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精神分裂症、自闭症和强迫症谱系障碍的形态计量共萎缩网络。

The morphometric co-atrophy networking of schizophrenia, autistic and obsessive spectrum disorders.

机构信息

GCS-FMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.

Focus Lab, Department of Psychology, University of Turin, Turin, Italy.

出版信息

Hum Brain Mapp. 2018 May;39(5):1898-1928. doi: 10.1002/hbm.23952. Epub 2018 Jan 18.

Abstract

By means of a novel methodology that can statistically derive patterns of co-alterations distribution from voxel-based morphological data, this study analyzes the patterns of brain alterations of three important psychiatric spectra-that is, schizophrenia spectrum disorder (SCZD), autistic spectrum disorder (ASD), and obsessive-compulsive spectrum disorder (OCSD). Our analysis provides five important results. First, in SCZD, ASD, and OCSD brain alterations do not distribute randomly but, rather, follow network-like patterns of co-alteration. Second, the clusters of co-altered areas form a net of alterations that can be defined as morphometric co-alteration network or co-atrophy network (in the case of gray matter decreases). Third, within this network certain cerebral areas can be identified as pathoconnectivity hubs, the alteration of which is supposed to enhance the development of neuronal abnormalities. Fourth, within the morphometric co-atrophy network of SCZD, ASD, and OCSD, a subnetwork composed of eleven highly connected nodes can be distinguished. This subnetwork encompasses the anterior insulae, inferior frontal areas, left superior temporal areas, left parahippocampal regions, left thalamus and right precentral gyri. Fifth, the co-altered areas also exhibit a normal structural covariance pattern which overlaps, for some of these areas (like the insulae), the co-alteration pattern. These findings reveal that, similarly to neurodegenerative diseases, psychiatric disorders are characterized by anatomical alterations that distribute according to connectivity constraints so as to form identifiable morphometric co-atrophy patterns.

摘要

本研究采用一种新颖的方法,能够从基于体素的形态学数据中统计推导出共改变分布模式,分析了三个重要精神科谱的脑改变模式,即精神分裂症谱障碍(SCZD)、自闭症谱系障碍(ASD)和强迫症谱障碍(OCSD)。我们的分析提供了五个重要结果。首先,在 SCZD、ASD 和 OCSD 中,脑改变并非随机分布,而是遵循类似网络的共改变模式。其次,共改变区域的集群形成了一个可以定义为形态计量共改变网络或共萎缩网络(在灰质减少的情况下)的改变网络。第三,在这个网络中,可以确定某些大脑区域为病理连通性枢纽,这些区域的改变被认为会增强神经元异常的发展。第四,在 SCZD、ASD 和 OCSD 的形态计量共萎缩网络中,可以区分出一个由 11 个高度连接节点组成的子网。这个子网包括前岛叶、下额前区、左侧颞上区、左侧海马旁区、左侧丘脑和右侧中央前回。第五,共改变区域也表现出正常的结构协方差模式,对于其中一些区域(如岛叶),这种模式与共改变模式重叠。这些发现表明,与神经退行性疾病类似,精神疾病的特征是根据连接约束分布的解剖学改变,从而形成可识别的形态计量共萎缩模式。

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