Bidirectional two-sample Mendelian randomization analysis reveals a causal correlations of inflammatory cytokines on diabetic nephropathy risk

Abstract

Abstract Objective: The causal correlations of inflammatory cytokines on diabetic nephropathy risk was explored by Bidirectional two-sample Mendelian randomization analysis. Method: In this study, the data of diabetic nephropathy (DN) was extracted from the IEU OpenGWAS Project database, and the data on inflammatory cytokines was obtained from GWAS summary statistics from catalog database. The inverse variance weighted (IVW) is used as the main analysis method, and MR-Egger regression, weighted mode, and weighted median (WM) are used as supplementary methods to analyze the causal correlations of inflammatory cytokines on diabetic nephropathy risk. Cochran Q test and MR-Egger regression intercept are used for sensitivity analysis, and the P value is used as the index of results. Result: A total of 4 SNPs associated with inflammatory cytokines were screened as instrumental variables, IVW results showed a causal relationship between tumor necrosis factor ligand superfamily member 14 levels and TNF-related activation-induced cytokine levels and DN with a positive correlation, while Interleukin-1-alpha levels and Transforming growth factor-alpha levels had a causal relationship with DN with a negative correlation. The results of the ME-Egger intercept test were not multiplicative (P > 0.05), indicating that Mendelian randomization was a valid method for causal inference in this study. The results of reverse MR analysis showed that there was no causal relationship between DN and the increased risk of positively identified inflammatory cytokines. Conclusion: Tumor necrosis factor ligand superfamily member 14 levels and TNF-related activation-induced cytokine levels are independent risk factors for DN, while Interleukin-1-alpha levels and Transforming growth factor-alpha levels are independent protective factors for DN.