【摘要】 目的 通过生物信息学分析，从基因表达数据库(GEO)数据集中筛选出肺动脉高压(PAH)的关键基因，并探索其潜在的生物学功能和信号通路。方法 下载GSE15197数据集，利用GEO2R识别差异表达基因(DEGs),通过加权基因共表达网络分析(WGCNA)识别与PAH相关性最大的模块，采用Venn图鉴别共表达的交集基因，对交集基因进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)富集通路分析，构建蛋白质相互作用网络(PPI),利用Cytosccape进行可视化并识别关键基因。结果 共识别出1677个DEGs,鉴定出198个交集基因，利用Cytosccape筛选出10个得分最高的关键基因。RT-PCR结果显示，CHUK、ANK2、PPP2CA在PAH患者外周血单核细胞和MCT诱导的PAH大鼠肺泡巨噬细胞中的mRNA表达量增高。结论 通过生物信息学分析筛选出与PAH相关的关键基因，为PAH的防治提供可靠的生物标志物。更多还原

【Abstract】 Objective To screen key genes of pulmonary arterial hypertension(PAH) from the dataset of gene expression omnibus(GEO), and to explore their potential biological functions and signaling pathways through bioinformatics analysis. Methods GSE15197 dataset was downloaded, GEO2R was used to identify differentially expressed genes(DEGs), and weighted correlation network analysis(WGCNA) was used to identify module with the highest correlation with PAH. Venn diagram was used to identify co-expressed intersecting genes, perform gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG) enrichment pathway analysis on intersecting genes, and construct protein-protein interaction(PPI). In addition, key genes were visualized and identified by Cytosccape. Results A total of 1677 DEGs were identified, 198 intersecting genes were identified, and 10 key genes with the highest scores were screened by Cytoscape. RT-PCR results showed that the mRNA expression levels of CHUK, ANK2, and PPP2CA increased in the peripheral blood mononuclear cells of PAH patients and pulmonary alveolar macrophages induced by MCT in PH rats. Conclusion Screening key genes related to PAH through bioinformatics analysis can provide reliable biomarkers for the prevention and treatment of PAH.更多还原