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Journal of Autism and Developmental Disorders

, Volume 44, Issue 12, pp 3045–3055 | Cite as

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

  • Stelios GeorgiadesEmail author
  • 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
  • Pathways in ASD Study Team
Original Paper

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.

Keywords

Autism symptoms Classification Phenotypic heterogeneity 

Notes

Acknowledgments

This study was supported by the Canadian Institutes of Health Research, Autism Speaks, the Government of British Columbia, the Alberta Innovates Health Solutions, and the Sinneave Family Foundation. Dr. Stelios Georgiades is supported by an Autism Research Training (ART) fellowship by the Canadian Institutes of Health Research. The authors thank all the families who participate in the Pathways in ASD study. The authors also acknowledge the members of the Pathways in ASD Study Team. Parts of this paper have been presented at the International Meeting for Autism Research (Spain, 2013). An earlier version of the paper was included as a chapter in a dissertation by Dr. Georgiades (PhD degree in Health Research Methodology, McMaster University, Ontario, Canada).

Supplementary material

10803_2014_2167_MOESM1_ESM.docx (18 kb)
Supplementary material 1 (DOCX 18 kb)

References

  1. Achenbach, T. M., & Rescorla, L. A. (2000). Manual for ASEBA preschool forms and profiles. Burlington, VT: University of Vermont, Research Center for Children, Youth, and Families.Google Scholar
  2. American Psychiatric Association. (1994). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: American Psychiatric Association.Google Scholar
  3. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed., Text Revision). Washington, DC: American Psychiatric Association.Google Scholar
  4. American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.Google Scholar
  5. Bodfish, J. W., Symons, F., & Lewis, M. (1999). The repetitive behavior scale: Test manual. Morganton: Western Carolina Center Research Reports.Google Scholar
  6. Bodfish, J. W., Symons, F. J., Parker, D. E., & Lewis, M. H. (2000). Varieties in repetitive behavior in autism. Journal of Autism and Developmental Disorders, 30, 237–243.PubMedCrossRefGoogle Scholar
  7. Constantino, J. N., & Gruber, C. P. (2005). Social responsiveness scale. Los Angeles: Western Psychological Services.Google Scholar
  8. Frazier, T. W., Youngstrom, E. A., Sinclair, L., Kubu, C. S., Law, P., Rezai, A., et al. (2010). Autism spectrum disorders as a qualitatively distinct category from typical behavior in a large, clinically ascertained sample. Assessment, 17, 308–320.PubMedCrossRefGoogle Scholar
  9. Frazier, T. W., Youngstrom, E. A., Speer, L., Embacher, R., Law, P., Constantino, J., et al. (2012). Validation of proposed DSM-5 criteria for autism spectrum disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 51, 28–40.PubMedCentralPubMedCrossRefGoogle Scholar
  10. Georgiades, S., Szatmari, P., Boyle, M., Hanna, S., Duku, E., Zwaigenbaum, L., et al. (2013a). Investigating phenotypic heterogeneity in children with autism spectrum disorder: A factor mixture modeling approach. Journal of Child Psychology and Psychiatry, 54, 206–215.PubMedCrossRefGoogle Scholar
  11. Georgiades, S., Szatmari, P., & Boyle, M. (2013b). Editorial: The importance of studying heterogeneity in autism. Neuropsychiatry: Future Medicine, 3(2), 123–125.CrossRefGoogle Scholar
  12. Geschwind, D. (2011). Genetics of autism spectrum disorders. Trends in Cognitive Sciences, 15, 409–416.PubMedCentralPubMedCrossRefGoogle Scholar
  13. Gotham, K., Pickles, A., & Lord, C. (2009). Standardizing ADOS scores for a measure of severity in autism spectrum disorders. Journal of Autism and Developmental Disorders, 39, 693–705.PubMedCentralPubMedCrossRefGoogle Scholar
  14. Happe, F. (2011). Criteria, categories, and continua: Autism and related disorders in DSM-5. Journal of the American Academy of Child and Adolescent Psychiatry, 50, 540–542.PubMedCrossRefGoogle Scholar
  15. Huerta, M., Bishop, S. L., Duncan, A., Hus, V., & Lord, C. (2012). Application of DSM-5 criteria for autism spectrum disorder to three samples of children with DSM-IV diagnoses of pervasive developmental disorders. American Journal of Psychiatry, 169, 1056–1064.PubMedCrossRefGoogle Scholar
