Prenatal maternal stress is associated with increased sensitivity to neuropathic pain and sex-specific epigenetic and transcriptomic dynamics in the prefrontal cortex
Bibliographic record
Abstract
Abstract Prenatal maternal stress (PNS) is a common early-life adversity. PNS has been linked to greater vulnerability to chronic pain in the offspring. PNS results in increased hypersensitivity after Chronic Constriction Injury (CCI) of the sciatic nerve, a common rodent model for chronic neuropathic pain. These behavioral effects are accompanied by altered levels of enzymes that regulate DNA methylation in the frontal cortex. DNA methylation, the addition of a methyl group onto cytosine bases of cytosine-guanine (CpG) sites in the genome, is an epigenetic mechanism by which life experiences can reprogram gene expression. The goal of this study was to identify differentially methylated regions that might contribute to the increased pain sensitivity following nerve injury in adulthood. Prior studies indicate widespread, sex-specific transcriptomic changes and numerous differentially methylated regions (DMRs) in the frontal cortex following PNS and nerve injury. Here we performed genome wide DNA methylation and transcriptome-wide RNAseq analysis in the frontal cortex of male and female mice that underwent PNS, CCI or both. Our analysis revealed sex-dependent changes in DNA methylation and mRNA expression, including in pathways related to neuronal and brain development, axonogenesis and synaptic regulation. The effect of DNA methylation on mRNA expression was tested in a subset of target genes. These studies suggest a role for DNA methylation in embedding increased risk for chronic pain in adulthood associated with early-life adversity.
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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".