Cytochrome P450 1A2 (CYP1A2) activity and risk factors for breast cancer: a cross-sectional study
Bibliographic record
Abstract
INTRODUCTION: Breast cancer risk may be determined by various genetic, metabolic, and lifestyle factors that alter sex hormone metabolism. Cytochrome P450 1A2 (CYP1A2) is responsible for the metabolism of estrogens and many exogenous compounds, including caffeine. METHODS: In a cross-sectional study of 146 premenopausal and 149 postmenopausal women, we examined the relationships between CYP1A2 activity and known or suspected risk factors for breast cancer. Blood levels of sex hormones, lipids, and growth factors were measured. In vivo CYP1A2 activity was assessed by measuring caffeine metabolites in urine. Stepwise and maximum R regression analyses were used to identify covariates related to CYP1A2 activity after adjustment for ethnicity. RESULTS: In both menopausal groups CYP1A2 activity was positively related to smoking and levels of sex hormone binding globulin. In premenopausal women, CYP1A2 activity was also positively related to insulin levels, caffeine intake, age, and plasma triglyceride levels, and negatively related with total cholesterol levels and body mass index. In postmenopausal women CYP1A2 activity was positively associated with insulin-like growth factor-1, and negatively associated with plasma triglyceride, high-density lipoprotein cholesterol, and age at menarche. CONCLUSION: These results suggest that CYP1A2 activity is correlated with hormones, blood lipids, and lifestyle factors associated with breast cancer risk, although some of the observed associations were contrary to hypothesized directions and suggest that increased CYP1A2 function may be associated with increased risk for breast 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 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".