Heavy Chain Constant Region Usage in Antibodies to Peptidylarginine Deiminase 4 as a Marker of Disease Subsets in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: The study of autoantibody isotypes in autoimmune diseases is useful for identifying clinically relevant endotypes. This study was undertaken to study the prevalence and clinical significance of different isotypes and IgG subclasses of anti-peptidylarginine deiminase 4 (anti-PAD4) autoantibodies in individuals with rheumatoid arthritis (RA). METHODS: In 196 RA subjects and 64 healthy controls, anti-PAD4 antibody types were determined using enzyme-linked immunosorbent assay. We investigated associations between anti-PAD4 antibodies and clinical outcomes, and relevant features were confirmed in an independent RA cohort. RESULTS: Anti-PAD4 IgG1, anti-PAD4 IgG2, anti-PAD4 IgG3, anti-PAD4 IgG4, anti-PAD4 IgA, and anti-PAD4 IgE antibodies were more frequent in RA patients than healthy controls (P < 0.001). Anti-PAD4 IgG1, anti-PAD4 IgG3, and anti-PAD4 IgE were associated with distinct clinical features. Anti-PAD4 IgG1 was predictive of progressive radiographic joint damage (odds ratio [OR] 4.88, P = 0.005), especially in RA patients without baseline joint damage (40% versus 0%, P = 0.003) or in those negative for anti-cyclic citrullinated peptide and/or rheumatoid factor (OR 32; P = 0.009). IgG1 was also associated with higher levels of C-reactive protein (P = 0.006) and interleukin-6 (P = 0.021). RA patients with anti-PAD4 IgG3 had higher baseline joint damage scores (median Sharp/van der Heijde score 13 versus 7, P = 0.046), while those with anti-PAD4 IgE had higher Disease Activity Score in 28 joints (median 4.0 versus 3.5, P = 0.025), more frequent rheumatoid nodules (31% versus 16%, P = 0.025), and more frequent interstitial lung disease (ground-glass opacification) (24% versus 9%, P = 0.014). Anti-PAD4 IgG1 antibody associations with joint damage were corroborated in an independent RA cohort. CONCLUSION: Anti-PAD4 IgG1, anti-PAD4 IgG3, and anti-PAD4 IgE antibodies identify discrete disease subsets in RA, suggesting that heavy chain usage drives distinct effector mechanisms of anti-PAD4 antibodies 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 | 0.001 |
| 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".