From Genome to Clinic: Gut Microbiota's Influence on Hyperuricemia Risk Unveiled by Mendelian Randomization

To assess whether the gut microbiota and HUA could be causally related, we used summary statistics from the MiBioGen and FinnGen consortia to conduct a two-sample MR analysis. All of the analyses were carried out via two-sample MR analysis using R (version 4.3.1) and the R package for MR (version 0.5.7) . The R2 was calculated as follows: R2 =[2×Beta2×MAF×(1-MAF)]/[(2×Beta2×MAF×(1-MAF)+SE2×2×N×MAF×(1-MAF)]. When evaluating how strongly IVs and exposure relate to one another, we computed the F statistic using the formula F=R2×(N-1-k)/[(1-R2)×k], where R2 is the proportion of phenotypic variation described by SNPs and k is the number of SNPs included in the instrument . When the F statistic's threshold was more than 10, it was deemed statistically significant, meaning that weak instrumental bias had no impact on the causal relationship .Using the IVW method, we computed the MR estimate based on multiple IVs, with significance determined by the magnitude of the P value . Heterogeneity was examined using Cochran's Q test (considered significant at P<0.05). Furthermore, we utilized MR‒Egger, the weighted median, and MR-PRESSO to verify the stability of the IVW results .MR‒Egger evaluates whether genetic variation exhibits pleiotropic influences on outcomes divergent from zero on average (directional pleiotropy) and offers reliable estimates of causal impacts under the weaker assumption known as the InSIDE assumption . The WM method provides precise estimates of causality. Outliers were detected and corrected after removing abnormal IVs by using the MR-PRESSO test . The outcomes derived from MR sensitivity analysis methods demonstrated robust concordance with the IVW approach (P< 0.05). Finally, a reverse magnetic resonance study was conducted to examine the causative relationship between the intestinal microbiota and HUA.