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DOI 10.1080/17501911.2026.2613012

Медицинская библиотека · Epigenomics · 2026

Genome-wide methylation patterns associated with chronic stress.

O'Toole Nicholas, Zhang Tie-Yuan, Fitzgerald Eamon, Wen Xianglan, Diorio Josie, Silveira Patricia P, Labonté Benoit, Nestler Eric J, Meaney Michael J

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Аннотация

BACKGROUND

Chronic social defeat stress (CSDS) is a validated animal model for depression that produces sustained behavioral and transcriptional changes in the brain, notably the nucleus accumbens (nAcc).

RESEARCH DESIGN AND

METHODS

We used genome-wide analysis of cytosine methylation patterns in mouse nAcc following CSDS to identify candidate epigenetic mechanisms.

RESULTS

CSDS produced extensive differential methylation, increasing CG hypermethylation compared to control conditions; non-CG methylation showed the opposite trend. Highly differentially methylated (DM) regions included several genes implicated in behavioral effects of CSDS, including estrogen receptor alpha (Esr1).

CONCLUSIONS

Analysis of DM sites within gene bodies revealed ß-catenin as a hub gene of a network including the ß-catenin-related WNT/frizzled signaling pathway. Analysis of DM sites upstream of transcription start sites revealed a gene network with the Tcf4 transcription factor as a hub. Genes DM within the gene body were enriched for synaptic function and primarily expressed in D1+ and D2+ medium spiny neurons, which, like the WNT/ß-catenin pathway, are estrogen sensitive and implicated in the behavioral effects of CSDS. We found significant overlap between DM genes associated with CSDS and those associated with major depressive disorder in genome-wide association studies, suggesting that effects on DNA methylation are implicated in the molecular pathways that link chronic stress to depression.

Для цитирования: O'Toole Nicholas, Zhang Tie-Yuan, Fitzgerald Eamon, Wen Xianglan, Diorio Josie, Silveira Patricia P, Labonté Benoit, Nestler Eric J, Meaney Michael J. Genome-wide methylation patterns associated with chronic stress.. Epigenomics. 2026. DOI: 10.1080/17501911.2026.2613012.

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