生物信息学分析筛选慢性阻塞性肺疾病急性加重的关键致病基因

目的通过生物信息学分析筛选慢性阻塞性肺疾病急性加重（AECOPD）的关键致病基因。 方法从基因表达谱（GEO）数据库下载GSE60399数据集，该数据集包含AECOPD患者（AECOPD组）与健康人和稳定期慢性阻塞性肺疾病（COPD）患者（对照组）的外周血单个核细胞（PBMCs）基因数据。使用GEO2R分析工具筛选AECOPD组与对照组PBMCs的差异表达基因（DEGs）。采用DAVID 6.8数据库进行基因本体（GO）分析和京都基因与基因组百科（KEGG）富集分析。利用STRING在线数据库对DEGs编码蛋白进行蛋白质-蛋白质相互作用（PPI）网络分析，并使用Cytoscape确定前10位DEGs。 结果从GSE60399数据集中共筛选出106个DEGs，其中94个上调基因和12个下调基因。GO分析显示，106个DEGs主要涉及3条生物途径、6类细胞定位和2类细胞功能；KEGG富集分析显示，106个DEGs主要包括百日咳、补体系统、金黄色葡萄球菌感染、系统性红斑狼疮、细胞黏附分子和美洲锥虫病6条KEGG通路。PPI网络图筛选出了前10位关键DEGs，包括纤维连接蛋白1（FN1）、血管内皮生长因子A（VEGFA）、肌动蛋白α2（ACTA2）、结缔组织生长因子（CCN2）、基质金属蛋白酶2（MMP2）、齿状蛋白1（JAG1）、正常上皮细胞特异性基因（NES）、细胞角蛋白19（KRT19）、粘附素5（CDH5）、黑素瘤细胞黏附分子（MCAM），均为上调基因。 结论FN1、VEGFA、ACTA2、CCN2、MMP2、JAG1、NES、KRT19、CDH5及MCAM是AECOPD患者的关键致病基因，今后可通过深入研究这些基因来进一步阐明AECOPD发生发展的机制。

Bioinformatics analysis to screen key pathogenic genes in acute exacerbation of chronic obstructive pulmonary disease

ObjectiveTo screen key pathogenic genes in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) by bioinformatics analysis. MethodsThe GSE60399 dataset was downloaded from the gene expression omnibus (GEO). The dataset included gene data of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD (AECOPD group) versus healthy individuals and patients with stable chronic obstructive pulmonary disease (control group). The differentially expressed genes (DEGs) of PBMCs between the AECOPD group and control group were screened by the GEO2R analysis tool. Gene ontology (GO) analysis and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were performed to select DEGs using the DAVID 6.8 database. Protein-protein interaction (PPI) network analysis was constructed on DEGs encoded proteins using the STRING online database, and the Cytoscape software was used to screen the top 10 key genes. ResultsA total of 106 DEGs were identified from the GSE60399 dataset, including 94 up-regulated genes and 12 down-regulated genes. GO analysis showed that the 106 DEGs were mainly involved in three biological pathways, six types of cell localization and two types of cell functions. KEGG enrichment analysis showed that the 106 DEGs mainly comprised six KEGG pathways including pertussis, complement system, staphylococcus aureus infection, systemic lupus erythematosus, cell adhesion molecules and American trypanosomiasis. The PPI network screened out 10 key genes, including fibronectin 1 (FN1), vascular endothelial growth factor A (VEGFA), actin-alpha 2 (ACTA2), connective tissue growth factor (CCN2), matrix metalloproteinase 2 (MMP2), jagged 1 (JAG1), normal epithelial cell specific (NES), cytokeratin 19 (KRT19), cadherin 5 (CDH5) and melanoma cell adhesion molecule (MCAM), which were all up-regulated genes. ConclusionFN1, VEGFA, ACTA2, CCN2, MMP2, JAG1, NES, KRT19, CDH5 and MCAM are key pathogenic genes in patients with AECOPD, and studies on these genes can further clarify mechanisms of occurrence and development of AECOPD.