Genetic polymorphisms in AHR and CYP1A2 are associated with habitual caffeine consumption and are modified by age and smoking
Bibliographic record
Abstract
Recent genome‐wide association studies (GWAS) from populations of European decent have identified polymorphisms in AHR and CYP1A2 that are associated with caffeine/coffee intake. We examined whether these polymorphisms in AHR (rs6968865 and rs4410790) and CYP1A2 (rs2472297 and rs2470893) were associated with caffeine consumption in a Costa Rican population. Subjects (n=4,612) were participants from a case‐control study of gene‐diet interactions and myocardial infarction. Those with hypertension (n=1,692), or missing information on genotype (n=389), caffeine intake (n=4) or smoking status (n=4) were excluded. Sequenom MassARRAY was used for genotyping, and caffeine intake was assessed by a validated food frequency questionnaire. Compared to those consuming <100 mg/d of caffeine, subjects consuming >400 mg/d were more likely to be carriers of the T, C or T allele for rs6968865, rs4410790 and rs2472297, respectively. The corresponding odds ratios (OR [95% CI]) were 1.41 (1.03–1.93), 1.41 (1.04–1.92) and 1.55 (1.01–2.36). The multivariate‐adjusted ORs (95% CI) for rs6968865 were 1.44 (1.03–2.00) for all subjects, 1.75 (1.16–2.65) for non‐smokers and 1.15 (0.58–2.30) for smokers, and 2.42 (1.45–4.04) for >57 yrs and 1.00 (0.65–1.56) for ≤57 yrs. Our findings confirm previous results from GWAS linking polymorphisms in AHR and CYP1A2 with caffeine consumption, but only in non‐smokers and older adults. Grant Funding Source : Canadian Institutes of Health Research (CIHR)
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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 | 0.000 |
| 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) | 0.000 | 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".