4.5 Article

Quantifying the Optimal Structure of the Autism Phenotype: A Comprehensive Comparison of Dimensional, Categorical, and Hybrid Models

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.jaac.2018.09.431

Keywords

autism spectrum disorder; ASD phenotype; classification; dimensional models; Child and Adolescent Symptom Inventory

Funding

  1. Matt and Debra Cody Center for Autism and Developmental Disabilities
  2. National Institute of Mental Health (NIMH) [R01MH073967]
  3. NIMH [R01MH110585, R01 MH077907]
  4. Case Western Reserve University [R01 MH077750]
  5. University of Pittsburgh [R01 MH077676]
  6. Stony Brook University [R01 MH 077997]
  7. National Institutes of Health (NIH) General Clinical Research Center [M01RR10710]
  8. Clinical and Translational Science Awards from the National Center for Advancing Translational Sciences grants [8UL1TR000090-05, UL1 RR024153, UL1TR000005]
  9. Simons Foundation Autism Research Initiative [SFARI 381283]
  10. NARSAD Young Investigator Award [24890]

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Objective: The two primary-seemingly contradictory-strategies for classifying child psychiatric syndromes are categorical and dimensional; conceptual ambiguities appear to be greatest for polythetic syndromes such as autism spectrum disorder (ASD). Recently, a compelling alternative has emerged that integrates both categorical and dimensional approaches (ie, a hybrid model), thanks to the increasing sophistication of analytic procedures. This study aimed to quantify the optimal phenotypic structure of ASD by comprehensively comparing categorical, dimensional, and hybrid models. Method: The sample comprised 3,825 youth, who were consecutive referrals to a university developmental disabilities or child psychiatric outpatient clinic. Caregivers completed the Child and Adolescent Symptom Inventory - 4R (CASI-4R), which includes an ASD symptom rating scale. A series of latent class analyses, exploratory and confirmatory factor analyses, and factor mixture analyses was conducted. Replication analyses were conducted in an independent sample (N = 2,503) of children referred for outpatient evaluation. Results: Based on comparison of 44 different models, results indicated that the ASD symptom phenotype is best conceptualized as multidimensional versus a categorical or categorical-dimensional hybrid construct. ASD symptoms were best characterized as falling along three dimensions (ie, social interaction, communication, and repetitive behavior) on the CASI-4R. Conclusion: Findings reveal an optimal structure with which to characterize the ASD phenotype using a single, parent-report measure, supporting the presence of multiple correlated symptom dimensions that traverse formal diagnostic boundaries and quantify the heterogeneity of ASD. These findings inform understanding of how neurodevelopmental disorders can extend beyond discrete categories of development and represent continuously distributed traits across the range of human behaviors.

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