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Altered structural brain network resulting from white matter injury in obstructive sleep apnea

Authors
Lee, Min-HeeYun, Chang-HoMin, AreumHwang, Yoon HoLee, Seung KuKim, Dong YounThomas, Robert J.Han, Bong SooShin, Chol
Issue Date
Sep-2019
Publisher
OXFORD UNIV PRESS INC
Keywords
obstructive sleep apnea; diffusion tensor imaging; fractional anisotropy; structural brain network
Citation
SLEEP, v.42, no.9
Indexed
SCIE
SCOPUS
Journal Title
SLEEP
Volume
42
Number
9
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/63084
DOI
10.1093/sleep/zsz120
ISSN
0161-8105
Abstract
Study Objectives: To assess, using fractional anisotropy (FA) analysis, alterations of brain network connectivity in adults with obstructive sleep apnea (OSA). Abnormal networks could mediate clinical functional deficits and reflect brain tissue injury. Methods: Structural brain networks were constructed using diffusion tensor imaging (DTI) from 165 healthy (age 57.99 +/- 6.02 years, male 27.9%) and 135 OSA participants (age 59.01 +/- 5.91 years, male 28.9%) and global network properties (strength, global efficiency, and local efficiency) and regional efficiency were compared between groups. We examined MRI biomarkers of brain tissue injury using FA analysis and its effect on the network properties. Results: Differences between groups of interest were noted in global network properties (p-value < 0.05, corrected), and regional efficiency (p-value < 0.05, corrected) in the left middle cingulate and paracingulate gyri, right posterior cingulate gyrus, and amygdala. In FA analysis, OSA participants showed lower FA values in white matter (WM) of the right transverse temporal, anterior cingulate and paracingulate gyri, and left postcentral, middle frontal and medial frontal gyri, and the putamen. After culling fiber tracts through WM which showed significant differences in FA, we observed no group difference in network properties. Conclusions: Changes in WM integrity and structural connectivity are present in OSA participants. We found that the integrity of WM affected brain network properties. Brain network analysis may improve understanding of neurocognitive deficits in OSA, enable longitudinal tracking, and provides explanations for specific symptoms and recovery kinetics.
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