Preclinical Alzheimer Disease and Driving

临床前阿尔茨海默病与驾驶

• 批准号: 10224075
• 负责人: Ganesh M Babulal
• 金额: $ 106.99万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10224075
• 关键词: Admission activity; Age; Age-Years; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer’s disease biomarker; Amyloid; Amyloid beta-42; Automobile Driving; Behavior; Behavioral; Biological Markers; Biostatistical Methods; Brain Pathology; Cerebrospinal Fluid; Cessation of life; Clinical; Cognitive; Communities; Data; Dementia; Destinations; Deterioration; Diagnosis; Disease; Disease Progression; Elderly; Enrollment; Environment; Evaluation; Event; Goals; Gold; Health; Image; Individual; Infrastructure; Injury; Institutes; Intervention Trial; Knowledge; Link; Long-Term Care; Longitudinal Studies; Measures; Mental Depression; Methodology; Outcome; Outcomes Research; Participant; Performance; Persons; Positioning Attribute; Predictive Value; Proxy; Research; Risk; Safety; Spinal Puncture; Standardization; Surveys; System; Testing; Time; Travel; United States; Vehicle crash; Vision; Visit; Work; aged; aging brain; amyloid imaging; cohort; data acquisition; driving behavior; driving safety; driving skills; imaging biomarker; innovation; interest; member; mild cognitive impairment; mortality; multidisciplinary; neuroimaging marker; novel; older driver; pre-clinical; predictive modeling; repository; research study; secondary analysis; tau Proteins; time use

PROJECT SUMMARY/ABSTRACT The goal of this research is to characterize the long-term impact of Alzheimer disease (AD) brain pathology on driving behavior and driving cessation among persons with and without preclinical AD. Our findings indicate that the long preclinical stage of AD, as reflected in amyloid imaging and cerebrospinal fluid (CSF) biomarkers among cognitively normal persons, is associated with poorer driving performance on a standardized road test. 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 years or older. Motor vehicle crashes are a leading cause of injury and death in older adults. The ability to identify who will be at most risk of driving decline and to predict when decline will occur will inform early driving safety intervention trials for older adults. Preclinical AD is an important stage during which to plan and implement safety measures in anticipation of changes in driving skills with disease progression. Our Specific Aims will determine how levels of both novel and well-established AD biomarkers and other age- and disease-associated factors are related to driving performance across the course of preclinical AD: (1) To maintain and grow our unique cohort of older adult drivers with and without preclinical AD. (2) To test whether preclinical AD predicts cross-sectional differences and longitudinal changes in naturalistic driving. (3) To identify driving, biomarker, clinical, physical, and behavioral predictors of driving cessation, and to develop predictive models using these variables. To test these Specific Aims, we have assembled a multidisciplinary team with expertise in AD, neuroimaging biomarkers, CSF biomarkers, driving generally, naturalistic driving specifically, cognitive and brain aging, and longitudinal biostatistical methods. We will capitalize on existing infrastructure to follow our current cohort of 180 cognitively normal participants with and without preclinical AD, and add additional participants to create a cohort of 300 individuals. This larger cohort will continue to undergo an annual driving test, as well as utilize a naturalistic driving methodology that will capture their driving behaviors on an everyday basis. The long-term impact of AD brain pathology will be defined in several ways to help understand its impact on driving performance, behavior, and cessation. Additionally, we will create predictive models of driving cessation. Once obtained, this knowledge can be used to create stage-appropriate, personalized, driving-related safety strategies that can be implemented upon diagnosis, and adjusted throughout disease progression.

项目总结/摘要 这项研究的目的是描述阿尔茨海默病（AD）大脑的长期影响。 在有和没有临床前AD的人中驾驶行为和驾驶停止的病理学。我们 研究结果表明，AD的长期临床前阶段，如淀粉样蛋白成像和脑脊液中所反映的， (CSF)在认知正常的人中，生物标志物与驾驶性能较差有关。 标准化道路测试。 这项研究意义重大，因为3600万持牌司机年龄在65岁或以上， 到2050年，美国老年人的数量预计将翻一番，届时每4名驾驶员中就有1名65岁 或者更老机动车碰撞是老年人受伤和死亡的主要原因。识别能力 谁最有可能出现驾驶能力下降，并预测何时会出现驾驶能力下降， 老年人的干预试验。临床前AD是计划和实施的重要阶段 预计随着疾病进展驾驶技能发生变化的安全措施。 我们的具体目标将确定新的和成熟的AD生物标志物和 其他年龄和疾病相关因素与临床前治疗过程中的驾驶性能有关。 AD：（1）维持和发展我们独特的老年驾驶员队列，无论是否患有临床前AD。(2)到 测试临床前AD是否预测自然驾驶的横截面差异和纵向变化。 (3)识别驾驶、生物标志物、临床、身体和行为预测因素，并 使用这些变量建立预测模型。 为了测试这些特定目标，我们组建了一个具有AD专业知识的多学科团队， 神经成像生物标志物，CSF生物标志物，一般驾驶，具体自然驾驶，认知和 脑老化和纵向生物统计方法。我们将利用现有的基础设施， 目前有180名认知正常的参与者，有和没有临床前AD，并增加额外的 参与者创建一个300人的队列。这一更大的群体将继续经历每年一次的驾驶 测试，以及利用自然主义的驾驶方法，将捕捉他们的驾驶行为的日常 基础AD脑病理学的长期影响将通过几种方式来定义，以帮助理解其影响 驾驶表现、行为和停止。此外，我们将创建驾驶的预测模型， 停止 一旦获得，这些知识可以用于创建适合舞台的，个性化的，驾驶相关的 可以在诊断时实施的安全策略，并在整个疾病进展过程中进行调整。