Sex-specific effects of the histone variant H2A.Z on fear memory, stress-enhanced fear learning and hypersensitivity to pain
Bibliographic record
Abstract
Emerging evidence suggests that histone variants are novel epigenetic regulators of memory, whereby histone H2A.Z suppresses fear memory. However, it is not clear if altered fear memory can also modify risk for PTSD, and whether these effects differ in males and females. Using conditional-inducible H2A.Z knockout (cKO) mice, we showed that H2A.Z binding is higher in females and that H2A.Z cKO enhanced fear memory only in males. However, H2A.Z cKO improved memory on the non-aversive object-in-place task in both sexes, suggesting that H2A.Z suppresses non-stressful memory irrespective of sex. Given that risk for fear-related disorders, such as PTSD, is biased toward females, we examined whether H2A.Z cKO also has sex-specific effects on fear sensitization in the stress-enhanced fear learning (SEFL) model of PTSD, as well as associated changes in pain sensitivity. We found that H2A.Z cKO reduced stress-induced sensitization of fear learning and pain responses preferentially in female mice, indicating that the effects of H2A.Z depend on sex and the type of task, and are influenced by history of stress. These data suggest that H2A.Z may be a sex-specific epigenetic risk factor for PTSD susceptibility, with implications for developing sex-specific therapeutic interventions.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".