基于生物信息学分析筛选镍变应性接触性皮炎的关键基因

Screening Key Genes for Nickel Allergic Contact Dermatitis Based on Bioinformatics Method

目的利用生物信息学方法分析镍变应性接触性皮炎(Ni-ACD)皮损与正常皮肤的差异基因,筛选关键基因,并进行治疗药物预测。方法由基因表达数据库(GEO)检索得到GSE60028及GSE168735数据集,采用R语言对数据进行校正、筛选差异表达基因、基因本体(GO)功能分析和京都基因与基因组百科全书数据库(KEGG)通路富集分析,并对2个数据集交集的差异基因进行蛋白-蛋白相互作用(PPI)分析,通过Cytoscape分析得到关键基因,将12个关键基因输入Connectivity Map(CMap)中预测治疗Ni-ACD的潜在化合物。结果本研究筛选获得GSE60028和GSE168735数据集交集差异表达基因417个,关键基因MX1、ISG15、IRF7、XAF1、BST2、IRF1、IFI35、OAS2、RSAD2、IFIT3、ISG20和OASL共12个。GO及KEGG分析结果表明,差异表达基因主要参与白细胞的细胞-细胞黏附、细胞因子介导的信号通路、白细胞迁移、T细胞激活的调节和白细胞的细胞-细胞黏附的调节等生物过程,主要富集在细胞因子及免疫相关通路上。预测得到10种化合物,可能对Ni-ACD具有潜在的治疗作用。结论本研究基于生物信息学方法筛选Ni-ACD关键基因,并预测潜在的治疗药物,为临床及药物研究提供参考。

Objective To analyze the key genes between nickel allergic contact dermatitis(Ni-ACD)lesions and normal skin,screen the key genes,and make therapeutic drug predictions using bioinformatics methods.Methods The GSE60028 and GSE168735 datasets were retrieved from the gene expression omnibus(GEO)database.R language was used to correct the data,screen for differentially expressed genes,analyze for gene ontology(GO)function and perform Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis.Protein-protein interaction(PPI)analysis of the common differentially expressed genes were performed in the two datasets.Next,the key genes were obtained by Cytoscape analysis.Finally,the 12 key genes were entered into Connectivity Map to predict potential compounds for the treatment of Ni-ACD.Results A total of 417 common differentially expressed genes were obtained from the intersection of GSE60028 and GSE168735 datasets and 12 key genes(MX1,ISG15,IRF7,XAF1,BST2,IRF1,IFI35,OAS2,RSAD2,IFIT3,I SG20,and OASL)were screened in the study.GO and KEGG analysis showed that the common differentially expressed genes were mainly involved in biological processes such as leukocyte cell-cell adhesion,cytokine-mediated signaling pathway,leukocyte migration,regulation of T cell activation and regulation of leukocyte cell-cell adhesion were mainly enriched in cytokines as well as immune-related pathways.In addition,ten compounds were predicted to have potential therapeutic effects on Ni-ACD.Conclusion This study was based on bioinformatics approach to screen the key genes of Ni-ACD and to predict the potential therapeutic drugs,which can provide reference for clinical and drug research.