Genetic Variations, Exposure to Persistent Organic Pollutants and Breast Cancer Risk – A Greenlandic Case–Control Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study investigated the effects of single nucleotide polymorphisms (SNPs) in xenobiotic and steroid hormone-metabolizing genes in relation to breast cancer risk and explored possible effect modifications on persistent organic pollutants (POPs) and breast cancer associations. The study also assessed effects of Greenlandic BRCA1 founder mutations. Greenlandic Inuit women (77 cases and 84 controls) were included. We determined two founder mutations in BRCA1: Cys39Gly (rs80357164) and 4684delCC, and five SNPs in xenobiotic and oestrogen-metabolizing genes: CYP17A1 -34T>C (rs743572), CYP19A1 *19C>T (rs10046), CYP1A1 Ile462Val (rs1048943), CYP1B Leu432Val (rs1056836) and COMT Val158Met (rs4680). We used chi-square test for comparison of categorical variables between groups. Odds ratio (OR) estimates with 95% confidence interval (95%CI) were obtained using logistic regression models. The variant allele of BRCA1 Cys39Gly increased breast cancer risk (Gly/Cys versus Cys/Cys, OR: 12.2, 95%CI: 1.53; 98.1), and carriers of the variant allele of CYP17A1 -34T>C had reduced risk (CT+CC versus TT, OR: 0.44, 95%CI: 0.21; 0.93). CYP17A1 -34T>C was an effect modifier on the association between perfluoroalkyl acids (PFAAs) and breast cancer risk (∑PFAA, ratio of OR: 0.18, 95%CI: 0.03; 0.97). Non-significant modifying tendencies were seen for the other SNPs on the effect of polychlorinated biphenyls, organochlorine pesticides and PFAAs. In summary, the BRCA1 Cys39Gly and CYP17A1 -34T>C genetic variations were associated with breast cancer risk. Our results indicate that the evaluated genetic variants modify the effects of POP exposure on breast cancer risk; however, further studies are needed to document the data from the relatively small sample size.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.040 | 0.001 |
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