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Record W4297348680 · doi:10.3390/genes13101743

Exome Sequencing Identifies a Biallelic GALNS Variant (p.Asp233Asn) Causing Mucopolysaccharidosis Type IVA in a Pakistani Consanguineous Family

2022· article· en· W4297348680 on OpenAlexafffund
Saima Ghafoor, Karina da Costa Silveira, Raheel Qamar, Maleeha Azam, Pekka Kannus

Bibliographic record

VenueGenes · 2022
Typearticle
Languageen
FieldMedicine
TopicLysosomal Storage Disorders Research
Canadian institutionsUniversity of Alberta
FundersWomen and Children's Health Research Institute
KeywordsExome sequencingMissense mutationMucopolysaccharidosisGeneticsMedicineLysosomal storage diseaseExomePhenotypePopulationDiseaseBiologyPediatricsBioinformaticsPathologyGene

Abstract

fetched live from OpenAlex

Mucopolysaccharidoses (MPS) type IVA is a lysosomal storage disease that mainly affects the skeletal system and is caused by a deficiency of the enzyme N-acetylgalactosamine-6-sulfatase (GALNS). The condition can mistakenly be diagnosed as a primary skeletal dysplasia such as spondylo-epiphyseal dysplasia, which shares many similar phenotypic features. Here, we utilised whole exome sequencing to make the diagnosis of MPS IVA in a resource poor country. We report for the first time the identification of a biallelic GALNS missense variant (c.697G>A, p.Asp233Asn) in the Pakistani population and highlight the potential contribution that academic institutions can make in rare disease diagnosis in the absence of a developed clinical genetic service.

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 score0.006
Threshold uncertainty score0.013

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
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 head0.057
GPT teacher head0.317
Teacher spread0.260 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

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