Maternal sensitivity and child internalizing and externalizing behavior: a mediating role for glucocorticoid receptor gene (<i>NR3C1</i>) methylation?
Bibliographic record
Abstract
Abstract The early caregiving environment can have lasting effects on child mental health. Animal models suggest that glucocorticoid receptor gene (NR3C1) DNA methylation plays a mediating role in linking more responsive caregiving to improved behavioral outcomes by its impact on the stress regulatory system. In this longitudinal study, we examined whether children’s NR3C1 methylation levels mediate an effect of maternal sensitivity in infancy on levels of child internalizing and externalizing behavior in a community sample. Maternal sensitivity of 145 mothers was rated at infant age 5 weeks, 12 months, and 30 months by observing mother–infant interactions. Buccal DNA methylation was assessed in the same children at age 6 years and maternal-reported internalizing and externalizing behavior was assessed at age 6 and 10 years. Higher sensitivity at age 5 weeks significantly predicted lower DNA methylation levels at two NR3C1 CpG loci, although methylation levels at these loci did not mediate an effect of maternal sensitivity on levels of child internalizing and externalizing behavior. Overall, the study provides evidence that maternal sensitivity in early infancy is associated with DNA methylation levels at loci involved in stress regulation, but the significance of this finding for child mental health remains unclear.
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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".