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Record W2016078825 · doi:10.1002/humu.22797

A Gain-of-Function Mutation in<i>NALCN</i>in a Child with Intellectual Disability, Ataxia, and Arthrogryposis

2015· article· en· W2016078825 on OpenAlexafffund
Kyota Aoyagi, Elsa Rossignol, Fadi F. Hamdan, Ben Mulcahy, Lin Xie, Shinya Nagamatsu, Guy A. Rouleau, Mei Zhen, Jacques L. Michaud

Bibliographic record

VenueHuman Mutation · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsMcGill UniversityMontreal Neurological Institute and HospitalUniversity of TorontoLunenfeld-Tanenbaum Research InstituteUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
FundersCanadian Institutes of Health Research
KeywordsArthrogryposisBiologyAtaxiaMutationGeneticsIntellectual disabilityGain of functionNeuroscienceGene

Abstract

fetched live from OpenAlex

NALCN and its homologues code for the ion channel responsible for half of background Na(+) -leak conductance in vertebrate and invertebrate neurons. Recessive mutations in human NALCN cause intellectual disability (ID) with hypotonia. Here, we report a de novo heterozygous mutation in NALCN affecting a conserved residue (p.R1181Q) in a girl with ID, episodic and persistent ataxia, and arthrogryposis. Interestingly, her episodes of ataxia were abolished by the administration of acetazolamide, similar to the response observed in episodic ataxia associated with other ion channels. Introducing the analogous mutation in the Caenorhabditis elegans homologue nca-1 induced a coiling locomotion phenotype, identical to that obtained with previously characterized C. elegans gain-of-function nca alleles, suggesting that p.R1181Q confers the same property to NALCN. This observation thus suggests that dominant mutations in NALCN can cause a neurodevelopmental phenotype that overlaps with, while being mostly distinct from that associated with recessive mutations in the same gene.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.350

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 head0.016
GPT teacher head0.245
Teacher spread0.229 · 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 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

Citations61
Published2015
Admission routes2
Has abstractyes

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