Distinct Symptom Network Structure and Shared Central Social Communication Symptomatology in Autism and Schizophrenia: A Bayesian Network Analysis

Autism (ASD) and schizophrenia spectrum disorders (SCZ) are neurodevelopmental conditions with overlapping and interrelated symptoms. A network analysis approach that represents clinical conditions as a set of “nodes” (symptoms) connected by “edges” (relations among symptoms) was used to compare symptom organization in the two conditions. Gaussian graphical models were estimated using Bayesian methods to model separate symptom networks for adults with confirmed ASD or SCZ diagnoses. Though overall symptom organization differed by diagnostic group, both symptom networks demonstrated high centrality of social communication difficulties. Autism-relevant restricted and repetitive behaviors and schizophrenia-related cognitive-perceptual symptoms were uniquely central to the ASD and SCZ networks, respectively. Results offer recommendations to improve differential diagnosis and highlight potential treatment targets in ASD and SCZ.