Global gene expression analyses in early experimental osteoarthritis reveal novel players in articular cartilage degenerations
Bibliographic record
Abstract
Introduction: Articular cartilage degeneration is a hallmark of osteoarthritis (OA). We sought to identify dysregulated genes in degenerating cartilage and hypothesized that altered growth factor expression causes cartilage degradation in OA. Methods: Genome-wide microarray analysis of RNA harvested directly from sham (control) and degenerating articular cartilage was performed using our previously characterized pre-clinical rat model of knee OA1. Known OA genes were validated using RNA samples (real-time PCR) and histological sections (immunofluorescence) from independent animals. Functional studies in chondrocytes and articular cartilage explants investigated the effects of one identified factor (transforming growth factor alpha (TGF-α)) on cartilage degeneration. The effects of TGF-α on primary chondrocyte morphology, proliferation, gene expression, and SOX9 transcription factor expression were assessed. Results: Dysregulated gene expression profiles in degenerating cartilage included known OA genes2. Microarray expression profiles were consistently validated at RNA and protein levels by alternative methods. Several genes previously unstudied in OA cartilage were upregulated, including growth factors (e.g. TGF-α and kit ligand), cell surface receptors (e.g. endothelin type A receptor), and proteases (e.g. cathepsin S). Functional studies demonstrated that TGF-α alters chondrocyte morphology through re-organization of the actin cytoskeleton. TGF-α also stimulated primary chondrocyte proliferation and chondrocyte cluster formation in cartilage explants. Chondrocyte expression of anabolic genes and total collagen protein levels were reduced by TGF-α, while expression of catabolic factors increased. Finally, TGF-α reduced both the expression of total SOX9 and levels of phosphorylated (active) SOX9. Conclusions: Our microarray study identified numerous factors previously unstudied in OA cartilage, including increased levels of TGF-α. Functional studies determined that TGF-α promotes cartilage degeneration through chondrocyte proliferation and catabolic factor expression. Further, TGF-α inhibits chondrocyte anabolism, likely through a mechanism involving suppression of SOX9. References: 1C.T.G. Appleton et al. (2007). Arthritis Res Ther 9(1):R13. 2C.T.G. Appleton et al. (2007), Arthritis Rheum In Press.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".