An iterative approach to detect pleiotropy and perform Mendelian Randomization analysis using GWAS summary statistics.

ABSTRACT:

Motivation

The overall association evidence of a genetic variant with multiple traits can be evaluated by cross-phenotype association analysis using summary statistics from genome-wide association studies. Further dissecting the association pathways from a variant to multiple traits is important to understand the biological causal relationships among complex traits.

Results

Here, we introduce a flexible and computationally efficient Iterative Mendelian Randomization and Pleiotropy (IMRP) approach to simultaneously search for horizontal pleiotropic variants and estimate causal effect. Extensive simulations and real data applications suggest that IMRP has similar or better performance than existing Mendelian Randomization methods for both causal effect estimation and pleiotrop

SUBMITTER: Zhu X 

PROVIDER: S-EPMC8208738 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature