类风湿关节炎免疫相关差异表达基因分析  

Analysis of immune-related differentially expressed genes in Rheumatoid Arthritis

作　　者：章鲁瑶 张洋 张书筠 代海燕 司子厚 白宇希 苏俊鹏 朱伟 ZHANG Lu-yao(Department of Immunology,Basic Medical School of Mudanjiang Medical University,Mudanjiang 157011,China)

机构地区：[1]牡丹江医学院基础医学院免疫学教研室,黑龙江牡丹江157011

出　　处：《牡丹江医学院学报》2023年第1期44-50,共7页Journal of Mudanjiang Medical University

基　　金：黑龙江省教育厅基本科研业务费项目(2021-KYYWF-0480)。

摘　　要：目的通过分析类风湿关节炎(Rheumatoid Arthritis,RA)差异表达基因(Differentially expressed genes,DEGs)及相关信号通路,探究RA发生发展过程中的分子免疫机制。方法从基因表达综合数据库(gene expression omnibus,GEO)下载基因表达谱数据GSE55235和GSE55457,使用在线R软件进行数据预处理,将GEOquery和R软件limma包过滤后的数据采用sva包ComBat函数去除批间差,通过ComplexHeatmap包绘制差异表达基因热图。用R软件对RA差异表达基因通过京都基因与基因组百科全书数据库(Kyoto Encyclopedia of Genes and Genomes,KEGG)进行富集分析,clusterProfiler包用于富集分析,ggplot2包用于可视化。用Enrichr网站进行在线基因富集分析,得到基因与疾病关系的柱状图。采用R软件clusterProfiler包用于基因富集分析(Gene Set Enrichment Analysis,GSEA),绘制基因相关信号通路网络图。差异基因通过基因功能(gene ontology,GO)富集分析绘制生物过程中的GO注释图。通过蛋白质相互作用网络(protein protein interaction network,PPI network)绘制PPI图。通过TIMER 2.0网站对筛选出来的差异基因进行免疫浸润分析。结果本研究筛选得到741个RA高风险差异基因,其中451个基因表达上调,290个基因表达下调。CXCL13、TNFRSF17、MMP1、TRAT1、IL32、CD52、FOSB、FKBP5、PCK1作为RA发生发展过程中与免疫相关的差异表达基因被筛选出。在RA中趋化因子信号通路、病毒蛋白与细胞因子和细胞因子受体的相互作用、造血细胞谱系及TNF信号通路发生功能富集。结论CXCL13、TNFRS17、CD52、IL32和TRAT1是RA发生发展过程中与细胞免疫相关的高风险差异表达基因。Objective Through the analysis of Differentially expressed genes(DEGs)and related signal pathways in Rheumatoid Arthritis(RA),to explore the molecular immune mechanism in the occurrence and development of RA.Methods The gene expression profile data GSE55235 and GSE55457 were downloaded from Gene expression omnibus(GEO)database,and the data were preprocessed by online R software.The data filtered by GEOquery and R software limma package were filtered by sva package ComBat function to remove the inter-batch difference,and the differentially expressed gene heat map was drawn by ComplexHeatmap package.RA differentially expressed genes were analyzed by Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis with R software.ClusterProfiler package was used for enrichment analysis and ggplot2 package was used for visualization.The Enrichr website was used for online gene enrichment and analysis,and the histogram of the relationship between genes and diseases was obtained.The R software clusterProfiler package was used for Gene Set Enrichment Analysis(GSEA)analysis,and the network map of gene-related signal pathway was drawn.The GO annotation map of the biological process was drawn by Gene ontology(GO)enrichment analysis of differential genes.The PPI diagram was drawn by Protein-protein interaction network(PPI network).TIMER 2.0 website was used to analyze the immune infiltration of the screened differential genes.Results In this study,741 RA high risk differential genes were screened,of which 451 genes were up-regulated and 290 genes were down-regulated.CXCL13,TNFRSF17,MMP1,TRAT1,IL32,CD52,FOSB,FKBP5 and PCK1 were screened as differentially expressed genes related to immunity during the occurrence and development of RA.Chemokine signaling pathway,interaction of viral proteins with cytokines and cytokine receptors,and functional enrichment of hematopoietic cell lineage and TNF signaling pathway in RA.Conclusion CXCL13,TNFRS17,CD52,IL32 and TRAT1 are high risk differentially expressed genes related to cellular im

关 键 词：类风湿关节炎 差异表达基因 蛋白质相互作用网络 

分 类 号：R593.22[医药卫生—内科学]