Thrombospondin-4 correlates with MRI measures of structural damage and pain sensitisation: a new biomarker in knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: We hypothesised thrombospondin-4 (TSP-4), a molecule mediating pain sensitisation in peripheral nerve injury, is associated with pain sensitisation in OA. METHODS: A cross-sectional study of clinical, imaging and fluid biomarkers from knee OA participants was conducted. TSP-4 was assessed by immunohistochemistry (IHC) for OA tissue samples and by ELISA in serum samples. Type II collagen degradation products (CTX-II), linked to OA structural damage, was determined from urine samples. A general linear model (GLM) was used to: a) investigate how patient-reported WOMAC (Western Ontario and McMaster Universities OsteoArthritis Index) pain/stiffness subscales and pain sensitisation measured by painDETECT, related to the Hospital Anxiety and Depression Scale (HADS), structural damage quantified from MRI and X-rays, CTX-II and TSP-4; b) how TSP-4 related to structural damage. We used linear discriminant analysis (LDA) to determine a classifier for pain-sensitisation from clinical and wet-biomarkers. RESULTS: TSP-4 was expressed in cartilage, bone marrow lesion (BML) and synovial tissue from OA samples. Upregulated TSP-4 protein was observed in cartilage, synovial tissue and BMLs in a perivascular distribution and in fibrotic tissue. Serum TSP-4 was significantly higher (p = 0.001) in those with pain sensitisation (painDETECT level ≥19) compared with non-sensitised participants. Serum TSP-4 was significantly increased with Hoffa's synovitis (p < 0.001) and number of BMLs (p < 0.001 to p < 0.05). LDA provided classification accuracy of 80 % for pain sensitisation using TSP-4, CTX-II and HADS, supporting the biopsychosocial model of pain in OA. CONCLUSION: Our data suggests TSP-4 is associated with pain sensitisation in OA and is a biomarker stratifying for pain sensitisation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".