ArticleScientific reports2021
Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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Who cites it
33 citing papers in PubMed, 48 citations in OpenAlex.
- The Role of Myeloperoxidase in Osteoarthritis and Its Potential Modulation by Resveratrol: An Integrated Study.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Glioma biomarker analysis and drug targeting prediction based on ferroptosis-related genes.Medicine · 2026Article
- Exploring the Toxicological Effects of Acetyl Tributyl Citrate Exposure on Osteoarthritis Based on Machine Learning, Network Toxicology and Molecular Docking Analysis.Open access rheumatology : research and reviews · 2026Article
- Paradigm shift in macrophage polarization in osteoarthritis: from M1/M2 imbalance to macrophage state reprogramming in the ageing immune microenvironment.Frontiers in immunology · 2026Review
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- Integrating bioinformatics and machine learning to identify biomarkers of branched chain amino acid related genes in osteoarthritis.BMC musculoskeletal disorders · 2025Article
- Bladder cancer biomarker analysis and drugtarget prediction based on pyroptosis-related genes.Discover oncology · 2025Article
- Identification of ferroptosis-related genes and potential drugs in osteoarthritis.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2025Article
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- Complement-mediated and direct activation of human neutrophils induced byFrontiers in immunology · 2025Article
- Integrated multi-omics and machine learning reveals immune-metabolic signatures in osteoarthritis: from bulk RNA-seq to single-cell resolution.Frontiers in immunology · 2025Article
- Identify the potential target of efferocytosis in knee osteoarthritis synovial tissue: a bioinformatics and machine learning-based study.Frontiers in immunology · 2025Article
- From essential basic understanding to clinical application - biological, physical and pathophysiological principles of (low-dose) radiotherapy in benign diseases.Frontiers in immunology · 2025Review
- CDC42 deficiency leads to endometrial stromal cell senescence in recurrent implantation failure.Human reproduction (Oxford, England) · 2024Article
- Role of signaling pathways in age-related orthopedic diseases: focus on the fibroblast growth factor family.Military Medical Research · 2024Review
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- Mendelian randomization and transcriptome analysis identified immune-related biomarkers for osteoarthritis.Frontiers in immunology · 2024Article
- Responding to ACL Injury and its Treatments: Comparative Gene Expression between Articular Cartilage and Synovium.Bioengineering (Basel, Switzerland) · 2023Article
- Identification ofAnnals of translational medicine · 2023Article
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Authors and funding
11 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.
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