阿尔茨海默病相关差异表达基因及其生物信息学分析
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篇名: 阿尔茨海默病相关差异表达基因及其生物信息学分析
TITLE:
摘要: 目的:为阿尔茨海默病(AD)发病机制的阐释、早期预防与诊断以及治疗靶点的筛选提供参考。方法:从美国国立生物技术信息中心公共数据平台基因表达数据库中下载基因芯片数据集GSE28146,使用GEO2R在线分析工具筛选出AD相关差异表达基因(DEGs);使用DAVID 6.8生物信息学资源数据库进行基因本体(GO)分析和KEGG通路富集分析;使用STRING数据库和Cytoscape 3.2.1软件进行蛋白-蛋白相互作用(PPI)网络分析。结果与结论:筛选出AD相关DEGs共1 478个,其中上调913个、下调565个。GO分析结果显示,DEGs主要分布于细胞质、膜、细胞外隙中,主要通过转录的正/负调节、核因子κB活性的正调节、Rho蛋白信号转导的调节、蛋白质磷酸化的调节等生物学过程以及蛋白质结合、DNA结合、转录因子活性(序列特异性DNA结合)等分子功能来诱导AD的发生。KEGG通路富集分析结果显示,DEGs显著富集于癌症途径、肺结核、破骨细胞分化、Janus激酶/信号传导及转录激活因子信号通路、叉头转录因子信号通路、EB病毒感染等信号通路上。DEGs编码蛋白的PPI网络含节点蛋白共1 205个、边3 931条;其中的关键核心基因为SOCS3、NEDD4、CBLB,可能是AD发生发展的潜在靶点。
ABSTRACT: OBJECTIVE: To provide reference for interpretation of pathogenesis, early prevention and diagnosis, and selection of therapeutic targets of Alzheimer’s disease (AD). METHODS: The gene chip dataset GSE28146 was downloaded from the NCBI public data platform GEO, and the AD-related differentially expressed genes (DEGs) were identified by using GEO2R online analysis tool. GO analysis and KEGG enrichment pathway analysis were performed by using DAVID 6.8 bioinformatics resource database. The protein-protein interaction (PPI) network analysis was performed by using STRING database and Cytoscape 3.2.1 software. RESULTS & CONCLUSIONS: A total of 1 478 AD-related DEGs were identified, consisting of 913 up-regulated genes and 565 down-regulated genes. GO function enrichment analysis showed that DEGs mainly distributed in cytoplasm, membrane, extracellular space, and induced AD via biological processes such as positive/negative regulation of transcription, positive regulation of NF-κB activity, regulation of Rho protein signaling transduction, protein phosphorylation; via protein binding, DNA binding, transcription factor activity (sequence specific DNA binding) and other molecular functions. KEGG pathway enrichment analysis showed that DEGs was enriched in cancer pathway, pulmonary tuberculosis, osteoclast differentiation, JAK/STAT signaling pathway, FoxO signaling pathway, EB virus infection and other signaling pathways. There are 1 205 nodes and 3 931 edges in the PPI network of DEGs coding protein. Among them, the key genes are SOCS3, NEDD4 and CBLB, which may be the potential target of AD development.
期刊: 2019年第30卷第24期
作者: 徐倩,苏湲淇,谭毅,杨元娟
AUTHORS: XU Qian,SU Yuanqi,TAN Yi,YANG Yuanjuan
关键字: 阿尔茨海默病;差异表达基因;生物信息学;基因本体;KEGG通路富集;蛋白-蛋白相互作用
KEYWORDS: Alzheimer’s disease;Differentially expressed genes;Bioinformatics; Gene ontology; KEGG pathway enrichment; Protein-protein interaction
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