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Record W2759153061 · doi:10.1038/s41525-017-0031-6

Atypical autism in a boy with double duplication of 22q11.2: implications of increasing dosage

2017· article· en· W2759153061 on OpenAlexafffund
Breanne Dale, Bonnie MacKinnon Modi, Sanne Jilderda, Beth McConnell, Ny Hoang, Pooja Swaroop, Jhoan Falcon, Bhooma Thiruvahindrapuram, Susan Walker, Stephen W. Scherer, Dimitri J. Stavropoulos, Irene Drmic, Melissa T. Carter

Bibliographic record

Venuenpj Genomic Medicine · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsChildren's Hospital of Eastern OntarioSickKids FoundationUniversity of TorontoHospital for Sick Children
FundersHospital for Sick ChildrenGlaxoSmithKlineUniversity of TorontoPhysicians' Services Incorporated FoundationCanadian Institutes of Health ResearchGenome CanadaAutism Speaks
KeywordsAutismGene duplicationPsychologyGeneticsDevelopmental psychologyBiologyGene

Abstract

fetched live from OpenAlex

Duplication of chromosome 22q11.2 (LCR A-D) has been reported at higher frequencies in clinical samples than the general population, but phenotypes vary widely. Triplication (4 copies) is rare, but studying the associated phenotype may provide insight into dosage-sensitivity of the genes in this chromosomal interval. We describe a proband with a triplication, specifically a "double duplication" (two copies per chromosome) of the 22q11.2 region, while his parents and two siblings each have a single duplication (3 copies). The proband had a heart malformation, dysmorphic features, and learning and socialization deficits, whereas the other family members did not. This family illustrates that while duplication of the 22q11.2 may not be sufficient to cause clinically significant neurodevelopmental or health-related phenotypes, triplication of the same region may result in a phenotype characterized by a mild neurodevelopmental disorder, facial dysmorphism, and possibly cardiac anomalies.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.876
Threshold uncertainty score0.258

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 head0.028
GPT teacher head0.335
Teacher spread0.307 · 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 designBench or experimental
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
Published2017
Admission routes2
Has abstractyes

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