Literature DB >> 24163114

Modeling the autism spectrum disorder phenotype.

Alexa T McCray1, Philip Trevvett, H Robert Frost.   

Abstract

Autism Spectrum Disorder (ASD) is highly heritable, and although there has been active research in an attempt to discover the genetic factors underlying ASD, diagnosis still depends heavily on behavioral assessments. Recently, several large-scale initiatives, including those of the Autism Consortium, have contributed to the collection of extensive information from families affected by ASD. Our goal was to develop an ontology that can be used 1) to provide improved access to the data collected by those who study ASD and other neurodevelopmental disorders, and 2) to assess and compare the characteristics of the instruments that are used in the assessment of ASD. We analyzed two dozen instruments used to assess ASD, studying the nature of the questions asked and items assessed, the method of delivery, and the overall scope of the content. These data together with the extensive literature on ASD contributed to our iterative development of an ASD phenotype ontology. The final ontology comprises 283 concepts distributed across three high-level classes, 'Personal Traits', 'Social Competence', and 'Medical History'. The ontology is fully integrated with the Autism Consortium database, allowing researchers to pose ontology-based questions. The ontology also allows researchers to assess the degree of overlap among a set of candidate instruments according to several objective criteria. The ASD phenotype ontology has promise for use in research settings where extensive phenotypic data have been collected, allowing a concept-based approach to identifying behavioral features of importance and for correlating these with genotypic data.

Entities:  

Mesh:

Year:  2014        PMID: 24163114      PMCID: PMC4000751          DOI: 10.1007/s12021-013-9211-4

Source DB:  PubMed          Journal:  Neuroinformatics        ISSN: 1539-2791


  83 in total

1.  Age, gender and IQ effects on the Rey-Osterrieth Complex Figure Test.

Authors:  Colin Gallagher; Teresa Burke
Journal:  Br J Clin Psychol       Date:  2007-03

2.  The NIFSTD and BIRNLex vocabularies: building comprehensive ontologies for neuroscience.

Authors:  William J Bug; Giorgio A Ascoli; Jeffrey S Grethe; Amarnath Gupta; Christine Fennema-Notestine; Angela R Laird; Stephen D Larson; Daniel Rubin; Gordon M Shepherd; Jessica A Turner; Maryann E Martone
Journal:  Neuroinformatics       Date:  2008-10-31

3.  Screening for autism spectrum disorders with the social communication questionnaire.

Authors:  Linda C Eaves; Heather D Wingert; Helena H Ho; Elizabeth C R Mickelson
Journal:  J Dev Behav Pediatr       Date:  2006-04       Impact factor: 2.225

4.  The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism.

Authors:  C Lord; S Risi; L Lambrecht; E H Cook; B L Leventhal; P C DiLavore; A Pickles; M Rutter
Journal:  J Autism Dev Disord       Date:  2000-06

Review 5.  Diagnostic procedures in autism spectrum disorders: a systematic literature review.

Authors:  Torbjörn Falkmer; Katie Anderson; Marita Falkmer; Chiara Horlin
Journal:  Eur Child Adolesc Psychiatry       Date:  2013-01-16       Impact factor: 4.785

6.  Using an integrated ontology and information model for querying and reasoning about phenotypes: The case of autism.

Authors:  Samson W Tu; Samson Tu; Lakshika Tennakoon; Martin O'Connor; Martin Connor; Ravi Shankar; Amar Das
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

7.  Confirmatory factor analysis of the child behavior checklist 1.5-5 in a sample of children with autism spectrum disorders.

Authors:  Vincent Pandolfi; Caroline I Magyar; Charles A Dill
Journal:  J Autism Dev Disord       Date:  2009-03-05

Review 8.  Autism spectrum disorders--a genetics review.

