Sun Yuxin, Cai Daxing, Hu Weitao, Fang Taiyong
Department of Gastroenterology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Department of Rheumatology, The Second Affiliated Hospital of Fujian Medical University, Quanzhou, Fujian, China.
Front Genet. 2022 Aug 31;13:950136. doi: 10.3389/fgene.2022.950136. eCollection 2022.
Crohn's disease (CD) is a disease that manifests mainly as chronic inflammation of the gastrointestinal tract, which is still not well understood in terms of its pathogenesis. The aim of this study was to use bioinformatics analysis to identify differentially expressed genes (DEGs) and miRNAs with diagnostic and therapeutic potential in CD. Three CD datasets (GSE179285, GSE102133, GSE75214) were downloaded from the Gene Expression Omnibus (GEO) database. DEGs between normal and CD tissues were identified using the GEO2R online tool. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were conducted using the clusterProfiler function in the R package. Protein-protein interaction network (PPI) analysis and visualization were performed with STRING and Cytoscape. Ten hub genes were identified using cytoHubba's MCC algorithm and validated with datasets GSE6731 and GSE52746. Finally, the miRNA gene regulatory network was constructed by Cytoscape and NetworkAnalyst to predict potential microRNAs (miRNAs) associated with DEGs. A total of 97 DEGs were identified, consisting of 88 downregulated genes and 9 upregulated genes. The enriched functions and pathways of the DEGs include immune system process, response to stress, response to cytokine and extracellular region. KEGG pathway analysis indicates that the genes were significantly enriched in Cytokine-cytokine receptor interaction, IL-17 signaling pathway, Rheumatoid arthritis and TNF signaling pathway. In combination with the results of the protein-protein interaction (PPI) network and CytoHubba, 10 hub genes including IL1B, CXCL8, CXCL10, CXCL1, CXCL2, CXCL5, ICAM1, IL1RN, TIMP1 and MMP3 were selected. Based on the DEG-miRNAs network construction, 5 miRNAs including hsa-mir-21-5p, hsa-mir-93-5p, hsa-mir-98-5p, hsa-mir-1-3p and hsa-mir-335-5p were identified as potential critical miRNAs. In conclusion, a total of 97 DEGs, 10 hub genes and 5 miRNAs that may be involved in the progression or occurrence of CD were identified in this study, which could be regarded as biomarkers of CD.
克罗恩病(CD)是一种主要表现为胃肠道慢性炎症的疾病,其发病机制仍未完全明确。本研究旨在通过生物信息学分析,鉴定出在克罗恩病中具有诊断和治疗潜力的差异表达基因(DEGs)和miRNAs。从基因表达综合数据库(GEO)下载了三个克罗恩病数据集(GSE179285、GSE102133、GSE75214)。使用在线工具GEO2R鉴定正常组织与克罗恩病组织之间的差异表达基因。利用R包中的clusterProfiler函数对差异表达基因进行基因本体(GO)术语和京都基因与基因组百科全书(KEGG)通路富集分析。使用STRING和Cytoscape进行蛋白质-蛋白质相互作用网络(PPI)分析和可视化。使用cytoHubba的MCC算法鉴定出10个枢纽基因,并用数据集GSE6731和GSE52746进行验证。最后,通过Cytoscape和NetworkAnalyst构建miRNA基因调控网络,以预测与差异表达基因相关的潜在微小RNA(miRNAs)。共鉴定出97个差异表达基因,其中88个基因下调,9个基因上调。差异表达基因的富集功能和通路包括免疫系统过程、应激反应、细胞因子反应和细胞外区域。KEGG通路分析表明,这些基因在细胞因子-细胞因子受体相互作用、IL-17信号通路、类风湿性关节炎和TNF信号通路中显著富集。结合蛋白质-蛋白质相互作用(PPI)网络和CytoHubba的结果,选择了包括IL1B、CXCL8、CXCL10、CXCL1、CXCL2、CXCL5、ICAM1、IL1RN、TIMP1和MMP3在内的10个枢纽基因。基于差异表达基因-微小RNA网络构建,鉴定出包括hsa-mir-21-5p、hsa-mir-93-5p、hsa-mir-98-5p、hsa-mir-1-3p和hsa-mir-335-5p在内的5个微小RNA为潜在的关键微小RNA。总之,本研究共鉴定出97个可能参与克罗恩病进展或发生的差异表达基因、10个枢纽基因和5个微小RNA,它们可被视为克罗恩病的生物标志物。