Histone Modifications in a Mouse Model of Early Adversities and Panic Disorder: Role for Asic1 and Neurodevelopmental Genes
Bibliographic record
Abstract
Hyperventilation following transient, CO2-induced acidosis is ubiquitous in mammals and heritable. In humans, respiratory and emotional hypersensitivity to CO2 marks separation anxiety and panic disorders, and is enhanced by early-life adversities. Mice exposed to the repeated cross-fostering paradigm (RCF) of interference with maternal environment show heightened separation anxiety and hyperventilation to 6% CO2-enriched air. Gene-environment interactions affect CO2 hypersensitivity in both humans and mice. We therefore hypothesised that epigenetic modifications and increased expression of genes involved in pH-detection could explain these relationships. Medullae oblongata of RCF- and normally-reared female outbred mice were assessed by ChIP-seq for H3Ac, H3K4me3, H3K27me3 histone modifications, and by SAGE for differential gene expression. Integration of multiple experiments by network analysis revealed an active component of 148 genes pointing to the mTOR signalling pathway and nociception. Among these genes, Asic1 showed heightened mRNA expression, coherent with RCF-mice's respiratory hypersensitivity to CO2 and altered nociception. Functional enrichment and mRNA transcript analyses yielded a consistent picture of enhancement for several genes affecting chemoception, neurodevelopment, and emotionality. Particularly, results with Asic1 support recent human findings with panic and CO2 responses, and provide new perspectives on how early adversities and genes interplay to affect key components of panic and related disorders.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".