State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Chinese Institute for Brain Research, Beijing, China.
Biol Psychiatry. 2022 Jun 1;91(11):945-955. doi: 10.1016/j.biopsych.2021.12.004. Epub 2021 Dec 11.
Neuroimaging studies have reported functional connectome aberrancies in autism spectrum disorder (ASD). However, the time-varying patterns of connectome topology in individuals with ASD and the connection between these patterns and gene expression profiles remain unknown.
To investigate case-control differences in dynamic connectome topology, we conducted mega- and meta-analyses of resting-state functional magnetic resonance imaging data of 939 participants (440 patients with ASD and 499 healthy control subjects, all males) from 18 independent sites, selected from the Autism Brain Imaging Data Exchange (ABIDE) dataset. Functional data were preprocessed and analyzed using harmonized protocols, and brain module dynamics was assessed using a multilayer network model. We further leveraged postmortem brain-wide gene expression data to identify transcriptomic signatures associated with ASD-related alterations in brain dynamics.
Compared with healthy control participants, individuals with ASD exhibited a higher global mean and lower standard deviation of whole-brain module dynamics, indicating an unstable and less regionally differentiated pattern. More specifically, individuals with ASD showed higher module switching, primarily in the medial prefrontal cortex, posterior cingulate gyrus, and angular gyrus, and lower switching in the visual regions. These alterations in brain dynamics were predictive of social impairments in individuals with ASD and were linked with expression profiles of genes primarily involved in the regulation of neurotransmitter transport and secretion as well as with previously identified autism-related genes.
This study is the first to identify consistent alterations in brain network dynamics in ASD and the transcriptomic signatures related to those alterations, furthering insights into the biological basis behind this disorder.
神经影像学研究报告称，自闭症谱系障碍（ASD）患者的功能连接组存在异常。然而，ASD 个体的连接组拓扑的时变模式以及这些模式与基因表达谱之间的联系尚不清楚。
为了研究自闭症患者的动态连接组拓扑的病例对照差异，我们对来自自闭症脑成像数据交换（ABIDE）数据集的 18 个独立站点的 939 名参与者（440 名 ASD 患者和 499 名健康对照者，均为男性）的静息态功能磁共振成像数据进行了 mega 和元分析。使用协调的方案预处理和分析功能数据，并使用多层网络模型评估大脑模块动力学。我们进一步利用大脑全基因表达数据来识别与 ASD 相关的大脑动力学改变相关的转录组特征。
与健康对照组相比，ASD 个体表现出更高的全脑模块动力学的全局均值和更低的标准差，这表明大脑动力学不稳定且区域差异较小。更具体地说，ASD 个体表现出更高的模块切换，主要发生在前内侧额皮质、后扣带和角回，以及较低的视觉区域切换。这些大脑动力学的改变可以预测 ASD 个体的社交障碍，并与主要参与神经递质转运和分泌调节以及先前确定的与自闭症相关基因的基因表达谱相关。
这项研究首次确定了 ASD 中大脑网络动力学的一致改变及其相关的转录组特征，进一步深入了解了这种疾病的生物学基础。
