The TLR-M-CSF axis is implicated in increased bone turnover and curve progression in adolescent idiopathic scoliosis
Bibliographic record
Abstract
BACKGROUND: Facet joint osteoarthritis (OA) is prevalent in patients with adolescent idiopathic scoliosis (AIS). The most pronounced OA presents above and below the curve's apex where the intervertebral rotation is the greatest. This indicates that facet joint OA is implicated and potentially contributes to AIS progression. OA impacts both cartilage and bone and we have previously demonstrated an association between lower bone quality and more severe OA in AIS facet joints. This study aimed to further investigate the molecular mechanisms underlying cartilage-bone crosstalk in the facet joints of patients with AIS. METHODS: Unbiased deep RNA sequencing was performed to compare gene expression in facet joint chondrocytes of age-matched AIS patients and non-scoliotic individuals. Differentially expressed genes of interest were validated through qPCR and ELISA in a larger sample cohort. Key regulatory pathways involved in cartilage-bone crosstalk were identified through bioinformatic analysis. Functional studies were conducted by treating chondrocytes with TLR2 and TLR4 agonists, collecting conditioned media, and administering it to an in vitro osteoclastogenesis model. The expression of M-CSF, a key regulatory factor influencing osteoclast proliferation, was measured in individual facet joint cartilage samples at different spinal levels and correlated with cartilage morphological grade and 3D structural parameters extracted from spine reconstruction. RESULTS: One thousand four hundred twenty six upregulated genes were detected, and gene ontology analysis revealed a significant enrichment of the TLR pathway, and bone-regulating biological processes in AIS chondrocytes. TLR activation of AIS chondrocytes induced expression of bone-regulating factors, including M-CSF, a key regulator of osteoclast proliferation. Furthermore, secreted factors from AIS chondrocytes enhanced osteoclast proliferation and maturation, with a stronger effect observed following TLR pre-activation. Clinically, M-CSF expression was found to correlate strongly with increased OA severity and a greater degree of intervertebral axial rotation. CONCLUSIONS: Together, our findings suggest that the TLR-M-CSF axis is implicated in osteoclastogenesis, resulting in increased bone turnover and may contribute to curve progression in AIS patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".