Vitamin D Receptor Polymorphism rs2228570 (Fok1) Is Associated with Rheumatoid Arthritis in North American Natives
Bibliographic record
Abstract
OBJECTIVE: Vitamin D (VitD) has immunomodulatory activity relevant to rheumatoid arthritis (RA) and acts by binding nuclear receptors that regulate gene transcription. VitD receptor polymorphisms have been variably associated with RA. Because North American Native (NAN) populations have a high prevalence of RA with a strong genetic contribution, we studied potential associations of the rs2228570 (Fok1) VitD receptor polymorphism in a Canadian NAN population. METHODS: The single-nucleotide polymorphism (SNP) Fok1 was tested by sequencing NAN patients with RA (n=448) and unrelated NAN controls (n=704). Associations were tested using genotypic, dominant, and recessive models. RESULTS: The minor allele frequency (F/C) in the NAN control population was 0.44 and lower than reported in white subjects of the same geographical area. The Fok1 VitD receptor SNP was significantly associated with RA. Comparing patients with RA to unaffected NAN controls, the Fok1 SNP was associated with RA using both genotypic [FF vs Ff vs ff: RA 20%, 54%, 26% vs control 22%, 44%, 34% (chi-square 13.35, p=0.003)] and dominant models [FF/Ff vs ff: RA 74% vs 26% control 66% vs 34% (OR 1.5, 95% CI 1.16-1.96, p=0.003)]. This association was strongest in shared-epitope-positive RA. CONCLUSION: VitD receptor polymorphisms may contribute to the high prevalence of RA in NAN populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".