Leveraging pleiotropy for joint analysis of genome-wide association studies with per trait interpretations.

ABSTRACT: We introduce pleiotropic association test (PAT) for joint analysis of multiple traits using genome-wide association study (GWAS) summary statistics. The method utilizes the decomposition of phenotypic covariation into genetic and environmental components to create a likelihood ratio test statistic for each genetic variant. Though PAT does not directly interpret which trait(s) drive the association, a per trait interpretation of the omnibus p-value is provided through an extension to the meta-analysis framework, m-values. In simulations, we show PAT controls the false positive rate, increases statistical power, and is robust to model misspecifications of genetic effect. Additionally, simulations comparing PAT to three multi-trait methods, HIPO, MTAG, and ASSET, show PAT identified 15.3% mor

SUBMITTER: Taraszka K 

PROVIDER: S-EPMC9671458 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature