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Record W3042838846 · doi:10.3389/fnins.2020.00664

Functional Validation of CLDN Variants Identified in a Neural Tube Defect Cohort Demonstrates Their Contribution to Neural Tube Defects

2020· article· en· W3042838846 on OpenAlexafffund
Amanda I. Baumholtz, Patrizia De Marco, Valeria Capra, Aimee K. Ryan

Bibliographic record

VenueFrontiers in Neuroscience · 2020
Typearticle
Languageen
FieldNeuroscience
TopicBarrier Structure and Function Studies
Canadian institutionsMcGill University Health CentreMcGill University
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of CanadaMcGill University Health CentreChildren's Hospital Foundation
KeywordsNeural tubeClaudinMissense mutationBiologyNeural tube defectGeneticsNeurulationBioinformaticsGeneMutationEmbryoTight junctionEmbryogenesis

Abstract

fetched live from OpenAlex

Neural tube defects (NTDs) are severe malformations of the central nervous system that affect 1-2 individuals per 2000 births. Their etiology is complex and involves both genetic and environmental factors. Our recent discovery that simultaneous removal of Cldn3, -4 and -8 from tight junctions results in cranial and spinal NTDs in both chick and mouse embryos suggests that claudins play a conserved role in neural tube closure in vertebrates. To determine if claudins were associated with NTDs in humans, we used a Fluidigm next generation sequencing approach to identify genetic variants in CLDN loci in 152 patients with spinal NTDs. We identified eleven rare and four novel missense mutations in ten CLDN genes. In vivo validation of variant pathogenicity using a chick embryo model system revealed that overexpression of four variants caused a significant increase in NTDs: CLDN3 A128T, CLDN8 P216L, CLDN19 I22T and E209G. Our data implicate rare missense variants in CLDN genes as risk factors for spinal NTDs and identify a new family of proteins involved in the pathogenesis of these malformations.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.031
GPT teacher head0.245
Teacher spread0.214 · 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.

Study designObservational
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

Citations9
Published2020
Admission routes2
Has abstractyes

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