Department of Orthopedics, The Second Affiliated Hospital of Fujian Medical University, 34 Zhongshan North Road, Licheng District, Quanzhou, 362000, Fujian, China.
Suzhou University Medical Department, Suzhou, 215000, Jiangsu, China.
BMC Musculoskelet Disord. 2024 Mar 21;25(1):227. doi: 10.1186/s12891-024-07347-8.
Osteoarthritis (OA) represents a prominent etiology of considerable pain and disability, and conventional imaging methods lack sensitivity in diagnosing certain types of OA. Therefore, there is a need to identify highly sensitive and efficient biomarkers for OA diagnosis. Zinc ions feature in the pathogenesis of OA. This work aimed to investugate the role of zinc metabolism-related genes (ZMRGs) in OA and the diagnostic characteristics of key genes.
We obtained datasets GSE169077 and GSE55235 from the Gene Expression Omnibus (GEO) and obtained ZMRGs from MSigDB. Differential expression analysis was conducted on the GSE169077 dataset using the limma R package to identify differentially expressed genes (DEGs), and the intersection of DEGs and ZMRGs yielded zinc metabolism differential expression-related genes (ZMRGs-DEGs). The clusterProfiler R package was employed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of ZMRGs-DEGs. Potential small molecule drugs were predicted using the CMap database, and immune cell infiltration and function in OA individuals were analyzed using the ssGSEA method. Protein-protein interaction (PPI) networks were constructed to detect Hub genes among ZMRGs-DEGs. Hub gene expression levels were analyzed in the GSE169077 and GSE55235 datasets, and their diagnostic characteristics were assessed using receiver operating characteristic (ROC) curves. The gene-miRNA interaction network of Hub genes was explored using the gene-miRNA interaction network website.
We identified 842 DEGs in the GSE169077 dataset, and their intersection with ZMRGs resulted in 46 ZMRGs-DEGs. ZMRGs-DEGs were primarily enriched in functions such as collagen catabolic processes, extracellular matrix organization, metallopeptidase activity, and pathways like the IL-17 signaling pathway, Nitrogen metabolism, and Relaxin signaling pathway. Ten potential small-molecule drugs were predicted using the CMap database. OA patients exhibited distinct immune cell abundance and function compared to healthy individuals. We identified 4 Hub genes (MMP2, MMP3, MMP9, MMP13) through the PPI network, which were highly expressed in OA and demonstrated good diagnostic performance. Furthermore, two closely related miRNAs for each of the 4 Hub genes were identified.
4 Hub genes were identified as potential diagnostic biomarkers and therapeutic targets for OA.
骨关节炎（OA）是一种主要的病因，会引起相当大的疼痛和残疾，而常规的影像学方法在诊断某些类型的 OA 方面缺乏敏感性。因此，需要寻找高度敏感和有效的 OA 诊断生物标志物。锌离子在 OA 的发病机制中起作用。本研究旨在探讨锌代谢相关基因（ZMRGs）在 OA 中的作用以及关键基因的诊断特征。
我们从基因表达综合数据库（GEO）中获取数据集 GSE169077 和 GSE55235，并从 MSigDB 中获取 ZMRGs。使用 limma R 包对 GSE169077 数据集进行差异表达分析，以鉴定差异表达基因（DEGs），并对 DEGs 和 ZMRGs 进行交集，得到锌代谢差异表达相关基因（ZMRGs-DEGs）。使用 clusterProfiler R 包对 ZMRGs-DEGs 进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析。使用 CMap 数据库预测潜在的小分子药物，并使用 ssGSEA 方法分析 OA 个体中的免疫细胞浸润和功能。构建蛋白质-蛋白质相互作用（PPI）网络，以检测 ZMRGs-DEGs 中的枢纽基因。分析 GSE169077 和 GSE55235 数据集的枢纽基因表达水平，并使用接收者操作特征（ROC）曲线评估其诊断特征。使用基因- miRNA 相互作用网络网站探索枢纽基因的基因- miRNA 相互作用网络。
我们在 GSE169077 数据集中鉴定了 842 个 DEGs，它们与 ZMRGs 的交集产生了 46 个 ZMRGs-DEGs。ZMRGs-DEGs 主要富集在胶原分解代谢过程、细胞外基质组织、金属肽酶活性等功能，以及 IL-17 信号通路、氮代谢、松弛素信号通路等途径。使用 CMap 数据库预测了 10 种潜在的小分子药物。与健康个体相比，OA 患者的免疫细胞丰度和功能存在明显差异。通过 PPI 网络，我们鉴定了 4 个枢纽基因（MMP2、MMP3、MMP9、MMP13），它们在 OA 中高表达，具有良好的诊断性能。此外，还为每个 4 个枢纽基因鉴定了两个密切相关的 miRNA。
4 个枢纽基因被确定为 OA 的潜在诊断生物标志物和治疗靶点。
