Anti-SMN autoantibodies in mixed connective tissue disease are associated with a severe systemic sclerosis phenotype
Bibliographic record
Abstract
OBJECTIVES: The survival of motor neuron (SMN) complex has an essential role in the assembly of small nuclear ribonucleoproteins (RNP). Recent reports have described autoantibodies (aAbs) to the SMN complex as novel biomarkers in anti-U1RNP+ myositis patients. The aim of this study was to compare phenotypic features of anti-U1RNP+ mixed connective tissue disease (MCTD) patients with and without anti-SMN aAbs. METHODS: A retrospective MCTD cohort was studied. Addressable laser bead immunoassay was used to detect specific anti-SMN aAbs with <300 mean fluorescence intensity (MFI) as normal reference range, 300-999 MFI as low-titre and ≥1000 MFI as high-titre positivity. Comparison of clinical features between anti-SMN+ and anti-SMN- subgroups used two-tailed Fisher's exact test, and logistic regression analyses. RESULTS: Sixty-six patients were included. Median age at MCTD diagnosis was 40.6 years, and duration of follow-up was 12 years. Based on the highest available titre, 39 (59%) were anti-SMN+: 10 (26%) had low titre and 29 (74%) had high titre. Anti-SMN+ patients had a higher frequency of fingertip pitting scars (anti-SMN+ 23% vs anti-SMN- 4%, p=0.04), lower gastrointestinal (GI) involvement (26% vs 4%, p=0.04), and myocarditis (16% vs 0%, p=0.04). The combined outcome of pitting scars and/or lower GI involvement and/or myositis and/or myocarditis was highest among high-titre anti-SMN+ patients: adjusted OR 7.79 (2.33 to 30.45, p=0.002). CONCLUSIONS: Anti-SMN aAbs were present in 59% of our MCTD cohort. Their presence, especially at high-titres, was associated with a severe systemic sclerosis (scleroderma) phenotype including myositis, myocarditis and lower GI involvement.
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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 | 0.000 | 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 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".