ArticleBone & joint research2020
Synovial fluid fingerprinting in end-stage knee osteoarthritis: a novel biomarker concept.
Article in Bone & joint research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Functional Attributes of Synovial Fluid from Osteoarthritic Knee Exacerbate Cellular Inflammation and Metabolic Stress, and Fosters Monocyte to Macrophage Differentiation.Biomedicines · 2025Article
- Combined multi-omics approach to identify the key metabolites, key microorganisms and biomarkers correlated with the neutrophil extracellular traps-associated gene TIMP1 in osteoarthritis.Frontiers in pharmacology · 2025Article
- Article
- Decreased Peli1 expression attenuates osteoarthritis by protecting chondrocytes and inhibiting M1-polarization of macrophages.Bone & joint research · 2023Article
- Molecular crosstalk between articular cartilage, meniscus, synovium, and subchondral bone in osteoarthritis.Bone & joint research · 2022Article
- ATF3 as a potential diagnostic marker of early-stage osteoarthritis and its correlation with immune infiltration through bioinformatics analysis.Bone & joint research · 2022Article
- Effect of a single intra-articular administration of stanozolol in a naturally occurring canine osteoarthritis model: a randomised trial.Scientific reports · 2022Article
- Tert-butylhydroquinone attenuates osteoarthritis by protecting chondrocytes and inhibiting macrophage polarization.Bone & joint research · 2021Article
- Diabetes - osteoarthritis and joint pain.Bone & joint research · 2021Article
- Signalling and putative therapeutic molecules on the regulation of synoviocyte signalling in rheumatoid arthritis.Bone & joint research · 2021Article
- Monocytes, Macrophages, and Their Potential Niches in Synovial Joints - Therapeutic Targets in Post-Traumatic Osteoarthritis?Frontiers in immunology · 2021Review
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
aimsThe lack of disease-modifying treatments for osteoarthritis (OA) is linked to a shortage of suitable biomarkers. This study combines multi-molecule synovial fluid analysis with machine learning to produce an accurate diagnostic biomarker model for end-stage knee OA (esOA).
methodsSynovial fluid (SF) from patients with esOA, non-OA knee injury, and inflammatory knee arthritis were analyzed for 35 potential markers using immunoassays. Partial least square discriminant analysis (PLS-DA) was used to derive a biomarker model for cohort classification. The ability of the biomarker model to diagnose esOA was validated by identical wide-spectrum SF analysis of a test cohort of ten patients with esOA.
resultsPLS-DA produced a streamlined biomarker model with excellent sensitivity (95%), specificity (98.4%), and reliability (97.4%). The eight-biomarker model produced a fingerprint for esOA comprising type IIA procollagen N-terminal propeptide (PIIANP), tissue inhibitor of metalloproteinase (TIMP)-1, a disintegrin and metalloproteinase with thrombospondin motifs 4 (ADAMTS-4), monocyte chemoattractant protein (MCP)-1, interferon-γ-inducible protein-10 (IP-10), and transforming growth factor (TGF)-β3. Receiver operating characteristic (ROC) analysis demonstrated excellent discriminatory accuracy: area under the curve (AUC) being 0.970 for esOA, 0.957 for knee injury, and 1 for inflammatory arthritis. All ten validation test patients were classified correctly as esOA (accuracy 100%; reliability 100%) by the biomarker model.
conclusionSF analysis coupled with machine learning produced a partially validated biomarker model with cohort-specific fingerprints that accurately and reliably discriminated esOA from knee injury and inflammatory arthritis with almost 100% efficacy. The presented findings and approach represent a new biomarker concept and potential diagnostic tool to stage disease in therapy trials and monitor the efficacy of such interventions.Cite this article:
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