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Record W3154130619 · doi:10.24908/iqurcp.10713

25. Identification of De novo, Deleterious Mutations through Exome Sequencing of Sporadic Autism Spectrum Disorder Trios

2018· article· en· W3154130619 on OpenAlexvenueno aff
Shalandra Wood

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
Fundersnot available
KeywordsExome sequencingGeneticsSanger sequencingAutism spectrum disorderSingle-nucleotide polymorphismBiologyNeurodevelopmental disorderCandidate geneExomeMassive parallel sequencingMutationGenetic heterogeneityGeneAutismDNA sequencingMedicineGenotypePhenotypePsychiatry

Abstract

fetched live from OpenAlex


 Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental disorder that has a strong genetic component consisting of many genes contributing to its cause. To help understand this complex genetic etiology, we are looking for novel genes that may be involved in the reason individuals develop ASD. We are doing this by using 5 sporadic ASD cases to determine de novo mutations (mutations new to the affected child that are not previously found in the family). These sporadic cases ensure that the disorder is not likely to arise through any inherited mutations, but through a new mutation found solely in the affected child. We use a trio analysis in which the genes of the affected child are compared to those of their mother and father, so pure de novo single nucleotide polymorphisms (SNPs) can be determined. These SNPs are then filtered based on predicted deleterious effect, quality and biological relevance. Using whole-exome sequencing on these 5 sporadic trios numerous deleterious, de novo mutations have been determined. These are being reviewed for biological relevance, and will be validated using Sanger Sequencing. Of these proposed SNPs being validated a few, such as SHANK3 and DVL1, have previously been linked to ASD. Whereas others, such as C11orf31, are novel candidate genes for the disorder. Through this experiment our understanding of the genetic etiology of ASD continues to grow and evolve, leading to greater insight into this disorder and new directions for possible treatments

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.005
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
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 head0.121
GPT teacher head0.389
Teacher spread0.268 · 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.

Study designTheoretical or conceptual
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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