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阿斯伯格综合征的脑结构协方差网络与自闭症谱系障碍及健康对照者的不同。

Brain Structural Covariance Network in Asperger Syndrome Differs From Those in Autism Spectrum Disorder and Healthy Controls.

作者信息

Faridi Farnaz, Seyedebrahimi Afrooz, Khosrowabadi Reza

机构信息

Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran.

出版信息

Basic Clin Neurosci. 2022 Nov-Dec;13(6):815-838. doi: 10.32598/bcn.2021.2262.1. Epub 2022 Nov 1.

Abstract

INTRODUCTION

Autism is a heterogeneous neurodevelopmental disorder associated with social, cognitive and behavioral impairments. These impairments are often reported along with alteration of the brain structure such as abnormal changes in the grey matter (GM) density. However, it is not yet clear whether these changes could be used to differentiate various subtypes of autism spectrum disorder (ASD).

METHOD

We compared the regional changes of GM density in ASD, Asperger's Syndrome (AS) individuals and a group of healthy controls (HC). In addition to regional changes itself, the amount of GM density changes in one region as compared to other brain regions was also calculated. We hypothesized that this structural covariance network could differentiate the AS individuals from the ASD and HC groups. Therefore, statistical analysis was performed on the MRI data of 70 male subjects including 26 ASD (age=14-50, IQ=92-132), 16 AS (age=7-58, IQ=93-133) and 28 HC (age=9-39, IQ=95-144).

RESULT

The one-way ANOVA on the GM density of 116 anatomically separated regions showed significant differences among the groups. The pattern of structural covariance network indicated that covariation of GM density between the brain regions is altered in ASD.

CONCLUSION

This changed structural covariance could be considered as a reason for less efficient segregation and integration of information in the brain that could lead to cognitive dysfunctions in autism. We hope these findings could improve our understanding about the pathobiology of autism and may pave the way towards a more effective intervention paradigm.

摘要

引言

自闭症是一种异质性神经发育障碍,与社交、认知和行为障碍相关。这些障碍常伴随着脑结构改变,如灰质(GM)密度异常变化。然而,这些变化是否可用于区分自闭症谱系障碍(ASD)的不同亚型尚不清楚。

方法

我们比较了ASD、阿斯伯格综合征(AS)个体和一组健康对照(HC)的GM密度区域变化。除了区域变化本身,还计算了一个区域与其他脑区相比的GM密度变化量。我们假设这种结构协方差网络可以区分AS个体与ASD和HC组。因此,对70名男性受试者的MRI数据进行了统计分析,其中包括26名ASD患者(年龄=14 - 50岁,智商=92 - 132)、16名AS患者(年龄=7 - 58岁,智商=93 - 133)和28名HC(年龄=9 - 39岁,智商=95 - 144)。

结果

对116个解剖学上分离区域的GM密度进行的单因素方差分析显示,各组之间存在显著差异。结构协方差网络模式表明,ASD患者脑区之间GM密度的协变发生了改变。

结论

这种改变的结构协方差可被视为大脑中信息分离和整合效率较低的原因,这可能导致自闭症患者出现认知功能障碍。我们希望这些发现能够增进我们对自闭症病理生物学的理解,并可能为更有效的干预模式铺平道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b001/10262285/ce3ccf6fdc27/BCN-13-815-g001.jpg

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