已发表论文

低功能自闭症谱系障碍儿童的异常度中心性:睡眠状态功能磁共振成像研究

 

Authors Xu S, Li M, Yang C, Fang X, Ye M, Wu Y, Yang B, Huang W, Li P, Ma X , Fu S, Yin Y, Tian J, Gan Y, Jiang G

Received 19 March 2022

Accepted for publication 23 June 2022

Published 5 July 2022 Volume 2022:18 Pages 1363—1374

DOI https://doi.org/10.2147/NDT.S367104

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Yuping Ning

Purpose: This study used the graph-theory approach, degree centrality (DC) to analyze whole-brain functional networks at the voxel level in children with ASD, and investigated whether DC changes were correlated with any clinical variables in ASD children.
Methods: The current study included 86 children with ASD and 54 matched healthy subjects Aged 2– 5.5 years. Next, chloral hydrate induced sleeping-state functional magnetic resonance imaging (ss-fMRI) datasets were acquired from these ASD and healthy subjects. For a given voxel, the DC was calculated by calculating the number of functional connections with significantly positive correlations at the individual level. Group differences were tested using two-sample -tests (< 0.01, AlphaSim corrected). Finally, relationships between abnormal DCs and clinical variables were investigated via Pearson’s correlation analysis.
Results: Children with ASD exhibited low DC values in the right middle frontal gyrus (MFG) (p < 0.01, AlphaSim corrected). Furthermore, significantly negative correlations were established between the decreased average DC values within the right MFG in ASD children and the total ABC scores, as well as with two ABC subscales measuring highly relevant impairments in ASD (ie, stereotypes and object-use behaviors and difficulties in language).
Conclusion: Taken together, the results of our ss-fMRI study suggest that abnormal DC may represent an important contribution to elucidation of the neuropathophysiological mechanisms of preschoolers with ASD.
Keywords: autism spectrum disorders, ASD, functional magnetic resonance imaging, fMRI, Degree centrality, DC, whole-brain functional networks, Pearson’s correlation analysis