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Defining autism subgroups: a taxometric solution.

The purpose of the present study was to determine which behavioral and physical phenotypes would be most likely to divide the ASD population into discrete subgroups. The taxometric methods of Maximum Covariance (MAXCOV) and Minus Mean Below A Cut (MAMBAC) were employed to test for categorical versus...

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Published in:Journal of Autism & Developmental Disorders Vol. 38; no. 5; pp. 950 - 961
Main Authors: Ingram DG, Takahashi TN, Miles JH
Format: research tables/charts Journal Article
Published: Springer Nature May2008
Online Access:View this record in EBSCOhost
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      dt: May2008
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      pub: Springer Nature
      place: New York, New York
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        atl: Defining autism subgroups: a taxometric solution.
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          Ingram DG
          Takahashi TN
          Miles JH
        affil: Thompson Center for Autism & Neurodevelopmental Disorders, University of Missouri-Columbia, 300 Portland Street, Suite 110, Columbia, MO 65201, USA
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          Autism Spectrum Disorder Classification
          Adaptation, Psychological
          Autism Spectrum Disorder Diagnosis
          Autism Spectrum Disorder Psychosocial Factors
          Behavior Rating Scales
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          Communication Skills
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          Interpersonal Relations
          Interrater Reliability
          Interview Guides
          Language Development
          Language Tests
          Latent Structure Analysis
          Male
          Motor Activity
          Phenotype
          Repeated Measures
          Scales
          Semi-Structured Interview
          Sensation
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          Child: 6-12 years
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          Male
      ab: The purpose of the present study was to determine which behavioral and physical phenotypes would be most likely to divide the ASD population into discrete subgroups. The taxometric methods of Maximum Covariance (MAXCOV) and Minus Mean Below A Cut (MAMBAC) were employed to test for categorical versus continuous variation of each phenotype across the ASD population. Data was retrieved from the Autism Genetic Resource Exchange and the University of Missouri Autism Database. The results of our analyses support subgrouping subjects based on variation in social interaction/communication, intelligence, and essential/complex phenotype; in contrast, subjects varied continuously in insistence on sameness, repetitive sensory motor actions, language acquisition, and, tentatively, adaptive functioning. Stratifying ASD samples based on taxometric results should increase power in gene-finding studies and aid in treatment efficacy research.
      pubtype: Academic Journal
      doctype:
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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