Altered topographical organization of grey matter structural network in early-onset schizophrenia

•Both neurodevelopmental abnormalities and brain dysconnectivity are crucial factors underlying the pathophysiology of schizophrenia, but little is known about the brain network changes in children and adolescents with schizophrenia.•The grey matter structural network of adolescents with early-onset...

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Veröffentlicht in:Psychiatry research. Neuroimaging 2021-10, Vol.316, p.111344-111344, Article 111344
Hauptverfasser: Zhou, Han-yu, Shi, Li-juan, Shen, Yan-mei, Fang, Yu-min, He, Yu-qiong, Li, Hua-bing, Luo, Xue-rong, Cheung, Eric F.C., Chan, Raymond C.K.
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Sprache:eng
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Zusammenfassung:•Both neurodevelopmental abnormalities and brain dysconnectivity are crucial factors underlying the pathophysiology of schizophrenia, but little is known about the brain network changes in children and adolescents with schizophrenia.•The grey matter structural network of adolescents with early-onset schizophrenia (EOS) showed a less optimal organization with reduced functional integration and more fragmented modules.•EOS patients demonstrated altered regional nodal degree in prefrontal-cerebellar-hippocampal areas and lacked a left-lateralized hub distribution observed in typically developing adolescents.•Future research should examine brain network abnormalities longitudinally using multimodal imaging methods to better understand progressive developmental changes of schizophrenia. Schizophrenia is characterized by both disrupted neurodevelopmental processes and abnormal brain connectivity. However, few studies have examined the atypical features of brain network topography associated with schizophrenia during childhood and adolescence. We used graph theory to compare the grey matter structural networks of individuals (aged 10-15 years) with early-onset schizophrenia (EOS) (n = 25) and a typically-developing (TD) comparison group (n = 31). Compared with the TD group, EOS patients showed significantly increased clustering and local efficiency across a range of network densities (0.3 – 0.4). The network of EOS patients also had more modules (6 modules in EOS vs. 3 modules in controls), indicating a more segregated network at the cost of functional integration. Although our results were preliminary and failed to survive corrections for multiple comparisons, EOS patients might be characterized by altered nodal centrality in several higher-order associative regions including the prefrontal cortex, the hippocampus and the cerebellum. The EOS structural network also lacked the typical left-hemispheric-dominant hub distribution compared with the TD group. These findings suggest that brain structural network was not only globally but also regionally altered in EOS patients.
ISSN:0925-4927
1872-7506
DOI:10.1016/j.pscychresns.2021.111344