来源：风湿病与关节炎,2019,8（2）:16-20,26.

基于GEO数据库对骨关节炎滑膜差异基因的筛选及生物信息学分析（临床研究）

程晓平¹，郑文伟²，倪国新¹

　　【摘　要】目的：利用生物信息学对骨关节炎与正常关节滑膜间差异基因进行分析，探索骨关节炎的发病机制。方法：从GEO数据库下载关节滑膜基因芯片数据库，利用GEO2R筛选出差异基因，DAVID 6.7数据库对差异基因进行功能GO分析及KEGG信号通路分析，String-db数据库构建蛋白之间的相互作用网络图（PPI），并采用Cytoscape 3.6.1软件获取关键靶基因。结果：GEO2R共筛选出差异基因490个，包含上调基因61个，下调基因429个，其主要涉及细胞分化、细胞生长、骨骼肌器官发育、cAMP反应等生理过程，且主要富集在细胞外基质受体互作、近端肾小管重吸收碳酸氢盐、胃酸分泌、催产素、环磷酸腺苷/蛋白激酶G、脂肪细胞因子信号通路中。从PPI网络中共获取13个关键靶基因，包含FOS、SMARCA4、SOCS3、LEP、FBXO32、MYOD1、TRIM63、SMARCA2、CALB1、MAPK12、ADIPOQ、TTN、EGR1。结论：利用生物信息学从不同角度揭示骨关节炎与正常关节滑膜间差异基因潜在特征，为骨关节炎的治疗提供新的思路。

　　【关键词】　骨关节炎；滑膜；差异基因；生物信息学

Screening and Bioinformatics Analysis of Synovial Differential Genes in Osteoarthritis Based on the GEO Database CHENG Xiao-ping,ZHENG Wen-wei,NI Guo-xin

　　【ABSTRACT】Objective:To explore the pathogenesis of osteoarthritis by bioinformatics analysis of differential genes between osteoarthritis and normal synovium.Methods:The Gene Chip Database of Synovium was downloaded from the GEO database,and differential genes were screened by GEO2R.An enrichment analysis was made for GO function and KEGG signaling pathway of differential genes by the DAVID 6.7 database.The PPI network was constructed by String-db database,and key target genes were obtained by Cytoscape 3.6.1 software.Results:A total of 490 differential genes,including 61 up-regulated genes and 429 down-regulated genes,were screened by GEO2R.They mainly involved in cell differentiation,cell growth,skeletal muscle organ development,cAMP response and other physiological processes.They were mainly concentrated in extracellular matrix receptor interaction,proximal renal tubule resorption of bicarbonate,gastric acid secretion,oxytocin,cyclic adenosine phosphate/protein kinase G,adipocyte factor signaling pathway.Thirteen key target genes were obtained from the PPI network,including FOS,SMARCA4,SOCS3,LEP,FBXO32,MYOD1,TRIM63,SMARCA2,CALB1,MAPK12,ADIPOQ,TTN and EGR1.Conclusion:Bioinformatics can reveal the potential characteristics of gene differences between osteoarthritis and normal joint synovium from different perspectives,and provide new ideas for the treatment of osteoarthritis.

　　【Keywords】 osteoarthritis;synovium;differential genes;bioinformatics