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Post published on Twitter/X on 5 Oct 2021 03:28

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Yapei Xie, Zhilei Xu, Mingrui Xia, Jin Liu, Xiaojing Shou, Zaixu Cui, Xuhong Liao, Yong He (2021). Alterations in Connectome Dynamics in Autism Spectrum Disorder: A Harmonized Mega- and Meta-Analysis Study Using the ABIDE Dataset. openRxiv.

Publication date
4 Oct 2021
Identifier
10.1101/2021.10.03.462909
Authors
Yapei Xie, Zhilei Xu, Mingrui Xia, Jin Liu, Xiaojing Shou, Zaixu Cui, Xuhong Liao, Yong He
Reference type
preprint
Publisher
openRxiv
Metadata source
crossref

Abstract

ABSTRACT BACKGROUND Neuroimaging studies have reported functional connectome aberrancies in autism spectrum disorder (ASD). However, the time-varying patterns of connectome topology in ASD individuals and the connection between these patterns and gene expression profiles remain unknown. METHODS 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 ASD patients and 499 healthy controls, all males) from 18 independent sites, selected from the ABIDE (Autism Brain Imaging Data Exchange) dataset. Functional data was 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. RESULTS Compared to healthy controls, ASD individuals exhibited a higher global mean and lower standard deviation of whole-brain module dynamics, indicating an unstable and less regionally differentiated pattern. More specifically, ASD individuals 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 ASD individuals 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. CONCLUSIONS 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.

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