Autoantibodies Against Unmodified and Citrullinated Human Endogenous Retrovirus K Envelope Protein in Patients With Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: Autoantibodies against proteins encoded by human endogenous retrovirus K (HERV-K) have been reported in patients with rheumatoid arthritis (RA), but their relevance, if any, has remained unresolved. We revisited this question and tested if such autoantibodies may react with citrullinated epitopes on the envelope (Env) protein of HERV-K. METHODS: Immunoblotting and ELISAs were conducted with unmodified Env protein and with Env citrullinated by protein arginine deiminase 4 (PAD4). Sera from 100 patients with RA, plasma from 32 patients with juvenile idiopathic arthritis (JIA), and healthy adult and pediatric controls were included. Antibody reactivity was evaluated for correlations with clinical and laboratory variables of the patients. RESULTS: We replicated and expanded upon published data suggesting that patients with RA or JIA have autoantibodies against HERV-K Env, some with high titers. Anti-HERV-K antibodies correlated with cigarette smoking and with circulating myeloperoxidase-DNA complexes indicative of nonapoptotic neutrophil cell death. Further, most of the patients with RA, but not those with JIA, had autoantibodies that reacted more strongly with Env that was citrullinated by PAD4. These anticitrullinated Env autoantibodies correlated with seropositivity and tended to be higher in patients with erosive disease. CONCLUSION: Our data suggest that anti-HERV-K immunity is elevated in RA and JIA and may have a connection with pathogenic protein citrullination 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".