差异表达基因联合加权共表达网络分析筛选骨关节炎滑膜中的关键基因  

Screening key genes in synovium of osteoarthritis by a combination of differentially expressed genes and weighted co-expression network analysis

作　　者：钱晓芬 曾平[2] 刘金富 王豪 周树龙 潘海达 Qian Xiaofen;Zeng Ping;Liu Jinfu;Wang Hao;Zhou Shulong;Pan Haida(School of Graduate,Guangxi University of Chinese Medicine,Nanning 530299,Guangxi Zhuang Autonomous Region,China;Second Department of Orthopedics,Xianhu Branch,First Affiliated Hospital,Guangxi University of Chinese Medicine,Nanning 530023,Guangxi Zhuang Autonomous Region,China)

机构地区：[1]广西中医药大学研究生院,广西壮族自治区南宁市530299 [2]广西中医药大学第一附属医院仙葫院区骨二科,广西壮族自治区南宁市530023

出　　处：《中国组织工程研究》2022年第33期5342-5349,共8页Chinese Journal of Tissue Engineering Research

基　　金：广西壮族自治区中医药局中医药适宜技术开发与推广项目(GZSY21-14),项目负责人:曾平。

摘　　要：背景:骨关节炎是一种常见的慢性退行性疾病,与年龄具有高度相关性,然而其具体的发病机制尚不明确,在早期诊断和治疗方面存在许多不足。目的:通过生物信息学方法筛选骨关节炎滑膜中的关键表达基因,为寻找诊断骨关节炎的生物标志物及阐明其潜在的发病机制奠定基础。方法:从GEO数据库下载4个骨关节炎滑膜数据集(GSE32317、GSE55235、GSE55457、GSE82107),共纳入27个正常滑膜组织样本和49个骨关节炎滑膜组织样本,运用R语言进行差异表达基因和加权基因共表达网络分析(Weighted Co-expression Network Construction Analysis,WGCNA)交集基因的筛选,对其进行功能分析、蛋白质相互作用网络分析(PPI)以及免疫浸润分析,并使用cytoscape进行网络可视化,用prism对degree排名前10个基因绘制ROC曲线并筛选出关键基因,并用另一组滑膜数据集GSE12021进行验证,最后采用PCR对广西中医药大学第一附属医院仙葫院区骨二科骨关节炎和非骨关节炎(关节创伤)患者各4例滑膜中的关键基因进行检测。结果与结论:①共筛选出差异表达基因263个,WGCNA关键模块基因1237个,两者共有98个交集基因;②PPI degree排名前10的基因分别为白细胞介素6、JUN、ATF3、MYC、DUSP1、VEGFA、FOSB、CXCL8、PTGS2、NR4A1;③根据ROC曲线显示ATF3和DUSP1诊断骨关节炎的准确度较高(AUC值>0.8);④用数据集GSE12021和PCR检测进行验证发现,ATF3和DUSP1在骨关节炎组和对照组中基因表达差异有显著性意义(P<0.01),且与网络分析结果一致;⑤上述结果证实,利用生物信息学方法筛选骨关节炎滑膜中的关键表达基因,基于现有的临床样本的验证结果推论,ATF3和DUSP1有可能成为骨关节炎诊断和治疗的潜在生物标志物和治疗靶点。BACKGROUND:Osteoarthritis is a common chronic degenerative disease with a high correlation with age.However,its specific pathogenesis is still unclea r,and there are many deficiencies in early diagnosis and treatment.OBJECTIVE:To screen the key expressed genes in the synovium of osteoarthritis by bioinformatics method,so as to lay a foundation for finding biomarkers for the diagnosis of osteoarthritis and elucidating its underlying pathogenesis.METHODS:Four osteoarthritic synovial tissue data sets were downloaded from the Gene Expression Omnibus database(GSE32317,GSE55235,GSE55457,GSE82107),including 27 normal synovial tissue samples and 49 osteoa rthritic synovial tissue samples.The intersection genes of differentially expressed genes and Weighted Co-expression Network Construction Analysis results were screened using R language.Functional annotation,protein-protein interaction network,and immune infiltration analyses of the intersection genes were performed,and cytoscape was used for network visualization.Prism was used to draw receiver operating characteristic curve for the top 10 genes for degree ranking and screen out key genes,and then another synovial data set,GSE12021,was used for verification.Finally,the key genes in the synovial samples from four osteoarthritis patients and four non-osteoarthritis patients(joint injury)were further detected by PCR.RESULTS AND CONCLUSION:(1)In this study,263 differentially expressed genes and 1237 key module genes of Weighted Co-expression Network Construction Analysis were identified,with a total of 98 inte rsection genes.(2)Protein-protein interaction node number of the top 10 most genes included interleukin 6,JUN,ATF3,MYC,DUSP1,VEGFA,FOSB,CXCL8,PTGS2,and NR4 A1.(3)According to the receiver operating characteristic curve,ATF3 and DUSP1 had a higher diagnostic accuracy(area under the curve>0.8).(4)Verification with the data set GSE12021 and PCR detection indicated that the gene expression difference of ATF3 and DUSP1 between the osteoarthritis group and the control grou

关 键 词：骨关节炎 滑膜组织 差异表达基因 加权共表达网络分析 细胞应激反应 信号通路 激活转录因子3 双特异性磷酸酶1 

分 类 号：R452[医药卫生—治疗学] R318[医药卫生—临床医学]