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Altered cortical structure network in children with obstructive sleep apnea

Min-Hee Lee1, Sanghun Sin2, Seonjoo Lee3

  • 1Institute of Human Genomic Study, College of Medicine, Korea University Ansan Hospital, Ansan, Republic of Korea.

Sleep
|May 13, 2022
PubMed

Insights

Children with obstructive sleep apnea (OSA) show altered brain network organization. This study reveals differences in cortical structure and connectivity in pediatric OSA patients compared to controls.

Area of Science:

  • Neuroscience
  • Pediatric Neurology
  • Sleep Medicine

Background:

  • Obstructive sleep apnea (OSA) involves recurrent airway collapse during sleep.
  • This leads to intermittent hypoxia and sleep fragmentation.
  • These factors may alter brain structure and function.

Purpose of the Study:

  • To investigate if obstructive sleep apnea in children reorganizes cortical structure.
  • To examine changes in cortical thickness correlation between brain regions in pediatric OSA.
  • To understand the etiology of OSA-related brain functional disorders.

Main Methods:

  • Cortical structure networks were constructed using cortical thickness measurements.
  • Data from 41 controls and 50 children with OSA were analyzed.
  • Global (clustering coefficient, path length, small-worldness) and regional (nodal betweenness centrality) network properties were examined.

Main Results:

  • Children with OSA exhibited increased clustering coefficients compared to controls.
  • Lower nodal betweenness centrality was observed in specific left and right hemisphere regions in the OSA group.
  • The OSA group had fewer and differently distributed brain network hubs.

Conclusions:

  • Pediatric OSA is associated with altered global and regional cortical network characteristics.
  • The findings suggest potential structural brain reorganization in children with OSA.
  • This network analysis approach may aid in understanding OSA-related neurological impacts.
Abstract

Keywords:
T1-weighted imagingchildren with obstructive sleep apneacortical structure networkcortical thickness

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