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Record W2488063178 · doi:10.1136/jmedgenet-2016-103818

Copy-number variations are enriched for neurodevelopmental genes in children with developmental coordination disorder

2016· article· en· W2488063178 on OpenAlexafffundabout
Stephen J. Mosca, Lisa Marie Langevin, Deborah Dewey, A. Micheil Innes, Anath C. Lionel, Christian Marshall, Stephen W. Scherer, Jillian S. Parboosingh, François P. Bernier

Bibliographic record

VenueJournal of Medical Genetics · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsAlberta Health ServicesHospital for Sick ChildrenUniversity of TorontoAlberta Children's HospitalUniversity of Calgary
FundersInstitute of Human Development, Child and Youth HealthCanadian Institutes of Health Research
KeywordsCopy-number variationNeurodevelopmental disorderGeneticsSNP arrayGenetic architectureGenome-wide association studyDevelopmental disorderPervasive developmental disorderIntellectual disabilityAutismBiologyGeneSingle-nucleotide polymorphismPsychologyGenomePsychiatryPhenotypeGenotype

Abstract

fetched live from OpenAlex

BACKGROUND: Developmental coordination disorder is a common neurodevelopment disorder that frequently co-occurs with other neurodevelopmental disorders including attention-deficit hyperactivity disorder (ADHD). Copy-number variations (CNVs) have been implicated in a number of neurodevelopmental and psychiatric disorders; however, the proportion of heritability in developmental coordination disorder (DCD) attributed to CNVs has not been explored. OBJECTIVE: This study aims to investigate how CNVs may contribute to the genetic architecture of DCD. METHODS: CNV analysis was performed on 82 extensively phenotyped Canadian children with DCD, with or without co-occurring ADHD and/or reading disorder, and 2988 healthy European controls using identical genome-wide SNP microarrays and CNV calling algorithms. RESULTS: An increased rate of large and rare genic CNVs (p=0.009) was detected, and there was an enrichment of duplications spanning brain-expressed genes (p=0.039) and genes previously implicated in other neurodevelopmental disorders (p=0.043). Genes and loci of particular interest in this group included: GAP43, RBFOX1, PTPRN2, SHANK3, 16p11.2 and distal 22q11.2. Although no recurrent CNVs were identified, 26% of DCD cases, where sample availability permitted segregation analysis, were found to have a de novo rare CNV. Of the inherited CNVs, 64% were from a parent who also had a neurodevelopmental disorder. CONCLUSIONS: These findings suggest that there may be shared susceptibility genes for DCD and other neurodevelopmental disorders and highlight the need for thorough phenotyping when investigating the genetics of neurodevelopmental disorders. Furthermore, these data provide compelling evidence supporting a genetic basis for DCD, and further implicate rare CNVs in the aetiology of neurodevelopmental disorders.

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 score0.024
Threshold uncertainty score0.292

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 head0.007
GPT teacher head0.234
Teacher spread0.227 · 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

Citations87
Published2016
Admission routes3
Has abstractyes

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