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Record W3135592076 · doi:10.82308/38024

Genetic risk factors of childhood onset schizophrenia

2017· article· en· W3135592076 on OpenAlexfundno aff
Amirthagowri Ambalavanan

Bibliographic record

VenueeScholarship@McGill (McGill) · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Neurodevelopmental Disorders
Canadian institutionsnot available
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchMcGill University
KeywordsSchizophrenia (object-oriented programming)PsychologyDevelopmental psychologyPsychiatry

Abstract

fetched live from OpenAlex

Schizophrenia is a severe psychiatric disorder that affects approximately 1% of the general population. Childhood Onset Schizophrenia (COS) is a rare form of schizophrenia diagnosed during childhood (i.e. 6 to 13 years of age). The signs and symptoms of this early form of schizophrenia are continuous with those observed for adult schizophrenia and as such they equally impair the ability of those who are affected. Relatives who are genetically closer to a schizophrenic patient are more likely to develop the disorder themselves, and there is considerable interest in specific genetic mechanisms involved in its transmission. To this day the number of studies that examined the genetic risk associated to COS remains limited and only a few of those studies were focused on the identification of causative genes. With the advent of high-throughput sequencing instruments and whole exome capture arrays, genetic studies of schizophrenia recently tested the implication of de novo variants (variant not inherited from one of the two parents). The first chapter of this thesis describes an investigation of de novo variants across the entire coding regions (whole exome) of individuals diagnosed with COS. Our results showed such COS cases appear to present an increased number of missense variants that are predicted to have deleterious impact suggesting that de novo variants could represent an important aspect of the genetic architecture that underlies the development of COS. The following chapter describes a reexamination of the same whole exome sequencing (WES) data to identify inherited recessive variants. This analysis revealed an enrichment of disease related variants across the X-linked genes of male patients. Interestingly, human brain transcriptome data derived from the general population shows those X-linked genes are highly expressed in the brain. Overall these results represent the first published reports linking COS to single nucleotide variants identified using a tandem high throughput sequencing and genome wide approach (exome). The genes identified in our two studies represent a list of potential genetic risk factors linked to COS, which in turn provide clues about the pathogenicity of this complex disorder.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.218
Teacher spread0.208 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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