基于生物信息学分析探究肺动脉高压关键基因和通路  

Bioinformatics Analysis of Key Genes and Pathways in Pulmonary Arterial Hypertension

作　　者：向杰 刘明鑫[1] 张伟[1] 黄从新[1] XIANG Jie;LIU Mingxin;ZHANG Wei;HUANG Congxin(Department of Cardiology,Renmin Hospital of Wuhan University,Wuhan 430060,Hubei,China)

机构地区：[1]武汉大学人民医院心内科,湖北武汉430060

出　　处：《心血管病学进展》2020年第4期428-433,共6页Advances in Cardiovascular Diseases

摘　　要：目的通过生物信息学方法寻找肺动脉高压中差异表达的基因,为肺动脉高压的预防和早期诊断及治疗提供新思路。方法从公共基因数据库(GEO)中下载基因芯片数据集GSE113439,使用在线分析工具GEO2R筛选出肺动脉高压肺组织和正常肺组织的差异表达基因。利用在线数据库DAVID和STRING分别进行功能、通路富集分析和蛋白互作分析,使用Cytoscape软件来筛选蛋白相互作用网络中的核心网络基因及显著相互作用模块。结果共筛选出559个差异基因,其中87个为上调基因,472个为下调基因(调整后P<0. 05,|log2FC|>1)。对差异基因进行GO和KEGG富集分析,GO富集分析(P<0. 05)结果提示:(1)生物过程:差异表达基因显著富集于DNA双解、DNA修复、有丝分裂等;(2)细胞单位:差异表达基因显著富集于核质、膜、核仁、细胞质、中心体、核、核斑点、染色体、高尔基体等;(3)分子功能:差异表达基因显著富集于聚(A) RNA结合、ATP结合、蛋白质结合、解旋酶活性、微管结合、ATP依赖性DNA解旋酶活性等。KEGG富集分析结果提示差异表达基因显著富集于真核生物的核糖体生物发生、RNA转运、类风湿性关节炎、RNA降解、血管平滑肌收缩、疟疾、癌症中的蛋白多糖等(P<0. 05)。STRING分析发现了蛋白质网络互作图中的10个关键基因,分别为CDK1、CDC5L、KIF11、SMC2、CENPE、TOP2A、NCAPG、CENPF、SMC4和SKIV2L2。结论细胞增殖与凋亡等生物学过程和肺血管平滑肌等通路可能在肺动脉高压发生发展过程中起着重要的作用,采用生物信息学方法筛选可能的核心靶点有利于从基因层面上了解疾病的发生机制,为肺动脉高压发生机制的进一步研究提供方向。Objective To find the differentially expressed genes in pulmonary arterial hypertension by bioinformatics method,and to provide new ideas for the prevention and early diagnosis and treatment of pulmonary hypertension. Methods The gene chip dataset GSE113439 was downloaded from the Gene Expression Omnibus( GEO), and differentially expressed genes in pulmonary arterial hypertension lung tissue and normal lung tissue were screened using the online analysis tool GEO2 R. We used the online databases DAVID and STRING for functional,pathway enrichment analysis and protein interaction analysis,and Cytoscape software was also used to screen core network genes and significant interaction modules in protein interaction networks. Results A total of 559 differential genes were screened,of which 87 were up-regulated and 472 were down-regulated( P<0. 05 after adjustment,| log2 FC | >1).GO and KEGG enrichment analysis of differential genes,GO enrichment analysis( P < 0. 05) showed that:( 1) Biological process: differentially expressed genes are significantly enriched in DNA duplex unwinding,DNA repair,mitotic nuclear division,etc;( 2) Cellar locution: differentially expressed genes are significantly enriched in nucleoplasm,membrane,nucleolus,cytoplasm,centrosome,nucleus,nuclear speck,chromosome,Golgi apparatus,etc;( 3) Molecular functions: differentially expressed genes are significantly enriched in poly( A) RNA binding,ATP binding,protein binding,helicase activity,microtubule binding,ATP-dependent DNA helicase activity,etc. KEGG enrichment analysis suggested that differentially expressed genes were significantly enriched in Ribosome biogenesis in eukaryotes,RNA transport,rheumatoid arthritis,RNA degradation,vascular smooth muscle contraction,malaria,proteoglycans in cancer and so on( P<0. 05). STRING analysis found 10 key genes in the protein network interaction map,namely CDK1,CDC5 L,KIF11,SMC2,CENPE,TOP2 A,NCAPG,CENPF,SMC4,SKIV2 L2. Conclusion Biological processes such as cell proliferation and apoptosis and pulmonary vascula

关 键 词：肺动脉高压 生物信息学分析 差异表达基因 基因芯片 

分 类 号：R544.1[医药卫生—心血管疾病]