基于GEO肺纤维化合并肺气肿综合征芯片数据的生物信息学分析

Bioinformatics analysis of combined pulmonary fibrosis and emphysema genome microarray based on GEO database

目的通过生物信息学的方法分析正常人和肺纤维化合并肺气肿综合征（CPFE）患者的差异基因,从分子水平上探讨CPFE可能的发病机制。方法从GEO数据库下载正常人群和CPFE患者的芯片信息,通过GCBI在线实验室分析获得差异基因。利用DAVID数据库分析差异基因获得GO富集分析和KEGG信号通路富集分析的结果。利用STRING筛选出互相作用蛋白≥10个作为关键基因,再将关键基因信息导入Cytoscape软件中形成编码蛋白互相作用的网络图。结果筛选获得了1303个差异基因,其中表达上调的基因828个,表达下调的基因475个。GO富集分析表明差异基因主要参与了免疫反应、细胞外基质的组成、信号转导生物过程,KEGG信号通路富集分析主要包括了细胞因子受体相互作用通路、趋化因子信号转导通路、细胞黏附分子信号通路。筛选获得了16个关键基因,为CCR5、IGF1、CXCL12、APP、CCL5、GNB4、SDC1、APOE、GNAQ、FPR2、ISG15、CD2、VCAM1、CCND1、JAK1、CCNB1。其中上调的13个,下调的3个。结论通过生物信息学分析可以获得CPFE的差异基因、关键基因、生物学过程和信号通路等信息,为探究CPFE的发病机制提供依据。

Objective To investigate the possible pathogenesis of combined pulmonary fibrosis and emphysema （CPFE） on the molecular level by bioinformatics analysis of differential expression genes （DEGs） in normal subjects and patients with CPFE. Methods The microarray information of the normal subjects and CPFE patients was downloaded from the GEO database, and DEGs were obtained by GCBI online laboratory analysis. Analysis of DEGs by DAVID database was used to obtain gene ontology and KEGG pathway. STRING was used to obtain more than 10 interacting proteins as the hubs genes, and then the hubs gene information was imported into Cytoscape software to form the protein-protein interaction network of hubs gene. Results 1 303 DEGs were obtained, of which 828 genes were upregulated and 475 genes were down-regulated. Gene ontology showed that the DEGs were mainly involved in the immune response, the composition of extracellular matrix, signal transduction biological processes, and KEGG pathway involved in cytokine-cytokine receptor interaction pathway, ehemokine signaling pathway, cell adhesion molecule pathway. Sixteen hubs genes included CCR5, IGF1, CXCL12, APP, CCLS, GNB4, SDC1, APOE, GNAQ, FPR2, ISG15, CD2, VCAM1, CCND1, JAK1, CCNB1. Among them, thirteen genes were up-regulated and three genes were down-regulated. Conclusions DEGs, hubs genes, gene ontology and KEGG pathway of CPFE can be obtained through bioinformatics analysis, which provides the basis for exploring the pathogenesis of CPFE.