Clinical associations of autoantibodies to a p155/140 kDa doublet protein in juvenile dermatomyositis
Bibliographic record
Abstract
OBJECTIVES: Myositis-specific autoantibodies (MSAs) may define homogeneous clinical subsets of adult patients with dermatomyositis (DM). Recently, there have been descriptions of novel autoantibodies in DM. This study was conducted to establish the clinical significance of anti-p155/140 autoantibodies in juvenile DM (JDM). METHODS: The first 116 children recruited to the JDM National Registry and Repository (UK and Ireland) were studied. Comprehensive clinical features were recorded and sera screened for anti-p155/140 autoantibodies using radio-immunoprecipitation. Sera from adults with DM (n = 20), PM (n = 25), SSc (n = 150), SLE (n = 40) and healthy subjects (n = 50) were used for comparison. Immunodepletion experiments were used to establish whether the p155/140 kDa targets recognized by JDM sera were the same as adult DM sera. RESULTS: Twenty-seven out of 116 (23%) JDM cases were positive for anti-p155/140 in comparison with 6/20 (30%) adults with DM. Immunodepletion confirmed that the 155/140 kDa proteins recognized by JDM and adult DM sera were the same targets. All other adult control sera were negative for anti-p155/140 autoantibodies. There was a higher frequency of males in the anti-p155/140-positive JDM group (P = 0.02). JDM patients with anti-p155/140 autoantibodies had significantly more cutaneous involvement including Gottron's papules (P = 0.003), ulceration (P = 0.005) and oedema (P = 0.013). The distribution of skin lesions was more extensive particularly periorbitally (P = 0.014) and over the small (P < 0.001) and large joints (P = 0.003). CONCLUSIONS: Anti-p155/140 autoantibodies are clinically significant in JDM and may define a clinical subset in terms of disease severity and outcome. The same autoantigen target is detected in adult DM patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".