Erythrocyte folate concentrations, CpG methylation at genomically imprinted domains, and birth weight in a multiethnic newborn cohort
Bibliographic record
Abstract
Epigenetic mechanisms are proposed to link maternal concentrations of methyl group donor nutrients with the risk of low birth weight. However, empirical data are lacking. We have examined the association between maternal folate and birth weight and assessed the mediating role of DNA methylation at nine differentially methylated regions (DMRs) of genomically imprinted genes in these associations. Compared with newborns of women with folate levels in the lowest quartile, birth weight was higher in newborns of mothers in the second (β = 143.2, se = 63.2, P = 0.02), third (β = 117.3, se = 64.0, P = 0.07), and fourth (β = 133.9, se = 65.2, P = 0.04) quartiles, consistent with a threshold effect. This pattern of association did not vary by race/ethnicity but was more apparent in newborns of non-obese women. DNA methylation at the PLAGL1, SGCE, DLK1/MEG3 and IGF2/H19 DMRs was associated with maternal folate levels and also birth weight, suggestive of threshold effects. MEG3 DMR methylation mediated the association between maternal folate levels and birth weight (P =0.06). While the small sample size and partial scope of examined DMRs limit our conclusions, our data suggest that, with respect to birth weight, no additional benefits may be derived from increased maternal folate concentrations, especially in non-obese women. These data also support epigenetic plasticity as a key mechanistic response to folate availability during early fetal development.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".