本研究旨在利用生物信息学方法鉴定类风湿关节炎（RA）滑膜巨噬细胞的候选基因，并探讨它们在RA发病机制中的途径。我们从基因表达数据库中获取GSE10500和GSE97779的微阵列数据，并对14名RA患者和8名健康供者的滑膜巨噬细胞进行分析。研究人员使用R软件鉴定差异表达基因，并确定功能富集途径。然后使用STRING和Cytoscape构建蛋白质相互作用网络。基因表达验证使用GSE71370数据集和RT-qPCR分析。与正常样本相比，我们在RA滑膜巨噬细胞中确定了102个差异表达基因（DEGs）。其中，72个上调，30个下调。GO和KEGG途径分析表明，DEGs主要调控免疫应答以及与炎症激活、凋亡和癌症相关的信号通路。来自DEGs蛋白质相互作用网络的前五个中心基因和前1个基因模块是VEGFA、MMP9、FN1、IGF1、CXCL9、ISG20、RSAD2、IFI27、GBP2和GBP1。GSE71370数据集和RT-qPCR分析显示，CXCL9和GBP1的上调显著（P ≤ .05）。CXCL9和GBP1可能对RA发病机制发挥作用，并作为RA的潜在生物标志物和治疗靶点。

This study sought to identify candidate genes of rheumatoid arthritis (RA) synovial macrophages using bioinformatics and to explore their pathways in the pathogenesis of RA.The microarray datasets GSE10500 and GSE97779 were obtained from the Gene Express Omnibus and analyzed with synovial macrophages of 14 RA patients and 8 healthy donors. The researchers used R software to identify differentially expressed genes and determine functional enrichment pathways. A protein-protein interaction network was then constructed using STRING and Cytoscape. Gene expression was validated with the GSE71370 dataset and RT-qPCR analysis.102 DEGs were identified in RA synovial macrophages relative to normal samples. Of these, 72 were upregulated; 30 were downregulated. GO and KEGG pathway analyses suggested that DEGs mainly regulated the immune response and signaling pathways associated with inflammatory activation, apoptosis, and cancer. The top five hub genes and top 1 gene module from the PPI network of DEGs were VEGFA, MMP9, FN1, IGF1, CXCL9, ISG20, RSAD2, IFI27, GBP2, and GBP1. The GSE71370 dataset and RT-qPCR analysis showed that CXCL9 and GBP1 were significantly upregulated (P ≤ .05).CXCL9 and GBP1 may contribute to RA pathogenesis and serve as potential biomarkers and therapeutic targets for RA.