Genetic Variation in the Vitamin D Receptor, Plasma 25-Hydroxyvitamin D, and Biomarkers of Cardiometabolic Disease in Caucasian Young Adults
Bibliographic record
Abstract
BACKGROUND/AIMS: Vitamin D regulates gene transcription by binding to the vitamin D receptor (VDR), potentially affecting cardiometabolic disease risk. However, studies of 25-hydroxyvitamin D [25(OH)D] and cardiometabolic disease are inconsistent. Inconsistencies may result from unaccounted for interactions between VDR genetic variants and 25(OH)D. We examined the effect of 25(OH)D on the association between VDR variants and cardiometabolic disease biomarkers. METHODS: The relationship between 25(OH)D, 24 VDR variants, and 10 cardiometabolic biomarkers was examined in 488 Caucasians aged 20-29 years. Covariate-adjusted general linear models were used to examine the interaction effect of 25(OH)D × VDR on each biomarker. When interactions were significant (p < 0.05), relationships were further examined with analysis of covariance, stratified by tertiles of 25(OH)D and adjusted for multiple comparisons. RESULTS: In the lowest tertile of 25(OH)D, major allele homozygotes for rs3819545 had higher insulin and HOMA-IR than minor allele carriers (p ≤ 0.002). Fasting insulin and HOMA-IR were lower in the highest than the lowest tertile of 25(OH)D among major allele homozygotes (p < 0.0001), but minor allele carriers had similar levels regardless of vitamin D status. CONCLUSIONS: We identified 25(OH)D-dependent associations between rs3819545 and glycemic dysregulation biomarkers. Major allele homozygotes with low vitamin D status may be at increased risk of insulin resistance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".