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Record W2138711760 · doi:10.1186/gb-2010-11-s1-o9

Candidate genes and biological processes in de novo CNVs from autistic individuals

2010· article· en· W2138711760 on OpenAlex
Hyun Ji Noh, Christian R. Marshall, Dalila Pinto, Stephen W. Scherer, Chris P. Ponting, Caleb Webber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGenome Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsAutismCopy-number variationGeneticsGeneCandidate geneAutistic traitsPsychologyBiologyComputational biologyDevelopmental psychologyGenomeAutism spectrum disorder

Abstract

fetched live from OpenAlex

There is growing evidence that common diseases might not result from a few common variants, but rather from many rare variants across many genes/loci. This is likely to be particularly true for disorders such as autism where the fecundity of affected individuals is exceptionally low (~5%) and thus disease-predisposing alleles are unlikely to be transmitted. Since these different disease-contributing genes give rise to a shared disease phenotype, it is likely that their protein products contribute to shared biological processes, such as particular protein pathways or cellular networks. Identifying the common network(s) among these genes would allow the screening of a small subset of genes for early diagnosis and these networks could present multiple points for early intervention. We examined two independent sets of de novo copy number variants (CNVs) identified in individuals with autism spectrum disorders (ASDs): (i) a large discovery set of 73 CNVs identified in 54 patients (median size 118Kb) from the Autism Genome Project (AGP) consortium [ 1 ]; and (ii) a small validation/replication set of 28 CNVs identified in 24 patients (median size 3Mb) [ 2 ]. To identify unexpected shared features among genes overlapped by these CNVs, we exploited phenotype data arising from the disruption of ~6000 human orthologues in mouse. We infer that genes are likely to act in the same biological process if, when disrupted in mouse, they exhibit comparable phenotypes. Thus, we aim to identify significantly over-represented mouse phenotypes among sets of human genes of interest (e.g. genes overlapped by autism-associated CNVs) [ 3 ]. Among genes overlapped by the AGP CNVs, significant enrichments of specific mouse phenotypes were discovered (FDR<5%), most of which were either replicated (FDR<5%) or validated ( p <0.05) in the Marshall set, including: (i) A significant enrichment of genes associated with four abnormal synaptic transmission phenotypes; (ii) A significant enrichment of genes associated with >10 behavioural phenotypes and five hearing phenotypes that are only found within duplicated CNVs. Many of these duplication-specific phenotypic associations are readily comparable to ASD symptoms, such as abnormal motor learning (60-80% of individuals with ASD exhibit impaired coordination), non-convulsive seizures (~1/3 of individuals with ASD suffer seizures, commonly non-convulsive) and sensorineural hearing impairment (25-40% individuals with ASD have hearing impairments). These enrichments identify >100 largely novel candidate genes and provide causal hypothesis for between 19-83% of patients in each cohort.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score0.468

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 head0.010
GPT teacher head0.234
Teacher spread0.224 · 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