Clinical significance of antibodies to Ro52/TRIM21 in systemic sclerosis
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Autoantibodies to Ro52 recently identified as TRIM21 are among the most common autoantibodies in systemic autoimmune rheumatic diseases, but their clinical association remains poorly understood. We undertook this study to determine the clinical and serologic associations of anti-Ro52/TRIM21 antibodies in patients with systemic sclerosis (SSc). METHODS: Detailed clinical data and sera from 963 patients with SSc enrolled in a multicenter cohort study were collected and entered into a central database. Antibodies to Ro52/TRIM21 and other autoantibodies were detected with an addressable laser-bead immunoassay and different enzyme-linked immunosorbent assay (ELISA) systems. Associations between anti-Ro52/TRIM21 antibodies and clinical and other serologic manifestations of SSc were investigated. RESULTS: Anti-Ro52/TRIM21 antibodies were present in 20% of SSc patients and overlapped with other main SSc-related antibodies, including anti-centromere (by immunofluorescence and centromere protein (CENP)-A and CENP-B ELISA), anti-topoisomerase I, anti-RNA polymerase III, and anti-Pm/Scl antibodies. Anti-Ro52/TRIM21 antibodies were strongly associated with interstitial lung disease (odds ratio (OR), 1.53; 95% confidence interval (CI), 1.11 to 2.12; P = 0.0091) and overlap syndrome (OR, 2.06; 95% CI, 1.01 to 4.19; P = 0.0059). CONCLUSIONS: Anti-Ro52/TRIM21 antibodies were the second most common autoantibodies in this SSc cohort. In SSc, anti-Ro52/TRIM21 antibodies may be a marker of interstitial lung disease and overlap syndrome.
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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 | 0.004 | 0.000 |
| 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 it