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Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.

ABSTRACT: 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.

SUBMITTER: Haiman CA

PROVIDER: S-EPMC3357304 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature

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Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.

Haiman Christopher A CA Fesinmeyer Megan D MD Spencer Kylee L KL Buzková Petra P Voruganti V Saroja VS Wan Peggy P Haessler Jeff J Franceschini Nora N Monroe Kristine R KR Howard Barbara V BV Jackson Rebecca D RD Florez Jose C JC Kolonel Laurence N LN Buyske Steven S Goodloe Robert J RJ Liu Simin S Manson Joann E JE Meigs James B JB Waters Kevin K Mukamal Kenneth J KJ Pendergrass Sarah A SA Shrader Peter P Wilkens Lynne R LR Hindorff Lucia A LA Ambite Jose Luis JL North Kari E KE Peters Ulrike U Crawford Dana C DC Le Marchand Loic L Pankow James S JS

Diabetes 20120403 6

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 a ...[more]

PMID: 22474029

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Project description:Aims/hypothesisElevated levels of fasting glucose and fasting insulin in non-diabetic individuals are markers of dysregulation of glucose metabolism and are strong risk factors for type 2 diabetes. Genome-wide association studies have discovered over 50 SNPs associated with these traits. Most of these loci were discovered in European populations and have not been tested in a well-powered multi-ethnic study. We hypothesised that a large, ancestrally diverse, fine-mapping genetic study of glycaemic traits would identify novel and population-specific associations that were previously undetectable by European-centric studies.MethodsA multiethnic study of up to 26,760 unrelated individuals without diabetes, of predominantly Hispanic/Latino and African ancestries, were genotyped using the Metabochip. Transethnic meta-analysis of racial/ethnic-specific linear regression analyses were performed for fasting glucose and fasting insulin. We attempted to replicate 39 fasting glucose and 17 fasting insulin loci. Genetic fine-mapping was performed through sequential conditional analyses in 15 regions that included both the initially reported SNP association(s) and denser coverage of SNP markers. In addition, Metabochip-wide analyses were performed to discover novel fasting glucose and fasting insulin loci. The most significant SNP associations were further examined using bioinformatic functional annotation.ResultsPreviously reported SNP associations were significantly replicated (p ≤ 0.05) in 31/39 fasting glucose loci and 14/17 fasting insulin loci. Eleven glycaemic trait loci were refined to a smaller list of potentially causal variants through transethnic meta-analysis. Stepwise conditional analysis identified two loci with independent secondary signals (G6PC2-rs477224 and GCK-rs2908290), which had not previously been reported. Population-specific conditional analyses identified an independent signal in G6PC2 tagged by the rare variant rs77719485 in African ancestry. Further Metabochip-wide analysis uncovered one novel fasting insulin locus at SLC17A2-rs75862513.Conclusions/interpretationThese findings suggest that while glycaemic trait loci often have generalisable effects across the studied populations, transethnic genetic studies help to prioritise likely functional SNPs, identify novel associations that may be population-specific and in turn have the potential to influence screening efforts or therapeutic discoveries.Data availabilityThe summary statistics from each of the ancestry-specific and transethnic (combined ancestry) results can be found under the PAGE study on dbGaP here: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000356.v1.p1.

Project description:By relating hundreds of thousands of genotypes to only a few phenotypes, mostly in individuals of one ancestry, genome-wide association (GWA) studies are identifying a rapidly growing number of associations. The Population Architecture using Genomics and Epidemiology (PAGE) Study is designed to further characterize the most promising variants along an epidemiological dimension that is substantial in its sample size, ethnic diversity, breadth of phenotypes, and exposures. PAGE includes scientists and population samples from large ongoing cohort studies: CALiCo (Causal Variants Across the Life Course, a consortium of ARIC, CARDIA, CHS, HCHS/SOL, Strong Heart Cohort Study, Strong Heart Family Study), EAGLE (Epidemiologic Architecture for Genes Linked to Environment, based on 3 National Health and Nutrition Examination Surveys (NHANES), MEC (Multiethnic Cohort) and WHI (Women's Health Initiative), with logistical and scientific support contributed by a Coordinating Center and the NHGRI Office of Population Genomics. These studies combined include over 270,000 participants, and populations represented include Asian Americans, African Americans, European Americans, Hispanic Americans, Native Hawaiians and American Indians. Health outcomes and traits of interest are prioritized, followed by replication of trait-genotype associations and generalization of their effects across population groups and environmental contexts. The first phase of genotyping focused on 901 high-profile SNPs having replicated associations with phenotypes related to diabetes, obesity, cardiovascular disease, lipids, cancers, menopause/menarche, inflammation and autoimmunity that are being genotyped in over 121,000 participants, as available for trait-specific analyses. SNP genotyping, quality control and population-specific association analyses are performed within each cohort, followed by meta-analyses using harmonized phenotypes and standardized analytic methods. The second phase of genotyping will be done using the Metabochip. The Metabochip is a custom large-scale (~200K SNPs) Illumina chip designed for association testing of several metabolic-related phenotypes. Genotyping will be performed at each study site and centralized analysis will be managed through the coordinating center. PAGE is generating 3 types of data: tier 1 (minimally curated phenotypes and analyses, all SNPs by all available phenotypes, used for Phenome-wide association study (PheWAS analysis)), tier 2 (carefully curated analyses of phenotypes available at only one of the four PAGE sites) and tier 3 (carefully curated phenotypes for multi-site analyses, data specifically generated for manuscripts). All tiers of data are submitted to the CC, where they undergo QC prior to submission to dbGaP.

Project description: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.

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Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.

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Consistent directions of effect for established type 2 diabetes risk variants across populations: the population architecture using Genomics and Epidemiology (PAGE) Consortium.

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