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Record W6901627189 · doi:10.60692/gxcc0-6se17

Novel loss-of-function variants expand ABCC9-related intellectual disability and myopathy syndrome

2024· article· en· W6901627189 on OpenAlexaff

Bibliographic record

VenueGreater South Information System · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsIntellectual disabilityPsychomotor learningZebrafishPhenotypeMicrocephalyMutationCorpus callosumGeneMyopathy

Abstract

fetched live from OpenAlex

Loss-of-function mutation of ABCC9, the gene encoding the SUR2 subunit of ATP sensitive-potassium (KATP) channels, was recently associated with autosomal recessive ABCC9-related intellectual disability and myopathy syndrome (AIMS). Here we identify nine additional subjects, from seven unrelated families, harboring different homozygous LoF variants in ABCC9 and presenting with a conserved range of clinical features. All variants are predicted to result in severe truncations or in-frame deletions within SUR2, leading to the generation of non-functional SUR2-dependent KATP channels. Affected individuals show psychomotor delay and intellectual disability of variable severity, microcephaly, corpus callosum and white matter abnormalities, seizures, spasticity, short stature, muscle fatigability, and weakness. Heterozygous parents do not show any conserved clinical pathology but report multiple incidences of intrauterine fetal death, which were also observed in an eighth family included in this study. In vivo studies of abcc9 LoF in zebrafish revealed an exacerbated motor response to pentylenetetrazole, a pro-convulsive drug, consistent with impaired neurodevelopment associated with an increased seizure susceptibility. Our findings define an ABCC9 LoF related phenotype, expanding the genotypic and phenotypic spectrum of AIMS and reveal novel human pathologies arising from KATP channel dysfunction.

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 score0.310
Threshold uncertainty score0.440

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 head0.018
GPT teacher head0.220
Teacher spread0.202 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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