  16. Lord, C., Risi, S., Lambrecht, L., Cook, E. H., Jr, Leventhal, B. L., DiLavore, P. C., et al. (2000). The autism diagnostic observation schedule-generic: A standard measure of social and communicative deficits associated with the spectrum of autism. Journal of Autism and Developmental Disorders, 30, 205–223.Google Scholar
  17. Lord, C., & Jones, R. M. (2012). Annual research review: Rethinking the classification of autism spectrum disorders. Journal of Child Psychology and Psychiatry, 53, 490–509.Google Scholar
  18. Lubke, G. H., & Muthen, B. O. (2005). Investigating population heterogeneity with factor mixture models. Psychological Methods, 10, 21–39.PubMedCrossRefGoogle Scholar
  19. Mandell, D. (2011). The heterogeneity in clinical presentation among individuals on the autism spectrum is a remarkably puzzling facet of this set of disorders. Autism: The International Journal of Research and Practice, 15(3), 259–261.CrossRefGoogle Scholar
  20. Muthen, B. (2004). Latent variable analysis: Growth mixture modeling and related techniques for longitudinal data. In D. Kaplan (Ed.), Handbook of quantitative methodology for the social sciences (pp. 345–368). Thousand Oaks: Sage.Google Scholar
  21. Muthén, L.K., & Muthén, B. (2008). Mplus 5.1 for windows. Los Angeles, CA: Author.Google Scholar
  22. Nylund, K. L., Asparouhov, T., & Muthen, B. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Structural Equation Modeling, 14, 535–569.CrossRefGoogle Scholar
  23. Ozonoff, S. (2012). Editorial perspective: autism spectrum disorders in DSM-5—an historical perspective and the need for change. Journal of Child Psychology and Psychiatry, 53, 1092–1094.PubMedCrossRefGoogle Scholar
  24. Pandolfi, V., Magyar, C. I., & Dill, C. A. (2009). Confirmatory factor analysis of the child behavior checklist 1.5-5 in a sample of children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 39, 986–995.PubMedCentralPubMedCrossRefGoogle Scholar
  25. Rutter, M. (2011). Research review: Child psychiatric diagnosis and classification: Concepts, findings, challenges and potential. Journal of Child Psychology and Psychiatry, 52, 647–660.PubMedCrossRefGoogle Scholar
  26. Rutter, M. (2012). Changing concepts and findings on autism. Journal of Autism and Developmental Disorders,. doi: 10.1007/s10803-012-1713-7.Google Scholar
  27. Rutter, M., LeCouteur, A., & Lord, C. (2003). ADI-R: The autism diagnostic interview-revised. Los Angeles, CA: Western Psychological Services.Google Scholar
  28. Sparrow, S. S., Cicchetti, D. V., & Balla, D. A. (2005). Vineland adaptive behavior scales: Second Edition (Vineland II), survey interview form/caregiver rating form. Livonia, MN: Pearson Assessments.Google Scholar
  29. Szatmari, P. (2011). New recommendations on autism spectrum disorder. BMJ, 342, d2456.PubMedCrossRefGoogle Scholar
  30. Walton, K. E., Ormel, J., & Krueger, R. F. (2011). The dimensional nature of externalizing behaviors in adolescence: Evidence from a direct comparison of categorical, dimensional, and hybrid models. Journal of Abnormal Child Psychology, 39, 553–561.PubMedCrossRefGoogle Scholar
  31. Wiggins, L. D., Robins, D. L., Adamson, L. B., Bakeman, R., & Henrich, C. (2011). Support for a dimensional view of autism spectrum disorders in toddlers. Journal of Autism and Developmental Disorders, 42, 191–200.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Stelios Georgiades
    • 1
    Email author
  • Michael Boyle
    • 1
  • Peter Szatmari
    • 2
  • Steven Hanna
    • 1
  • Eric Duku
    • 1
  • Lonnie Zwaigenbaum
    • 3
  • Susan Bryson
    • 4
  • Eric Fombonne
    • 5
  • Joanne Volden
    • 3
  • Pat Mirenda
    • 6
  • Isabel Smith
    • 4
  • Wendy Roberts
    • 7
  • Tracy Vaillancourt
    • 8
  • Charlotte Waddell
    • 9
  • Teresa Bennett
    • 1
  • Mayada Elsabbagh
    • 5
  • Ann Thompson
    • 1
  • Pathways in ASD Study Team
  1. 1.Offord Centre for Child StudiesMcMaster UniversityHamiltonCanada
  2. 2.Centre for Addiction and Mental Health, The Hospital for Sick ChildrenUniversity of TorontoTorontoCanada
  3. 3.University of AlbertaEdmontonCanada
  4. 4.Dalhousie University/IWK Health CenterHalifaxCanada
  5. 5.McGill UniversityMontrealCanada
  6. 6.University of British ColumbiaVancouverCanada
  7. 7.University of TorontoTorontoCanada
  8. 8.University of OttawaOttawaCanada
  9. 9.Simon Fraser UniversityVancouverCanada

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