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Record W7052888145

Testing the network hypothesis for schizophrenia and autism spectrum disorder using whole exome sequencing data

2018· dissertation· en· W7052888145 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2018
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsMcGill UniversityMcGill Genome Centre
Fundersnot available
KeywordsExome sequencingProbandAutism spectrum disorderSchizophrenia (object-oriented programming)ExomeAutismGeneSanger sequencing
DOInot available

Abstract

fetched live from OpenAlex

Background Schizophrenia (SCZ) and autism spectrum disorder (ASD) are psychiatric diseases with complex inheritance.Genetic studies have not identified susceptibility genes to adequately explain the heritability and the etiology of these diseases is largely unknown. MethodsWe identified susceptibility genes enriched for de novo mutations (DNMs) in at least two independent whole exome sequencing (WES) publications.Genes associated with hypertrophic cardiomyopathy (HC) were used as control genes.We selected for rare inherited and DNMs in the ASD network using a WES dataset (2392 ASD families) and in the SCZ network using three independent WES datasets (35 trios; 598 trios; 5090 case controls).We compared the mutation load in the 'disease network' between affected and unaffected individuals for each dataset.The analyses were repeated using the 'HC network'.Results 14 SCZ genes and 143 ASD genes were identified.When using the 598 SCZ trios, probands were enriched in functional variants relative to the average mutation load of parents in the SCZ network (p = 0.04) but not in the HC genes (p = 0.23).All functional variants identified in the SCZ network were inherited.Similar results were obtained using the case control dataset (SCZ network: p = 0.02; HC network: p = 0.09).When analyzing ASD sibpairs, unaffected siblings were significantly enriched in functional variants in the ASD network (p = 0.02) but also throughout the exome based on a permutation analysis using all genes with functional variants.When controlling for sequencing depth through a conditional logistic regression and applying stricter filtering criteria, the difference was not statistically significant (p = 0.1358). ConclusionsWe provide preliminary evidence that the accumulation of rare variants (mainly inherited) in the identified SCZ susceptibility genes is associated with SCZ.However, this was not the case for the ASD dataset that we had access to.

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)0.007
metaresearch head score (Gemma)0.025
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 score0.009
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0040.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.043
GPT teacher head0.247
Teacher spread0.205 · 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
Published2018
Admission routes1
Has abstractyes

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