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Record W2726119716 · doi:10.1038/mp.2017.161

A neurogenetic model for the study of schizophrenia spectrum disorders: the International 22q11.2 Deletion Syndrome Brain Behavior Consortium

2017· article· en· W2726119716 on OpenAlexaff
Raquel E. Gur, Anne S. Bassett, Donna M. McDonald‐McGinn, Carrie E. Bearden, Eva W.C. Chow, B S Emanuel, Michael J. Owen, Ann Swillen, Marianne B. M. van den Bree, Joris Vermeesch, J.A.S. Vorstman, Stephen T. Warren, Thomas Lehner, Bernice E. Morrow

Bibliographic record

VenueMolecular Psychiatry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsToronto General HospitalUniversity of TorontoCentre for Addiction and Mental Health
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Center for Advancing Translational SciencesNational Institute of Mental HealthMedical Research CouncilSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungWellcome Trust
KeywordsSchizophrenia (object-oriented programming)PsychosisLocus (genetics)DiGeorge syndromeGeneticsCopy-number variationPhenotypeGenome-wide association studyPopulationBiologyDeletion syndromeBioinformaticsNeurosciencePsychologyMedicineGenePsychiatrySingle-nucleotide polymorphismGenomeGenotype

Abstract

fetched live from OpenAlex

Rare copy number variants contribute significantly to the risk for schizophrenia, with the 22q11.2 locus consistently implicated. Individuals with the 22q11.2 deletion syndrome (22q11DS) have an estimated 25-fold increased risk for schizophrenia spectrum disorders, compared to individuals in the general population. The International 22q11DS Brain Behavior Consortium is examining this highly informative neurogenetic syndrome phenotypically and genomically. Here we detail the procedures of the effort to characterize the neuropsychiatric and neurobehavioral phenotypes associated with 22q11DS, focusing on schizophrenia and subthreshold expression of psychosis. The genomic approach includes a combination of whole-genome sequencing and genome-wide microarray technologies, allowing the investigation of all possible DNA variation and gene pathways influencing the schizophrenia-relevant phenotypic expression. A phenotypically rich data set provides a psychiatrically well-characterized sample of unprecedented size (n=1616) that informs the neurobehavioral developmental course of 22q11DS. This combined set of phenotypic and genomic data will enable hypothesis testing to elucidate the mechanisms underlying the pathogenesis of schizophrenia spectrum 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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score0.489

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 science0.0010.000
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 head0.016
GPT teacher head0.309
Teacher spread0.293 · 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

Citations97
Published2017
Admission routes1
Has abstractyes

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