Luo Xiao, Li Kaicheng, Zeng Qingze, Liu Xiaocao, Li Jixuan, Zhang Xinyi, Zhong Siyan, Liu Lingyun, Wang Shuyue, Wang Chao, Chen Yanxing, Zhang Minming, Huang Peiyu
Department of Radiology The Second Affiliated Hospital of Zhejiang University School of Medicine Hangzhou China.
Department of Neurology The Second Affiliated Hospital of Zhejiang University School of Medicine Hangzhou China.
Alzheimers Dement (Amst). 2025 Jan 29;17(1):e70077. doi: 10.1002/dad2.70077. eCollection 2025 Jan-Mar.
This study explores the impact of sleep disturbances on gray matter structural covariance networks (SCNs) across the Alzheimer's disease (AD) continuum.
Amyloid-negative participants served as controls, whereas amyloid positive (A+) individuals were categorized into six groups based on cognitive status and sleep quality. SCNs for the default mode network (DMN), salience network (SN), and executive control network (ECN) were derived from T1-weighted magnetic resonance images.
In the DMN, increased structural associations were observed in cognitive unimpaired (CU) A+ and mild cognitive impairment (MCI) groups regardless of sleep quality, whereas AD with poor sleep (PS) showed a decrease and AD with normal sleep (NS) an increase. For the ECN, AD-NS showed increased and AD-PS showed reduced associations. In the SN, reduced associations were observed in CU A+ NS and MCI-NS, whereas AD-NS displayed increased associations; only AD-PS had decreased associations.
Distinct SCN damage patterns between normal and poor sleepers provide insights into sleep disturbances in AD.
We delineated distinct patterns of structural covariance networks (SCN) impairment across the Alzheimer's disease (AD) continuum, uncovering significant disparities between individuals with normal sleep architecture and those afflicted by sleep disturbances.These observations underscore the pivotal importance of addressing sleep disruptions in AD therapeutics, providing a refined understanding of their detrimental impact on brain networks implicated in the disease.Our investigation epitomizes methodological precision by constructing an AD continuum using amyloid positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers to minimize diagnostic heterogeneity, further enhanced by a substantial cohort size that bolsters the robustness and generalizability of our findings.
本研究探讨睡眠障碍对阿尔茨海默病（AD）连续体中灰质结构协方差网络（SCNs）的影响。
淀粉样蛋白阴性参与者作为对照，而淀粉样蛋白阳性（A+）个体根据认知状态和睡眠质量分为六组。默认模式网络（DMN）、突显网络（SN）和执行控制网络（ECN）的SCNs由T1加权磁共振图像得出。
在DMN中，无论睡眠质量如何，认知未受损（CU）A+组和轻度认知障碍（MCI）组的结构关联性均增加，而睡眠不佳（PS）的AD患者显示下降，睡眠正常（NS）的AD患者显示增加。对于ECN，AD-NS组显示增加，AD-PS组显示减少。在SN中，CU A+ NS组和MCI-NS组的关联性降低，而AD-NS组显示增加；只有AD-PS组的关联性降低。
正常睡眠者和睡眠不佳者之间不同的SCN损伤模式为AD中的睡眠障碍提供了见解。
我们描绘了阿尔茨海默病（AD）连续体中结构协方差网络（SCN）损伤的不同模式，揭示了睡眠结构正常的个体与受睡眠障碍影响的个体之间的显著差异。这些观察结果强调了在AD治疗中解决睡眠中断问题的关键重要性，提供了对其对该疾病相关脑网络的有害影响的更精确理解。我们的研究通过使用淀粉样蛋白正电子发射断层扫描（PET）和脑脊液（CSF）生物标志物构建AD连续体来体现方法的精确性，以尽量减少诊断异质性，大量的队列规模进一步增强了我们研究结果的稳健性和普遍性。
