Impact of sleep disruptions on gray matter structural covariance networks across the Alzheimer's disease continuum.

IF 4 Q1 CLINICAL NEUROLOGY

Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Pub Date : 2025-01-29 eCollection Date: 2025-01-01 DOI:10.1002/dad2.70077

Xiao Luo, Kaicheng Li, Qingze Zeng, Xiaocao Liu, Jixuan Li, Xinyi Zhang, Siyan Zhong, Lingyun Liu, Shuyue Wang, Chao Wang, Yanxing Chen, Minming Zhang, Peiyu Huang

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引用次数: 0

Abstract

Background: This study explores the impact of sleep disturbances on gray matter structural covariance networks (SCNs) across the Alzheimer's disease (AD) continuum.

Methods: 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.

Results: 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.

Conclusion: Distinct SCN damage patterns between normal and poor sleepers provide insights into sleep disturbances in AD.

Highlights: 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.

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睡眠中断对阿尔茨海默病连续体灰质结构协方差网络的影响。

背景：本研究探讨了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（scn）的影响。方法：淀粉样蛋白阴性的参与者作为对照，而淀粉样蛋白阳性（A+）的个体根据认知状态和睡眠质量分为六组。默认模式网络（DMN）、显著性网络（SN）和执行控制网络（ECN）的scn来自t1加权磁共振图像。结果：在DMN中，无论睡眠质量如何，认知未受损（CU） A+和轻度认知障碍（MCI）组均观察到结构关联增加，而睡眠不良（PS） AD组的结构关联减少，睡眠正常（NS） AD组的结构关联增加。对于ECN， AD-NS增加，AD-PS减少。在SN中，CU A+ NS和MCI-NS的相关性降低，而AD-NS的相关性增加；只有AD-PS的相关性降低。结论：正常睡眠者和睡眠不良者之间不同的SCN损伤模式为阿尔茨海默病的睡眠障碍提供了见解。重点：我们描述了阿尔茨海默病（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和睡眠障碍患者之间的显著差异。这些观察结果强调了在阿尔茨海默病治疗中解决睡眠中断的关键重要性，提供了对其对涉及该疾病的大脑网络的有害影响的精确理解。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，以最大限度地减少诊断异质性，从而体现了方法的精确性，进一步增强了大量队列规模，从而增强了我们研究结果的稳健性和普遍性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Alzheimer''s and Dementia: Diagnosis, Assessment and Disease Monitoring Medicine-Psychiatry and Mental Health

CiteScore

7.80

自引率

7.50%

发文量

101

审稿时长

8 weeks

期刊介绍： Alzheimer''s & Dementia: Diagnosis, Assessment & Disease Monitoring (DADM) is an open access, peer-reviewed, journal from the Alzheimer''s Association® that will publish new research that reports the discovery, development and validation of instruments, technologies, algorithms, and innovative processes. Papers will cover a range of topics interested in the early and accurate detection of individuals with memory complaints and/or among asymptomatic individuals at elevated risk for various forms of memory disorders. The expectation for published papers will be to translate fundamental knowledge about the neurobiology of the disease into practical reports that describe both the conceptual and methodological aspects of the submitted scientific inquiry. Published topics will explore the development of biomarkers, surrogate markers, and conceptual/methodological challenges. Publication priority will be given to papers that 1) describe putative surrogate markers that accurately track disease progression, 2) biomarkers that fulfill international regulatory requirements, 3) reports from large, well-characterized population-based cohorts that comprise the heterogeneity and diversity of asymptomatic individuals and 4) algorithmic development that considers multi-marker arrays (e.g., integrated-omics, genetics, biofluids, imaging, etc.) and advanced computational analytics and technologies.