Causal association between 637 human metabolites and ovarian cancer: a mendelian randomization study

Current evidence suggests a significant association between metabolites and ovarian cancer (OC); however, the causal relationship between the two remains unclear. This study employs Mendelian randomization (MR) to investigate the causal effects between different metabolites and OC. In this study, a total of 637 metabolites were selected as the exposure variables from the Genome-wide Association Study (GWAS) database ( http://gwas.mrcieu.ac.uk/datasets/ ). The OC related GWAS dataset (ieu-b-4963) was chosen as the outcome variable. R software and the TwoSampleMR package were utilized for the analysis in this study. MR analysis employed the inverse variance-weighted method (IVW), MR-Egger and weighted median (WM) for regression fitting, taking into consideration potential biases caused by linkage disequilibrium and weak instrument variables. Metabolites that did not pass the tests for heterogeneity and horizontal pleiotropy were considered to have no significant causal effect on the outcome. Steiger's upstream test was used to determine the causal direction between the exposure and outcome variables. The results from IVW analysis revealed that a total of 31 human metabolites showed a significant causal effect on OC (P