Prenatal exposure to maternal depression, neonatal methylation of human glucocorticoid receptor gene (NR3C1) and infant cortisol stress responses
Bibliographic record
Abstract
BACKGROUND: In animal models, variations in early maternal care are associated with differences in hypothalamic-pituitary-adrenal(HPA) stress response in the offspring, mediated via changes in the epigenetic regulation of glucocorticoid receptor (GR) gene (Nr3c1) expression. OBJECTIVE: To study this in humans, relationships between prenatal exposure to maternal mood and the methylation status of a CpG-rich region in the promoter and exon 1F of the human GR gene (NR3C1) in newborns and HPA stress reactivity at age three months were examined. RESULTS: Prenatal exposure to increased third trimester maternal depressed/anxious mood was associated with increased methylation of NR3C1 at a predicted NGFI-A binding site. Increased NR3C1 methylation at this site was also associated with increased salivary cortisol stress responses at 3 months, controlling for prenatal SRI exposure, postnatal age and pre and postnatal maternal mood. METHODS: The methylation status of a CpG-rich region of the NR3C1 gene, including exon 1F, in genomic DNA from cord blood mononuclear cells was quantified by bisulfite pyrosequencing in infants of depressed mothers treated with a serotonin reuptake inhibitor antidepressant (SRI) (n = 33), infants of depressed nontreated mothers (n = 13) and infants of non depressed/non treated mothers (n = 36). To study the functional implications of the newborn methylation status of NR3C1 in newborns, HPA function was assessed at three months using salivary cortisol obtained before and following a non noxious stressor and at a late afternoon basal time. CONCLUSIONS: Methylation status of the human NR3C1 gene in newborns is sensitive to prenatal maternal mood and may offer a potential epigenetic process that links antenatal maternal mood and altered HPA stress reactivity during infancy.
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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) | 0.001 | 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".