Disrupted small-world brain functional network topology in male patients with severe obstructive sleep apnea revealed...

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that can damage cognitive function. However, the functional network organization remains poorly understood. The aim of this study was to investigate the topological properties of OSA patients using a graph theoretical analysis.

A total of 30 male patients with untreated severe OSA and 25 male education- and age-matched good sleepers (GSs) underwent functional magnetic resonance imaging (MRI) examinations. Clinical and cognitive evaluations were conducted by an experienced psychologist. GRETNA (a toolbox for topological analysis of imaging connectomics) was used to construct the brain functional network and calculate the small-world properties (γ, λ, σ, E_glob, and E_loc). Relationships between these small-world properties and clinical and neuropsychological assessments were investigated in OSA patients.

The networks of both OSA patients and GSs exhibited efficient small-world topology over the sparsity range of 0.05-0.40. Compared with GSs, the OSA group had significantly decreased γ, but significantly increased λ and σ. The OSA group's brain network showed significantly decreased E_glob (P<0.05) over the sparsity range of 0.09-0.15, but significantly increased E_loc over the sparsity range of 0.23-0.40. In OSA patients, γ was significantly negatively correlated with apnea-hypopnea index (AHI; r=-0.326, P=0.015) and Epworth Sleepiness Scale (ESS; r=-0.274, P=0.043), λ was significantly positively correlated with AHI (r=0.373, P=0.005) and ESS (r=0.269, P=0.047), and σ was significantly negatively correlated with AHI (r=-0.363, P=0.007) and ESS (r=-0.295, P=0.029).

Our results suggest that the high degree of local integration and integrity of the brain connections in OSA patients may be disrupted. The topological alterations of small-world properties may be the mechanism of cognitive impairment in OSA patients. In addition, σ, γ, and λ could be used as a quantitative physiological index for auxiliary clinical diagnoses.