MRBEE: A novel bias-corrected multivariable Mendelian Randomization method.

Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes using summary data from genome-wide association studies (GWAS). Since GWAS summary statistics are subject to estimation errors, most existing MR approaches suffer from the error-in-variable bias, whose scale and direction are influenced by weak instrumental variables and GWAS sample overlap, respectively. We introduce MRBEE (MR using Bias-corrected Estimating Equation), a novel multivariable MR method capable of simultaneously removing error-in-variable bias and identifying horizontal pleiotropy. In simulations, we showed that MRBEE is the only method capable of effectively removing error-in-variable bias with weak instrumental variables and arbitrary sample overlap. In two independent real data analyses, we discovered that the causal effect of BMI on coronary artery disease risk is entirely mediated by blood pressure, and that existing MR methods may underestimate the causal effect of cannabis use disorder on schizophrenia risk compared to MRBEE. MRBEE holds significant potential for advancing genetic research by providing a valuable tool to study causality between multiple risk factors and disease outcomes, particularly as a large number of GWAS summary statistics become publicly available.