Estrogen pathway polymorphisms and mammographic density.
Why this work is in the frame
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Bibliographic record
Abstract
Elevated mammographic density (MD) is strongly associated with breast cancer risk and the estrogen pathway has been proposed as a potential mechanism for this association. It has been repeatedly observed that several established estrogen-related factors associated with breast cancer risk, such as parity and hormone replacement therapy, are also associated with MD. However, the association of circulating estrogen levels (known to be strongly positively associated with breast cancer risk) with MD has so far been inconsistent. Since MD is highly heritable, single nucleotide polymorphisms (SNPs) in genes involved in the estrogen pathway and their relation with MD could provide information that would help understand the link between MD and breast cancer risk. This review of 18 studies describes the relation of SNPs located in genes of the estrogen pathway (genes coding for hydroxysteroid dehydrogenases (HSD3B1, HSD17B1), cytochrome P450 (CYP1A1, CYP1A2, CYP17A1, CYP19A1 and CYP1B1), catechol-O-methyltransferase (COMT), uridine diphospho-glucuronosyltransferase (UGT1A1), sulfotransferases (SULT1A1, SULT1E1) and for estrogen receptors alpha and beta (ESR1, ESR2)) with MD. Most of the SNPs evaluated showed no association with MD when analyses were performed on overall study population. However, when this relation was assessed within strata based on estrogen-related factors, a few SNPs (HSD17B1 (rs2010750, rs598126 and rs676387), COMT (rs4680), UGT1A1 (rs8175347) and ESR1 (rs9340799)) seemed to be related to MD in the same direction of their associations with breast cancer risk. Since such data are very limited, additional research including stratified analyses by factors related to estrogen are needed to validate these findings.
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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) | 0.001 | 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 it