Dietary folate, alcohol and B vitamins in relation to LINE-1 hypomethylation in colon cancer
Bibliographic record
Abstract
BACKGROUND AND AIMS: Although critical for methylation reactions, how dietary folate and B vitamins affect global DNA methylation level in colorectal cancers is currently unknown. Long interspersed nucleotide element-1 (LINE-1) is an emerging indicator of genome-wide DNA methylation level that has previously been linked to colon cancer survival. METHODS: We examined the association between dietary intake of folate, alcohol and B vitamins and LINE-1 hypomethylation in 609 incident colon cancers, utilising the database of two independent prospective cohort studies. RESULTS: Participants with > or = 400 microg folate intake per day were significantly less likely to develop LINE-1 hypomethylated colon cancers than those reporting <200 microg of folate intake per day (RR=0.57, 95% CI=0.36 to 0.91 for <55% LINE-1 methylated colon tumours; RR=0.74, 95% CI=0.51 to 1.06 for 55-64% LINE-1 methylated colon tumours; and RR=1.08, 95% CI=0.66 to 1.75 for > or = 65% LINE-1 methylated tumours; P(interaction)=0.01). By contrast, high alcohol consumption conferred a higher risk of LINE-1 hypomethylated cancers (> or = 15 g alcohol per day versus none, RR=1.67, 95% CI=1.04 to 2.67 for <55% LINE1 methylated tumours; and RR=1.55, 95% CI=1.10 to 2.18 for 55-64% LINE-1 methylated tumours) but had no association with > or = 65% LINE-1 methylated tumours (RR=1.06, 95% CI=0.69 to 1.62). High intakes of vitamin B(6), B(12) or methionine were not significantly associated with colon cancers, regardless of LINE-1 methylation level. CONCLUSION: The influence of dietary folate intake and alcohol consumption on colon cancer risk differs significantly according to tumoral LINE-1 methylation level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".