LAUSR

Children with autism spectrum disorder (ASD) present with heterogeneous levels of abilities and deficits. The identification of subgroups within a specific age range could be useful for understanding prognosis and treatment planning. We applied Hierarchical Clustering on Principal Components (HCPC) with a sample of 188 preschoolers with ASD and identified three distinct subgroups based on multiple developmental and behavioral domains. Cluster 1 was characterized by relatively high cognitive, language and adaptive abilities, and relatively low levels of social symptoms, repetitive behaviors, and sensory issues within the sample. Cluster 2 was characterized by similarly high cognitive, language and adaptive abilities compared to Cluster 1, but more severe social deficits as well as repetitive and sensory behaviors. Finally, Cluster 3 was characterized by lower cognitive, language and adaptive abilities, and more severe social, repetitive, and sensory symptoms. These findings provide insights into how considering multiple developmental and behavioral domains and core autism symptoms simultaneously can distinguish subgroups of young children with ASD and provide more comprehensive developmental profiles. Moreover, the unique profile of children in Cluster 2 highlighted the usefulness of including different measures and informants when evaluating the abilities and deficits of preschoolers with ASD and the importance of understanding the relationships among different developmental and behavioral factors in this specific population. Autism Res 2020, 13: 796–809. © 2020 International Society for Autism Research, Wiley Periodicals, Inc.