Genetic Polymorphisms of<i>CYP2E1</i>and Risk of Colorectal Cancer: The Fukuoka Colorectal Cancer Study
Bibliographic record
Abstract
Cytochrome P450 2E1 (CYP2E1) is involved in the metabolic activation of a wide variety of potential carcinogens, and functional polymorphisms in the CYP2E1 gene have been investigated in relation to colorectal cancer. We examined the relation of the CYP2E1 RsaI and 96-bp insertion polymorphisms to colorectal cancer risk and the interaction between these polymorphisms and some lifestyle risk factors. Subjects were 685 incident cases of colorectal cancer and 778 community controls. Statistical adjustment was made for alcohol use, body mass index, physical activity, and other factors. The RsaI c2 allele was associated with a decreased risk of rectal cancer [adjusted odds ratio for at least one c2 allele, 0.71; 95% confidence interval (95% CI), 0.53-0.95], and an increased risk of rectal cancer was observed among individuals having one or two 96-bp insertion alleles (adjusted odds ratio, 1.40; 95% CI, 1.06-1.85). Individuals with two 96-bp insertion alleles showed a 2.28-fold increase in colon cancer risk (95% CI, 1.29-4.01). The two polymorphisms were in almost complete linkage disequilibrium (D' = 0.94). A positive association between alcohol intake and colorectal cancer was observed only in individuals without RsaI c2 allele (P(trend) = 0.03) or in those without 96-bp insertion allele (P(trend) = 0.009). Colon cancer risk was increased in relation to red meat intake only in individuals having one or two 96-bp insertion alleles (P(interaction) = 0.03). The present study suggests that variation in activity and inducibility of CYP2E1, in relation to alcohol or red meat intake, contributes to the development of colorectal cancer.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".