Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6

Stelios Georgiades, Michael Boyle, Peter Szatmari, Steven Hanna, Eric Duku, Lonnie Zwaigenbaum, Susan Bryson, Eric Fombonne, Joanne Volden, Pat Mirenda, Isabel Smith, Wendy Roberts, Tracy Vaillancourt, Charlotte Waddell, Teresa Bennett, Mayada Elsabbagh, Ann Thompson

Research output: Contribution to journalArticle

10 Scopus citations

Abstract

The latent class structure of autism symptoms from the time of diagnosis to age 6 years was examined in a sample of 280 children with autism spectrum disorder. Factor mixture modeling was performed on 26 algorithm items from the Autism Diagnostic Interview - Revised at diagnosis (Time 1) and again at age 6 (Time 2). At Time 1, a “2-factor/3-class” model provided the best fit to the data. At Time 2, a “2-factor/2-class” model provided the best fit to the data. Longitudinal (repeated measures) analysis of variance showed that the “2-factor/3-class” model derived at the time of diagnosis allows for the identification of a subgroup of children (9 % of sample) who exhibit notable reduction in symptom severity.

Original languageEnglish (US)
Pages (from-to)3045-3055
Number of pages11
JournalJournal of autism and developmental disorders
Volume44
Issue number12
DOIs
StatePublished - Dec 1 2014

Keywords

  • Autism symptoms
  • Classification
  • Phenotypic heterogeneity

ASJC Scopus subject areas

  • Developmental and Educational Psychology

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    Georgiades, S., Boyle, M., Szatmari, P., Hanna, S., Duku, E., Zwaigenbaum, L., Bryson, S., Fombonne, E., Volden, J., Mirenda, P., Smith, I., Roberts, W., Vaillancourt, T., Waddell, C., Bennett, T., Elsabbagh, M., & Thompson, A. (2014). Modeling the Phenotypic Architecture of Autism Symptoms from Time of Diagnosis to Age 6. Journal of autism and developmental disorders, 44(12), 3045-3055. https://doi.org/10.1007/s10803-014-2167-x