Immune Responses Targeting Homocitrullinated Peptides Drive Rheumatoid Arthritis-like Pathology in HLA-DR4 Transgenic Mice
Bibliographic record
Abstract
Abstract Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by persistent synovial inflammation and progressive joint destruction. A hallmark feature of RA is the presence of anti-citrullinated protein autoantibodies (ACPAs), which have been extensively studied in disease pathogenesis. The development of these autoantibodies is strongly associated with the expression of HLA-DR4, containing the shared epitope. More recently, anti-homocitrullinated protein autoantibodies (AHCPAs) have also been implicated in RA and demonstrate a similar genetic association. Therefore, this study aimed to evaluate the role of homocitrulline immune responses in RA pathogenesis. HLA-DR4 transgenic (DR4tg) and B6 mice were immunized with a synthetic homocitrullinated peptide (HomoCitJED) or PBS followed by a booster 21 days later. Beginning on day 75 post-primary immunization mice received knee intra-articular (i.a.) injections of HomoCitJED once a week for three consecutive weeks. Swelling post i.a. injection was measured using digital calipers. IgG antibodies against homocitrullinated peptides/proteins were measured using enzyme-linked immunosorbent assay (ELISA). Knees were sectioned and analyzed for histopathological damage and citrullinated/homocitrullinated protein levels. HomoCitJED immunized DR4tg mice exhibited significantly greater swelling and incidence of anti-HomoCitJED and -homocitrullinated fibrinogen IgG autoantibodies. Additionally, 30% had responses against CitJED, a synthetic citrullinated peptide. HomoCitJED immunized DR4tg mice also experienced greater total histopathological damage; however, the immunizations/injections did not affect citrullinated/homocitrullinated protein levels. In conclusion, homocitrulline-specific immune responses can induce RA-like disease in DR4tg mice, supporting the pathogenic role of AHCPAs 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".