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, modelling the pleiotropic effect as a normally distributed random effect, we proposed 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. In addition, applying this novel method to the data of Atherosclerosis Risk in Communications Study, we conclude that body mass index is a potential risk factor of and has a significant causal effect on the systolic blood pressure.
嘉宾简介 About the Speaker
胡跃清，复旦大学生物统计研究所PI，博士，教授，博士生导师。长期从事统计学基础理论研究和应用统计研究工作，在John Wiley & Sons 出版著作《Statistical DNA Forensics: Theory, Methods and Computation》，研究论文发表在统计、生物、医学类SCI期刊上，当前的研究兴趣是多表型数据关联分析、因果推断、多组学数据整合分析等。