Integrative Mendelian randomization for detecting exposure-by-group interactions using group-specific and combined summary statistics.

ABSTRACT: Interactions between risk factors and covariate-defined groups are commonly observed in complex diseases. Existing methods for detecting interactions typically require individual-level data. The data availability and the measurements of risk exposures and covariates often limit the power and applicability in assessing interactions. To address these limitations, we propose int2MR, an integrative Mendelian randomization (MR) method that leverages GWAS summary statistics on exposure traits and group-separated and/or combined GWAS statistics on outcome traits. The int2MR can assess a broad range of risk exposure effects on diseases and traits, revealing interactions unattainable with incomplete or limited individual-level data. Simulation studies demonstrate that int2MR effectively controls ty

SUBMITTER: Xu K 

PROVIDER: S-EPMC12440225 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature