Maternal One-carbon Nutrients Status and Effects on DNA Methylation and Hydroxymethylation in Newborn Infants
Bibliographic record
Abstract
DNA methylation is an important epigenetic determinant in gene expression, aberrancies of which are mechanistically related to the development of several diseases. During embryogenesis, a new DNA methylation pattern of the fetus is established, rendering this period highly susceptible to environmental modifiers. Maternal dietary intake and status of one-carbon nutrients (folate, vitamins B6, B12, choline, and betaine) have the potential to modulate DNA methylation via the provision of S-adenosylmethionine. The primary objective of this study was to determine the effects of maternal one-carbon nutrient status on DNA methylation and hydroxymethylation in umbilical cord blood mononuclear cells. This study also characterized folate and pyridoxal 5â phosphate (vitamin B6) concentrations in Canadian pregnant women and in umbilical cord blood. Demographic and dietary information was assessed in 368 pregnant women. Maternal blood samples were collected in early pregnancy and at the time of delivery when an umbilical cord blood sample was also collected. Blood concentrations of one-carbon nutrients including serum and RBC folate, serum vitamin B12, plasma pyridoxal 5â phosphate, plasma choline and betaine were measured. Mononuclear cells from umbilical cord blood were extracted and total global DNA 5-methylcytosine and 5-hydroxymethylcytosine content was calculated. Folate concentrations in maternal and cord blood were high, while pyridoxal 5â phosphate concentrations were adequate. There were no strong associations between one-carbon nutrient concentrations and DNA methylation or hydroxymethylation, although maternal concentrations measured in early pregnancy seemed to have more association than later time point measurements. Further studies are warranted to elucidate the potential impact of maternal one-carbon nutrient status on DNA methylation and hydroxymethylation in the developing fetus, which has the potential to modulate disease risk, including cancer, osteoporosis, metabolic and cardiovascular diseases, in the offspring later in life.
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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) | 0.001 | 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".