PsyRiskMR: A Comprehensive Resource for Identifying Psychiatric Disorder Risk Factors Through Mendelian Randomization.

BACKGROUND

Psychiatric disorders pose an enormous economic and emotional burden on individuals, their families, and society. Given that the current analysis of the pathogenesis of psychiatric disorders remains challenging and time consuming, elucidating modifiable risk factors is crucial for the diagnosis and management of psychiatric disorders. However, inferring causal risk factors for these disorders from disparate data sources is challenging due to constraints in data collection and analytical capabilities.

METHODS

By leveraging the largest available genome-wide association study summary statistics for 10 psychiatric disorders and compiling an extensive set of risk factor datasets, including 71 psychiatric disorder-specific phenotypes, 3935 brain imaging traits, and over 30 brain tissue/cell-specific quantitative trait loci datasets (covering 6 types of quantitative trait loci), we performed comprehensive Mendelian randomization analyses to explore the potential causal links between various exposures and psychiatric outcomes using genetic variants as instrumental variables.

RESULTS

After Bonferroni correction for multiple testing, we identified multiple potential risk factors for psychiatric disorders (including phenotypic-level and molecular-level traits) and provided robust Mendelian randomization evidence that supports these associations utilizing rigorous sensitivity analyses and colocalization analyses. Furthermore, we have established the PsyRiskMR database (http://bioinfo.ahu.edu.cn/PsyRiskMR/), which serves as an interactive platform for showcasing and querying risk factors for psychiatric disorders.

CONCLUSIONS

Our study offers a user-friendly PsyRiskMR database for the research community to browse, search, and download all Mendelian randomization results, potentially revealing new insights into the biological etiology of psychiatric disorders.