基于综合生物信息学筛选骨关节炎潜在生物标记物的研究

Screening potential biomarkers of osteoarthritis based on integrated bioinformatics

目的基于基因芯片筛选骨关节炎特征基因谱及信号通路。方法基于Gene Expression Omnibus(GEO)数据库的2个人类关节滑膜组织微阵列(GSE82107和GSE55235),包括20个骨关节炎样本和17个健康对照样本,采用GEO2R工具筛选骨关节炎和健康对照之间的差异表达基因(DEGs)。使用注释、可视化和集成发现数据库进行基因本体论功能(GO)和基于京都基因与基因组百科全书(KEGG)的生物通路富集(https://david.ncifcrf.gov/),以确定DEGs的路径和功能注释。以蛋白-蛋白互作(PPI)基因数据库检索工具为基础,利用Cytoscape软件进行可视化处理(http://www.string-db.org/),分析这些DEGs的PPI,并筛选出关键基因。结果2个微阵列数据库共筛选出滑膜组织191个上调的DEGs和49个下调的DEGs。DEGs主要被富集到"炎症反应"、"骨细胞分化"、"正向凋亡细胞调控"等生物功能调控上以及HTLV-I感染、丝裂原活化蛋白激酶(MAPK)信号通路、甲型流感、肿瘤坏死因子信号通路、NF-κB信号通路、PI3激酶/Akt途径、Toll样受体途径、军团杆菌、沙门氏菌等14条信号通路。PPI在MNC和连接度(Degree)两个模式筛选出前10个关键基因,其中白细胞介素-6、JUN、CXCL8、EGR1、CCND1被确定为有价值的骨关节炎生物标记物。结论通过对骨关节炎的芯片分析筛选出的14条信号通路和10个特征性基因谱,可能为阐明骨关节炎的发病机制提供新的线索。

Objective To screen the potential characteristic gene spectrums and signal pathways of osteoarthritis based on gene chips.Methods We analyzed 2 microarrays of human joint synovial tissue(GSE82107 and GSE55235)derived from the Gene Expression Omnibus(GEO)database and included for this study 20 osteoarthritis(OA)samples and 17 healthy control samples.The differentially expressed genes(DEGs)between OA and HC were screened by GEO2R tool.Analyses of Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment were performed using the Database for Annotation,Visualization and Integrated Discovery to identify the pathways and functional annotations of DEGs(https://david.ncifcrf.gov/).Protein-protein interaction of these DEGs was analyzed based on the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software(http://www.string-db.org/).Results 191 up-regulated DEGs and 49 down-regulated DEGs were screened out from the 2 microarray databases.Enrichment of DEGs was mainly found in regulation of such biological functions as"inflammation","bone cell differentiation"and"positive apoptotic cell regulation",HTLV-I infection,silk crack on the original amp-activated protein kinase(MAPK)signaling pathway,swine flu,tumor necrosis factor(TNF)signaling pathway,the nf-kappa B signaling pathway,PI3 kinase/Akt pathway,toll-like receptor pathway,legionella,salmonella and other 14 signaling pathways.In 2 modes of MNC and Degree,the top 10 core genes were screened,of which interleukin-6(IL6),JUN,chemokine 8(CXCL8),early reaction growth factor(EGR1)and cyclin(CCND1)were identified as valuable biomarkers of OA.Conclusions Based on GEO chips,10 characteristic gene profiles such as IL6,JUN,CXCL8,EGR1,CCND and 14 signal pathways such as tumor necrosis factor(TNF)signal pathway,NF-κB signal pathway,PI3 kinase/Akt pathway and Toll-like receptor pathway were screened,which may provide new clues for understanding of the pathogenesis of osteoarthritis.