in non-Hispanic whites (with ADAMT59 rs4607103, CDKN2A/2B rs1801282, and FTO rs8050136), two in non-Hispanic blacks (with ADAMT59 rs4607103 and THADA rs7578597), and two in Mexican Americans (with THADA rs7578597 and TSPAN8-LGRS rs796158) at the P < 0.05 level. Interactions between the GRS and nutrients failed to reach significance in all the racial/ethnic groups. Conclusion Our results suggest that dietary carbohydrates and fiber may modify T2D-associated variants, highlighting the importance of dietary nutrients in predicting T2D risk.
    BMC Genetics 06/2014; 15(1):69. DOI:10.1186/1471-2156-15-69 · 2.40 Impact Factor
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    ABSTRACT: Genome wide association studies (GWAS) have transformed the study of heritable factors influencing complex diseases such as type 2 diabetes (T2D), with the current tally of established risk loci approaching 70. Each of these loci has the potential to offer novel insights into the biology of this disease, and opportunities for clinical exploitation. However, the complexity of this condition has often frustrated efforts to achieve these functional and translational advances. This review describes progress made over the past year to expand genome wide association studies, to characterize the mechanisms through which diabetes risk loci operate, and to define the processes involved in diabetes predisposition.
    Current Cardiovascular Risk Reports 02/2013; 7(1). DOI:10.1007/s12170-012-0281-x
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    ABSTRACT: Using a phenome-wide association study (PheWAS) approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE) network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA), African Americans (AA), Hispanics/Mexican-Americans, and Asian/Pacific Islanders) in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA) a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high-density lipoprotein cholesterol levels in EA) had multiple potentially novel PheWAS associations, with hypertension related phenotypes in AA and with serum calcium levels and coronary artery disease phenotypes in EA. PheWAS identifies associations for hypothesis generation and exploration of the genetic architecture of complex traits.
    PLoS Genetics 01/2013; 9(1):e1003087. DOI:10.1371/journal.pgen.1003087 · 7.53 Impact Factor
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