Wu Liming, Wen Disheng, Wang Weizhou, Wang Yanghao, Zhang Li
Department of Orthopedics, Sichuan Santai County People's Hospital, Mianyang, China.
Department of Orthopedics (Fourth), Dali Bai Autonomous Prefecture People's Hospital, Dali, China.
Front Med (Lausanne). 2025 Jul 2;12:1518580. doi: 10.3389/fmed.2025.1518580. eCollection 2025.
Osteoarthritis (OA) is the most common joint disorder and a leading cause of disability in the older adult. Early diagnosis and treatment are crucial for effective disease management and improved outcomes. This study aims to identify key genes involved in OA progression using bioinformatics, which may serve as diagnostic biomarkers and therapeutic targets.
Synovial tissue sequencing data (GSE1919, GSE55235, GSE82107) were retrieved from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were analyzed using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analysis. ROC curve analysis was used to assess diagnostic potential, and results were validated using the GSE29746 dataset and synovial tissues from five OA patients and controls.
A total of 33 common DEGs were identified across three datasets. Four hub genes (CXCL8, CXCL2, DUSP5, TNFSF11) showed high diagnostic potential [area under the receiver operating characteristic curve (AUC) > 0.8]. These genes were also linked to potential therapeutic agents, including lipopolysaccharide and acetaminophen.
CXCL8, CXCL2, DUSP5, and TNFSF11 represent novel multi-functional biomarkers that advance OA research by addressing two critical limitations of prior biomarker studies: (1) overcoming the diagnostic inadequacy of single-biomarker approaches through synergistic clusters, and (2) revealing an unreported integrative mechanism linking inflammatory pathways (CXCL8/2) and bone remodeling processes (TNFSF11/DUSP5). This dual diagnostic-therapeutic potential significantly expands the clinical applicability of OA biomarkers.
骨关节炎（OA）是最常见的关节疾病，也是老年人残疾的主要原因。早期诊断和治疗对于有效的疾病管理和改善预后至关重要。本研究旨在利用生物信息学确定参与OA进展的关键基因，这些基因可作为诊断生物标志物和治疗靶点。
从基因表达综合数据库（GEO）中检索滑膜组织测序数据（GSE1919、GSE55235、GSE82107）。使用基因本体论（GO）、京都基因与基因组百科全书（KEGG）和蛋白质-蛋白质相互作用（PPI）网络分析来分析差异表达基因（DEG）。采用ROC曲线分析评估诊断潜力，并使用GSE29746数据集以及来自五名OA患者和对照的滑膜组织进行结果验证。
在三个数据集中共鉴定出33个常见的DEG。四个枢纽基因（CXCL8、CXCL2、DUSP5、TNFSF11）显示出较高的诊断潜力[受试者操作特征曲线下面积（AUC）>0.8]。这些基因还与潜在的治疗药物相关，包括脂多糖和对乙酰氨基酚。
CXCL8、CXCL2、DUSP5和TNFSF11代表了新型多功能生物标志物，通过解决先前生物标志物研究的两个关键局限性推动了OA研究：（1）通过协同聚类克服单生物标志物方法的诊断不足；（2）揭示一种未报道的整合机制，将炎症途径（CXCL8/2）与骨重塑过程（TNFSF11/DUSP5）联系起来。这种双重诊断治疗潜力显著扩展了OA生物标志物的临床适用性。
