Identification of autoantibodies targeting citrullinated CLEC12A in rheumatoid arthritis patients
Bibliographic record
Abstract
Objective: Rheumatoid arthritis is an autoimmune disease characterized by anti-citrullinated protein antibodies (ACPA). The pathogenic and protective roles of ACPA of distinct specificities are emerging and remains poorly understood. Thus, it is crucial to define the range of ACPA specificities and determine their contribution to disease and their potential clinical relevance. Since extracellular citrullination occurs in RA, we investigated whether autoantibodies in RA patients bind a citrullinated form of the cell-surface receptor CLEC12A that is expressed on neutrophils, the most abundant leukocyte in inflamed joints. Methods: We generated a FLAG-tagged, recombinant form of the extracellular portion of human CLEC12A. After purification, the tag was removed prior to citrullination by PAD2 that was confirmed by mass spectrometry. We developed an ELISA for citrullinated CLEC12A to screen for seropositivity in sera of 68 RA patients and 36 healthy controls. Potential associations between these autoantibodies and clinical variables were determined. Results: In our cohort, 40 % of RA patients were positive for anti-citrullinated CLEC12A autoantibodies. Those seropositive patients were younger than RA patients that tested negative for these autoantibodies (p = 0.0058). Most patients had antibodies to multiple citrullinated and homocitrullinated antigens; 17 % of patients negative for other ACPA were positive for anti-citrullinated CLEC12A autoantibodies. Conclusion: This is the first report of seropositivity towards citrullinated CLEC12A in RA patients. A validation cohort will confirm our findings and identify additional correlations between these autoantibodies and clinical parameters. Citrullination may be a mechanism through which CLEC12A's inhibitory function is altered to exacerbate inflammation in RA. Identifying citrullinated neoantigens advances our understanding of the diverse molecular mechanisms that contribute to RA pathogenesis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".