The presence of anti-nuclear antibodies alone is associated with changes in B cell activation and T follicular helper cells similar to those in systemic autoimmune rheumatic disease
Bibliographic record
Abstract
Diagnosis of systemic autoimmune rheumatic diseases (SARD) relies on the presence of hallmark anti-nuclear antibodies (ANA), many of which can be detected years before clinical manifestations. However, ANAs are also seen in healthy individuals, most of whom will not develop SARD. Here, we examined a unique cohort of asymptomatic ANA + individuals to determine whether they share any of the cellular immunologic features seen in SARD. Healthy ANA − controls and ANA + (ANA ≥1:160 by immunofluorescence) participants with no SARD criteria, with at least one criterion (undifferentiated connective tissue disease (UCTD)), or meeting SARD classification criteria were recruited. Peripheral blood cellular immunological changes were assessed by flow cytometry and transcript levels of BAFF , interferon (IFN)-induced and plasma cell-expressed genes were quantified by NanoString. A number of the immunologic abnormalities seen in SARD, including changes in peripheral B (switched memory) and T (iNKT, T regulatory, activated memory T follicular helper) subsets and B cell activation, were also seen in asymptomatic ANA + subjects and those with UCTD. The extent of these immunologic changes correlated with ANA titer or the number of different specific ANAs produced. Principal component analysis of the cellular data indicated that a significant proportion of asymptomatic ANA + subjects and subjects with UCTD clustered with patients with early SARD, rather than ANA − healthy controls. ANA production is associated with altered T and B cell activation even in asymptomatic individuals. Some of the currently accepted cellular features of SARD may be associated with ANA production rather than the immunologic events that cause symptoms in SARD.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".