类风湿关节炎基因表达谱芯片的生物信息学分析  

Bioinformatics analysis of rheumatoid arthritis gene expression profile microarray

作　　者：袁文华 解琪琪 刘正 沈伟 冯晓飞 周海宇(指导)[1] YUAN Wen-Hua;XIE Qi-Qi;LIU Zheng;SHEN Wei;FENG Xiao-Fei;ZHOU Hai-Yu(Department of Orthopaedics,Second Hospital of Lanzhou University,Gansu Provincial Key Laboratory of Bone and Joint Diseases,Lanzhou 730000,China)

机构地区：[1]兰州大学第二医院骨科,甘肃省骨与关节疾病研究重点实验室,兰州730000

出　　处：《中国免疫学杂志》2020年第24期3003-3009,共7页Chinese Journal of Immunology

基　　金：甘肃省自然科学基金项目(17JR5RA189)。

摘　　要：目的:探讨类风湿关节炎(RA)基因表达和生物学过程的改变,为RA分子机制的进一步研究提供生物信息学依据。方法:从GEO数据库下载已构建的RA患者滑膜样本的mRNA表达谱芯片数据集,应用生物信息学方法筛选差异表达基因(DEGs),并利用DAVID数据库对DEGs进行基因本体论(GO)及通路富集分析(KEGG),然后通过STRING数据库、Cytoscape及其插件cytoHubba、NetworkAnalyzer分析蛋白质互作网络的中心节点蛋白质,寻找关键(Hub)基因。结果:通过对GSE1919、GSE55235、GSE554573个数据集整合取交集获得了58个DEGs;DEGs主要涉及免疫应答、趋化因子介导的信号通路、炎症反应及细胞表面受体信号通路等生物过程,介导趋化因子活性、抗原结合、免疫球蛋白受体结合等分子过程,主要富集于质膜外区域;KEGG分析结果显示DEGs主要富集于细胞因子-细胞因子受体相互作用、趋化因子信号通路和Toll样受体信号通路等经典信号通路;筛选得到CCR2、CCR5、CCL5、PTPRC、CXCL9等10个Hub基因。结论:通过生物信息学方法分析所得Hub基因及信号通路可能是RA潜在的治疗靶点,本文为RA发病机制的进一步研究提供了理论依据。Objective:To investigate the changes of gene expression and biological process in rheumatoid arthritis(RA),and to provide bioinformatics basis for further study of RA molecular mechanism.Methods:Download the constructed mRNA expression microarray data set of synovial samples from RA patients from GEO database,the differentially expressed genes(DEGs)were screened by bioinformatics methods,and the gene ontology(GO)and pathway enrichment analysis(KEGG)of DEGs were performed using DAVID database.Then,the core node proteins of protein interaction network were analyzed by STRING database,Cytoscape and its plug-in cytoHubba and Network Analyzer to find the key(Hub)genes.Results:58 DEGs was obtained by integrating three sets of data sets of GSE1919,GSE55235 and GSE55457.DEGs are mainly involved in immune response,chemokine-mediated signaling pathway,inflammatory reaction and cell surface receptor signaling pathway,which mediate chemokine activity,antigen binding,immunoglobulin receptor binding and other molecular processes,and are mainly concentrated in extraplasmic region.KEGG analysis showed that DEGs were mainly concentrated in classical signaling pathways such as cytokine-cytokine receptor interaction,chemokine signaling pathway and Toll-like receptor signaling pathway.10 key node genes such as CCR2,CCR5,CCL5,PTPRC and CXCL9 were screened.Conclusion:Hub genes and signaling pathway obtained by bioinformatics analysis may be potential therapeutic targets for RA,this article provide a theoretical basis for further study of the pathogenesis of RA.

关 键 词：类风湿关节炎 分子机制 差异表达基因 基因芯片 生物信息学 

分 类 号：R684.3[医药卫生—骨科学]