The Effects of Specific Gut Microbiota and Metabolites on IgA Nephropathy-Based on Mendelian Randomization and...

Although recent research suggests that alterations in gut microbiota and metabolites play a critical role in the pathophysiology of immunoglobulin A nephropathy (IgAN), the causal relationship between specific intestinal flora and metabolites and the risk of IgAN remains unclear.

This study employed Mendelian randomization (MR) to investigate the causal association between gut microbiota and IgAN. To explore potential associations between gut microbiota and various outcomes, four MR methods were applied: inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode. If the results of the four methods are inconclusive, we prefer the IVW as the primary outcome. Additionally, MR-Egger, MR-PRESSO-Global, and Cochrane's Q tests were used to detect heterogeneity and pleiotropy. The stability of MR findings was assessed using the leave-one-out approach, and the strength of the causal relationship between exposure and outcome was tested using Bonferroni correction. Additional clinical samples were utilized to validate the results of Mendelian randomization, and the outcomes were visualized through an ROC curve, confusion matrix, and correlation analysis.

This study examined a total of 15 metabolites and 211 microorganisms. Among them, eight bacteria and one metabolite were found to be associated with the risk of IgAN (p < 0.05). The Bonferroni-corrected test reveals that only Class. Actinobacteria (OR: 1.20, 95% CI: 1.07-1.36, p = 0.0029) have a significant causal relationship with IgAN. According to Cochrane's Q test, there is no substantial heterogeneity across different single-nucleotide polymorphisms (p > 0.05). Furthermore, MR-Egger and MR-PRESSO-Global tests (p > 0.05) showed no evidence of pleiotropy. No reverse causal association was found between the risk of IgAN and microbiota or metabolites (p > 0.05). Clinical specimens demonstrated the effectiveness and accuracy of Actinobacteria in distinguishing IgAN patients from those with other glomerular diseases (AUC = 0.9, 95% CI: 0.78-1.00). Additionally, our correlation analysis revealed a potential association between Actinobacteria abundance and increased albuminuria (r = 0.85) and poorer prognosis in IgAN patients (p = 0.01).

Through MR analysis, we established a causal link between Actinobacteria and the incidence of IgAN. Moreover, clinical validation using fecal samples indicated that Actinobacteria might be associated with the onset and poorer prognosis of IgAN. This finding could provide valuable biomarkers for early, noninvasive detection of the disease and potential therapeutic targets in IgAN.