慢性阻塞性肺疾病病人慢性支气管炎和肺气肿表型转录组学数据的生物信息学分析  

Bioinformatics analysis of transcriptomic data of chronic bronchitis and emphysema phenotypes in patients with chronic obstructive pulmonary disease

作　　者：高丽娟 秦江月 徐丹[1] 申永春[1] 陈梅 陈磊[1] 文富强[1] GAO Lijuan;QIN Jiangyue;XU Dan;SHEN Yongchun;CHEN Mei;CHEN Lei;WEN Fuqiang(Department of Respiratory and Critical Care Medicine,West China Hospital of Sichuan University and Division of Pulmonary Diseases,State Key Laboratory of Biotherapy of China,Chengdu 610041,China;Department of Respiratory and Critical Care Medicine,Chengdu Fifth People’s Hospital,Chengdu 611130,China)

机构地区：[1]四川大学华西医院呼吸与危重症医学科/生物治疗国家重点实验室呼吸病学研究室,成都610041 [2]成都市第五人民医院呼吸与危重症医学科,成都611130

出　　处：《西南医科大学学报》2022年第5期399-403,共5页Journal of Southwest Medical University

基　　金：国家自然科学基金(31871157,81830001,82170046);四川省医学会专项科研课题(2019HR43);成都市卫健委课题(2019083)。

摘　　要：目的通过生物信息学的方法分析慢性阻塞性肺疾病(简称慢阻肺)(chronic obstructive pulmonary disease,COPD)病人慢支炎表型和肺气肿表型的差异基因,从分子水平上探讨慢阻肺不同临床表型可能的发生发展机制。方法从GEO数据库下载慢阻肺病人慢支炎表型和肺气肿表型的肺组织转录组学数据GSE69818,通过Rank Prod获得差异基因。进一步对差异表达基因通过DAVID数据库进行功能及通路富集化分析。再对差异表达基因通过STRING进行蛋白相互作用网络图(PPI)分析,筛选关键基因。结果共获得3734个差异基因,其中在肺气肿表型组中表达上调的基因有1661个,表达下调的基因有2073个。GO富集分析提示差异基因主要参与了免疫反应、内质网钙离子稳态、细胞外结构等。KEGG信号通路富集分析主要包含了细菌侵袭上皮细胞、细胞外基质(ECM)-受体相互作用、c GMP-PKG信号通路、原发性免疫缺陷等。PPI分析筛选排名前10的关键基因,分别为ACTB、ITGB1、RHOA、FN1、SRSF1、CAV1、CTNNA1、VEGFA、HNRNPA1、APP。其中有9个下调基因(APP、ITGB1、FN1、RHOA、CAV1、CTNNA1、VEGFA、HNRNPA1、SRSF1),1个上调基因(ACTB)。结论通过生物信息学方法,筛选出了参与慢阻肺病人慢支炎表型和肺气肿表型发生发展过程的关键基因和信号通路,为慢阻肺精准治疗提供了潜在的靶点。ObjectiveTo analyze the differential genes of chronic bronchitis phenotype and emphysema phenotype in patients with chronic obstructive pulmonary disease(COPD)by bioinformatics method,and to explore the possible molecular pathogenesis of different clinical phenotypes of COPD.MethodsThe transcriptomic data GSE69818 of lung tissue of COPD patients with chronic bronchitis phenotype and emphysema phenotype were downloaded from GEO database,and the differential genes were obtained by Rank Prod.Further function and pathway enrichment analysis of differentially expressed genes were carried out by DAVID database.The protein-protein interaction(PPI)networks were established using STRING to identify key genes.ResultsA total of 3734 DEGs were obtained,of which 1661 genes were up-regulated and 2073 genes were down-regulated in emphysema group.Geneontology indicated that the DEGs were mainly involved in immune response,endoplasmic reticulum calcium homeostasis and extracellular structure,and KEGG pathway involved bacterial invasion of epithelial cells,extracellular matrix(ECM)-receptor interaction,CGMP-PKG signaling pathway and primary immunodeficiency.Ten hub genes were recognized by PPI analysis,including ACTB,ITGB1,RHOA,FN1,SRSF1,CAV1,CTNNA1,VEGFA,HNRNPA1 and APP.There were 9 down-regulated genes(APP,ITGB1,FN1,RHOA,CAV1,CTNNA1,VEGFA,HNRNPA1,SRSF1)and 1 up-regulated gene(ACTB).ConclusionThe key genes and signal pathways involved in the development of chronic bronchiolitis and emphysema in COPD patients could be obtained through bioinformatics analysis,which provided potential targets for precise treatment of COPD.

关 键 词：慢性阻塞性肺疾病 肺气肿 慢支炎 差异表达基因 蛋白相互作用网络 靶点 生物信息学 

分 类 号：R563.3[医药卫生—呼吸系统]