Repurposing Antidiabetic Drugs for Gangrene: A Mendelian Randomization and Text Mining Study.

IF 3.2 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
International Journal of Medical Sciences Pub Date : 2025-06-12 eCollection Date: 2025-01-01 DOI:10.7150/ijms.111050
Chenfeng Wang, Huiwei Wang, Ting Feng, Yihe Hu, Feng Liang
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引用次数: 0

Abstract

Objective: Gangrene has been a problem for many people with diabetes. Besides, the relationship and pathomechanism of diabetes-induced gangrene (DG) are still unclear. The aim of this study was to investigate the causal relationship between diabetes and gangrene through Mendelian randomization (MR) and to identify potential therapeutic agents using bioinformatics analysis. Method: Summary data from genome-wide association studies (GWAS) were utilized to evaluate the connection between two types of diabetes and gangrene risk using a two-sample MR design. Single nucleotide polymorphisms (SNPs) that were significantly associated with diabetes were selected as instrumental variables, and their validity was verified by F-statistics and other methods. Next, we used text mining and protein-protein interaction (PPI) networks to filtrate significant genes for drug-gene interaction (DGI) to identify prospective medications for the therapy of DG. Results: Through multiple methods analysis (IVW, MR-Egger and MR-PRESSO etc.), MR analysis showed that genetic susceptibility to type 1 diabetes was related to a higher risk of gangrene risk (OR: 1.19, 95% CI: 1.04-1.36, P-value: 0.0134), while type 2 diabetes mellitus (T2DM) could also increase the gangrene risk (OR: 1.57, 95% CI: 1.05-2.33, P-value: 0.0269). The outcomes of text mining disclosed 50 genes enriched in NOD-like receptor and RAGE signaling pathways commonly associated with both diabetes and gangrene for PPI analysis. Subsequent DGI analysis revealed six genes targeted by 12 drugs (DGI score > 5), presenting them as candidates for treating DG. Conclusion: In conclusion, this study not only validates the causal effect of diabetes on gangrene risk but also identifies several potential therapeutic agents (CILAZAPRIL, RESATORVID, SILTUXIMAB, and OLOKIZUMAB) by integrating bioinformatics analysis, providing new directions for future clinical interventions.

重新利用降糖药治疗坏疽:孟德尔随机化和文本挖掘研究。
目的:坏疽一直是许多糖尿病患者的一个问题。此外,糖尿病性坏疽(diabesinduced gangrene, DG)的发病关系和发病机制尚不清楚。本研究的目的是通过孟德尔随机化(MR)研究糖尿病和坏疽之间的因果关系,并利用生物信息学分析确定潜在的治疗药物。方法:采用双样本MR设计,利用全基因组关联研究(GWAS)的汇总数据来评估两种类型的糖尿病与坏疽风险之间的联系。选择与糖尿病显著相关的单核苷酸多态性(snp)作为工具变量,并通过f统计等方法验证其有效性。接下来,我们使用文本挖掘和蛋白质-蛋白质相互作用(PPI)网络来过滤药物-基因相互作用(DGI)的重要基因,以确定治疗DG的潜在药物。结果:通过IVW、MR- egger、MR- presso等多种方法分析,MR分析显示1型糖尿病遗传易感性与较高的坏疽风险相关(OR: 1.19, 95% CI: 1.04 ~ 1.36, p值:0.0134),2型糖尿病(T2DM)也可增加坏疽风险(OR: 1.57, 95% CI: 1.05 ~ 2.33, p值:0.0269)。文本挖掘的结果揭示了50个富含nod样受体和RAGE信号通路的基因,这些基因通常与糖尿病和坏疽相关,用于PPI分析。随后的DGI分析揭示了12种药物靶向的6个基因(DGI评分为bb50),将它们作为治疗DG的候选药物。结论:综上所述,本研究不仅验证了糖尿病与坏疽风险的因果关系,而且通过整合生物信息学分析,确定了几种潜在的治疗药物(CILAZAPRIL、RESATORVID、SILTUXIMAB、OLOKIZUMAB),为未来的临床干预提供了新的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
International Journal of Medical Sciences
International Journal of Medical Sciences MEDICINE, GENERAL & INTERNAL-
CiteScore
7.20
自引率
0.00%
发文量
185
审稿时长
2.7 months
期刊介绍: Original research papers, reviews, and short research communications in any medical related area can be submitted to the Journal on the understanding that the work has not been published previously in whole or part and is not under consideration for publication elsewhere. Manuscripts in basic science and clinical medicine are both considered. There is no restriction on the length of research papers and reviews, although authors are encouraged to be concise. Short research communication is limited to be under 2500 words.
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