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Record W7047703786

A HUMAN IN VITRO INVESTIGATION OF THE AUTISM SPECTRUM DISORDER RISK GENE SCN2A

2022· dissertation· en· W7047703786 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsnot available
Fundersnot available
KeywordsPhenotypeGeneSodium channelAutism spectrum disorderSCN3ACandidate geneDiseaseNeurodevelopmental disorderExome sequencing
DOInot available

Abstract

fetched live from OpenAlex

Autism spectrum disorder (ASD) encompasses a group of heterogeneous disorders that affect approximately 1% of children worldwide. ASD is characterized by two core symptoms, the first being deficits in social communication and interaction, and the second being restrictive and repetitive behaviours. Although environmental and genetic factors are known to contribute to the development of ASD, the etiology remains unknown. Genetic sequencing studies have implicated over 1000 genes with risk variants that are ASD-associated. Recent sequencing studies have highlighted that SCN2A, a gene that encodes the Voltage-Gated Sodium Channel Type II Alpha Subunit habours a large proportion of genetic risk variants for ASD. An emphasis was put on this gene because many of the top genes regulate transcription and cytoskeletal dynamics and not sodium flux aiding in regulating neuron excitability. Initial investigations of complete loss of Scn2a in mice led to perinatal lethality where heterozygous loss exhibited many behavioural phenotypes associated with ASD. Through our collaboration with Dr. Stephen Scherer (Hospital for Sick Children, Toronto) we identified two de novo truncating point variants in SCN2A. In our study, we focused on using human iPSC-derived neurons for disease modelling. We found these two variants caused a reduction in synapses suggesting that neuronal communication may be altered. Furthermore, electrophysiological characterization of the neurons harbouring the differing SCN2A variants showcased that loss-of-function (LoF) variants can produce differential phenotypes based on their location. Beyond the initial ion channel characterization, we wanted to probe whether cellular pathways were altered directly or indirectly by atypical neuronal activity. Proteomics of neurons expressing the more severe variant, p.R607*, found differentially expressed proteins (DEP)s that were upregulated and downregulated. Moreover, these DEPs were enriched and clustered into cellular pathways that were altered, with one of these clusters representing mitochondrial function. We functionally validated these findings in the same neurons and found corroboration between the molecular and cellular data of impaired mitochondria. Lastly, we used Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 gene editing to generate an isogenic model to validate our findings of the less severe p.G1744* variant. Together, this will aid in the discovery of new variant categorizations and targeted treatments for rescues of atypical neural connectivity or pathways that are altered downstream.

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)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.181
Teacher spread0.177 · 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 designBench or experimental
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
Published2022
Admission routes1
Has abstractyes

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