背景:糖尿病是由胰岛素产生或胰岛素功能受损引起的日益普遍的全球性疾病。从长远来看,糖尿病会导致微血管和大血管并发症,可能导致视网膜病变。肾病,神经病,外周动脉疾病,动脉粥样硬化性心血管疾病,和脑血管疾病。已经花费了相当大的努力来研究许多基因和途径以解释导致糖尿病相关并发症的机制。姜黄素是一种传统药物,具有抗氧化等多种特性,抗炎,抗癌,和抗微生物,可用于治疗糖尿病并发症。这项研究,基于系统生物学方法,目的探讨姜黄素对糖尿病相关关键基因和通路的影响。
方法:我们首先在三个不同的数据库中搜索了姜黄素的相互作用,包括STITCH,TTD,还有DGIdb.随后,我们在OMIM和DisGeNET数据库中调查了糖尿病的关键的筛选蛋白靶标.为了在疾病网络中找到重要的聚类组(MCODE)和关键的枢纽基因,我们借助字符串数据库和Cytoscape软件,为糖尿病患者获得的所有蛋白质创建了PPI网络.接下来,我们使用维恩图研究了姜黄素对糖尿病相关基因的可能相互作用.此外,分析了姜黄素对模块化集群得分最高的影响.最后,我们使用基于enruriRWeb服务器的基因本体(GO)和KEGG进行了生物过程和途径富集分析。
结果:我们获得了417个与糖尿病相关的基因,他们构建的PPI网络包含298个节点和1651个边缘。接下来,对PPI网络中心性的分析表明,有15个基因具有最高的中心性。此外,MCODE分析确定了三个模块化集群,哪个得分最高的集群(MCODE1)包括19个节点和92条边,得分为10.22。在数据库中筛选姜黄素相互作用鉴定了158个蛋白质靶标。与糖尿病相关的基因和姜黄素的蛋白质靶标的维恩图显示了35种共享蛋白质,观察到姜黄素可以与十个hub基因强烈相互作用。此外,我们证明姜黄素与MCODE1的相互作用在所有MCOD中最高。与35共享的KEGG富集相关的几个重要生物学途径包括糖尿病并发症中的AGE-RAGE信号通路,HIF-1信号通路,PI3K-Akt信号通路,TNF信号,和JAK-STAT信号通路。GO分析的生物过程与细胞对细胞因子刺激的反应有关,细胞因子介导的信号通路,炎症反应中细胞内信号转导和细胞因子产生的正向调节。
结论:姜黄素靶向几个与糖尿病有关的重要基因,支持先前的研究,表明它可能作为糖尿病的治疗剂。
BACKGROUND: Diabetes is an increasingly prevalent global disease caused by the impairment in insulin production or insulin function. Diabetes in the long term causes both microvascular and macrovascular complications that may result in retinopathy, nephropathy, neuropathy, peripheral arterial disease, atherosclerotic cardiovascular disease, and cerebrovascular disease. Considerable effort has been expended looking at the numerous genes and pathways to explain the mechanisms leading to diabetes-related complications. Curcumin is a traditional medicine with several properties such as being antioxidant, anti-inflammatory, anti-cancer, and anti-microbial, which may have utility for treating diabetes complications. This study, based on the system biology approach, aimed to investigate the effect of curcumin on critical genes and pathways related to diabetes.
METHODS: We first searched interactions of curcumin in three different databases, including
STITCH, TTD, and DGIdb. Subsequently, we investigated the critical curated protein targets for diabetes on the OMIM and DisGeNET databases. To find important clustering groups (MCODE) and critical hub genes in the network of diseases, we created a PPI network for all proteins obtained for diabetes with the aid of a string database and Cytoscape software. Next, we investigated the possible interactions of curcumin on diabetes-related genes using Venn diagrams. Furthermore, the impact of curcumin on the top scores of modular clusters was analysed. Finally, we conducted biological process and pathway enrichment analysis using Gene Ontology (GO) and KEGG based on the enrichR web server.
RESULTS: We acquired 417 genes associated with diabetes, and their constructed PPI network contained 298 nodes and 1651 edges. Next, the analysis of centralities in the PPI network indicated 15 genes with the highest centralities. Additionally, MCODE analysis identified three modular clusters, which highest score cluster (MCODE 1) comprises 19 nodes and 92 edges with 10.22 scores. Screening curcumin interactions in the databases identified 158 protein targets. A Venn diagram of genes related to diabetes and the protein targets of curcumin showed 35 shared proteins, which observed that curcumin could strongly interact with ten of the hub genes. Moreover, we demonstrated that curcumin has the highest interaction with MCODE1 among all MCODs. Several significant biological pathways in KEGG enrichment associated with 35 shared included the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, PI3K-Akt signaling pathway, TNF signaling, and JAK-STAT signaling pathway. The biological processes of GO analysis were involved with the cellular response to cytokine stimulus, the cytokine-mediated signaling pathway, positive regulation of intracellular signal transduction and cytokine production in the inflammatory response.
CONCLUSIONS: Curcumin targeted several important genes involved in diabetes, supporting the previous research suggesting that it may have utility as a therapeutic agent in diabetes.