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Record W4387405672 · doi:10.3390/ijms241914926

Transcriptional Dysregulation and Impaired Neuronal Activity in FMR1 Knock-Out and Fragile X Patients’ iPSC-Derived Models

2023· article· en· W4387405672 on OpenAlexafffund
Gilles Maussion, Cecilia Rocha, Narges Abdian, Dimitri Yang, J Turk, Dulce Carrillo Valenzuela, Luisa Pimentel, Zhipeng You, Barbara Morquette, Michaël Nicouleau, Éric Deneault, Samuel G. Higgins, Carol X.‐Q. Chen, Wolfgang Reintsch, Stanley Ho, Vincent Soubannier, Sarah Lépine, Zora Modrušan, Jessica Lund, William Stephenson, Rajib Schubert, Thomas M. Durcan

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsMcGill University Health CentreMcGill UniversityHealth CanadaMontreal Neurological Institute and Hospital
FundersDjavad Mowafaghian FoundationCanada First Research Excellence FundMcGill University
KeywordsFMR1Fragile X syndromeBiologyInduced pluripotent stem cellForebrainCell biologyNeuroscienceNeural stem cellGeneGeneticsStem cellFragile xEmbryonic stem cell

Abstract

fetched live from OpenAlex

Fragile X syndrome (FXS) is caused by a repression of the FMR1 gene that codes the Fragile X mental retardation protein (FMRP), an RNA binding protein involved in processes that are crucial for proper brain development. To better understand the consequences of the absence of FMRP, we analyzed gene expression profiles and activities of cortical neural progenitor cells (NPCs) and neurons obtained from FXS patients’ induced pluripotent stem cells (IPSCs) and IPSC-derived cells from FMR1 knock-out engineered using CRISPR-CAS9 technology. Multielectrode array recordings revealed in FMR1 KO and FXS patient cells, decreased mean firing rates; activities blocked by tetrodotoxin application. Increased expression of presynaptic mRNA and transcription factors involved in the forebrain specification and decreased levels of mRNA coding AMPA and NMDA subunits were observed using RNA sequencing on FMR1 KO neurons and validated using quantitative PCR in both models. Intriguingly, 40% of the differentially expressed genes were commonly deregulated between NPCs and differentiating neurons with significant enrichments in FMRP targets and autism-related genes found amongst downregulated genes. Our findings suggest that the absence of FMRP affects transcriptional profiles since the NPC stage, and leads to impaired activity and neuronal differentiation over time, which illustrates the critical role of FMRP protein in neuronal development.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.018
GPT teacher head0.255
Teacher spread0.236 · 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
GenreEmpirical

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

Citations13
Published2023
Admission routes2
Has abstractyes

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