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Record W4411884089 · doi:10.3899/jrheum.2025-0314.3

Clinically Available Biomarkers Associated with Systemic Autoimmune Rheumatic Disease Progression in Anti-Nuclear Antibody Positive Individuals

2025· article· en· W4411884089 on OpenAlexaffvenueabout
Nazanin Soghrati, Sindhu R. Johnson, Zahi Touma, Zareen Ahmad, Dennisse Bonilla, Linda T. Hiraki, Arthur Bookman, Joan Wither

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsToronto Western HospitalSickKids FoundationMount Sinai HospitalUniversity Health NetworkQueen's University
Fundersnot available
KeywordsMedicineAutoantibodyDiseaseBiomarkerInternal medicineAutoimmune diseaseClinical significanceImmunologyRheumatologyAntibody

Abstract

fetched live from OpenAlex

Objectives The presence of Anti-Nuclear Antibodies (ANA) are a hallmark of Systemic Autoimmune Rheumatic Disease (SARD) and can be present years before clinical diagnosis. Although this suggests that ANAs could be used as potential biomarker for disease progression, they are also found in up to 25% of women, only a small fraction of whom (<5%) will develop a SARD. As the onset of symptomatic disease is not infrequently associated with organ damage, there is tremendous interest in identifying biomarkers associated with a high risk of progression, which could potentially enable initiation of preventative therapy. Here, we sought to determine whether any of the tests typically available to rheumatologists can be used to identify ANA positive individuals at high risk of imminent progression. Methods Study participants were recruited from the Early Autoimmune Rheumatic Disease Clinic at Toronto Western Hospital, where ANA positive (≥1:160 by IF or ≥1:80 with a specific autoantibody) individuals without a SARD diagnosis (based upon clinical classification criteria) were followed yearly, or earlier if they had new symptoms, for development of SARD symptoms. Participants either lacked SARD clinical criteria or had insufficient criteria for a SARD diagnosis (UCTD), with progression being defined as the onset of a new clinical criteria for SARD. All ANAs, complements, and specific autoantibodies were measured through the hospital laboratory, with specific ANAs being measured by Bioplex. Results 124 ANA positive individuals were followed by a minimum of 2 years, 15 of which clinically progressed within 2 years of follow-up. The mean age and proportion of female progressors did not differ significantly from that of non-progressors, however progressors were more likely to be non-Caucasian than non-progressors. Although the ANA titer and serum complement levels were similar in progressors and non-progressors, progressors had significantly more specific ANAs (1.53 ±1.41 vs 0.88 ± 0.92, p = 0.019, Student’s t test). With the exception of anti-dsDNA antibodies, all specific ANAs were more prevalent in progressors, but this difference was only significant for anti-La antibodies. The most prevalent antibody in the cohort in both progressors and non-progressors was anti-Ro (46.7% and 35.8%, respectively). Within anti-Ro positive individuals, discrimination between anti-Ro52 and -Ro60 showed that anti-Ro52 but not anti-Ro60 antibodies were significantly associated with progression, particularly when in tandem with a positive RF (Table 1). Table 1: Clinical and Serologic Associations with Progression Conclusion The presence of anti-La and -Ro52 antibodies is associated with an increased risk of imminent clinical progression in the subsequent 2 years and such individuals merit close follow-up.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.328
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

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