ArticleJournal of multidisciplinary healthcare2025
Integrated Bioinformatics and Experimental Validation Reveal Macrophage Polarization-Related Biomarkers for Osteoarthritis Diagnosis.
Article in Journal of multidisciplinary healthcare, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Investigating the mechanisms by which bisphenol A affects osteoarthritis through a novel network toxicology framework and experimental validation.BMC pharmacology & toxicology · 2026Article
- Elucidating the mechanisms by which acetyl tributyl citrate affects fracture healing: a comprehensive network toxicology study.BMC pharmacology & toxicology · 2026Article
- GeneCytNet: an interpretable deep learning framework for rheumatoid arthritis classification andFrontiers in immunology · 2026Article
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Authors and funding
9 authors.
Funding
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Abstract
Purpose: Osteoarthritis (OA) is the most common type of arthritis and early detection is crucial to improving prognosis. In this study, we identified crucial genes associated with macrophage polarization in OA and constructed a diagnostic model to provide novel insights for diagnostic and therapeutic strategies. Methods: The GSE55235 and GSE55457 datasets were merged through the GEO database to identify genes related to macrophage polarization by conducting weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Least absolute shrinkage and selection operator (LASSO), random forest (RF), and support vector machine recursive feature elimination (SVM-RFE) algorithms were used to identify hub genes and construct a diagnostic model validated through internal datasets and multiple external bulk RNA-seq and single-cell RNA-seq data. Additionally, various analyses, including immune infiltration, gene set enrichment analysis, competing endogenous RNA (ceRNA) construction, and drug prediction, were conducted. Finally, clinical samples were clinically validated through RT-qPCR (OA: Control = 10: 5) and IHC (6: 5) experiments. Results: Three hub genes (MYC, SIK1, and NFIL3) were identified, and the diagnostic model constructed using them demonstrated good diagnostic efficacy in both internal and external datasets (internal AUC = 0.965, external AUC = 0.847). In vitro experiments revealed that the hub genes in the synovial tissue of OA patients were significantly down-regulated ( Conclusion: We constructed an OA diagnostic model related to macrophage polarization through comprehensive bioinformatics analysis, and the results indicated that these genes have high diagnostic value. However, further clinical studies and experimental assessments are needed to validate these findings.
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