ADH3 genotype, alcohol intake and breast cancer risk
Bibliographic record
Abstract
Moderate alcohol consumption of approximately 1-2 drinks per day has been associated with a 30-50% increase in breast cancer risk. Individuals differ in their ability to metabolize alcohol through genetic differences in alcohol dehydrogenase (ADH), the enzyme that catalyzes the oxidation of approximately 80% of ethanol to acetaldehyde, a known carcinogen. Individuals differ in their ADH genotype, and one locus in particular (ADH3) is polymorphic in Caucasian populations. Using data from the Long Island Breast Cancer Study Project, we examined whether fast metabolizers of alcohol, as measured by the ADH3(1-1) genotype, have a higher risk of breast cancer from alcohol intake compared with those individuals who are slow metabolizers, but consume similar amounts of alcohol. We combined genotyping information with questionnaire data on 1047 breast cancer cases and 1101 controls and used unconditional logistic regression methods to estimate multivariate-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) between alcohol intake and breast cancer risk. Among individuals homozygous for the fast metabolizing allele (ADH(3)1-1), a lifetime alcohol consumption of 15-30 g/day (approximately 1-2 drinks per day) increased breast cancer risk by 2-fold (OR=2.0, 95% CI=1.1-3.5). In contrast, the increase in risk from a lifetime alcohol consumption of 15-30 g/day was less pronounced in the intermediate and slow metabolizing groups, respectively: ADH3(1-2) (OR=1.5, 95% CI 0.9-2.4) and ADH(3)2-2 (OR=1.3, 95% CI 0.5-3.5). Fast metabolizers who drank 15-30 g/day of alcohol had 2.3 times (95% CI 1.3-4.0) greater risk of breast cancer than non-drinkers who were intermediate or slow metabolizers. This association for fast metabolizers who drank 15-30 g/day was particularly pronounced among premenopausal women (premenopausal women OR=2.9, 95 % CI=1.2-7.1; postmenopausal women OR=1.8, 95% CI=0.9-3.8). These population-based data support the hypothesis that fast metabolizers of alcohol have a higher risk of breast cancer risk, from alcohol intake than slow metabolizers.
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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 | 0.002 |
| 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) | 0.002 | 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".