Abstract
BACKGROUND: Diabetic polyneuropathy (DPN) is a common diabetes complication with limited treatment options. We aimed to identify circulating plasma proteins as potential therapeutic targets for DPN using Mendelian Randomization (MR). METHODS: The protein quantitative trait loci (pQTLs) utilized in this study were derived from seven previously published genome-wide association studies (GWASs) on plasma proteomics. The DPN data were obtained from the IEU OpenGWAS project. This study employed two-sample MR using MR-Egger and inverse-variance weighted methods to evaluate the causal relationship between plasma proteins and DPN risk, with Cochran's Q test, and I(2) statistics, among other methods, used to validate the robustness of the results. RESULTS: Using cis-pQTLs as genetic instruments, we identified 62 proteins associated with DPN, with 33 increasing the risk and 29 decreasing the risk of DPN. Using cis-pQTLs + trans-pQTLs, we identified 116 proteins associated with DPN, with 44 increasing the risk and 72 decreasing the risk of DPN. Steiger directionality tests indicated that the causal relationships between circulating plasma proteins and DPN were consistent with expected directions. CONCLUSION: This study identified 96 circulating plasma proteins with genetically determined levels that affect the risk of DPN, providing new potential targets for DPN drug development, particularly ITM2B, CREG1, CD14, and PLXNA4.