Epigenetic signatures of chronic social stress in stress-susceptible animals
Bibliographic record
Abstract
Abstract Exposure of mice to chronic social defeat stress (CSDS) produces depressive- and anxiety-like behaviors and widespread transcriptomic changes in several brain regions in susceptible animals. Here we present the first study of genome-wide cytosine methylation patterns of mice susceptible to CSDS using whole-genome bisulfite sequencing on DNA from the nucleus accumbens, a critical region for CSDS effects on behavior. We found extensive evidence for differential methylation following exposure to CSDS in susceptible animals, with a greater proportion of CG hypermethylation than hypomethylation in CSDS-susceptible mice compared to non-stressed controls; non-CG methylation shows the opposite trend. Several genes previously implicated in the effects of CSDS are among those with the greatest number of differentially methylated sites, including estrogen receptor alpha ( Esr1 ), the deleted in colorectal cancer ( Dcc ) gene and Cacna1c , which has been associated with a range of psychiatric conditions. Informatic analysis of DM sites revealed a gene network with ß-catenin as the hub gene of a network that included the ß-catenin-related WNT/frizzled signaling pathway as well as both Esr1 and Dcc . Finally, we found considerable overlap between DM genes associated with CSDS in susceptible animals and those associated with human neuroticism in a genome-wide association study. Analysis of these overlapping genes revealed ‘WNT signaling’ as the top pathway, which features ß-catenin as the primary hub gene. These findings reveal a striking convergence between the molecular pathways identified through either transcriptional or epigenomic analyses of the mouse model of susceptibility to chronic stress and the genomic architecture of increased stress susceptibility reflected in neuroticism in humans.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".