Proteome-wide and network pharmacology integration identifies sunitinib as a potential therapeutic for type 2 diabetes targets

通过蛋白质组学和网络药理学整合分析,我们发现舒尼替尼是治疗2型糖尿病的潜在靶点药物。

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Abstract

BACKGROUND: The proteome is vital for discovering therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) analysis to identify potential Type 2 Diabetes (T2D) biomarkers and therapeutic targets. METHODS: Data from deCODE Genetics (4907 proteins in 35,559 individuals) and the FinnGen study (65,085 T2D cases, 335,112 controls) were analyzed using inverse-variance weighted MR. Robustness was ensured through reverse MR and external cohort validation. Bayesian weighted MR further corroborated results. Additional analyses included protein-protein interaction (PPI) networks, pathway enrichment, druggability evaluation, and single-cell expression analysis. RESULTS: Proteome-wide MR analysis identified 233 proteins associated with T2D risk. After adjusting for false discovery rate at 0.05, 15 proteins remained significant. Further reverse MR and validation using external cohorts confirmed that TPST2 and CHRDL1 (Chordin-like 1) were identified as the most promising potential therapeutic targets. For the 233 proteins associated with T2D risk, we conducted Gene Ontology enrichment and KEGG pathway enrichment analyses. These causal proteins were found to be involved in regulating inflammation and oxidative stress, atherosclerosis progression, and intracellular signaling mechanisms. A PPI network identified the top 10 hub genes: IGF1R, PPARGC1A, PDGFRB, ADIPOQ, IL15, BDNF, MET, SCARB2, KDR, and VWF. Drug enrichment analysis revealed that IGF1R, PPARGC1A, ADIPOQ, MET, and von Willebrand Factor (VWF) are targeted by metformin. Notably, sunitinib targets IGF1R, PDGFRB, MET, KDR, and VWF. Single-cell RNA sequencing confirmed these proteins' expression. CONCLUSION: This study identifies novel T2D therapeutic targets and highlights sunitinib as a promising candidate. Future work should validate these findings and assess sunitinib's efficacy in clinical trials.

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