二叶式主动脉瓣合并升主动脉扩张的生物信息学分析

Bioinformatics analysis for bicuspid aortic valve with ascending aorta dilation

目的通过生物信息学方法探究二叶式主动脉瓣(bicuspid aortic valve,BAV)合并升主动脉扩张的关键基因及相关富集通路,寻找扩张升主动脉组织中浸润的关键免疫细胞。方法从基因表达综合数据库下载表达谱数据GSE83675(截至2022年5月12日),使用R语言筛选差异表达基因、进行基因集富集分析(gene set enrichment analysis,GSEA),应用STRING数据库及Cytoscape软件构建蛋白互作网络并筛选Hub基因,通过CIBERSORT反卷积算法计算主动脉组织中免疫细胞浸润比例。结果筛选获得19个上调基因和180个下调基因,GSEA表明主要的富集通路有细胞因子-细胞因子受体相互作用、癌症相关通路、肌动蛋白细胞骨架调节、趋化因子信号通路、丝裂原活化蛋白激酶信号通路等。基于蛋白互作网络筛选出EGFR、RIMS3、DLGAP2、RAPH1、CCNB3、CD3E、PIK3R5、TP73、PAK3、AGAP2这10个Hub基因。CIBERSORT分析表明活化自然杀伤细胞在BAV合并升主动脉扩张患者的主动脉组织中浸润较多。结论筛选出的关键基因及信号通路有助于加深对BAV合并升主动脉扩张分子机制的理解,活化自然杀伤细胞浸润可能参与了升主动脉扩张的发生发展。

Objective To explore the key genes,pathways and immune cell infiltration of bicuspid aortic valve(BAV)with ascending aortic dilation by bioinformatics analysis.Methods The data set GSE83675 was downloaded from the Gene Expression Omnibus database(up to May 12th,2022).Differentially expressed genes(DEGs)were analyzed and gene set enrichment analysis(GSEA)was conducted using R language.STRING database and Cytoscape software were used to construct protein-protein interaction(PPI)network and identify hub genes.The proportion of immune cells infiltration was calculated by CIBERSORT deconvolution algorithm.Results There were 199 DEGs identified,including19 up-regulated DEGs and 180 down-regulated DEGs.GSEA showed that the main enrichment pathways were cytokinecytokine receptor interaction,pathways in cancer,regulation of actin cytoskeleton,chemokine signaling pathway and mitogen-activated protein kinase signaling pathway.Ten hub genes(EGFR,RIMS3,DLGAP2,RAPH1,CCNB3,CD3E,PIK3R5,TP73,PAK3,and AGAP2)were identified in PPI network.CIBERSORT analysis showed that activated natural killer cells were significantly higher in dilated aorta with BAV.Conclusions These identified key genes and pathways provide new insights into BAV aortopathy.Activated natural killer cells may participate in the dilation of ascending aorta with BAV.