Dataset Information

Transethnic insight into the genetics of glycaemic traits: fine-mapping results from the Population Architecture using Genomics and Epidemiology (PAGE) consortium.

ABSTRACT:

Aims/hypothesis

Elevated 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.

Methods

A 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.

Results

Previously 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/interpretation

These 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 availability

The 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.

SUBMITTER: Bien SA

PROVIDER: S-EPMC5918310 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

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.