Association Between HLA Alleles and Autoantibodies in Dermatomyositis Defined by Sarcoplasmic Expression of Myxovirus Resistance Protein A
Bibliographic record
Abstract
Objective The diagnosis in the studies analyzing HLA of dermatomyositis (DM) was based on a combined clinical category of polymyositis/DM. This retrospective study investigated the associations of HLA with 5 DM-specific autoantibodies in Japanese patients diagnosed by muscle pathology. Methods We diagnosed Japanese patients with DM based on sarcoplasmic expression of myxovirus resistance protein A. These patients underwent investigation for 5 DM-specific autoantibodies and HLA genotyping. Results Of 175 patients (83 males and 92 females; range 1-86 yrs; mean 46 yrs), 173 (98.9%) had 1 of the 5 autoantibodies. Seven alleles— A*02:07, B*46:01, DRB1*04:07, DRB1*07:01, DRB1*08:03, DQB1*06:01 , and DPB1*02:02 —were more frequently detected in the patients with DM than healthy controls, but these associations were not significant after multiple testing correction. Stratifying by DM-specific autoantibodies, we found the associations of 6 already known and 7 new alleles— B*48:01, B*52:01, C*12:02, DRB1*04:05, DRB1*15:02, DPB1*05:01 , and DPB1*09:01 —with subsets of DM. Moreover, significant associations of 5 alleles with antinucleosome remodeling deacetylase complex (Mi-2) remained after multiple testing correction. In particular, the DRB1*04:07 (odds ratio [OR 28.9]; corrected P = 2.7 × 10 −6 ) and DQB1*06:01 (OR 4.0; corrected P = 1.6 × 10 −4 ) alleles were significantly more prevalent in patients with anti-Mi-2 antibody than in controls. Conclusion This study demonstrates DM-specific autoantibodies defined immunogenetic subsets of DM.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".