Genetic Variation in Steroid and Xenobiotic Metabolizing Pathways and Enterolactone Excretion Before and After Flaxseed Intervention in African American and European American Women
Bibliographic record
Abstract
BACKGROUND: Metabolism and excretion of the phytoestrogen enterolactone (ENL), which has been associated with breast cancer risk, may be affected by variation in steroid hormone and xenobiotic-metabolizing genes. METHODS: We conducted a randomized, crossover flaxseed intervention study in 252 healthy, postmenopausal women [137 European ancestry (EA) and 115 African ancestry (AA)] from western New York. Participants were randomly assigned to maintain usual diet or consume 10 g/day ground flaxseed for 6 weeks. After a 2-month washout period, participants crossed over to the other diet condition for an additional 6 weeks. Urinary ENL excretion was measured by gas chromatography-mass spectrometry and 70 polymorphisms in 29 genes related to steroid hormone and xenobiotic metabolism were genotyped. Mixed additive genetic models were constructed to examine association of genetic variation with urinary ENL excretion at baseline and after the flaxseed intervention. RESULTS: . A greater number of SNPs were associated among AA women than among EA women, and no SNPs were associated in both races. No SNP-ENL associations were statistically significant after correction for multiple comparisons. CONCLUSIONS: Variation in several genes related to steroid hormone metabolism was associated with lignan excretion at baseline and/or after flaxseed intervention among postmenopausal women. IMPACT: These findings may contribute to our understanding of the differences observed in urinary ENL excretion among AA and EA women and thus hormone-related breast cancer risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".