CYP17, Catechol-O-Methyltransferase, and Glutathione Transferase M1 Genetic Polymorphisms, Lifestyle Factors, and Breast Cancer Risk in Women on Prince Edward Island
Bibliographic record
Abstract
Genetic polymorphisms in enzymes controlling the formation and disposition of estrogens and their metabolites have been shown to influence breast cancer risk. Environmental and lifestyle factors may interact with estrogen metabolism polymorphisms to influence breast cancer risk. We studied the role of lifestyle factors and genetic polymorphisms in estrogen metabolism in women from Prince Edward Island (PEI), a small province of 135,000 people on the east coast of Canada. Women (207 cases; 621 controls) were matched on age, menopausal status, and family history of breast cancer. The predominant lifestyle risk factors previously reported to influence breast cancer risk such as body mass index (BMI), parity, and smoking had similar influences in the PEI population. Genetic polymorphisms in CYP17, GSTM1, and catechol-O-methyltransferase (COMT) were not associated with a general increase in breast cancer risk. However, the CYP17 A2/A2 genotype was only observed in women with estrogen receptor (ER) positive breast cancer and not in ER negative breast cancer. The increased risk associated with elevated BMI was only observed in women homozygous for the CYP17 and COMT reference alleles. Similarly, the increased risk associated with extended use of oral contraceptives (≥ 15years), was only observed in women homozygous for the reference alleles of CYP17 and COMT. The GSTM1 homozygous gene deletion was associated with a significantly increased risk of breast cancer in postmenopausal women with a family history of breast cancer risk. These results suggest the polymorphic genes that control estrogen formation and disposition interact significantly with other risk factors to influence breast cancer risk.
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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 | 0.001 |
| 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".