Prevalence of Anti-Peptidylarginine Deiminase Type 4 Antibodies in Rheumatoid Arthritis and Unaffected First-degree Relatives in Indigenous North American Populations
Bibliographic record
Abstract
OBJECTIVE: To determine whether anti-peptidylarginine deiminase type 4 (PAD4) antibodies were present in first-degree relatives (FDR) of patients with rheumatoid arthritis (RA) in 2 indigenous North American populations with high prevalence of RA. METHODS: Participants were recruited from 2 indigenous populations in Canada and the United States, including patients with RA (probands), their unaffected FDR, and healthy unrelated controls. Sera were tested for the presence of anti-PAD4 antibodies, anticyclic citrullinated peptide (anti-CCP) antibodies, and rheumatoid factor (RF). HLA-DRB1 subtyping was performed and participants were classified according to number of shared-epitope alleles present. RESULTS: Antibodies to PAD4 were detected in 24 of 82 (29.3%) probands; 2 of 147 (1.4%) relatives; and no controls (p < 0.0001). Anti-CCP was present in 39/144 (27.1%) of the relatives, and there was no overlap between positivity for anti-CCP and PAD4 in the relatives. In RA patients, anti-PAD4 antibodies were associated with disease duration (p = 0.0082) and anti-CCP antibodies (p = 0.008), but not smoking or shared-epitope alleles. CONCLUSION: Despite a significant prevalence of anti-CCP in FDR, anti-PAD4 antibodies were almost exclusively found in established RA. The prevalence of anti-PAD4 antibodies in RA is similar to the prevalence described in other populations and these autoantibodies are associated with disease duration and anti-CCP in RA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".