Associations between vitamin D receptor gene polymorphisms and osteoarthritis: an updated meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Vitamin D receptor (VDR) gene polymorphisms may be associated with the risk of OA, however, evidence for this is controversial. This meta-analysis aims to confirm whether VDR gene polymorphisms are associated with OA. METHODS: Meta-analyses on the association between OA and VDR ApaI, BsmI, TaqI and FokI polymorphisms were conducted using allele and homozygote contrast and contrasts in the recessive and dominant models. Stratification analyses by different demographic regions (Europe vs Asian) were also performed and pooled odds ratios (ORs) were obtained using the random effects model if the results were heterogeneous. RESULTS: A total of 13 relevant studies involving OA patients (n = 2104) and controls (n = 2939) were included in the analysis. There were significant associations between VDR ApaI polymorphisms and OA in the Asian population (A vs a: OR= 1.16, 95% CI 1.02, 1.32, P = 0.025; AA vs Aa/aa: OR= 1.36, 95% CI 1.04, 1.77, P = 0.025; AA vs aa: OR= 1.35, 95% CI 1.00, 1.80, P = 0.047), but not in the whole population. There was also a statistically significant association between FokI polymorphism and OA (FF vs Ff/ff: OR= 0.65, 95% CI 0.44, 0.95, P = 0.024); however, this result was derived from only two studies. No significant associations were found between VDR TaqI and BsmI polymorphisms and OA. CONCLUSION: There are modest but statistically significant associations between VDR ApaI polymorphisms and the susceptibility of OA in the Asian population.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.035 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".