女性骨关节炎患者外周血单个核细胞基因表达谱的生物信息学分析

Bioinformatics analysis of gene expression profile of peripheral blood mononuclear cells in female patients with osteoarthritis

目的通过生物信息学方法分析中老年女性骨关节炎(osteoarthritis,OA)患者与正常人(NC)外周血单个核细胞(PBMCs)基因表达谱差异,探索血液中OA的诊疗靶点。方法从GEO数据库中下载GSE48556数据集。用R语言筛选出OA和NC之间的差异表达基因。利用基因集合富集分析(GSEA)获取目的基因子集;通过DAVID对其进行GO和KEGG通路分析。用STRING和Cytoscape软件构建PPI网络,Mcode和centiscape插件进行模块分析,Cytohubba筛选出关键基因。结果GSEA分析及P.adjust<0.05&|log2FC|>0.2筛选出292个目的基因,其中上调81个,下调211个,对其进行GO富集分析主要集中在“NIK/NF-κB的调节”、“单核细胞增殖”、“凋亡信号通路的调控”、“TNF介导的信号通路”、“Wnt信号通路的调控”、“MAP激酶活性的调节”和“自噬的调节”等生物功能上;KEGG主要富集在以下4条通路:自然杀伤细胞介导的细胞毒性、TNF信号通路、MAPK信号通路和细胞凋亡。利用PPI网络及相关插件筛选出MAPK1、I L10、PTGS2、IL18、GSK3B、NFKBIA、TNFRSF1A、EGR1八个核心基因与OA炎症和细胞凋亡高度相关。结论通过生物信息学分析发现OA和NC的PBMCs基因表达差异集中在细胞凋亡和炎症反应,使其成为OA的诊疗靶点。

Objective Through bioinformatics methods to analyze the differences in the gene expression profiles of peripheral blood mononuclear cells(PBMCs)between middle-aged and elderly women and normal people,so as to explore the diagnosis and treatment targets of OA.Methods We downloaded the GSE48556 data set from GEO databases.We utilized the R language to screen out the differentially expressed genes(DEGs)between OA and NC.By gene set enrichment analysis(GSEA),we obtained the target gene subset.The GO and KEGG pathways of the target gene subset were analyzed by DAVID.We applied STRING and Cytoscape software to construct PPI network.The module analysis was performed by the Mcode and centiscape plug-in,and the key genes were screened out by Cytohubba.Results By GSEA analysis and P.adjust<0.05&|log2FC|>0.2,a total of 292 target genes were screened,consisting of 81 upregulated genes and 211 downregulated genes.The GO enrichment analysis of all target genes mainly focused on the biological functions,such as“regulation of NIK/NF-κB”,“monocytes”,“proliferation”,“regulation of apoptosis signaling pathway”,“TNF-mediated signaling pathway”,“regulation of Wnt signaling pathway”,“regulation of MAP kinase activity”,and“regulation of autophagy”.KEGG was mainly enriched in four pathways:cytotoxicity of natural killer cell mediation,TNF signaling pathway,MAPK signaling pathway,and apoptosis.We employed PPI network and related plug-ins to screen out eight core genes highly related to OA inflammation and apoptosis,namely,MAPK1,IL10,PTGS2,IL18,GSK3B,NFKBIA,TNFRSF1A,and EGR1.Conclusion Bioinformatics analysis revealed that the differences in PBMCs gene expressions between OA and NC were concentrated in the biological events of apoptosis and inflammation,making blood expression profile an effective breakthrough for monitoring OA target markers.