Heterogeneity of Degree Centrality Revealed Different Subtypes in Children with Autism Spectrum Disorder.

Abstract

Introduction: Autism spectrum disorder (ASD) is a neurodevelopmental condition that exhibits a wide range of clinical heterogeneity. This study aimed to explore the heterogeneity of ASD based on deviations in brain functional networks. Methods: Resting-state functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange database were analyzed in 105 children with ASD and 102 demographically matched typical controls (TC) children. Heterogeneity through discriminative analysis (HYDRA) was utilized to identify subtypes of ASD based on the degree centrality (DC) maps. Voxel-wise group comparisons were then performed between ASD subtypes and the TC group. The relationship between the altered DC and the symptom severity was finally analyzed for ASD subtypes using the multivariate support vector regression approach. Results: HYDRA identified three subtypes of ASD. Distinct DC alteration patterns were observed in brain regions including the fusiform gyrus, insula, and inferior frontal gyrus in ASD subtypes. Moreover, the altered DC values for ASD subtype 1 and subtype 3 can predict the restricted and repetitive behavior and social communication impairments in ASD, respectively. Conclusions: Our findings demonstrated the heterogeneity of brain functional networks in ASD and provided a promising way to explain the high heterogeneity of clinical symptoms and outcomes.