CYP2E1*1D regulatory polymorphism: association with alcohol and nicotine dependence.
Bibliographic record
Abstract
OBJECTIVE: CYP2E1 bioactivates environmental protoxins and metabolizes alcohol. CYP2E1 is induced by alcohol and cigarette smoking and may contribute to metabolic tolerance in alcoholics. The CYP2E1*1D polymorphism has been associated with greater CYP2E1 inducibility. One objective was to determine the frequency of the variant allele in eight ethnic groups. Further, the Canadian Native Indian, South-east Asian Canadian and Caucasian Canadian groups were stratified by alcohol and nicotine dependence (as measured by DSM-IV criteria) to examine the potential association of CYP2E1*1D with drug dependence. RESULTS AND CONCLUSIONS: We found a significantly greater frequency of the CYP2E1*1D allele among Indo-Asian Canadians (0.31), Chinese Canadians (0.19), Taiwanese (0.20), Japanese Canadians (0.18), African Americans (0.13), African Canadians (0.10) and Canadian Native Indians (0.09) compared to Caucasian Canadians (0.02). Although the power of the association study was low among some subgroups, the CYP2E1*1D genotype (subjects with at least one variant allele) was associated with alcohol as well as nicotine dependence. Specifically, Canadian Native Indians dependent on nicotine alone or alcohol alone exhibited significantly greater CYP2E1*1D frequencies compared to non-drug dependent controls, while the variant frequency among Southeast Asians dependent on nicotine was greater than their non-drug dependent counterparts. We also found that CYP2E1*1D genotype was associated with significantly greater 3-hydroxycotinine per cigarette in African Americans. The variable frequency of CYP2E1*1D among ethnic groups suggests a greater risk for diseases putatively related to CYP2E1 in some non-Caucasian ethnic groups. The association of CYP2E1*1D with alcohol and nicotine dependence suggests that CYP2E1 may contribute to the development of these dependencies.
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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) | 0.000 | 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 | 0.001 |
| 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".