Hou Ailin, Pang Xueming, Zhang Xi, Peng Yanmin, Li Dongyue, Wang He, Zhang Quan, Liang Meng, Gao Feng
College of Precision Instrument and Optoelectronics Engineering, Tianjin University, Tianjin, China.
School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin, China.
Front Neurosci. 2022 Aug 1;16:920765. doi: 10.3389/fnins.2022.920765. eCollection 2022.
Obstructive sleep apnea (OSA) is a sleep-related breathing disorder with high prevalence and is associated with cognitive impairment. Previous neuroimaging studies have reported abnormal brain functional connectivity (FC) in patients with OSA that might contribute to their neurocognitive impairments. However, it is unclear whether patients with OSA have a characteristic pattern of FC changes that can serve as a neuroimaging biomarker for identifying OSA.
A total of 21 patients with OSA and 21 healthy controls (HCs) were included in this study and scanned using resting-state functional magnetic resonance imaging (fMRI). The automated anatomical labeling (AAL) atlas was used to divide the cerebrum into 90 regions, and FC between each pair of regions was calculated. Univariate analyses were then performed to detect abnormal FCs in patients with OSA compared with controls, and multivariate pattern analyses (MVPAs) were applied to classify between patients with OSA and controls.
The univariate comparisons did not detect any significantly altered FC. However, the MVPA showed a successful classification between patients with OSA and controls with an accuracy of 83.33% ( = 0.0001). Furthermore, the selected FCs were associated with nearly all brain regions and widely distributed in the whole brain, both within and between, many resting-state functional networks. Among these selected FCs, 3 were significantly correlated with the apnea-hypopnea index (AHI) and 2 were significantly correlated with the percentage of time with the saturation of oxygen (SaO) below 90% of the total sleep time (%TST < 90%).
There existed widespread abnormal FCs in the whole brain in patients with OSA. This aberrant FC pattern has the potential to serve as a neurological biomarker of OSA, highlighting its importance for understanding the complex neural mechanism underlying OSA and its cognitive impairment.
阻塞性睡眠呼吸暂停（OSA）是一种患病率较高的与睡眠相关的呼吸障碍，与认知障碍有关。先前的神经影像学研究报告称，OSA患者存在脑功能连接（FC）异常，这可能导致他们的神经认知障碍。然而，尚不清楚OSA患者是否具有FC变化的特征模式，可作为识别OSA的神经影像学生物标志物。
本研究共纳入21例OSA患者和21名健康对照（HCs），并使用静息态功能磁共振成像（fMRI）进行扫描。采用自动解剖标记（AAL）图谱将大脑划分为90个区域，并计算每对区域之间的FC。然后进行单变量分析，以检测OSA患者与对照组相比的异常FC，并应用多变量模式分析（MVPA）对OSA患者和对照组进行分类。
单变量比较未发现任何显著改变的FC。然而，MVPA显示OSA患者和对照组之间成功分类，准确率为83.33%（=0.0001）。此外，所选的FC与几乎所有脑区相关，并广泛分布于整个大脑，在许多静息态功能网络内部和之间。在这些所选的FC中，3个与呼吸暂停低通气指数（AHI）显著相关，2个与总睡眠时间中氧饱和度（SaO）低于90%的时间百分比（%TST<90%）显著相关。
OSA患者全脑存在广泛的异常FC。这种异常的FC模式有可能作为OSA的神经生物标志物，突出了其对于理解OSA及其认知障碍背后复杂神经机制的重要性。
