Diagnostics for Pleiotropy in Mendelian Randomization Studies: Global and Individual Tests for Direct Effects

Abstract

Diagnosing pleiotropy is critical for assessing the validity of Mendelian randomization (MR) analyses. The popular MR-Egger method evaluates whether there is evidence of bias-generating pleiotropy among a set of candidate genetic instrumental variables. In this article, we propose a statistical method-global and individual tests for direct effects (GLIDE)-for systematically evaluating pleiotropy among the set of genetic variants (e.g., single nucleotide polymorphisms (SNPs)) used for MR. As a global test, simulation experiments suggest that GLIDE is nearly uniformly more powerful than the MR-Egger method. As a sensitivity analysis, GLIDE is capable of detecting outliers in individual variant..