Li Hui, Long Zhenxue, Wei Chengguang, Zhang Tingyuan, Fang Dalang, Hua Shuliang
Department of Bone and Joint Surgery, Affiliated Southwest Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi, China.
Department of Gland Surgery, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise 533000, Guangxi, China; Key Laboratory of Tumor Molecular Pathology of Baise, Baise 533000, Guangxi, China.
Cytokine. 2025 Sep;193:156988. doi: 10.1016/j.cyto.2025.156988. Epub 2025 Jun 30.
Rheumatoid arthritis (RA) and osteoarthritis (OA) are the most common joint diseases globally, posing major public health challenges. Although they are often distinguished from each other in clinical diagnoses, we hypothesize that RA and OA could have overlapping molecular pathways. Hence, this study was designed to explore the shared molecular changes and potential therapeutic targets for RA and OA. Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database (GSE51588, GSE12021 and GSE55235), which included 117 synovial membrane samples (33 healthy, 50 OA, and 34 RA). Differentially expressed genes (DEGs) were identified using the "limma" package in R, and functional enrichment analyses were conducted using Gene ontology and Kyoto Encyclopedia of Genes and Genomes frameworks. Protein-protein interaction networks were constructed through STRING, and further analyzed using GeneMANIA. Immune cell infiltration in RA and OA samples was evaluated using the CIBERSORT algorithm; microRNA-messenger RNA interactions were predicted through miRanda, miRDB, miRWalk, and TargetScan databases; and lncRNAs targets were identified via the SpongeScan database. Gene-drug interactions were analyzed using DGIdb, and the results were validated in RA and OA mouse models via immunohistochemistry and western blot. In RA and OA, 38 DEGs were identified, including 23 downregulated and 15 upregulated genes (FDR < 0.05, |log2FC| > 0), associated with key pathways such as ubiquitin-mediated proteolysis, mTOR, JAK-STAT, and Wnt signaling. Hub genes, including EIF3B, KHSRP, nucleolin (NCL), PDCD1LG2, SLC25A37, demonstrated significant differential expression (p < 0.05). In addition, the receiver operating characteristic (ROC) curve analysis indicated good diagnostic potential, with areas under the curve (AUC) values ranging from 0.795 to 0.958. Furthermore, immune cell infiltration analysis revealed significant involvement of plasma cells, T cells, monocytes, and dendritic cells (p < 0.05). Several hub genes were targeted by existing drugs, such as NCL by AS1411, and PDCD1LG2 by Pembrolizumab. In vivo validation revealed that EIF3B, KHSRP, NCL, and PDCD1LG2 were downregulated in both RA and OA mouse models compared to controls (p < 0.01), with EIF3B exhibiting higher expression in RA than in OA (p < 0.01). Mitoferrin 1 expression showed no significant differences among groups. These findings suggest that RA and OA share common molecular pathways that may serve as promising diagnostic biomarkers and therapeutic targets.
类风湿性关节炎（RA）和骨关节炎（OA）是全球最常见的关节疾病，对公共卫生构成重大挑战。尽管它们在临床诊断中常常相互区分，但我们推测RA和OA可能具有重叠的分子途径。因此，本研究旨在探索RA和OA共同的分子变化及潜在治疗靶点。转录组数据来自基因表达综合数据库（GEO）（GSE51588、GSE12021和GSE55235），其中包括117个滑膜样本（33个健康样本、50个OA样本和34个RA样本）。使用R语言中的“limma”软件包鉴定差异表达基因（DEG），并使用基因本体论和京都基因与基因组百科全书框架进行功能富集分析。通过STRING构建蛋白质-蛋白质相互作用网络，并使用GeneMANIA进行进一步分析。使用CIBERSORT算法评估RA和OA样本中的免疫细胞浸润；通过miRanda、miRDB、miRWalk和TargetScan数据库预测微小RNA-信使RNA相互作用；并通过SpongeScan数据库鉴定长链非编码RNA（lncRNA）靶点。使用DGIdb分析基因-药物相互作用，并通过免疫组织化学和蛋白质印迹在RA和OA小鼠模型中验证结果。在RA和OA中，鉴定出38个DEG，包括23个下调基因和15个上调基因（FDR < 0.05，|log2FC| > 0），这些基因与泛素介导的蛋白水解、mTOR、JAK-STAT和Wnt信号等关键途径相关。包括真核翻译起始因子3B（EIF3B）、富含AU元件的RNA结合蛋白（KHSRP）、核仁素（NCL）、程序性死亡蛋白1配体2（PDCD1LG2）、溶质载体家族25成员37（SLC25A37）在内的枢纽基因表现出显著差异表达（p < 0.05）。此外，受试者工作特征（ROC）曲线分析表明具有良好的诊断潜力，曲线下面积（AUC）值在0.795至0.958之间。此外，免疫细胞浸润分析显示浆细胞、T细胞、单核细胞和树突状细胞有显著参与（p < 0.05）。几个枢纽基因是现有药物的靶点，如AS1411靶向NCL，帕博利珠单抗靶向PDCD1LG2。体内验证显示，与对照组相比，EIF3B、KHSRP、NCL和PDCD1LG2在RA和OA小鼠模型中均下调（p < 0.01），EIF3B在RA中的表达高于OA（p < 0.01）。线粒体铁转运蛋白1的表达在各组间无显著差异。这些发现表明，RA和OA共享共同的分子途径，这些途径可能成为有前景的诊断生物标志物和治疗靶点。
