Abstract
OBJECTIVE: Gout, common metabolic disorders, have poorly understood links with blood metabolites. Exploring these relationships could enhance clinical prevention and treatment strategies. METHODS: We applied bidirectional two-sample Mendelian randomization (MR) analysis, using data from a genome-wide association (GWAS) study of 486 blood metabolites. Gout data was obtained from FinnGen R8 (7461 gout and 221,323 control cases). We implemented the inverse variance-weighted (IVW) method for main analytical approach. Extensive heterogeneity, pleiotropy tests, leave-one-out analysis, and reverse MR were conducted to validate the robustness of our findings. Both Bonferroni and False Discovery Rate (FDR) corrections were used to adjust for multiple comparisons, ensuring stringent validation of our results. RESULTS: Initial MR identified 31 candidate metabolites with potential genetic associations to gout. Following rigorous sensitivity analysis, 23 metabolites as potential statistical significance after final confirmation. These included metabolites enhancing gout risk such as X-11529 (OR = 1.225, 95% CI 1.112-1.350, P < 0.001), as well as others like piperine and stachydrine, which appeared to confer protective effects. The analysis was strengthened by reverse MR analysis. Additionally, an enrichment analysis was conducted, suggesting that 1-methylxanthine may be involved in the metabolic process of gout through the caffeine metabolism pathway. CONCLUSION: Identifying causal metabolites offers new insights into the mechanisms influencing gout, suggesting pathways for future research and potential therapeutic targets.