Genome-wide association studies (GWAS) have identified hundreds of loci associated with cardio metabolic traits. It is becoming increasingly evident that association signals for these traits overlap within these loci. However, the extent to which these overlapping association signals demonstrate complex patterns of allelic heterogeneity between traits that do or do not follow epidemiological expectations has not been fully evaluated. To address this challenge, the Cross-Consortia Pleiotropy Group was formed and it aims at investigating patterns of multi-trait associations across the human genome for cardio-metabolic traits and disease outcomes. In the present study, we investigated the architecture of 151 genomic regions associated with more than one cardio-metabolic trait. We considered published associated SNPs (thru Sep 2012) from meta-analyses of genome-wide association studies (GWAS) in Europeans for 20 quantitative traits (including blood pressure, glycaemic, anthropometric and lipids traits) and two disease phenotypes (T2D and hypertension), from six cardio-metabolic trait consortia. We tested the overlap of 374 autosomal SNPs representing 438 cardio-metabolic SNP-trait associations. We identified 151 regions associated with multiple traits, defined as sets of adjacent variants located less than 500kb apart. We tested the independence of variants within regions through approximate conditional analysis implemented in GCTA (Genome-wide Complex Trait Analysis) software using three different reference cohorts: PIVUS (Prospective Investigation of the Vasculature in Uppsala Seniors), FHS (Framingham Heart Study) and GOYA Study (Genetics of Overweight Young Adults).
Dissecting the genetic architecture of loci with established effects on multiple cardiometabolic phenotypes and type 2 diabetes
MARULLO, Letizia
Primo
;SCAPOLI, Chiara;
2014
Abstract
Genome-wide association studies (GWAS) have identified hundreds of loci associated with cardio metabolic traits. It is becoming increasingly evident that association signals for these traits overlap within these loci. However, the extent to which these overlapping association signals demonstrate complex patterns of allelic heterogeneity between traits that do or do not follow epidemiological expectations has not been fully evaluated. To address this challenge, the Cross-Consortia Pleiotropy Group was formed and it aims at investigating patterns of multi-trait associations across the human genome for cardio-metabolic traits and disease outcomes. In the present study, we investigated the architecture of 151 genomic regions associated with more than one cardio-metabolic trait. We considered published associated SNPs (thru Sep 2012) from meta-analyses of genome-wide association studies (GWAS) in Europeans for 20 quantitative traits (including blood pressure, glycaemic, anthropometric and lipids traits) and two disease phenotypes (T2D and hypertension), from six cardio-metabolic trait consortia. We tested the overlap of 374 autosomal SNPs representing 438 cardio-metabolic SNP-trait associations. We identified 151 regions associated with multiple traits, defined as sets of adjacent variants located less than 500kb apart. We tested the independence of variants within regions through approximate conditional analysis implemented in GCTA (Genome-wide Complex Trait Analysis) software using three different reference cohorts: PIVUS (Prospective Investigation of the Vasculature in Uppsala Seniors), FHS (Framingham Heart Study) and GOYA Study (Genetics of Overweight Young Adults).File | Dimensione | Formato | |
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