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Record W2754543134 · doi:10.1002/ajmg.a.38400

Compound heterozygous <i>TRPV4</i> mutations in two siblings with a complex phenotype including severe intellectual disability and neuropathy

2017· article· en· W2754543134 on OpenAlexaff
My Linh Thibodeau, Colin H. Peters, Katelin N. Townsend, Yaoqing Shen, Glenda Hendson, Shelin Adam, Kathryn Selby, Patrick MacLeod, Cynthia Gershome, Peter C. Ruben, Steven J.M. Jones, Jan M. Friedman, William T. Gibson, Gabriella Horváth

Bibliographic record

VenueAmerican Journal of Medical Genetics Part A · 2017
Typearticle
Languageen
FieldNeuroscience
TopicIon Channels and Receptors
Canadian institutionsCanada's Michael Smith Genome Sciences CentreVictoria General HospitalBC Children's HospitalSimon Fraser UniversityUniversity of British Columbia
Fundersnot available
KeywordsTRPV4PhenotypeCompound heterozygosityLoss functionIntellectual disabilityGeneticsMutationLoss of heterozygosityDiseaseFamilial hemiplegic migraineBiologyClinical phenotypeMedicineTransient receptor potential channelGenePathologyAllele

Abstract

fetched live from OpenAlex

TRPV4 encodes a polymodal calcium-permeable plasma membrane channel. Dominant pathogenic mutations in TRPV4 lead to a wide spectrum of abnormal phenotypes. This is the first report of biallelic TRPV4 mutations and we describe two compound heterozygous siblings presenting with a complex phenotype including severe neuromuscular involvement. In light of previously well described dominant inheritance for TRPV4-related neuromuscular disease, our study suggests a role for compound heterozygosity and loss-of-function as a potential novel disease mechanism for this group of disorders. Profound intellectual disability was also noted in both affected children, suggesting that TRPV4 may be necessary for normal brain 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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.072
GPT teacher head0.354
Teacher spread0.282 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations24
Published2017
Admission routes1
Has abstractyes

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Same venueAmerican Journal of Medical Genetics Part ASame topicIon Channels and ReceptorsFrench-language works237,207