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Record W4411384835 · doi:10.1002/brb3.70608

A Meta‐Analysis of the Effects of Early Life Stress on the Prefrontal Cortex Transcriptome Reveals Long‐Term Downregulation of Myelin‐Related Gene Expression

2025· review· en· W4411384835 on OpenAlexaff
Toni Q. Duan, Megan Hastings Hagenauer, Elizabeth I. Flandreau, Anne Bader, Duy Manh Nguyen, Pamela M. Maras, Randriely Merscher Sobreira de Lima, Trevonn Gyles, Christabel Mclain, Michael J. Meaney, Eric J. Nestler, Stanley J. Watson, Huda Akil

Bibliographic record

VenueBrain and Behavior · 2025
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsDouglas Mental Health University InstituteDouglas CollegeMcGill University
FundersNational Institute of Mental HealthInternational Brain Research OrganizationGrinnell CollegeNational Institute on Drug AbuseHope for Depression Research Foundation
KeywordsPrefrontal cortexGene expressionOutlierTranscriptomeBiologyMicroarrayFalse discovery rateGene expression profilingMicroarray analysis techniquesPsychologyGeneCognitionGeneticsNeuroscienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Early life stress (ELS) refers to exposure to negative childhood experiences, such as neglect, disaster, and physical, mental, or emotional abuse. ELS can permanently alter the brain, leading to cognitive impairment, increased sensitivity to future stressors, and mental health risks. The prefrontal cortex (PFC) is a key brain region implicated in the effects of ELS. METHODS: To better understand the effects of ELS on the PFC, we ran a meta-analysis of publicly available transcriptional profiling datasets. We identified five datasets (GSE89692, GSE116416, GSE14720, GSE153043, and GSE124387) that characterized the long-term effects of multiday postnatal ELS paradigms (maternal separation, limited nesting/bedding) in male and female laboratory rodents (rats, mice). The outcome variable was gene expression in the PFC later in adulthood as measured by microarray or RNA-Seq. To conduct the meta-analysis, preprocessed gene expression data were extracted from the Gemma database. Following quality control, the final sample size was n = 89(n = 42 controls and n = 47 ELS: GSE116416, n = 23 (no outliers); GSE116416, n = 44 (two outliers); GSE14720, n = 7 (no outliers); GSE153043, n = 9 (one outlier); and GSE124387, n = 6 (no outliers)). Differential expression was calculated using the limma pipeline followed by an empirical Bayes correction. For each gene, a random-effects meta-analysis model was then fit to the ELS versus control effect sizes (Log2 Fold Changes) from each study. RESULTS: Our meta-analysis yielded stable estimates for 11,885 genes, identifying five genes with differential expression following ELS (false discovery rate < 0.05) - transforming growth factor alpha (Tgfa), IQ motif containing GTPase activating protein 3 (Iqgap3), collagen, type XI, alpha 1 (Col11a1), claudin 11 (Cldn11), and myelin-associated glycoprotein (Mag) - all of which were downregulated. Broadly, gene sets associated with oligodendrocyte differentiation, myelination, and brain development were downregulated following ELS. In contrast, genes previously shown to be upregulated in major depressive disorder patients were upregulated following ELS. CONCLUSION: These findings suggest that ELS during critical periods of development may produce long-term effects on the efficiency of transmission in the PFC and drive changes in gene expression similar to those underlying depression.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.641
Threshold uncertainty score0.667

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.328
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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