Noninvasive Low-cost Biomarkers for Preclinical Diagnosis and Longitudinal Tracking of Alzheimer's Disease Using Sleep and Resting State EEG

项目总结 本研究的目的是开发低成本、非侵入性的脑电生理生物标志物 临床前和先兆阿尔茨海默病(AD)患者的淀粉样蛋白和神经变性 睡眠和休息状态脑电(EEG)。最近为“临床前”制定的诊断标准 前驱症状的AD取决于β-淀粉样蛋白(A-β)的测量以及脑结构和功能的变化。 提顿。不幸的是，这些“黄金标准”生物标记物过于昂贵(约3000美元/患者)、侵入性或专业性太强 用于大规模的筛查工作。因此，迫切需要新的成本效益高的生物标记物，这些标记物是严格的- 与临床前AD的既定标准密切相关。越来越多的人意识到大脑的振荡-- 睡眠和静息状态下的脑电与阿尔茨海默病的病理生理密切相关。这很好 众所周知，阿尔茨海默病与睡眠动力学紊乱和睡眠振荡改变有关。净空 大脑Aβ通过大脑的神经胶质淋巴管或“淋巴”系统发生在非快速 眼球运动(NREM)睡眠，并依赖于脑电的缓慢振荡活动。大脑皮质生成器 睡眠和休息状态的脑电振荡可以通过源定位来估计，它与大脑重叠 阿尔茨海默病中表现为皮质变薄和功能连接丧失的区域。这些关系并没有 在临床前或先兆AD中得到了广泛的研究。因此，我们建议1)描述关系的特征- 睡眠和静息状态脑电定量测量与神经影像AD的关系 标志物，2)利用这些新的关系以及已知的AD相关脑电变化来开发 基于脑电的AD预测指标，以及3)开发一个框架，将这些发现转化为低成本 (只需20美元)，高度可扩展的工具，用于筛查和跟踪临床前和前驱AD。

PROJECT SUMMARY The objective of this research is to develop low-cost, non-invasive, electrophysiological biomarkers of brain amyloid and neurodegeneration in patients with Preclinical and Prodromal Alzheimer's disease (AD) using the sleep and resting state electroencephalogram (EEG). Diagnostic criteria recently developed for “Preclinical” and “Prodromal” AD hinge upon measurements of beta-amyloid (Aβ) and changes in brain structure and func- tion. Unfortunately, these “gold standard” biomarkers are too expensive (~$3k/patient), invasive, or specialized for large-scale screening efforts. Thus, there is urgent need for novel cost-effective biomarkers that are rigor- ously linked to established criteria for Preclinical AD. There is a growing appreciation that brain oscillations ob- served in the sleep and resting state EEG are closely associated with underlying AD pathophysiology. It is well known that AD dementia is associated with disrupted sleep dynamics and altered sleep oscillations. Clearance of cerebral Aβ through the brain's glial lymphatic or “glymphatic” system occurs specifically during non-rapid eye movement (NREM) sleep, and is dependent on EEG slow oscillation activity. The cortical generators of sleep and resting state EEG oscillations, which can be estimated using source localization, overlap with brain regions that display cortical thinning and loss of functional connectivity in AD. These relationships have not been extensively studied in preclinical nor prodromal AD. We therefore propose to 1) characterize the rela- tionship between quantitative measures of sleep and resting state EEG and neuroimaging AD bi- omarkers, 2) use these novel relationships alongside known AD-related changes in the EEG to develop EEG-based predictors of AD, and 3) develop a framework for translating these findings into low-cost (as little as $20), highly-scalable tools for screening and tracking of preclinical and prodromal AD.