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: 10450133
• 负责人: Ganesh M Babulal
• 金额: $ 128万
• 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/10450133
• 关键词: Accelerometer; Activities of Daily Living; Age; Alzheimer' s Disease; Alzheimer' s disease test; 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; 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.

项目概要/摘要 我们的长期目标是准确识别谁有驾驶能力下降的风险，以确定驾驶是否 行为可用作阿尔茨海默病 (AD) 的功能性神经行为生物标志物，以预测何时发生 驾驶衰退将会发生，在衰退发生之前进行干预，并防止大量的 碰撞、受伤和死亡。我们的研究结果表明，AD 的长期临床前阶段，如淀粉样蛋白所反映的 认知正常老年人中的 tau 成像和脑脊液 (CSF) 生物标志物相关 路试驾驶表现较差，私家车出行次数也较少。这 该项目将测试车载数据记录仪连续测量日常驾驶行为的程度， 反映了潜在的神经病理性 AD，并与普遍的和偶发的认知障碍有关。 这项研究意义重大，因为 3600 万持有执照的驾驶员年龄在 65 岁或以上，而且 到 2050 年，美国老年人数量预计将增加一倍，届时四分之一的驾驶员年龄将达到 65 岁以上。我们的 研究表明，驾驶是一种涉及认知和认知的日常生活工具性活动。 功能能力，可能反映神经病理学 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) 和成像生物标志物来定义 临床前 AD 并测试驾驶真实世界车载评估系统 (DRIVES) 的能力 将患有和未患有临床前 AD 的人与认知正常的个体区分开，并评估能力 该系统预测痴呆症未来发病情况，（2）测试DRIVES数据区分的能力 将认知正常的人与痴呆症患者进行横断面比较，并检查驾驶行为 (3) 确定 DRIVES 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提高对认知障碍和痴呆症事件的预测。 为了测试这些具体目标，我们组建了一支具有 AD 专业知识的多学科团队， 神经影像生物标志物（淀粉样蛋白和 tau 蛋白）、液体生物标志物（脑脊液和血液）、自然驾驶、空间 导航、认知和大脑老化以及纵向生物统计方法。我们将利用现有 机构基础设施纵向跟踪 300 名认知正常的老年人和 50 名患有认知障碍的老年人 轻度或极轻度痴呆症，创建一个由 350 人组成的队列。该队列将使用自然主义方法进行跟踪 驾驶方法将捕捉他们的日常驾驶行为。他们的认知将受到考验 每年使用临床痴呆评级和各种神经心理学测量。 一旦获得，这些知识可用于将驾驶映射为神经行为生物标志物，该标志物可能 在 AD 疾病进展的整个过程中进行监测和用于临床试验和干预。