The Role of Genetic Variants in the Association between Dietary Acrylamide and Advanced Prostate Cancer in the Netherlands Cohort Study on Diet and Cancer
Bibliographic record
Abstract
To investigate the association between dietary acrylanide and advanced prostate cancer, we examined acrylamide-gene interactions for advanced prostate cancer risk by using data from the Netherlands Cohort Study. Participants (n = 58,279 men) completed a baseline food frequency questionnaire (FFQ), from which daily acrylamide intake was calculated. At baseline, 2,411 men were randomly selected from the full cohort for case-cohort analysis. Fifty eight selected single nucleotide polymorphisms (SNPs) and two gene deletions in genes in acrylamide metabolism, DNA repair, sex steroid systems, and oxidative stress were analyzed. After 20.3 years of follow-up, 1,608 male subcohort members and 948 advanced prostate cancer cases were available for Cox analysis. Three SNPs showed a main association with advanced prostate cancer risk after multiple testing correction: catalase (CAT) rs511895, prostaglandin-endoperoxide synthase 2 (PTGS2) rs5275, and xeroderma pigmentosum group C (XPC) rs2228001. With respect to acrylamide-gene interactions, only rs1800566 in NAD(P)H quinone dehydrogenase 1 (NQO1) and rs2301241 in thioredoxin (TXN) showed a nominally statistically significant multiplicative interaction with acrylamide intake for advanced prostate cancer risk. After multiple testing corrections, none were statistically significant. In conclusion, no clear evidence was found for interaction between acrylamide intake and selected genetic variants for advanced prostate 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".