Table_3_Identification of Common Differentially Expressed Genes and Potential Therapeutic Targets in Ulcerative Colitis and Rheumatoid Arthritis.XLSX

Ulcerative colitis (UC) and rheumatoid arthritis (RA) are immune-mediated inflammatory diseases (IMIDs) with similar symptoms and common genomics. However, the relationship between UC and RA has not been investigated thoroughly. Therefore, this study aimed to establish the differentially expressed genes (DEGs) and potential therapeutic targets in UC and RA. Three microarray datasets (GSE38713, GSE1919, and GSE12251) were selected from the Gene Expression Omnibus (GEO) database for analysis. We used R software to identify the DEGs and performed enrichment analyses. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Cytoscape software were used to construct the protein-protein interaction (PPI) network and identify the hub genes. A regulatory network based on the constructed PPI was generated using StarBase and PROMO databases. We identified a total of 1542 and 261 DEGs in UC and RA. There were 169 common DEGs identified in both UC and RA, including 63 upregulated genes (DEGs1) and nine downregulated genes (DEGs2). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of DEGs1 and DEGs2 in the PPI network revealed that the genes enriched were involved in immunity. A total of 45 hub genes were selected based on high scores of correlation; three hub genes (SRGN, PLEK, and FCGR3B) were found to be upregulated in UC and RA, and downregulated in UC patients with response to infliximab treatment. The identification of novel DEGs and hub genes in the current study contributes to a novel perception for latent functional mechanisms and presents potential prognostic indicators and therapeutic targets in UC and RA.

溃疡性结肠炎（Ulcerative colitis, UC）与类风湿关节炎（rheumatoid arthritis, RA）均为免疫介导的炎症性疾病（immune-mediated inflammatory diseases, IMIDs），二者症状相似且共享基因组学特征。但目前二者之间的关联尚未得到全面深入的研究。因此本研究旨在明确溃疡性结肠炎与类风湿关节炎中的差异表达基因（differentially expressed genes, DEGs）及潜在治疗靶点。本研究从基因表达综合数据库（Gene Expression Omnibus, GEO）中选取了3个微阵列数据集（GSE38713、GSE1919及GSE12251）用于分析。我们使用R软件筛选差异表达基因并开展富集分析，借助STRING数据库（Search Tool for the Retrieval of Interacting Genes/Proteins）与Cytoscape软件构建蛋白质相互作用（protein-protein interaction, PPI）网络并筛选核心基因，同时利用StarBase与PROMO数据库构建基于该PPI网络的调控网络。本研究分别在溃疡性结肠炎与类风湿关节炎中筛选出1542个和261个差异表达基因，二者共有169个共同差异表达基因，其中包括63个上调差异表达基因（DEGs1）与9个下调差异表达基因（DEGs2）。对PPI网络中的DEGs1与DEGs2进行基因本体（Gene Ontology, GO）及京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）通路富集分析后发现，富集得到的基因均参与免疫过程。基于较高的关联评分，本研究共筛选出45个核心基因。其中3个核心基因（SRGN、PLEK及FCGR3B）在溃疡性结肠炎与类风湿关节炎中均呈上调表达，而在对英夫利昔单抗（infliximab）治疗有应答的溃疡性结肠炎患者中则呈下调表达。本研究筛选得到的新型差异表达基因与核心基因，为阐释溃疡性结肠炎与类风湿关节炎潜在的功能机制提供了全新视角，同时也为二者的预后评估及治疗靶点开发提供了潜在候选方向。