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确定谁有驱动下降的风险，确定是否开车 行为可以用作阿尔茨海默氏病（AD）的功能性的神经行为生物标志物，以预测 驱动下降将发生，在下降之前进行干预，并防止大量 坠机，伤害和死亡。我们的发现表明，淀粉样蛋白反映的AD的长临床前阶段 在认知正常的老年人中，tau成像和脑脊液（CSF）生物标志物是相关的 在公路测试中驾驶性能较差，并且在个人车辆中进行的旅行较少。这 项目将测试车载数据核格的程度，持续测量日常驾驶行为， 反映了潜在的神经病理学AD，并且与普遍和事件的认知障碍有关。 这项研究很重要，因为3600万许可的驾驶员年龄在65岁以上，以及 预计到2050年，美国的老年人人数预计将翻一番，而四分之一的驾驶员将为65岁以上。我们的 工作表明，驾驶的变化是一种涉及认知和的日常生活的工具活动 功能能力可以反映神经病理AD，并在痴呆症状的出现之前。 我们的具体目的（1）使用已建立的脑脊液（CSF）和成像生物标志物来定义 临床前广告并测试驾驶现实世界中评估系统（驱动器）的能力 在认知正常人中区分有或没有临床前广告的人，并评估能力 该系统以预测痴呆症的未来发作，（2）测试驱动数据区分数据的能力 从痴呆截面上的认知正常人的认知正常人，并检查驾驶行为 两组的时间，（3）确定驱动数据是否与认知，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。 为了测试这些特定目标，我们组建了一个具有广告专业知识的多学科团队， 神经影像学生物标志物（淀粉样蛋白和TAU），流体生物标志物（CSF和血液），自然主义驾驶，空间 导航，认知和大脑衰老以及纵向生物统计学方法。我们将利用现有 机构基础设施至纵向遵循300名认知正常的老年人和50名老年人 轻度或非常轻度的痴呆症，创建350名人群。这种队列将使用自然主义 驾驶方法将每天捕获其驾驶行为。他们的认知将被测试 每年使用临床痴呆评级和各种神经心理学措施。 一旦获得，这些知识可用于将驱动映射为可能是神经行为的生物标志物 在AD的疾病进展中，监测并用于临床试验和干预措施。