生物信息学预测类风湿关节炎核心基因与互作miRNA

Prediction of key coding genes and miRNAs associated with rheumatoid arthritis using bioinformatics

目的通过生物信息学分析筛选类风湿性关节炎(RA)滑膜炎中相关的核心差异基因与相互作用的微小核糖核酸(miRNA)。方法通过GEO数据库下载基因芯片GSE55235,通过R语言3.5.0筛选出差异表达基因,并通过David在线数据库进行功能富集分析。应用String 10.5、Cytoscape v3.6.1和MCODE插件建立蛋白相互作用网络,筛选出RA发生过程中的核心基因。通过CyTargetLinker预测与核心基因互作的miRNA。结果筛选出605个差异表达基因,其中上调314个,下调291个。其功能主要富集于免疫反应和细胞大分子生物合成和结合等过程。蛋白相互作用网络共有552个节点和5163条边,筛选出了前4的作用模块和10个核心基因:蛋白酪氨酸磷酸酶受体C型(PTPRC)、血管内皮生长因子α(VEGFα)、纤连蛋白1基因(FN1)、整合素亚基M(ITGAM)、表皮生长因子(EGFR)、CD86、基质金属蛋白酶9(MMP9)、整合素亚基β2(ITGB2)、TYRO蛋白酪氨酸激酶结合蛋白(TYROBP)和MYC。并预测了36个miRNA可与其中3个核心基因靶向性相互作用。结论筛选出的核心基因与相互作用的miRNA可能成为RA潜在治疗的靶点。

Objective To screen synovitis-related core differential genes and interacting microRNAs(miRNAs)in rheumatoid arthritis(RA)using bioinformatics.Methods The gene chip GSE55235 was downloaded from the GEO database,and the differentially expressed genes were screened by R software 3.5.0,and functional enrichment analysis was performed by David online database.The protein interaction network was established by using String 10.5,Cytoscape v3.6.1 and MCODE to screen out the core genes during RA development.miRNAs that interact with core genes were predicted by CyTargetLinker.Results 605 differentially expressed genes were screened,of which 314 were up-regulated and 291 were down-regulated.Their functions were mainly concentrated in the process of immune reaction and biosynthesis and binding of macromolecules.The protein interaction network contained a total of 552 nodes and 5163 interaction edges.The first four cluster modules were listed and 10 core genes were screened:protein tyrosine phosphatase receptor type C(PTPRC),vascular endothelial growth factor(VEGF),fibronectin 1(FN1),integrin Subunit Alpha M(ITGAM),epidermal growth factor(EGFR),CD86,matrix metalloproteinase-9(MMP-9),integrin subunit Beta 2(ITGB2),TYRO protein tyrosine kinase binding protein(TYROBP)and MYC.It was predicted that 36 miRNAs could interact with three core genes by CyTargetLinker.Conclusion The selected core genes and interacting miRNAs may be potential targets for RA treatment.