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Record W2130763741 · doi:10.1186/1866-1955-5-30

A molecular genetic study of autism and related phenotypes in extended pedigrees

2013· article· en· W2130763741 on OpenAlexaff
Joseph Piven, Veronica J. Vieland, Morgan Parlier, Ann Thompson, Irene O’Conner, Mark Woodbury-Smith, Yungui Huang, Kimberly A. Walters, Bridget A. Fernandez, Péter Szatmári

Bibliographic record

VenueJournal of Neurodevelopmental Disorders · 2013
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsCentre for Addiction and Mental HealthSt. John’s Health Sciences CentreUniversity of TorontoMcMaster University
FundersNational Institutes of Health
KeywordsPedigree chartPhenotypeAutismNeurologyGeneticsHuman geneticsNeuropsychologyAutism spectrum disorderPsychologyBiologyComputational biologyNeurosciencePsychiatryGeneCognition

Abstract

fetched live from OpenAlex

BACKGROUND: Efforts to uncover the risk genotypes associated with the familial nature of autism spectrum disorder (ASD) have had limited success. The study of extended pedigrees, incorporating additional ASD-related phenotypes into linkage analysis, offers an alternative approach to the search for inherited ASD susceptibility variants that complements traditional methods used to study the genetics of ASD. METHODS: We examined evidence for linkage in 19 extended pedigrees ascertained through ASD cases spread across at least two (and in most cases three) nuclear families. Both compound phenotypes (i.e., ASD and, in non-ASD individuals, the broad autism phenotype) and more narrowly defined components of these phenotypes, e.g., social and repetitive behavior, pragmatic language, and anxiety, were examined. The overarching goal was to maximize the aggregate information available on the maximum number of individuals and to disaggregate syndromic phenotypes in order to examine the genetic underpinnings of more narrowly defined aspects of ASD behavior. RESULTS: Results reveal substantial between-family locus heterogeneity and support the importance of previously reported ASD loci in inherited, familial, forms of ASD. Additional loci, not seen in the ASD analyses, show evidence for linkage to the broad autism phenotype (BAP). BAP peaks are well supported by multiple subphenotypes (including anxiety, pragmatic language, and social behavior) showing linkage to regions overlapping with the compound BAP phenotype. Whereas 'repetitive behavior', showing the strongest evidence for linkage (Posterior Probability of Linkage = 62% at 6p25.2-24.3, and 69% at 19p13.3), appears to be linked to novel regions not detected with other compound or narrow phenotypes examined in this study. CONCLUSIONS: These results provide support for the presence of key features underlying the complexity of the genetic architecture of ASD: substantial between-family locus heterogeneity, that the BAP appears to correspond to sets of subclinical features segregating with ASD within pedigrees, and that different features of the ASD phenotype segregate independently of one another. These findings support the additional study of larger, even more individually informative pedigrees, together with measurement of multiple, behavioral- and biomarker-based phenotypes, in both affected and non-affected individuals, to elucidate the complex genetics of familial ASD.

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)0.003
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.260
Teacher spread0.248 · 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

Citations28
Published2013
Admission routes1
Has abstractyes

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