Table_1_Six macrophage-associated genes in synovium constitute a novel diagnostic signature for osteoarthritis.xlsx

BackgroundSynovial macrophages play important roles in the formation and progression of osteoarthritis (OA). This study aimed to explore the biological and clinical significance of macrophage-associated genes (MAGs) in OA.
MethodsThe OA synovial gene expression profiles GSE89408 and GSE82107 were obtained from the GEO database. Single-sample gene set enrichment analysis (ssGSEA) and GSEA were employed to decipher differences in immune infiltration and macrophage-associated biological pathways, respectively. Protein–protein interaction (PPI) network analysis and machine learning were utilized to establish a macrophage-associated gene diagnostic signature (MAGDS). RT-qPCR was performed to test the expression of key MAGs in murine models.
ResultsOA synovium presented high levels of immune infiltration and activation of macrophage-associated biological pathways. A total of 55 differentially expressed MAGs were identified. Using PPI analysis and machine learning, a MAGDS consisting of IL1B, C5AR1, FCGR2B, IL10, IL6, and TYROBP was established for OA diagnosis (AUC = 0.910) and molecular pathological evaluation. Patients with high MAGDS scores may possess higher levels of immune infiltration and expression of matrix metalloproteinases (MMPs), implying poor biological alterations. The diagnostic value of MAGDS was also validated in an external cohort (AUC = 0.886). The expression of key MAGs was validated in a murine model using RT-qPCR. Additionally, a competitive endogenous RNA network was constructed to reveal the potential posttranscriptional regulatory mechanisms.
ConclusionsWe developed and validated a MAGDS model with the ability to accurately diagnose and characterize biological alterations in OA. The six key MAGs may also be latent targets for immunoregulatory therapy.

背景 滑膜巨噬细胞在骨关节炎（Osteoarthritis, OA）的发生与进展中发挥关键作用。本研究旨在探讨巨噬细胞相关基因（Macrophage-associated Genes, MAGs）在骨关节炎中的生物学与临床意义。
方法 从基因表达综合数据库（Gene Expression Omnibus, GEO）中获取骨关节炎滑膜基因表达谱数据集GSE89408与GSE82107。分别采用单样本基因集富集分析（Single-sample Gene Set Enrichment Analysis, ssGSEA）与基因集富集分析（Gene Set Enrichment Analysis, GSEA）解析免疫浸润与巨噬细胞相关生物学通路的差异。通过蛋白质相互作用（Protein-Protein Interaction, PPI）网络分析与机器学习方法，构建巨噬细胞相关基因诊断标签（Macrophage-associated Gene Diagnostic Signature, MAGDS）。采用逆转录实时定量聚合酶链反应（Reverse Transcription Quantitative Polymerase Chain Reaction, RT-qPCR）检测小鼠模型中关键巨噬细胞相关基因的表达水平。
结果 骨关节炎滑膜组织呈现高水平免疫浸润与巨噬细胞相关生物学通路激活。共筛选得到55个差异表达的巨噬细胞相关基因。通过蛋白质相互作用网络分析与机器学习，构建由IL1B、C5AR1、FCGR2B、IL10、IL6及TYROBP组成的巨噬细胞相关基因诊断标签，用于骨关节炎诊断（AUC = 0.910）与分子病理评估。MAGDS评分较高的患者往往伴随更高水平的免疫浸润与基质金属蛋白酶（Matrix Metalloproteinases, MMPs）表达，提示不良生物学改变。该诊断标签的诊断价值在外部验证队列中得到证实（AUC = 0.886）。采用逆转录实时定量聚合酶链反应验证了小鼠模型中关键巨噬细胞相关基因的表达水平。此外，本研究构建了竞争性内源RNA网络，以揭示潜在的转录后调控机制。
结论 本研究构建并验证了可精准诊断骨关节炎并表征其生物学改变的巨噬细胞相关基因诊断标签模型。上述6个关键巨噬细胞相关基因或可成为免疫调节治疗的潜在靶点。