Osteoarthritis (OA) is a chronic musculoskeletal disease affecting approximately 500 million people worldwide. Globally, OA is one of the most common and leading causes of disability. Several genetic factors are involved in OA, including inherited genes, genetic susceptibility, and genetic predisposition. As the pathogenesis of OA is unknown, there are almost no effective treatments available to prevent the onset or progression of the disease. In recent years, many researchers focused on bioinformatics analysis to explore new biomarkers for the diagnosis, treatment, and prognosis of human diseases. In this work, we obtain the traditional RNA sequencing data of OA patients from the GEO database. By performing the differentially expressed analysis, we successfully obtain the genes that are closely associated with the OA. In addition, the Venn diagram was applied to evaluate the genes that are involved in OA and immune-related genes. The protein-protein interaction analysis was further conducted to explore the hub genes. The single-cell RNA sequencing analysis was used to evaluate the expression distribution of the MMP, VEGFA, SPI1, and IRF8 in synovial tissues of patients with osteoarthritis. Finally, the GSVA enrichment analysis discovered the potential pathways involved in OA patients. Our analysis provides a new direction for the exploration of the process of OA patients. In addition, VEGFA may be considered a promising biomarker in OA.

骨关节炎 (OA) 是一种慢性肌肉骨骼疾病，影响全球约 5 亿人。在全球范围内，骨关节炎是导致残疾的最常见和主要原因之一。OA 涉及多种遗传因素，包括遗传基因、遗传易感性和遗传易感性。由于 OA 的发病机制尚不清楚，几乎没有有效的治疗方法可以预防该疾病的发作或进展。近年来，许多研究人员致力于生物信息学分析，探索新的生物标志物用于人类疾病的诊断、治疗和预后。在这项工作中，我们从GEO数据库中获取了OA患者的传统RNA测序数据。通过差异表达分析，我们成功获得了与OA密切相关的基因。此外，还应用维恩图来评估与 OA 相关的基因和免疫相关基因。进一步进行蛋白质-蛋白质相互作用分析以探索枢纽基因。采用单细胞RNA测序分析评估骨关节炎患者滑膜组织中MMP、VEGFA、SPI1、IRF8的表达分布。最后，GSVA 富集分析发现了 OA 患者中涉及的潜在途径。我们的分析为探索 OA 患者的发病过程提供了新的方向。此外，VEGFA 可能被认为是 OA 中一个有前途的生物标志物。