Hedgehog inhibits β-catenin activity in synovial joint development and osteoarthritis
Bibliographic record
Abstract
Both the WNT/β-catenin and hedgehog signaling pathways are important in the regulation of limb development, chondrocyte differentiation, and degeneration of articular cartilage in osteoarthritis (OA). It is not clear how these signaling pathways interact in interzone cell differentiation and synovial joint morphogenesis. Here, we determined that constitutive activation of hedgehog signaling specifically within interzone cells induces joint morphological changes by selectively inhibiting β-catenin-induced Fgf18 expression. Stabilization of β-catenin or treatment with FGF18 rescued hedgehog-induced phenotypes. Hedgehog signaling induced expression of a dominant negative isoform of TCF7L2 (dnTCF7L2) in interzone progeny, which may account for the selective regulation of β-catenin target genes observed. Knockdown of TCF7L2 isoforms in mouse chondrocytes rescued hedgehog signaling-induced Fgf18 downregulation, while overexpression of the human dnTCF7L2 orthologue (dnTCF4) in human chondrocytes promoted the expression of catabolic enzymes associated with OA. Similarly, expression of dnTCF4 in human chondrocytes positively correlated with the aggrecanase ADAMTS4. Consistent with our developmental findings, activation of β-catenin also attenuated hedgehog-induced or surgically induced articular cartilage degeneration in mouse models of OA. Thus, our results demonstrate that hedgehog inhibits selective β-catenin target gene expression to direct interzone progeny fates and articular cartilage development and disease. Moreover, agents that increase β-catenin activity have the potential to therapeutically attenuate articular cartilage degeneration as part of OA.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".