Naturalistic driving as a functional neurobehavioral marker of preclinical and symptomatic Alzheimer disease

自然驾驶作为临床前和症状性阿尔茨海默病的功能性神经行为标志

• 批准号: 10040061
• 负责人: Ganesh M Babulal
• 金额: $ 131.72万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10040061
• 关键词: Accelerometer; Activities of Daily Living; Age; Alzheimer' s Disease; Alzheimer’s disease biomarker; Amyloid; Area; Area Under Curve; Automobile Driving; Behavior; Biological; Biological Markers; Biostatistical Methods; Blood; Cerebrospinal Fluid; Cessation of life; Clinical; Clinical Trials; Cognition; Cognitive; Complex; Data; Data Collection; Dementia; Diagnostic; Disease Progression; Elderly; Enrollment; Environment; Evaluation; Frequencies; Future; Global Positioning System; Goals; Gold; Health; Home environment; Image; Impaired cognition; Individual; Infrastructure; Injury; Intervention; Knowledge; Length; Licensure; Liquid substance; Maps; Measures; Methodology; Methods; Monitor; Motor; Neuropsychological Tests; Neuropsychology; Participant; Performance; Persons; Population; Proxy; Public Health; Research; Risk; Sea; Sensory; Speed; Spinal Puncture; Symptoms; System; Testing; Time; Transportation; United States; Vehicle crash; Visual; Visuospatial; Weather; Work; age group; aged; aging brain; base; behavior measurement; blood-based biomarker; cognitive ability; cohort; comorbidity; cost; data standards; digital; driving behavior; executive function; fitness; functional disability; human old age (65+); imaging biomarker; improved; in vivo; instrumental activity of daily living; mobile application; molecular marker; multidisciplinary; neurobehavioral; neuroimaging marker; novel; older driver; pre-clinical; prevent; response; skills; tau Proteins; way finding

PROJECT SUMMARY/ABSTRACT Our long-term goal is to accurately identify who is at risk of driving decline, to establish whether driving behavior can be used as a functional, neurobehavioral biomarker of Alzheimer disease (AD), to forecast when driving decline will occur, to intervene before the time of decline, and to prevent a significant number of crashes, injuries, and death. Our findings indicate that the long preclinical stage of AD, as reflected in amyloid and tau imaging and cerebrospinal fluid (CSF) biomarkers among cognitively normal older adults, is associated with poorer driving performance on a road test, as well as with fewer trips made in a personal vehicle. This project will test the extent to which an in-vehicle datalogger, measuring everyday driving behavior continuously, reflects underlying neuropathological AD and is associated with prevalent and incident cognitive impairment. This research is significant because 36 million licensed drivers are aged 65 years or older, and the number of older adults in the United States is expected to double by 2050, when 1 in 4 drivers will be 65+. Our work suggests that changes in driving, an instrumental activity of daily living that involves both cognitive and functional abilities, may reflect neuropathological AD and precede the emergence of dementia symptoms. Our Specific Aims will (1) Use established cerebrospinal fluid (CSF) and imaging biomarkers to define preclinical AD and test the ability of the Driving Real-world In-Vehicle Evaluation System (DRIVES) to distinguish persons with and without preclinical AD among cognitively normal individuals, and assess the ability of this system to predict the future onset of dementia, (2) Test the ability of the DRIVES data to distinguish cognitively normal persons from those with dementia cross-sectionally, and to examine driving behavior over time for both groups, (3) Determine whether the DRIVES data, combined with cognitive, health, and functional data from older adults, can improve prediction of incident cognitive impairment and dementia. To test these Specific Aims, we have assembled a multidisciplinary team with expertise in AD, neuroimaging biomarkers (amyloid and tau), fluid biomarkers (CSF and blood), naturalistic driving, spatial navigation, cognitive and brain aging, and longitudinal biostatistical methods. We will capitalize on existing institutional infrastructure to longitudinally follow 300 cognitively normal older adults and 50 older adults with mild or very mild dementia, to create a cohort of 350 individuals. This cohort will be followed using a naturalistic driving methodology that will capture their driving behaviors on a daily basis. Their cognition will be tested annually using the Clinical Dementia Rating and various neuropsychological measures. Once obtained, this knowledge can be used to map driving as a neurobehavioral biomarker that may be monitored and used for clinical trials and interventions throughout disease progression of AD.

项目摘要/摘要 我们的长期目标是准确识别谁有驾驶衰退的风险，以确定驾驶是否 行为可以作为阿尔茨海默病(AD)的功能和神经行为生物标记物，以预测何时 推动下跌将会发生，在下跌之前进行干预，并防止大量的 撞车、受伤和死亡。我们的研究结果表明，AD的长期临床前阶段，反映在淀粉样蛋白上 在认知正常的老年人中，tau成像和脑脊液(CSF)生物标记物之间存在关联 路考成绩较差，私家车出行次数也较少。这 该项目将测试车载数据记录器连续测量日常驾驶行为的程度， 反映潜在的神经病理性阿尔茨海默病，并与普遍和偶发的认知损害有关。 这项研究意义重大，因为3600万持有执照的司机年龄在65岁或以上，而 预计到2050年，美国老年人的数量将翻一番，届时每四名司机中就有一人年龄在65岁以上。我们的 研究表明，驾驶的变化，一种日常生活中的工具性活动，涉及认知和 功能能力，可反映神经病理性AD，并先于痴呆症状的出现。 我们的具体目标将(1)使用已建立的脑脊液(CSF)和成像生物标记物来确定 临床前AD和测试驾驶真实世界车内评估系统(DRIVES)的能力 在认知正常的个体中区分有无临床前阿尔茨海默病的人，并评估其能力 本系统用于预测未来痴呆症的发病情况，(2)测试驱动器数据的区分能力 对认知正常的人和痴呆症患者进行横断面比较，并对驾驶行为进行检查 两组时间，(3)确定驱动器数据是否与认知、健康和功能相结合 来自老年人的数据可以改善对认知障碍和痴呆症的预测。 为了测试这些具体目标，我们组建了一个拥有AD专业知识的多学科团队， 神经成像生物标记物(淀粉样蛋白和tau)，流体生物标记物(脑脊液和血液)，自然驾驶，空间 导航、认知和脑老化，以及纵向生物统计学方法。我们将利用现有的 机构基础设施纵向跟踪300名认知正常的老年人和50名患有 轻度或非常轻微的痴呆症，以建立一个350人的队列。这一队列将使用自然主义者的 驾驶方法，将捕捉他们每天的驾驶行为。他们的认知能力将受到考验。 每年使用临床痴呆症评分和各种神经心理测量。 一旦获得这一知识，就可以将驾驶作为一种神经行为生物标记物进行定位 在阿尔茨海默病的整个疾病发展过程中监测和用于临床试验和干预。