A Novel Method for Mendelian Randomization Analyses With Pleiotropy and Linkage Disequilibrium in Genetic Variants From Individual Data - Wang, Yuquan; Li, Tingting; Fu, Liwan; Yang, Siqian; Hu, Yue-Qing (Frontiers in Genetics, 2021)
Mendelian randomization takes use of genetic variants as instrumental variables to eliminate the influence induced by unknown confounders on causal estimation in epidemiology studies. However, with the soaring genetic variants identified in genome-wide association studies, the pleiotropy and linkage disequilibrium in genetic variants are unavoidable and may produce severe bias in causal inference. In this study, by modelling the pleiotropic effect as a normally distributed random effect, we propose a novel mixed-effects regression model-based method PLDMR, pleiotropy and linkage disequilibrium adaptive Mendelian randomization, which takes linkage disequilibrium into account and also corrects for the pleiotropic effect in causal effect estimation and statistical inference. We conduct voluminous simulation studies to evaluate the performance of the proposed and existing methods. Simulation results illustrate the validity and advantage of the novel method, especially in the case of linkage disequilibrium and unbalanced pleiotropic effect, compared with other methods. In addition, by applying this novel method to the data on Atherosclerosis Risk in Communications Study, we conclude that body mass index is a potential risk factor of and has a significant causal effect on systolic blood pressure. The novel method is implemented in R and the corresponding R code is provided for free download.