GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy; Functional Neuroimaging and Complex Neural Systems (FOCUS) Laboratory, Department of Psychology, University of Turin, Turin, Italy.
Department of Psychology, University of Miami, Coral Gables, FL, USA; Neuroscience Program, University of Miami Miller School of Medicine, Miami, FL, USA.
Neuroimage Clin. 2021;30:102583. doi: 10.1016/j.nicl.2021.102583. Epub 2021 Feb 12.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored.
An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD.
Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations.
These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders.
自闭症谱系障碍(ASD)是一种神经发育障碍,其特征为异常的大脑解剖结构和连接。图论方法主要应用于检测 ASD 个体的白质束和功能脑激活的改变模式。ASD 中灰质(GM)异常的网络拓扑仍相对未被探索。
为了研究 GM 变化是否可以以大脑内特定的共改变模式发展,我们对基于体素的形态计量学数据(45 项实验,1786 名 ASD 患者)进行了创新的元连接组学分析。然后将该模式与结构和遗传共表达图谱的规范图谱进行比较。还应用了中心性和聚类的图测度来识别 ASD 中观察到的共改变网络中具有最高拓扑层次结构和核心子图组件的脑区。
ASD 个体表现出独特的、拓扑定义的 GM 共改变模式,该模式与结构连接约束适度相关。这在遗传共表达模式上并未观察到。共改变网络的枢纽区域主要为左侧化,包括楔前叶、腹侧前扣带和中枕叶回。默认模式网络的区域似乎是共改变拓扑的核心。
这些发现为 ASD 的病理生物学提供了新的视角,表明空间分布的 GM 区域之间存在网络级功能障碍。同时,这项研究支持病理连接组学作为一种深入理解神经精神障碍的方法。