Evidence map›Paper›PMID 41566898›Full record

SynthesisBrain and behavior2026

A Meta-Analysis of the Effects of Chronic Stress on the Prefrontal Transcriptome in Animal Models and Convergence With Existing Human Data.

Jinglin Xiong, Megan H Hagenauer, Cosette A Rhoads, Elizabeth Flandreau, Nancy Rempel-Clower, Erin Hernandez, Duy Manh Nguyen, Annaka Saffron, Toni Duan, Stanley Watson and 1 more

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Epigenetic Signatures of Social Defeat Stress Varying Duration.International journal of molecular sciences · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Jinglin XiongGrinnell College, Grinnell, Iowa, USA.
Megan H HagenauerMichigan Neuroscience Institute, University of Michigan, Ann Arbor, Michigan, USA.
Cosette A RhoadsGrinnell College, Grinnell, Iowa, USA.
Elizabeth FlandreauGrand Valley State University, Allendale, Michigan, USA.
Nancy Rempel-ClowerGrinnell College, Grinnell, Iowa, USA.
Erin HernandezGrinnell College, Grinnell, Iowa, USA.
Duy Manh NguyenGrinnell College, Grinnell, Iowa, USA.
Annaka SaffronJohns Hopkins University, Baltimore, Maryland, USA.
Toni DuanGrinnell College, Grinnell, Iowa, USA.
Stanley WatsonMichigan Neuroscience Institute, University of Michigan, Ann Arbor, Michigan, USA.
Huda AkilMichigan Neuroscience Institute, University of Michigan, Ann Arbor, Michigan, USA.

Funding

Investigating the role of Bmp4 in glial subtype specification and temperamentU01DA043098 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI HUDA AKIL, Jun Li · 2017 to 2026
$6.9M
Faculty for Undergraduate NeuroscienceGrinnell CollegeHope for Depression Research FoundationInternational Brain Research OrganizationNIDA NIH HHS U01 DA043098Pritzker Neuropsychiatric Disorders Research Foundation
6 · The paper itself

Abstract

backgroundChronic stress is a major risk factor for psychiatric disorders, including anxiety, depression, and post-traumatic stress disorder. Chronic stress can cause structural alterations like grey matter atrophy in key emotion-related areas such as the prefrontal cortex (PFC). To identify biological pathways affected by chronic stress in the PFC, researchers have performed transcriptional profiling (RNA sequencing, microarray) to measure gene expression in rodent models. However, transcriptional signatures in the PFC that are shared across different chronic stress paradigms and laboratories remain relatively unexplored.

methodsWe performed a meta-analysis of publicly available transcriptional profiling datasets within the Gemma database. We identified six datasets that characterized the effects of either chronic social defeat stress (CSDS) or chronic variable stress and/or chronic unpredictable mild stress (CUMS) on gene expression in the PFC in mice (n = 117). We fit a random effects meta-analysis model to the chronic stress effect sizes (log(2) fold changes) for each transcript (n = 21,379) measured in most datasets. We then compared our results with two other published chronic stress meta-analyses, as well as transcriptional signatures associated with psychiatric disorders.

resultsWe identified 133 genes that were consistently differentially expressed across chronic stress studies and paradigms (false discovery rate [FDR] < 0.05). Fast gene set enrichment analysis (fGSEA) revealed 53 gene sets enriched with differential expression (FDR < 0.05), dominated by glial and neurovascular markers (e.g., oligodendrocyte, astrocyte, endothelial/vascular) and stress-related signatures (e.g., major depressive disorder [MDD], hormonal responses). Immediate-early gene markers of neuronal activity (Fos, Junb, Arc, Dusp1) were consistently suppressed. Many of the identified effects resembled those seen in previous meta-analyses characterizing stress effects (CSDS, early life stress), despite minimal overlap in included samples. Moreover, some effects resembled previous observations from psychiatric disorders, including alcohol abuse disorder, ma, bipolar disorder, and schizophrenia.

conclusionOur study demonstrates that chronic stress induces a robust, cross-paradigm PFC signature characterized by downregulation of glia/myelin and vascular pathways and suppression of immediate-early gene activity, highlighting cellular processes linking chronic stress exposure, PFC dysfunction, and psychiatric disorders.

Indexed as

Prefrontal CortexStress, PsychologicalTranscriptomeAnimalsChronic DiseaseDisease Models, AnimalGene Expression ProfilingHumansMiceSocial Defeatchronic stressmeta‐analysismicroarrayprefrontal cortexRNA sequencing (RNA‐Seq)

Identifiers

PMID41566898
PMCPMC12824456

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.