Effect modification by vitamin D receptor genetic polymorphisms in the association between cumulative lead exposure and pulse pressure: a longitudinal study
Bibliographic record
Abstract
BACKGROUND: Although the association between lead and cardiovascular disease is well established, potential mechanisms are still poorly understood. Calcium metabolism plays a role in lead toxicity and thus, vitamin D receptor (VDR) polymorphisms have been suggested to modulate the association between lead and health outcomes. We investigated effect modification by VDR genetic polymorphisms in the association between cumulative lead exposure and pulse pressure, a marker of arterial stiffness. METHODS: We examined 727 participants (3,100 observations from follow-ups from 1991 to 2011) from the Normative Aging Study (NAS), a longitudinal study of aging. Tibia and patella bone lead levels were measured using K-x-ray fluorescence. Four single nucleotide polymorphisms (SNPs) in the VDR gene, Bsm1, Taq1, Apa1, and Fok1, were genotyped. Linear mixed effects models with random intercepts were implemented to take into account repeated measurements. RESULTS: Adjusting for potential confounders, pulse pressure was 2.5 mmHg (95% CI: 0.4-4.7) and 1.9 mmHg (95% CI: 0.1-3.8) greater per interquartile range (IQR) increase in tibia lead (15 μg/g) and patella lead (20 μg/g), respectively, in those with at least one minor frequency allele in Bsm1 compared with those with major frequency allele homozygotes. The observed interaction effect between bone lead and the Bsm1 genotype persists over time during the follow-up. Similar results were observed in effect modification by Taq1. CONCLUSIONS: This study suggests that subjects with the minor frequency alleles of VDR Bsm1 or Taq1 may be more susceptible to cumulative lead exposure-related elevated pulse pressure.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".