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Rare Genome-Wide Copy Number Variation and Expression of Schizophrenia in 22q11.2 Deletion Syndrome

2017· article· en· W2741030453 on OpenAlexafffund
Anne S. Bassett, Chelsea Lowther, Daniele Merico, Gregory Costain, Eva W.C. Chow, Thérèse van Amelsvoort, Donna M. McDonald‐McGinn, Raquel E. Gur, Ann Swillen, Marianne B. M. van den Bree, Kieran C. Murphy, Doron Gothelf, Carrie E. Bearden, Stéphan Eliez, Wendy R. Kates, Nicole Philip, Vandana Sashi, Linda Campbell, Jacob Vorstman, Joseph F. Cubells, Gabriela M. Repetto, Erik Boot, Tracy Heung, Rens Evers, Claudia Vingerhoets, Esther van Duin, Elaine H. Zackai, Elfi Vergaelen, Koenraad Devriendt, Joris Vermeesch, Michael J. Owen, Clodagh M. Murphy, Elena Michaelovosky, Leila Kushan, Maude Schneider, Wanda Fremont, Tiffany Busa, Stephen R. Hooper, Kathryn McCabe, Sasja N. Duijff, Keren Isaev, Giovanna Pellecchia, John Wei, Matthew J. Gazzellone, Stephen W. Scherer, Beverly S. Emanuel, Tingwei Guo, Bernice E. Morrow, Christian R. Marshall

Bibliographic record

VenueAmerican Journal of Psychiatry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital heart defects research
Canadian institutionsCentre for Addiction and Mental Health
FundersCanadian Institutes of Health ResearchPerelman School of Medicine, University of PennsylvaniaDepartment of Psychiatry, University of TorontoCampbell Family Mental Health Research InstituteSyracuse UniversityClínica Alemana de SantiagoKU LeuvenNational Institute of Mental HealthHospital for Sick ChildrenJane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los AngelesTel Aviv UniversityMedical Research CouncilCardiff UniversityEmory UniversityRoyal College of Surgeons in IrelandUniversity of TorontoUniversiteit MaastrichtUniversity Health NetworkUniversity of California, DavisBrain and Behavior Research FoundationKing's College LondonChildren's Hospital of PhiladelphiaUniversité de GenèveUniversity of Pennsylvania
KeywordsCopy-number variationSchizophrenia (object-oriented programming)GeneticsBiologyGeneMicroarrayPhenotypeGenome-wide association studyGenomeGenotypeMedicineSingle-nucleotide polymorphismPsychiatryGene expression

Abstract

fetched live from OpenAlex

OBJECTIVE: Chromosome 22q11.2 deletion syndrome (22q11.2DS) is associated with a more than 20-fold increased risk for developing schizophrenia. The aim of this study was to identify additional genetic factors (i.e., "second hits") that may contribute to schizophrenia expression. METHOD: Through an international consortium, the authors obtained DNA samples from 329 psychiatrically phenotyped subjects with 22q11.2DS. Using a high-resolution microarray platform and established methods to assess copy number variation (CNV), the authors compared the genome-wide burden of rare autosomal CNV, outside of the 22q11.2 deletion region, between two groups: a schizophrenia group and those with no psychotic disorder at age ≥25 years. The authors assessed whether genes overlapped by rare CNVs were overrepresented in functional pathways relevant to schizophrenia. RESULTS: Rare CNVs overlapping one or more protein-coding genes revealed significant between-group differences. For rare exonic duplications, six of 19 gene sets tested were enriched in the schizophrenia group; genes associated with abnormal nervous system phenotypes remained significant in a stepwise logistic regression model and showed significant interactions with 22q11.2 deletion region genes in a connectivity analysis. For rare exonic deletions, the schizophrenia group had, on average, more genes overlapped. The additional rare CNVs implicated known (e.g., GRM7, 15q13.3, 16p12.2) and novel schizophrenia risk genes and loci. CONCLUSIONS: The results suggest that additional rare CNVs overlapping genes outside of the 22q11.2 deletion region contribute to schizophrenia risk in 22q11.2DS, supporting a multigenic hypothesis for schizophrenia. The findings have implications for understanding expression of psychotic illness and herald the importance of whole-genome sequencing to appreciate the overall genomic architecture of schizophrenia.

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 score0.156
Threshold uncertainty score0.328

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 head0.006
GPT teacher head0.278
Teacher spread0.272 · 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

Citations100
Published2017
Admission routes2
Has abstractyes

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