ArticleEuropean archives of psychiatry and clinical neuroscience2026
Brain morphological changes in autism spectrum disorder related to multiple behavioral spectrums: a behavioral-causal structural covariance network analysis.
Article in European archives of psychiatry and clinical neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneities in behavioral symptoms and gray matter (GM) volume changes across the brain. However, progressive and causal GM volume changes and their associations with behavioral symptoms remain unclear. Our study aimed to explore the heterogeneity of causal GM volume changes in individuals with ASD across behavioral spectrums.
methodsBrain structural imaging and clinical data of 131 autistic individuals and 246 neurotypical individuals (NTs) were included, and were clustered into neuroanatomical subtypes. A novel behavioral-causal structural covariance network (BCaSCN) analysis approach was developed. GM volume maps from each ASD subtype were sequenced according to the social responsiveness scale (SRS) value and values from each behavioral domain of SRS, generating pseudo-time series data with disease progression. We performed BCaSCN analysis on the pseudo-time series data to explore the causal relationship of the GM volume changes across behavior spectrums among ASD subtypes.
resultsTwo neurosubtypes of ASD with distinct GM volume alterations were observed. CaSCN analysis revealed heterogeneity in causal GM volume alterations between the two ASD neurostypes. Furthermore, BCaSCN analysis across behavior spectrums demonstrated that subtype 1 exhibited higher overall out- and in-degree GC values in the cognition domain, whereas subtype 2 displayed higher overall out- and in-degree GC values in the domain of motivation, mannerism and communication. LIMITATION: CaSCN and BCaSCN applied pseudo time-series data rather than real time-series data, longitudinal data are needed to validate the results of this study in the future. Therefore, the results should be interpreted with caution.
conclusionsThese findings suggest that ASD subtypes are associated with heterogeneous causal GM volume changes, which may be related to distinct behavioral domains.
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