Familial seropositive rheumatoid arthritis in North American Native families: effects of shared epitope and cytokine genotypes.
Bibliographic record
Abstract
OBJECTIVE: A number of North American native (NAN) populations have high prevalence rates of both rheumatoid arthritis (RA) and the shared epitope (SE). We examined the phenotype and familial incidence of RA in a NAN population, and investigated how the SE and cytokine genes may affect disease risk within affected families. METHODS: NAN patients with seropositive RA or polyarthritis rheumatoid factor (RF) positive juvenile idiopathic arthritis (JIA) were identified from clinical databases. Patients were recruited consecutively as they presented for clinic visits. Family pedigrees were constructed and consenting relatives were interviewed and examined. The risk of RA within families was calculated by multiple logistic regression. Input variables were the SE and cytokine genotypes. Probands and affected relatives were entered as the affected group, and unaffected relatives within families as the unaffected group. Results were confirmed among unrelated subjects, i.e., unrelated patients and unaffected relatives of other probands. RESULTS: The familial prevalence of RA was 0.50 (95% confidence intervals 0.30, 0.70) among 28 families studied. The interleukin 10 (IL-10) promoter -1082 G/A genotype decreased the odds of RA relative to the A/A genotype in affected families (OR 0.247, 95% CI 0.081, 0.751; p = 0.014) and among unrelated subjects (OR 0.203, 95% CI 0.064, 0.640; p = 0.006). The G/G genotype yielded an OR of 0.093 (95% 0.013, 0.676; p = 0.019) among unrelated subjects. The SE had no effect in these calculations. CONCLUSION: There was a high familial prevalence of RA in this NAN cohort. In susceptible NAN families, the risk of RA was reduced by IL-10 genotypes, whereas the SE did not affect risk. Study of healthy NAN controls is required to determine if these conclusions apply to this NAN population as a whole.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".