Permissive epigenetic regulatory mechanisms at the histone level are enhanced in postmortem dorsolateral prefrontal cortex of individuals with schizophrenia
Bibliographic record
Abstract
Background: Susceptibility to schizophrenia is determined by interactions between genes and environment, possibly via epigenetic mechanisms. Schizophrenia has been associated with a restrictive epigenome, and histone deacetylase (HDAC) inhibitors have been postulated as coadjuvant agents to potentiate the efficacy of current antipsychotic drugs. We aimed to evaluate global histone posttranslational modifications (HPTMs) and HDAC expression and activity in the dorsolateral prefrontal cortex (DLPFC) of individuals with schizophrenia. Methods: We used postmortem DLPFC samples of individuals with schizophrenia and controls matched for sex, age, and postmortem interval. Schizophrenia samples were classified into antipsychotic-treated or antipsychotic-free subgroups according to blood toxicology. Expression of HPTMs and HDAC was quantified by Western blot. HDAC activity was measured with a fluorometric assay. Results: H3K9ac, H3K27ac, and H3K4me3 were globally enhanced in the DLPFC of individuals with schizophrenia (+24%–42%, p < 0.05). HDAC activity (−17%, p < 0.01) and HDAC4 protein expression (−20%, p < 0.05) were downregulated in individuals with schizophrenia. Analyses of antipsychotic-free and antipsychotic-treated subgroups revealed enhanced H3K4me3 and H3K27ac (+24%–49%, p < 0.05) and reduced HDAC activity in the antipsychotic-treated, but not in the antipsychotic-free subgroup. Limitations: Special care was taken to control the effect of confounding factors: age, sex, postmortem interval, and storage time. However, replication studies in bigger cohorts might strengthen the association between permissive HPTMs and schizophrenia. Conclusion: We found global HPTM alterations consistent with an aberrantly permissive epigenome in schizophrenia. Further studies to elucidate the significance of enhanced permissive HPTMs in schizophrenia and its association with the mechanism of action of antipsychotic drugs are encouraged.
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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 | 0.001 | 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".