Gestational intake of methyl donors and global LINE-1 DNA methylation in maternal and cord blood: Prospective results from a folate-replete population
Bibliographic record
Abstract
Maternal diet affects offspring DNA methylation in animal models, but evidence from humans is limited. We investigated the extent to which gestational intake of methyl donor nutrients affects global DNA methylation in maternal and umbilical cord blood. Among mother-infant pairs in Project Viva, a folate-replete US population, we estimated maternal intakes of vitamin B12, betaine, choline, folate, cadmium, zinc and iron periconceptionally and during the second trimester. We examined associations of these nutrients with DNA methylation, measured as %5-methyl cytosines (%5mC) in Long Interspersed Nuclear Element-1 (LINE-1), in first trimester (n = 830) and second trimester (n = 671) maternal blood and in cord blood at delivery (n = 516). Cord blood methylation was higher for male than female infants {mean [standard deviation (SD)] 84.8 [0.6] vs. 84.4 [0.7]%}. In the multivariable-adjusted model, maternal intake of methyl donor nutrients periconceptionally and during the second trimester of pregnancy was not positively associated with first trimester, second trimester or cord blood LINE-1 methylation. Periconceptional betaine intake was inversely associated with cord blood methylation [regression coefficient = -0.08% (95% confidence interval (CI): -0.14,-0.01)] but this association was attenuated after adjustment for dietary cadmium, which itself was directly associated with first trimester methylation and inversely associated with cord blood methylation. We also found an inverse association between periconceptional choline [-0.10%, 95% CI: -0.17,-0.03 for each SD (~63 mg/day)] and cord blood methylation in males only. In this folate-replete population, we did not find positive associations between intake of methyl donor nutrients during pregnancy and DNA methylation overall, but among males, higher early pregnancy intakes of choline were associated with lower cord blood methylation.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".