Contributions of sleep to preclinical and clinical Alzheimer's disease

睡眠对阿尔茨海默病临床前和临床的影响

基本信息

批准号：
9887564
负责人：
Jayandra Jung Himali
金额：
$ 84.69万
依托单位：
UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-04-01 至 2024-02-29
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9887564
关键词：
Abeta synthesis Accounting Acute Age Alzheimer&apos s Disease Alzheimer&apos s disease brain Amyloid beta-Protein Atherosclerosis Risk in Communities Biological Biological Markers Biology Brain Brain Injuries Buffers Clinical Cluster Analysis Cognition Cognitive Communities Country Coupling Data Dementia Development Diagnosis Electroencephalography Enrollment Event Flushing Framingham Heart Study Genetic Risk Gold Hippocampus (Brain)Home environment Hypoxia Incidence Individual Infarction Intervention Investigation Ischemic Brain Injury Magnetic Resonance Imaging Measures Memory Meta-Analysis Metabolic Methodology Nerve Degeneration Neurocognitive Outcome Participant Pathway interactions Phase Phenotype Play Polysomnography Prevention REM Sleep Research Resources Risk Risk stratification Role Sample Size Sampling Sleep Sleep Apnea Syndromes Sleep Disorders Sleep Wake Cycle Sleep disturbances Slow-Wave Sleep Subgroup Synaptic plasticity Therapeutic Time Wakefulness White Matter Disease Work abeta accumulation age difference aging brain apolipoprotein E-4 base blood-brain barrier permeabilization brain volume cardiovascular health cerebral atrophy cognitive ability cognitive function cognitive performance cohort dementia risk density endophenotype executive function glymphatic system high risk improved innovation ischemic injury memory consolidation men neuroinflammation neurophysiology non-demented novel osteoporosis with pathological fracture population based pre-clinical protein aggregation rate of change response sex sex risk sleep quality sleep spindle socioeconomics success wasting

项目摘要

Identifying the specific aspects of sleep that relate to incident dementia is the first step towards the development of sleep interventions to reduce dementia risk. Detailed overnight sleep studies, known as polysomnography (PSG), provide the gold-standard assessment of sleep. As obtaining PSG is burdensome, studies with PSG tend to enroll a limited number of participants and consequently have limited statistical power to detect small but potentially important associations between sleep and dementia. We propose to curate data from 5 large population-based cohorts (Atherosclerosis Risk in Communities, Cardiovascular Health Study, Framingham Heart Study, Osteoporotic Fractures in Men, and the Study of Osteoporotic Fractures) with methodologically consistent sleep studies and neurocognitive outcomes. By combining study-level data in meta-analysis, we propose the following aims: Aim 1 is to examine the aspects of sleep that relate to a higher risk of incident Alzheimer's disease (AD) dementia (N=2776, 499 incident cases). We will capture 134 sleep metrics, measuring all aspects of sleep neurophysiology. We will then identify clusters and calculate the first principal component from each cluster as the exposers. We will further assess the association between cluster specific sleep metrics and outcomes using least absolute shrinkage and selection operator (LASSO) regression 1.a. We will examine each aspect of sleep neurophysiology with respect to the risk of incident AD dementia, after accounting for known confounders. 1.b. We will leverage our statistical power to explore differences by age decades, sex, and genetic risk (e.g., APOE ε4 positivity). Aim 2 is to examine the aspects of sleep (defined in Aim 1) that relate cross-sectionally to dementia endophenotypes. As poor sleep is potentially modifiable, it is important to know whether poor sleep is related to preclinical phenotypes of dementia—a time when dementia risk may still be malleable. Brain atrophy on MRI and subtle deficits in cognitive ability precede dementia diagnosis by up to a decade. We will relate each sleep marker to general and domain-specific cognitive performance (N=6723) as well as brain volume (total brain and hippocampal) and brain injury (white matter disease, silent infarcts) on MRI (N=1157). Aim 3 is to examine whether changes in sleep neurophysiology over ~6 years predict incident dementia (N=1558, 275 events), cognition (N=3065), or brain volume (N=763). Leveraging repeated PSGs ~6 years apart, we will examine if changes in sleep neurophysiology relate to incident AD dementia, brain volume, or cognitive function. Our large analysis of community-based participants from across the U.S. will provide the most robust evidence yet on the associations between sleep and AD dementia risk. Moreover, leveraging our large pooled sample size to examine subgroup differences (e.g., by age decades, sex and APOE) and the comprehensive investigation of sleep neurophysiology, including innovative sleep measures (e.g., spindle density), may inform therapeutic strategies for dementia prevention by identifying subgroups most at risk, new biomarkers to improve dementia risk stratification, and novel biological pathways.

识别与事件痴呆有关的睡眠的特定方面是迈向发展的第一步睡眠干预措施以降低痴呆症风险。详细的过夜睡眠研究，称为多渗透学（PSG），提供睡眠的金标准评估。由于获得PSG是燃烧的，因此对PSG的研究趋于要注册有限数量的参与者，因此统计能力有限，无法检测到较小但睡眠与痴呆之间的潜在重要关联。我们建议策划5个大的数据基于人群的队列（社区动脉粥样硬化风险，心血管健康研究，弗雷明汉心脏研究，男性骨质疏松性骨折以及骨质疏松骨折的研究）一致的睡眠研究和神经认知结果。通过在荟萃分析中结合研究级数据，我们建议以下目的：目标1是检查与较高事件风险有关的睡眠方面阿尔茨海默氏病（AD）痴呆症（n = 2776，499事件病例）。我们将捕获134个睡眠指标，测量睡眠神经生理学的所有方面。然后，我们将识别簇并计算第一本主体每个群集的分量是暴露的。我们将进一步评估群集特定之间的关联使用最少绝对收缩和选择操作员（LASSO）回归1.A的睡眠指标和结果。我们将检查睡眠神经生理学的各个方面，相对于出现痴呆的风险考虑已知的混杂因素。 1.B.我们将利用我们的统计能力来探索按年龄的差异数十年，性别和遗传风险（例如ApoEε4积极性）。目标2是检查睡眠的各个方面（定义）。在AIM 1）与痴呆型内表型相关的。由于睡眠不良可能会改变，因此重要的是要知道睡眠不足是否与痴呆的临床前表型有关痴呆症风险可能仍然可延展。在MRI和认知能力的微妙防御之前，大脑萎缩先于痴呆症诊断长达十年。我们将将每个睡眠标记与一般和域特异性认知联系起来性能（n = 6723）以及大脑体积（总脑和海马）和脑损伤（白质 MRI上的疾病，无声梗塞）（n = 1157）。 AIM 3是检查睡眠神经生理学的变化是否超过6年的预测痴呆症（n = 1558，275事件），认知（n = 3065）或大脑体积（n = 763）。利用重复的PSG相距约6年，我们将检查睡眠神经生理学的变化是否相关到入射AD痴呆，大脑体积或认知功能。我们对社区参与者的大量分析来自美国各地将提供有关睡眠与广告之间关联的最有力的证据痴呆症风险。此外，利用我们的大型样本量来检查亚组差异（例如，按年龄数十年，性别和apoe）以及对睡眠神经生理学的全面研究，包括创新睡眠度量（例如纺锤体密度）可以通过识别来为预防痴呆的治疗策略提供依据亚组最有风险，改善痴呆症风险分层的新生物标志物以及新型的生物学途径。