Novel therapeutic targets for metabolism-related diseases: proteomic Mendelian randomization and colocalization analyses.

Abstract

Background: In recent years, driven by the rapid advancement of proteomics research, numerous scholars have investigated the intricate associations between plasma proteins and various diseases. Thus, this study aimed to identify novel therapeutic targets for preventing and treating metabolic-related diseases through Mendelian randomization (MR).

Methods: This study primarily utilized the MR method, leveraging genetic data from multiple large-scale publicly available genome-wide association studies. We employed two-sample MR within this framework to assess the associations between 1001 plasma proteins and 5 metabolism-related diseases. Finally, we strengthen the robustness and reliability of the MR results by conducting a series of sensitivity analyses, including bidirectional MR, colocalization analysis, Cochran's Q test, and the MR-Egger intercept test.

Results: The results from the inverse variance weighted method revealed that, following false discovery rate correction, many plasma proteins are significantly associated with metabolic-related diseases. Genetically predicted risks vary across diseases: for coronary artery disease, from 0.82 FGR proto-oncogene, Src family tyrosine kinase (FGR) to 1.13 (interleukin-6); for obesity, from 0.992 (POLR2F) to 1.005 (PRKAB1); for osteoporosis, from 0.998 (AIF1) to 1.001 (CLC); for stroke, from 0.71 (TNFRSF1A) to 1.47 (TGM2); and for type 2 diabetes, from 0.79 (KRT18) to 1.47 (RAB37).

Conclusion: Our findings reveal numerous plasma proteins linked to metabolic-related diseases. These findings offer fresh insights into the etiology, diagnostics, and treatment of these conditions.