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Record W4295887081 · doi:10.3390/genes13091633

Biallelic Loss of Function Mutation in Sodium Channel Gene SCN10A in an Autism Spectrum Disorder Trio from Pakistan

2022· article· en· W4295887081 on OpenAlexafffund
Ansa Rabia, Ricardo Harripaul, Anna Mikhailov, Saqib Mahmood, Shazia Maqbool, John B. Vincent, Muhammad Ayub

Bibliographic record

VenueGenes · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsQueen's UniversityUniversity of TorontoCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsGeneticsProbandExome sequencingBiologyAutism spectrum disorderGeneCopy-number variationPhenotypeMutationCompound heterozygosityGenetic heterogeneityConsanguinityAutismMedicineGenome

Abstract

fetched live from OpenAlex

The genetic dissection of autism spectrum disorders (ASD) has uncovered the contribution of de novo mutations in many single genes as well as de novo copy number variants. More recent work also suggests a strong contribution from recessively inherited variants, particularly in populations in which consanguineous marriages are common. What is also becoming more apparent is the degree of pleiotropy, whereby mutations in the same gene may have quite different phenotypic and clinical consequences. We performed whole exome sequencing in a group of 115 trios from countries with a high level of consanguineous marriages. In this paper we report genetic and clinical findings on a proband with ASD, who inherited a biallelic truncating pathogenic/likely pathogenic variant in the gene encoding voltage-gated sodium channel X alpha subunit, SCN10A (NM_006514.2:c.937G>T:(p.Gly313*)). The biallelic pathogenic/likely pathogenic variant in this study have different clinical features than heterozygous mutations in the same gene. The study of consanguineous families for autism spectrum disorder is highly valuable.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.021
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.298
Teacher spread0.266 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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