CYP24A1 variant modifies the association between use of oestrogen plus progestogen therapy and colorectal cancer risk
Bibliographic record
Abstract
BACKGROUND: Menopausal hormone therapy (MHT) use has been consistently associated with a decreased risk of colorectal cancer (CRC) in women. Our aim was to use a genome-wide gene-environment interaction analysis to identify genetic modifiers of CRC risk associated with use of MHT. METHODS: We included 10 835 postmenopausal women (5419 cases and 5416 controls) from 10 studies. We evaluated use of any MHT, oestrogen-only (E-only) and combined oestrogen-progestogen (E+P) hormone preparations. To test for multiplicative interactions, we applied the empirical Bayes (EB) test as well as the Wald test in conventional case-control logistic regression as primary tests. The Cocktail test was used as secondary test. RESULTS: The EB test identified a significant interaction between rs964293 at 20q13.2/CYP24A1 and E+P (interaction OR (95% CIs)=0.61 (0.52-0.72), P=4.8 × 10(-9)). The secondary analysis also identified this interaction (Cocktail test OR=0.64 (0.52-0.78), P=1.2 × 10(-5) (alpha threshold=3.1 × 10(-4)). The ORs for association between E+P and CRC risk by rs964293 genotype were as follows: C/C, 0.96 (0.61-1.50); A/C, 0.61 (0.39-0.95) and A/A, 0.40 (0.22-0.73), respectively. CONCLUSIONS: Our results indicate that rs964293 modifies the association between E+P and CRC risk. The variant is located near CYP24A1, which encodes an enzyme involved in vitamin D metabolism. This novel finding offers additional insight into downstream pathways of CRC etiopathogenesis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".