Investigating the causal relationships between mental and physical health outcomes using Mendelian randomization

Mendelian Randomization (MR) is a statistical genetics approach that allows inferring causal relationships between human traits and health outcomes using genetic variants as instrumental variables. Specifically, 2-sample MR... [ view full abstract ]

Mendelian Randomization (MR) is a statistical genetics approach that allows inferring causal relationships between human traits and health outcomes using genetic variants as instrumental variables. Specifically, 2-sample MR analysis utilizes genetic effects on the exposure and the outcome to infer the exposure-outcome causal relationship. The effects of genetic variants on the exposure and the outcome can be estimated with standard genetic association analysis and are often available from existing genome-wide association studies (GWAS). With publicly available GWAS summary results for a wide range of human traits, 2-sample MR analysis enabled us to comprehensively investigate the causal relationships between human traits and health outcomes. Here, we utilized 95 publicly available GWAS summary results and UK Biobank to investigate the causal relationships between human traits and mental and physical health outcomes. We focused on the causal relationship between psychiatric disorders and physical health outcomes, including schizophrenia, bipolar disorder, major depression, autism spectrum disorder, autoimmune disorders, coronary artery disease, diabetes, etc. We also investigated the effects of complex traits, such as height, BMI, blood lipids, brain imaging, personality, on health outcomes. Multiple methods were used to detect and control for potential pleiotropic biases in the MR analysis, including modified Q and Q' test, Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test, Multivariable MR, MR-Egger regression, weighted median-based MR estimator, and weighted mode-based MR estimator. We also conducted bi-directional MR analysis to elucidate the causal relationship for given pairs of traits and health outcomes. Our analysis highlighted the complex causal relationships between mental and physical health outcomes.