Polymorphisms in genes involved in the estrogen pathway and mammographic density
Bibliographic record
Abstract
BACKGROUND: Single nucleotide polymorphisms (SNPs) in genes involved in the estrogen pathway appear to be associated with breast cancer risk and possibly with mammographic density (MD), but little is known of these associations among premenopausal women. This study examines the association of 11 polymorphisms in five estrogen-related genes (estrogen receptors alpha and beta (ERα, ERβ), 17β-hydroxysteroid dehydrogenase 1 (HSD17B1), catechol-O-methyltransferase (COMT), cytochrome P450 1B1 (CYP1B1)) with premenopausal MD. Effect modification of four estrogen-related factors (parity, age at menarche, hormonal derivatives use and body mass index (BMI)) on this relation is also assessed. METHODS: Polymorphisms were genotyped in 741 premenopausal Caucasian women whose MD was measured in absolute density (AD, cm²) and percent density using a computer-assisted method. Multivariate linear models were used to examine the associations (P(trend)) and interactions (Pi). RESULTS: None of the SNPs showed a statistically significant association with AD. However, each additional rare allele of rs1056836 CYP1B1 was associated with a reduction in AD among nulliparous women (P(trend) = 0.004), while no association was observed among parous women (P(trend) = 0.62; Pi = 0.02). An increase in the number of rare alleles of the HSD17B1 SNP (rs598126 and rs2010750) was associated with an increase in AD among women who never used hormonal derivatives (P(trend) = 0.06 and P(trend) = 0.04, respectively), but with a decrease in AD among past hormonal derivatives users (P(trend) = 0.04; Pi = 0.02 and P(trend) = 0.08; Pi = 0.01, respectively). Moreover, a negative association of rs598126 HSD17B1 SNP with AD was observed among women with higher BMI (>median) (P(trend) = 0.01; Pi = 0.02). A negative association between an increased number of rare alleles of COMT rs4680 SNP and AD was limited to women who never used hormonal derivatives (P(trend) = 0.02; Pi = 0.03) or with late age at menarche (>median) (P(trend) = 0.03; Pi = 0.02). No significant association was observed between polymorphisms in the ERα or ERβ genes and AD. Similar results, although less significant, were observed when MD was assessed in percent density. CONCLUSION: SNPs located in CYP1B1, COMT or HSD17B1 genes seem to be associated with MD in some strata of estrogen-related factors. Our findings suggest that modifying effects of estrogen-related factors should be considered when evaluating associations of polymorphisms in estrogen-related genes with premenopausal mammographic density.
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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 | 0.000 | 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 | 0.000 |
| 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".