StressNeurosciencePeer-reviewed journal article
The impact of pubertal stress and adult hormone exposure on the transcriptome of the developing hypothalamus
Karissa N. Gautier, Samantha L. Higley, John M. Mendoza, Kathleen E. MorrisoniD
Abstract
Why individuals suffer negative consequences following stress is a complex phenomenon that is dictated by individual factors, the timing of stress within the lifespan, and when in the lifespan the consequences are measured. Women who undergo adverse childhood experiences are at risk for lasting biological consequences, including affective and stress dysregulation. We have shown that pubertal adversity is associated with a blunted hypothalamic-pituitary-adrenal axis glucocorticoid response in peripartum humans and mice. In mice, our prior examination of the paraventricular nucleus (PVN) of the hypothalamus showed that pubertal stress led to an upregulation of baseline mRNA expression of six immediate early genes (IEGs) in the PVN of adult, pregnant mice. Separately, we showed that the pregnancy-associated hormone allopregnanolone is necessary and sufficient to produce the blunted stress response phenotype in pubertally stressed mice. In the current study, we further examined a potential mechanistic role for the IEGs in the PVN. We found that in pubertally stressed adult female, but not male, mice, intra-PVN allopregnanolone was sufficient to recapitulate the baseline IEG mRNA expression profile previously observed in pubertally stressed, pregnant mice. We also examined baseline IEG mRNA expression during adolescence, where we found that IEGs have developmental trajectories that showed sex-specific disruption by pubertal stress. Altogether, these data establish that IEGs may act as a key molecular switch involved in increased vulnerability to negative outcomes in adult, pubertally stressed animals. How the factors that produce vulnerability combine throughout the lifespan is key to our understanding of the etiology of stress-related disorders.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 2
- FWCI
- 0.58
- Field percentile
- top 42%
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