Authors:  Judith H Miles
Journal:  Genet Med       Date:  2011-04       Impact factor: 8.822

9.  Improving the reliability of autism diagnoses: examining the utility of adaptive behavior.

Authors:  Stacey S Tomanik; Deborah A Pearson; Katherine A Loveland; David M Lane; J Bryant Shaw
Journal:  J Autism Dev Disord       Date:  2007-05

10.  Use of machine learning to shorten observation-based screening and diagnosis of autism.

Authors:  D P Wall; J Kosmicki; T F Deluca; E Harstad; V A Fusaro
Journal:  Transl Psychiatry       Date:  2012-04-10       Impact factor: 6.222

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  14 in total

1.  An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data.

Authors:  Omri Mugzach; Mor Peleg; Steven C Bagley; Stephen J Guter; Edwin H Cook; Russ B Altman
Journal:  J Biomed Inform       Date:  2015-07-04       Impact factor: 6.317

Review 2.  Can data repositories help find effective treatments for complex diseases?

Authors:  Gregory K Farber
Journal:  Prog Neurobiol       Date:  2016-03-24       Impact factor: 11.685

3.  Executive Functioning: A Mediator Between Sensory Processing and Behaviour in Autism Spectrum Disorder.

Authors:  Montse Fernandez-Prieto; Célia Moreira; Sara Cruz; Vânia Campos; Rocío Martínez-Regueiro; Maria Taboada; Angel Carracedo; Adriana Sampaio
Journal:  J Autism Dev Disord       Date:  2021-06

Review 4.  Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

Authors:  Muhammad Amith; Zhe He; Jiang Bian; Juan Antonio Lossio-Ventura; Cui Tao
Journal:  J Biomed Inform       Date:  2018-02-17       Impact factor: 6.317

5.  Peabody Picture Vocabulary Test: Proxy for Verbal IQ in Genetic Studies of Autism Spectrum Disorder.

Authors:  Kate E Krasileva; Stephan J Sanders; Vanessa Hus Bal
Journal:  J Autism Dev Disord       Date:  2017-04

6.  Executive Functions in Children and Adolescents with Autism Spectrum Disorder in Family and School Environment.

Authors:  Ana Gentil-Gutiérrez; Mirian Santamaría-Peláez; Luis A Mínguez-Mínguez; Jessica Fernández-Solana; Jerónimo J González-Bernal; Josefa González-Santos; Ana I Obregón-Cuesta
Journal:  Int J Environ Res Public Health       Date:  2022-06-26       Impact factor: 4.614

7.  Future directions for research in autism spectrum disorders.

Authors:  Cara R Damiano; Carla A Mazefsky; Susan W White; Gabriel S Dichter
Journal:  J Clin Child Adolesc Psychol       Date:  2014

Review 8.  Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry.

Authors:  Peter Washington; Natalie Park; Parishkrita Srivastava; Catalin Voss; Aaron Kline; Maya Varma; Qandeel Tariq; Haik Kalantarian; Jessey Schwartz; Ritik Patnaik; Brianna Chrisman; Nathaniel Stockham; Kelley Paskov; Nick Haber; Dennis P Wall
Journal:  Biol Psychiatry Cogn Neurosci Neuroimaging       Date:  2019-12-13

Review 9.  Molecular Mechanisms of Aberrant Neuroplasticity in Autism Spectrum Disorders (Review).

Authors:  A A Anashkina; E I Erlykina
Journal:  Sovrem Tekhnologii Med       Date:  2021-02-28

10.  Acquisition, Analysis, and Sharing of Data in 2015 and Beyond: A Survey of the Landscape: A Conference Report From the American Heart Association Data Summit 2015.

Authors:  Elliott M Antman; Emelia J Benjamin; Robert A Harrington; Steven R Houser; Eric D Peterson; Mary Ann Bauman; Nancy Brown; Vincent Bufalino; Robert M Califf; Mark A Creager; Alan Daugherty; David L Demets; Bernard P Dennis; Shahram Ebadollahi; Mariell Jessup; Michael S Lauer; Bernard Lo; Calum A MacRae; Michael V McConnell; Alexa T McCray; Michelle M Mello; Eric Mueller; Jane W Newburger; Sally Okun; Milton Packer; Anthony Philippakis; Peipei Ping; Prad Prasoon; Véronique L Roger; Steve Singer; Robert Temple; Melanie B Turner; Kevin Vigilante; John Warner; Patrick Wayte
Journal:  J Am Heart Assoc       Date:  2015-11-05       Impact factor: 5.501

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