Clinical correlates of monospecific anti-PM75 and anti-PM100 antibodies in a tri-nation cohort of 1574 systemic sclerosis subjects
Bibliographic record
Abstract
OBJECTIVE: Autoantibodies directed against the two principal antigens of the human exosome complex, PM75 and PM100, are present in systemic sclerosis (SSc) sera and have been associated with myositis and calcinosis. However, there is a paucity of data on the clinical correlates of these autoantibodies separately and in the absence of other SSc-specific antibodies. The aim of this study was to assess the clinical correlates of monospecific anti-PM75 and anti-PM100 in SSc. METHODS: A tri-nation cohort of 1574 SSc subjects was formed, clinical variables were harmonized and sera were tested for anti-PM75 and anti-PM100 antibodies using a line immunoassay. RESULTS: Forty-eight (3.0%) subjects had antibodies against PM75 and 18 (1.1%) against PM100. However, only 16 (1%) had monospecific anti-PM75 antibodies and 11 (0.7%) monospecific anti-PM100 antibodies (i.e. in isolation of each other and other SSc-specific antibodies). Monospecific profiles of each autoantibody included more calcinosis. An increased frequency of myositis was only seen in subjects positive for both anti-PM75 and anti-PM100 antibodies. Lung disease was only associated with anti-PM75 and subjects with anti-PM100 antibodies had better survival compared to other antibody subsets. CONCLUSION: The prevalence of monospecific anti-PM75 and anti-PM100 antibodies in this large SSc cohort was low. Disease features associated with anti-PM/Scl antibodies may depend on particular and possibly multiple antigen specificities. However, due to the small samples, these results need to be interpreted with caution. International collaborations are key to understanding the clinical correlates of uncommon serological profiles in SSc.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".