Antibodies to<i>Porphyromonas gingivalis</i>Are Associated with Anticitrullinated Protein Antibodies in Patients with Rheumatoid Arthritis and Their Relatives
Bibliographic record
Abstract
OBJECTIVE: Anticitrullinated protein antibodies (ACPA) are relatively specific for rheumatoid arthritis (RA), and predate disease. The oral pathogen Porphyromonas gingivalis may play a role in breaking immune tolerance to citrullinated antigens. We studied a cohort of patients with RA and their relatives looking for associations between anti-P. gingivalis antibodies and ACPA. METHODS: Patients with RA (n = 82) and their relatives (n = 205) from a North American Native (NAN) population were studied, along with 47 NAN and 60 non-NAN controls. IgM and IgA rheumatoid factor (RF) were tested by nephelometry and ELISA. Second-generation anticyclic citrullinated peptide (anti-CCP2) isotypes and IgG anti-P. gingivalis lipopolysaccharides were tested by ELISA. HLA-DRB1 typing was performed by sequencing. Oral hygiene and smoking habits were assessed by questionnaires. RESULTS: Autoantibody frequency in patients with RA and relatives: ACPA 91% vs 19%, respectively; IgM RF 82% vs 17%; IgA RF 48% vs 22%. Anti-P. gingivalis levels were higher in patients with RA compared to relatives and controls (p = 0.005) and higher in ACPA-positive patients with RA than in ACPA-negative patients with RA (p = 0.04) and relatives (p < 0.001), but comparable in RF-positive and RF-negative patients and relatives. Poor oral hygiene and smoking were prevalent, but with no clear association with autoantibodies. Relatives with 2 shared-epitope alleles were more likely to be ACPA-positive (OR 2.5, p = 0.02). CONCLUSION: In a genetically predisposed population of NAN patients with RA and their relatives, anti-P. gingivalis antibodies were associated with ACPA. These findings suggest that immune responses to P. gingivalis may be involved in breaking immune tolerance to citrullinated antigens.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".