Altered hypothalamic DNA methylation and stress-induced hyperactivity following early life stress
Bibliographic record
Abstract
Exposure to early life stress (ELS) during childhood or prenatally increases the risk of future psychiatric disorders. The effect of stress exposure during the neonatal period is less well understood. In preterm infants, exposure to invasive procedures is associated with altered brain development and future stress responses suggesting that the neonatal period could be a key time for the programming of mental health. Previous studies suggest that ELS affects the hypothalamic epigenome, making it a good candidate to mediate these effects. In this study, we used a mouse model of early life stress (modified maternal separation; MMS). We hypothesised MMS would affect the hypothalamic transcriptome and DNA methylome, and impact on adult behaviour. MMS involved repeated stimulation of pups for 1.5 h/day, whilst separated from their mother, from postnatal day (P) 4-6. 3'mRNA sequencing and DNA methylation immunoprecipitation (meDIP) sequencing were performed on hypothalamic tissue at P6. Behaviour was assessed with the elevated plus, open field mazes and in-cage monitoring at 3-4 months of age. MMS was only associated with subtle changes in gene expression, but there were widespread alterations in DNA methylation. Notably, differentially methylated regions were enriched for synapse-associated loci. MMS resulted in hyperactivity in the elevated plus and open field mazes, but in-cage monitoring revealed that this was not representative of habitual hyperactivity. ELS has marked effects on DNA methylation in the hypothalamus in early life and results in stress-specific hyperactivity in young adulthood. These results have implications for the understanding of ELS-mediated effects on brain 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 | 0.000 | 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".