Disease‐Modifying Osteoarthritis Treatment With Interleukin‐1 Receptor Antagonist Gene Therapy in Small and Large Animal Models
Bibliographic record
Abstract
OBJECTIVE: Gene therapy holds great promise for the treatment of osteoarthritis (OA) because a single intraarticular injection can lead to long-term expression of therapeutic proteins within the joint. This study was undertaken to investigate the use of a helper-dependent adenovirus (HDAd)-mediated intraarticular gene therapy approach for long-term expression of interleukin-1 receptor antagonist (IL-1Ra) as sustained symptomatic and disease-modifying therapy for OA. METHODS: In mouse models of OA, efficacy of HDAd-IL-1Ra was evaluated by histologic analysis, micro-computed tomography (micro-CT), and hot plate analysis. In a horse OA model, safety and efficacy of HDAd-IL-1Ra were evaluated by blood chemistry, analyses of synovial fluid, synovial membrane, and cartilage, and gross pathology and lameness assessments. RESULTS: In skeletally immature mice, HDAd-IL-1Ra prevented development of cartilage damage, osteophytes, and synovitis. In skeletally immature and mature mice, treatment with HDAd-interleukin-1 receptor antagonist post-OA induction resulted in improved-albeit not significantly-cartilage status assessed histologically and significantly increased cartilage volume, cartilage surface, and bone surface covered by cartilage as assessed by micro-CT. Fewer osteophytes were observed in HDAd-IL-1Ra-treated skeletally immature mice. Synovitis was not affected in skeletally immature or mature mice. HDAd-IL-1Ra protected against disease-induced thermal hyperalgesia in skeletally mature mice. In the horse OA model, HDAd-IL-1Ra therapy significantly improved lameness parameters, indicating efficient symptomatic treatment. Moreover, macroscopically and histologically assessed cartilage and synovial membrane parameters were significantly improved, suggesting disease-modifying efficacy. CONCLUSION: These data from OA models in small and large animals demonstrated safe symptomatic and disease-modifying treatment with an HDAd-expressing IL-1Ra. Furthermore, this study establishes HDAd as a vector for joint gene therapy.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".