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The complexity and heterogeneity of neuroimaging findings in individuals with autism spectrum disorder has suggested that many of the underlying alterations are subtle and involve many brain regions and networks. The ability to account for multivariate brain features and identify neuroimaging measures that can be used to characterize individual variation have thus become increasingly important for interpreting and understanding the neurobiological mechanisms of autism. In the present study, we utilize the Mahalanobis distance, a multidimensional counterpart of the Euclidean distance, as an informative index to characterize individual brain variation and deviation in autism. Longitudinal diffusion tensor imaging data from 149 participants (92 diagnosed with autism spectrum disorder and 57 typically developing controls) between 3.1 and 36.83 years of age were acquired over a roughly 10-year period and used to construct the Mahalanobis distance from regional measures of white matter microstructure. Mahalanobis distances were significantly greater and more variable in the autistic individuals as compared to control participants, demonstrating increased atypicalities and variation in the group of individuals diagnosed with autism spectrum disorder. Distributions of multivariate measures were also found to provide greater discrimination and more sensitive delineation between autistic and typically developing individuals than conventional univariate measures, while also being significantly associated with observed traits of the autism group. These results help substantiate autism as a truly heterogeneous neurodevelopmental disorder, while also suggesting that collectively considering neuroimaging measures from multiple brain regions provides improved insight into the diversity of brain measures in autism that is not observed when considering the same regions separately. Distinguishing multidimensional brain relationships may thus be informative for identifying neuroimaging-based phenotypes, as well as help elucidate underlying neural mechanisms of brain variation in autism spectrum disorders.

A gap exists in the literature regarding aggression in autism spectrum disorders and how this behavior compares to other groups. In this multisite study, the Children's Scale for Hostility and Aggression: Reactive/Proactive and the Aggression subscale of the Child Behavior Checklist were rated for 414 children with autism spectrum disorder (autistic disorder, 69%; pervasive developmental disorder not otherwise specified, 24%; Asperger's disorder, 7%) and 243 clinic-referred children without autism spectrum disorder, aged 1-21 years (mean age about 7 years). Participants were not selected for aggressive behavior. Relative to the comparison group, children with autism spectrum disorder were reported to have less aggression and were more likely to be rated as reactive rather than proactive. Among all subjects, sex was not associated with aggression; higher IQ/adaptive behavior and older age were associated with more sophisticated types of aggression, while lower scores on IQ, adaptive behavior, and communication measures were associated with more physical aggression. The interaction between demographic variables and diagnosis was significant only for age: younger but not older children with autism spectrum disorder showed less aggression than clinic-referred controls., (© The Author(s) 2014.)