Neuroimaging and multiomics reveal cross-scale circuit abnormalities in schizophrenia

精神分裂症(面向对象编程) 神经科学 神经影像学 微尺度化学 心理学 生物 精神科 数学教育
作者
Meng Wang,Hao Yan,Xiaohan Tian,Weihua Yue,Yong Liu,Lingzhong Fan,Ke Hu,Yuqing Sun,Yuxin Zhao,Jing Lou,Ming Song,Peng Li,Jun Chen,Yunchun Chen,Huaning Wang,Wenming Liu,Zhigang Li,Yongfeng Yang,Hua Guo,Luxian Lv
标识
DOI:10.1038/s44220-023-00110-3
摘要

Schizophrenia (SCZ) is a highly heterogeneous disorder with diverse clinical manifestations and macro- and microscale biological variations, usually observed at dissociable levels. Here we propose a cross-scale, circuit-based framework to connect heterogeneous clinical symptoms, large-scale brain circuit dysfunctions, and genetic, molecular and cellular abnormalities in SCZ. Using connectomic and predictive models on three independent neuroimaging datasets (n = 1,199, including patients with SCZ and healthy controls), we first identified two macroscale dysconnectivity dimensions for corticocortical and corticostriatal circuits, each associated with specific clinical symptoms. We then associated macroscale dysconnectivity with disrupted cellular circuits using extended imaging transcriptomic and genetic analyses on multiomics data. Our findings suggest a two-dimensional cross-scale heterogeneity model of SCZ, which reveals how distinct genetic disruptions affect specific cellular-level deficits, resulting in system-level brain circuit dysconnectivity responsible for the heterogeneous symptoms in SCZ. These findings significantly improve our understanding of cross-scale heterogeneity in SCZ, advancing its pathophysiology and treatment development. Using an integrated analysis on three independent large human datasets, Wang et al. map macroscale dysconnectivity in schizophrenia onto layer- and cell-type-specific microscale alterations. The authors identify different alterations of corticocortical and corticostriatal connectivity in schizophrenia and their relationship to different symptom dimensions and functional domains.
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