A0792
Title: Mendelian randomization identifying and estimating causal heterogeneity effect using summary statistics
Authors: Xingjie Shi - East China Normal University (China) [presenting]
Abstract: Mendelian randomization (MR) employs genetic variants as instrumental variables to investigate the causal effect of exposure on an outcome using summary statistics from genome-wide association studies. However, conventional MR approaches can be prone to omitted variable bias when the causal effect is moderated by an environmental variable. CHESS is introduced, a novel method aimed at assessing the causal effect of exposure on outcome while also examining how this effect is altered by a given environmental factor. Through simulations, it is shown that CHESS is more effective in avoiding false positives resulting from causal heterogeneity effects compared to existing methods. When applied to traits studied in recent GWAS research, CHESS reveals diverse causal relationships between males and females that are supported by existing literature while also minimizing the identification of less plausible heterogeneity.
