Abstract
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.
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Acknowledgments
We gratefully acknowledge the resources provided by the Autism Genetic Resource Exchange (AGRE) Consortium and the participating AGRE families. The Autism Genetic Resource Exchange is a program of Cure Autism Now and is supported, in part, by grant MH64547 from the National Institute of Mental Health to Daniel H. Geschwind (PI). We would like to thank John Ruscio for his help with taxometric theory, Thomas Piasecki for introducing us to taxometrics, and finally our patients, whose courage makes this work possible. We received support from the Missouri Department of Mental Health, Leda J. Sears Trust, and Ridgeway Scholarship.
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Ingram, D.G., Takahashi, T.N. & Miles, J.H. Defining Autism Subgroups: A Taxometric Solution. J Autism Dev Disord 38, 950–960 (2008). https://doi.org/10.1007/s10803-007-0469-y
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DOI: https://doi.org/10.1007/s10803-007-0469-y