摘要
目的:从基因层面分析挖掘钙化性主动脉瓣疾病(CAVD)的差异表达基因,为其提供新的治疗靶点。方法:基于GEO数据库,获取钙化主动脉瓣膜及非钙化主动脉瓣膜的表达谱数据,利用R软件筛选两者相关差异表达基因(DEGs)。利用DAVID和KEGG数据库对表达上调的DEGs进行功能富集分析。同时,通过STRING数据库构建上述相关DEGs的蛋白互作网络(PPI)。最后,挑选出PPI得分最高的模块基因与已报道与CAVD相关的基因取交集,并在临床标本中进行验证。结果:3个数据集共筛选出49个表达上调DEGs。构建PPI网络中模块得分最高的基因和已报道的相关基因取交集获得6个核心基因,包括OPN、MMP1、MMP9、CCR5、DPP4和Runx2。结论:利用生物信息学方法对钙化瓣膜与非钙化瓣膜进行差异表达基因的分析,可有效挖掘参与CAVD进程的关键调控基因,为CAVD提供新的药物靶点和诊疗思路。
Objective:To explore the differentially expressed genes(DEGs)in calcific aortic valve disease(CAVD)for new therapeutic approach.Methods:The expression profiles of calcific and normal aortic valves were obtained from Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified using R software.Functional enrichment analysis of DEGs was conducted by the Database for Annotation,Visualization and Integrated Discovery(DAVID)and Kyoto encyclopedia of genes and genomes(KEGG).Next,a protein-protein interaction(PPI)network was formed on the Search Tool for the Retrieval of Interacting Genes/Proteins(STRING),and the hub genes were screened out with the highest PPI-score.Finally,the hub genes were compared with those already reported CAVD-related genes to get the common genes,and the common ones would be verified in the clinical samples.Results:A total of 49 DEGs were identified from three datasets.Six genes including OPN、MMP1、MMP9、CCR5、DPP4 and Runx2 were screened out by the intersection of the genes with highest PPI-score and those already reported CAVDrelated.Conclusion:Bioinformatics can analyze DEGs in calcific and normal aortic valves,effectively identifying the hub genes related to the course of CAVD,which provides a new drug target as well as a diagnostic and therapeutic method of CAVD.
作者
朱恩谊
吴晓英
聂如琼
ZHU En-yi;WU Xiao-ying;NIE Ru-qiong(The Department of Cardiology,Sun Yat-sen Memorial Hospital of Sun Yat-sen University,510120)
出处
《岭南急诊医学杂志》
2019年第2期136-140,共5页
Lingnan Journal of Emergency Medicine
基金
国家自然科学基金面上项目(81370309)
关键词
钙化性主动脉瓣疾病
生物信息学
差异表达基因
calcific aortic valve disease
bioinformatics
differentially expressed genes
