Evidence map›Paper›PMID 41009596›Full record

ArticleInternational journal of molecular sciences2025

Transcriptional Consequences of MeCP2 Knockdown and Overexpression in Mouse Primary Cortical Neurons.

Mostafa Rezapour, Joshua Bowser, Christine Richardson, Metin Nafi Gurcan

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Artificial Intelligence in Bulk RNA-Seq: Challenges and Potential Solutions.Computational and structural biotechnology journal · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Mostafa RezapourWake Forest Institute for Regenerative Medicine (WFIRM), Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.ORCID 0000-0001-9569-118X
Joshua BowserDepartment of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.ORCID 0009-0004-0997-8133
Christine RichardsonDepartment of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC 28223, USA.
Metin Nafi GurcanCenter for Artificial Intelligence Research, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.ORCID 0000-0002-2421-8229

Funding

Culturally Augmented Learning In Biomedical Informatics Research (CALIBIR) ProgramR25LM014214 · NLM · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI Metin Nafi Gurcan, AREZOO MOVAGHAR · 2022 to 2026
$671k
NLM NIH HHS R25 LM014214
6 · The paper itself

Abstract

Rett syndrome (RTT) and MECP2 duplication syndrome, a subtype of autism spectrum disorder (ASD), are neurodevelopmental disorders caused by MeCP2 loss and gain of function, respectively. While MeCP2 is known to regulate transcription through its interaction with methylated DNA and chromatin-associated factors such as topoisomerase IIβ (TOP2β), the downstream transcriptional consequences of MeCP2 dosage imbalance remain partially characterized. Here, we present a transcriptome-centered analysis of mouse primary cortical neurons subjected to MeCP2 knockdown (KD) or overexpression (OE), which model RTT and ASD-like conditions in parallel. Using a robust computational pipeline integrating generalized linear models with quasi-likelihood F-tests and Magnitude-Altitude Scoring (GLMQL-MAS), we identified differentially expressed genes (DEGs) in KD and OE relative to wild-type (WT) neurons. This study represents a computational analysis of secondary transcriptomic data aimed at nominating candidate genes for future experimental validation. Gene Ontology enrichment revealed both shared and condition-specific biological processes, with KD uniquely affecting neurodevelopmental and stress-response pathways, and OE perturbing extracellular matrix, calcium signaling, and neuroinflammatory processes. To prioritize robust and disease-relevant targets, we applied Cross-MAS and further filtered DEGs by correlation with MeCP2 expression and regulation directional consistency. This yielded 16 high-confidence dosage-sensitive genes that were capable of classifying WT, KD, and OE samples with 100% accuracy using PCA and logistic regression. Among these, RTT-associated candidates such as Plcb1, Gpr161, Mknk2, Rgcc, and Abhd6 were linked to disrupted synaptic signaling and neurogenesis, while ASD-associated genes, including Aim2, Mcm6, Pcdhb9, and Cbs, implicated neuroinflammation and metabolic stress. These findings establish a compact and mechanistically informative set of MeCP2-responsive genes, which enhance our understanding of transcriptional dysregulation in RTT and ASD and nominate molecular markers for future functional validation and therapeutic exploration.

Indexed as

Cerebral CortexMethyl-CpG-Binding Protein 2NeuronsRett SyndromeTranscription, GeneticAnimalsAutism Spectrum DisorderCells, CulturedGene Expression ProfilingGene Expression RegulationGene Knockdown TechniquesMiceTranscriptomeMecp2 protein, mouseMethyl-CpG-Binding Protein 2autism spectrum disorderbiomarker discoveryCross-MASdifferential expression analysisGLMQL-MASMeCP2mouse cortical neuronsneurodevelopmental disorderRett syndromeRNA-seq

Identifiers

PMID41009596
PMCPMC12469642

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.