Effects of Maternal Vitamin D Supplementation on the Maternal and Infant Epigenome
Bibliographic record
Abstract
INTRODUCTION: Mothers and infants are at high risk for inadequate vitamin D status. Mechanisms by which vitamin D may affect maternal and infant DNA methylation are poorly understood. OBJECTIVE: supplementation on DNA methylation in pregnant and lactating women and their breastfed infants. MATERIALS AND METHODS: 400 international units (IU) (n = 6; control) or 3,800 IU (n = 7; intervention) daily from late second trimester through 4-6 weeks postpartum. Epigenome-wide DNA methylation was quantified in leukocytes collected from mothers at birth and mother-infant dyads at 4-6 weeks postpartum. RESULTS: At birth, intervention group mothers showed DNA methylation gain and loss at 76 and 89 cytosine-guanine (CpG) dinucleotides, respectively, compared to controls. Postpartum, methylation gain was noted at 200 and loss at 102 CpGs. Associated gene clusters showed strongest biologic relevance for cell migration/motility and cellular membrane function at birth and cadherin signaling and immune function at postpartum. Breastfed 4-6-week-old infants of intervention mothers showed DNA methylation gain and loss in 217 and 213 CpGs, respectively, compared to controls. Genes showing differential methylation mapped most strongly to collagen metabolic processes and regulation of apoptosis. CONCLUSIONS: Maternal vitamin D supplementation during pregnancy and lactation alters DNA methylation in mothers and breastfed infants. Additional work is needed to fully elucidate the short- and long-term biologic effects of vitamin D supplementation at varying doses, which could hold important implications for establishing clinical recommendations for prenatal and offspring health promotion.
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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 | 0.000 |
| 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) | 0.002 | 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".