Novel application of Digital signals of movement, sleep and heart rhythms for detection of Alzheimer's Disease and Related Dementias

运动、睡眠和心律数字信号在阿尔茨海默病和相关痴呆症检测中的新应用

• 批准号: 10710169
• 负责人: Lin Yee Chen
• 金额: $ 75.32万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710169
• 关键词: Accelerometer; Address; Alleles; Alzheimer disease detection; Alzheimer' s disease related dementia; Amyloid beta-Protein; Apolipoprotein E; Atherosclerosis Risk in Communities; Atrial Fibrillation; Atrial Premature Complexes; Atrial Tachycardia; Atrophic; Biological; Blood Vessels; Brain; Brain Pathology; Clinical; Cognitive; Data; Data Collection; Dementia; Development; Diagnosis; Digital biomarker; Disease; Early Diagnosis; Elderly; Electrocardiogram; Environment; Exhibits; Free Association; Frequencies; Future; Genetic; Goals; Health; Heart Abnormalities; Impaired cognition; Individual; Intervention; Joints; Knowledge; Link; Measures; Monitor; Movement; Multivariate Analysis; Nerve Degeneration; Neurocognitive; Neuropsychology; Participant; Pathology; Pathway interactions; Pattern; Phase; Phenotype; Physical Function; Physical activity; Physiological; Positron-Emission Tomography; Prevention trial; Principal Component Analysis; Research; Rest; Risk; Risk Factors; Role; Severities; Signal Transduction; Sleep; Sleep Fragmentations; Time; Variant; Ventricular Premature Complexes; Ventricular Tachycardia; White Matter Disease; abeta deposition; adjudication; brain health; brain magnetic resonance imaging; circadian; clinically relevant; cognitive change; cognitive function; cognitive performance; cognitive testing; cost effective; dementia risk; digital; digital measure; digital technology; fighting; follow-up; functional decline; heart rate variability; heart rhythm; high risk; improved; individual variation; mild cognitive impairment; neuroimaging; novel; poor sleep; response; screening; sedentary; sex; sleep abnormalities; sleep onset; tool; wearable device; β-amyloid burden

PROJECT SUMMARY Early detection of cognitive and functional decline is a major goal of the NIA in its fight against Alzheimer's Disease and Related Dementias (ADRD). Physical, physiological, and cognitive changes associated with ADRD may emerge years prior to clinical manifestations, thus there is an urgent need for novel, cost-effective, noninvasive, and scalable tools to improve detection of ADRD risk. Older adults with cognitive impairment often exhibit changes in movement, sleep, and heart rhythms, suggesting possible shared vascular or neurodegenerative pathways. Emerging research from our group and others links digital signals from movement, sleep, and heart rhythms with brain and cognitive health; however, knowledge gaps remain in the associations among these signals and brain and cognitive health across the cognitive spectrum. In response to NOT-AG-20- 017, this application will directly address these gaps using existing and ongoing/new data collection from wearable technology (7-day accelerometry and 14-day ambulatory electrocardiogram (ECG)), cognitive assessments (neuropsychological battery, adjudicated cognitive diagnosis), and neuroimaging (florbetapir PET for beta amyloid (Aβ), 3T brain MRI for neurodegeneration and white matter disease) from ≥1000 older adults participating in the Atherosclerosis Risk in Communities (ARIC) Neurocognitive Study. We will use novel analytic approaches to integrate movement, sleep, and heart rhythm features and assess their individual and joint associations with brain and cognitive health. Our overarching goal is to identify clinically relevant digital biomarkers that combine movement, sleep, and heart rhythm signals as sensitive indicators of cognitive function, cognitive trajectories, ADRD pathology, and cognitive diagnosis. To this end, this research will inform the future use of wearable devices in large-scale studies, provide novel targets for screening and early detection of ADRD in disease stages during which intervention and treatment are more likely to be effective, and aid in identifying high-risk participants for prevention trials.

项目概要 早期发现认知和功能衰退是 NIA 抗击阿尔茨海默病的主要目标 疾病和相关痴呆症（ADRD）。与 ADRD 相关的身体、生理和认知变化 可能在临床表现前数年出现，因此迫切需要新颖的、具有成本效益的、 用于改进 ADRD 风险检测的非侵入性且可扩展的工具。老年人经常有认知障碍 表现出运动、睡眠和心律的变化，表明可能存在共享血管或 神经退行性途径。我们小组和其他人的新兴研究将运动中的数字信号联系起来， 睡眠、心律与大脑和认知健康；然而，协会中仍然存在知识差距 这些信号与整个认知范围内的大脑和认知健康有关。回应 NOT-AG-20- 017，该应用程序将使用现有的和正在进行的/新的数据收集来直接解决这些差距 可穿戴技术（7 天加速度测量和 14 天动态心电图 (ECG)）、认知 评估（神经心理学电池、裁定的认知诊断）和神经影像学（氟倍他吡 PET） 来自 ≥1000 名老年人的 β 淀粉样蛋白 (Aβ)、针对神经退行性变和白质疾病的 3T 脑部 MRI 参与社区动脉粥样硬化风险 (ARIC) 神经认知研究。我们将使用新颖的分析 整合运动、睡眠和心律特征并评估其个体和关节的方法 与大脑和认知健康的关联。我们的首要目标是识别临床相关的数字 结合运动、睡眠和心律信号作为认知功能敏感指标的生物标记物， 认知轨迹、ADRD 病理学和认知诊断。为此，这项研究将为未来提供信息 在大规模研究中使用可穿戴设备，为 ADRD 筛查和早期检测提供新靶标 在干预和治疗更有可能有效的疾病阶段，并帮助识别 预防试验的高风险参与者。