Anti-MDA5 juvenile idiopathic inflammatory myopathy: a specific subgroup defined by differentially enhanced interferon-α signalling
Bibliographic record
Abstract
OBJECTIVES: JDM and juvenile overlap myositis represent heterogeneous subtypes of juvenile idiopathic inflammatory myopathy (JIIM). Chronic evolution can occur in up to 60% of cases, and morbidity/mortality is substantial. We aimed to describe the clinical, biological, histological and type I IFN status in JIIM associated with anti-melanoma differentiation-associated protein 5 (anti-MDA5) autoantibodies at presentation (group 1) in comparison with other JIIM (group 2). METHODS: This was a retrospective and prospective study of patients with JIIM ascertained from three French paediatric rheumatology reference centres between 2013 and 2019. Muscle biopsies were reviewed. Type I interferon pathway activity was assessed by dosage of IFNα serum protein and the expression of IFN-stimulated genes. RESULTS: Sixty-four patients were included, 13 in group 1 (54% JDM and 46% juvenile overlap myositis) and 51 in group 2 (76% JDM and 24% juvenile overlap myositis). Group 1 patients demonstrated more arthritis, skin ulcerations, lupus features and interstitial lung disease, and a milder muscular involvement. Serum IFNα levels were higher in group 1 than 2, and decreased after treatment or improvement in both groups. Outcome was similar in both groups. Unconventional treatment (more than two lines) was required in order to achieve remission, especially when skin ulceration was reported. CONCLUSION: This study indicates a higher frequency of arthritis, skin ulcerations and interstitial lung disease, but milder muscular involvement, in JIIM with positive anti-MDA5 autoantibodies compared with other JIIM. Our data support an important role of systemic IFNα in disease pathology, particularly in the anti-MDA5 auto-antibody-positive subgroup. In severe and refractory forms of JIIM, IFNα may represent a therapeutic target.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".