Age, Disease, and Their Interaction Effects on Intrinsic Connectivity of Children and Adolescents in Autism Spectrum Disorder Using Functional Connectomics

Brain Connect. 2018 Sep;8(7):407-419. doi: 10.1089/brain.2018.0616. Epub 2018 Aug 29.

Abstract

Brain connectivity analysis has provided crucial insights to pinpoint the differences between autistic and typically developing (TD) children during development. The aim of this study is to investigate the functional connectomics of autism spectrum disorder (ASD) versus TD and underpin the effects of development, disease, and their interactions on the observed atypical brain connectivity patterns. Resting-state functional magnetic resonance imaging (rs-fMRI) from the Autism Brain Imaging Data Exchange (ABIDE) data set, which is stratified into two cohorts: children (9-12 years) and adolescents (13-16 years), is used for the analysis. Differences in various graph theoretical network measures are calculated between ASD and TD in each group. Furthermore, two-factor analysis of variance test is used to study the effect of age, disease, and their interaction on the network measures and the network edges. Furthermore, the differences in connection strength between TD and ASD subjects are assessed using network-based statistics. The results showed that ASD exhibits increased functional integration at the expense of decreased functional segregation. In ASD adolescents, there is a significant decrease in modularity suggesting a less robust modular organization, and an increase in participation coefficient suggesting more random integration and widely distributed connection edges. Furthermore, there is significant hypoconnectivity observed in the adolescent group especially in the default mode network, while the children group shows both hyper- and hypoconnectivity. This study lends support to a model of global atypical connections and further identifies functional networks and areas that are independently affected by age, disease, and their interaction.

Keywords: ABIDE; autism; default mode network; graph theory; neurodevelopmental disorders; resting-state functional MRI.