Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study - Li, Haijun; Li, Lan; Li, Kunyao; Li, Panmei; Xie, Wei; Zeng, Yaping; Kong, Linghong; Long, Ting; Huang, Ling; Liu, Xiang; Shu, Yongqiang; Zeng, Li; et al. (Frontiers in Aging Neuroscience, 2022)
Objective: Many neuroimaging studies have used static functional connectivity of magnetic resonance imaging methods to explore the neural mechanisms of obstructive sleep apnea (OSA) patients. Dynamic functional connectivity captures the temporal changes in functional connectivity during MRI acquisition and is used to understand the neural mechanisms in patients with OSA. The purpose of this study was to investigate the dynamic functional network connectivity (dFNC) and its relationship with cognitive function in OSA patients. Material and Methods: 82 OSA patients and 48 healthy controls (HCs) were included in this study. Clinical and resting-state fMRI data were collected, and 8 resting-state networks were determined by independent component analysis. Then, a sliding-window approach was used to construct the dFNC, and differences of temporal properties and functional connectivity strength were compared between OSA patients and the HC groups. Furthermore, the relationship between temporal properties and clinical assessments such as cognition were analysed in OSA patients. Results: Two different connection states were identified, namely, state I with stronger connection and lower frequency, and state II with lower connection and relatively high frequency. Compared to HCs, OSA patients had a longer mean dwell time and higher fractional window in stronger connectivity states I, and showed shorter mean dwell time and lower fractional window in state II, which was mainly reflected in OSA-MCI patients, but was not significantly different in OSA-NC. Although the number of transitions was no different between OSA patients and HCs, there was an increasing trend in OSA-MCI patients, and the number of transitions was positively correlated with cognitive assessment. Compared with HCs, OSA patients had extensive functional connectivity abnormalities in stronger connectivity state I and less reduced functional connectivity in lower connectivity state II, which were mainly located in the salience network, default mode network and executive control network. Conclusions: Our study found that OSA patients showed abnormal dFNC properties, which was a continuous trend from HC, and OSA-NC to OSA-MCI, and OSA patients showed abnormal dynamic functional connection strength. These changes were associated with cognitive impairment, which may provide new insights into the neural mechanisms in OSA patients.