Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials. Author summary Genome-wide association studies (GWAS) established numerous associations between genetic variants and human traits. The anonymized summary of GWAS results is generally made publicly available to the scientific community and can be explored further. Amongst the many possible secondary analyses, one is to study the effect of a genetic variant on several traits (multi-trait GWAS) rather than a unique trait. We compared several tests to conduct multi-trait GWAS on simulated and real data. We detected 322 new associations that were not previously reported by standard univariate GWAS. We then detected clusters of genetic variants having a similar effect across several traits. Focusing on two subsets of immunity and metabolism traits, we demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster and success of drug targets in randomized controlled trials. We propose this method for improving the functional interpretation of GWAS results.
【초록키워드】 Randomized controlled trials, Immunity, variant, variants, metabolism, Genome-wide association studies, Interpretation, Cluster, drug target, phenotype, Scientific community, genetic variants, mechanisms, Genetic variant, GWAS, Integrative analysis, disease, association, genetic associations, genetic association, Phenotypes, profiles, GWASs, traits, Secondary analyses, common variants, biological pathways, breakdown, gene cluster, GWAS summary statistics, genetic architecture, reported, functional, unique, subset, mapped, biological pathway, Focusing, 【제목키워드】 variant, disease, mechanism,