Mahmoudi Ali, Butler Alexandra E, De Vincentis Antonio, Jamialahmadi Tannaz, Sahebkar Amirhossein
Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Curr Med Chem. 2024;31(23):3631-3652. doi: 10.2174/0929867330666230516123028.
Non-alcoholic fatty liver disease (NAFLD) is a prevalent cause of chronic liver disease and encompasses a broad spectrum of disorders, including simple steatosis, steatohepatitis, fibrosis, cirrhosis, and liver cancer. However, due to the global epidemic of NAFLD, where invasive liver biopsy is the gold standard for diagnosis, it is necessary to identify a more practical method for early NAFLD diagnosis with useful therapeutic targets; as such, molecular biomarkers could most readily serve these aims. To this end, we explored the hub genes and biological pathways in fibrosis progression in NAFLD patients.
Raw data from microarray chips with GEO accession GSE49541 were downloaded from the Gene Expression Omnibus database, and the R package (Affy and Limma) was applied to investigate differentially expressed genes (DEGs) involved in the progress of low- (mild 0-1 fibrosis score) to high- (severe 3-4 fibrosis score) fibrosis stage NAFLD patients. Subsequently, significant DEGs with pathway enrichment were analyzed, including gene ontology (GO), KEGG and Wikipathway. In order to then explore critical genes, the protein-protein interaction network (PPI) was established and visualized using the STRING database, with further analysis undertaken using Cytoscape and Gephi software. Survival analysis was undertaken to determine the overall survival of the hub genes in the progression of NAFLD to hepatocellular carcinoma.
A total of 311 significant genes were identified, with an expression of 278 being upregulated and 33 downregulated in the high vs. low group. Gene functional enrichment analysis of these significant genes demonstrated major involvement in extracellular matrix (ECM)-receptor interaction, protein digestion and absorption, and the AGE-RAGE signaling pathway. The PPI network was constructed with 196 nodes and 572 edges with PPI enrichment using a p-value < 1.0 e-16. Based on this cut-off, we identified 12 genes with the highest score in four centralities: Degree, Betweenness, Closeness, and Eigenvector. Those twelve hub genes were CD34, THY1, CFTR, COL3A1, COL1A1, COL1A2, SPP1, THBS1, THBS2, LUM, VCAN, and VWF. Four of these hub genes, namely CD34, VWF, SPP1, and VCAN, showed significant association with the development of hepatocellular carcinoma.
This PPI network analysis of DEGs identified critical hub genes involved in the progression of fibrosis and the biological pathways through which they exert their effects in NAFLD patients. Those 12 genes offer an excellent opportunity for further focused research to determine potential targets for therapeutic applications.
非酒精性脂肪性肝病(NAFLD)是慢性肝病的常见病因,涵盖一系列广泛的病症,包括单纯性脂肪变性、脂肪性肝炎、纤维化、肝硬化和肝癌。然而,由于NAFLD在全球流行,而侵入性肝活检是诊断的金标准,因此有必要确定一种更实用的早期NAFLD诊断方法以及有用的治疗靶点;分子生物标志物最有可能实现这些目标。为此,我们探索了NAFLD患者纤维化进展中的核心基因和生物学途径。
从基因表达综合数据库下载基因表达综合登录号为GSE49541的微阵列芯片原始数据,并应用R包(Affy和Limma)研究参与低(轻度0 - 1纤维化评分)至高(重度3 - 4纤维化评分)纤维化阶段NAFLD患者病情进展的差异表达基因(DEG)。随后,对具有通路富集的显著DEG进行分析,包括基因本体论(GO)、京都基因与基因组百科全书(KEGG)和维基通路。为了进一步探索关键基因,使用STRING数据库建立并可视化蛋白质 - 蛋白质相互作用网络(PPI),并使用Cytoscape和Gephi软件进行进一步分析。进行生存分析以确定核心基因在NAFLD进展为肝细胞癌过程中的总体生存率。
共鉴定出311个显著基因,高分组与低分组相比,其中278个基因表达上调,33个基因表达下调。对这些显著基因的基因功能富集分析表明,它们主要参与细胞外基质(ECM) - 受体相互作用、蛋白质消化和吸收以及晚期糖基化终末产物受体(AGE - RAGE)信号通路。构建的PPI网络有196个节点和572条边,PPI富集的p值<1.0×10⁻¹⁶。基于此临界值,我们在度、介数、紧密性和特征向量四个中心性方面鉴定出得分最高的12个基因。这12个核心基因是CD34、THY1、囊性纤维化跨膜传导调节因子(CFTR)、Ⅲ型胶原蛋白α1链(COL3A1)、Ⅰ型胶原蛋白α1链(COL1A1)、Ⅰ型胶原蛋白α2链(COL1A2)、骨桥蛋白(SPP1)、血小板反应蛋白1(THBS1)、血小板反应蛋白2(THBS2)、 Lumican蛋白(LUM)、多功能蛋白聚糖(VCAN)和血管性血友病因子(VWF)。其中4个核心基因,即CD34、VWF、SPP1和VCAN,与肝细胞癌的发生发展显著相关。
对DEG进行的这种PPI网络分析确定了参与纤维化进展的关键核心基因以及它们在NAFLD患者中发挥作用的生物学途径。这12个基因提供了一个绝佳机会,可进行进一步的重点研究以确定潜在的治疗应用靶点。