Characterizing Alzheimer's Disease with INSPECDS: Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes

使用 INSPECDS 表征阿尔茨海默病：用于痴呆亚型内表型分类的综合神经认知和睡眠行为分析仪

• 批准号: 9345457
• 负责人: Chris Berka
• 金额: $ 53.85万
• 依托单位: ADVANCED BRAIN MONITORING, INC.
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-15 至 2019-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9345457
• 关键词: Accelerometer; Address; Adult; Algorithms; Alzheimer' s Disease; Architecture; Automatic Data Processing; Behavior; Behavior assessment; Biological Markers; Blinded; Brain; California; Cardiovascular Diseases; Cause of Death; Characteristics; Chin; Classification; Clinic; Clinical; Clinical Research; Clinical Trials; Data; Data Analyses; Databases; Dementia; Depressed mood; Devices; Diagnosis; Disease; Disease Progression; Drug Industry; Economic Burden; Elderly; Electrocardiogram; Electroencephalography; Electrophysiology (science); Enrollment; Etiology; Frontotemporal Dementia; Funding; General Hospitals; Goals; Head Movements; Home environment; Impaired cognition; Individual; Lewy Body Dementia; Machine Learning; Malignant Neoplasms; Massachusetts; Measures; Memory; Minor; Modification; Monitor; Neurocognitive; Neurodegenerative Disorders; Neurologic; Neuropsychological Tests; Obstructive Sleep Apnea; Parkinson Disease; Parkinson' s Dementia; Patients; Performance; Phase; Probability; Process; REM Sleep Behavior Disorder; Reporting; Research; Research Infrastructure; Research Personnel; Sampling; Secure; Sleep; Sleep Architecture; Sleep Deprivation; Small Business Innovation Research Grant; Stratification; Stroke; Study Subject; System; Technology; Technology Assessment; Testing; Time; Training; United States National Institutes of Health; Universities; Vascular Dementia; Wireless Technology; alertness; base; brain behavior; cloud based; cognitive function; cohort; computerized; data acquisition; diagnostic accuracy; genetic association; human subject; limb movement; mild cognitive impairment; neurocognitive test; relating to nervous system; synucleinopathy; tool

PROJECT SUMMARY AND ABSTRACT It is estimated that Alzheimer's and other neurodegenerative diseases causing dementia will surpass cancer as the leading cause of death by the year 2040. Alzheimer's is the leading cause of dementia, followed by synucleinopathies, including dementia with Lewy bodies (DLB) and Parkinson's disease with dementia (PDD), Fronto-temporal dementia and Vascular dementia. Among clinical researchers focused on investigating the varying etiologies, genetic associations, biomarkers, and treatment options for Alzheimer's disease, there is an urgent need for effective tools to aid in the classification of dementia subtypes, in the earliest detectable stages of the pathophysiological process. To address this unmet need Advanced Brain Monitoring (ABM) proposes to leverage day and night assessment technologies to create an Integrated Neurocognitive and Sleep-Behavior Profiler for the Endophenotypic Classification of Dementia Subtypes (INSPECDS) to profile Alzheimer's and other dementias. The core components of the INSPECDS platform will be the Alertness and Memory Profiler (AMP), the Sleep Profiler, and integrated machine-learning, classification algorithms, hosted on a secure, cloud-based, infrastructure for automated data processing, analysis, and reporting. The AMP was developed and validated intially for the purpose of detecting the neurocognitive effects of sleep deprivation in adults diagnosed with obstructive sleep apnea but has more recently been applied to assess Alzheimer's and Parkinson's disease. The AMP is unique among neurocognitive testing platforms in that it is the only one which integrates advanced, electrophysiological measures (e.g., 24-channel, wireless EEG and ECG) during the performance of computerized neurocognitive tasks and has proven effective in characterizing cognitive decline in Alzheimer's. This advanced capability permits researchers to explore real- time relations between fluctuations in alertness, discrete cognitive functions, and specific neural processes believed to subserve observed performance deficits in Alzheimer's and other dementias. The Sleep Profiler is an FDA-cleared, easily applied, wireless-EEG device that was developed and validated to measure sleep architecture for in-home sleep studies with submental (chin) EMG and wireless accelerometers to monitor head and limb movements to quantify the characteristics of REM-sleep behavior disorder (RBD), considered to be a prodromal expression of synucleinopathy. Furthermore, the application of sophisticated, machine- learning, classification algorithms will streamline the processing and analyses of these data to derive statistical probabilities of Alzheimer's and other dementia subtypes. The overarching goal of the current, Direct-to-Phase II, SBIR project is to finalize implementation of a secure, cloud-based infrastructure to compile the data obtained from the AMP and Sleep Profiler, train classification algorithms to discriminate among Alzheimer's and other dementia subtypes, validate diagnostic accuracy, and integrate optimized classifiers within the cloud- based architecture. Once completed, the INSPECDS system will be the first clinical research tool of its kind and find immediate application in both university-based research settings and pharmaceutical industry clinical trials to aid in the endophenotypic stratification of Alzheimer's and other dementias.

项目概要和摘要 据估计，阿尔茨海默病和其他导致痴呆的神经退行性疾病将超过 到 2040 年，癌症将成为导致死亡的主要原因。阿尔茨海默病是导致痴呆症的主要原因，其次是 突触核蛋白病，包括路易体痴呆 (DLB) 和帕金森病伴痴呆 (PDD)、额颞叶痴呆和血管性痴呆。临床研究人员重点关注 研究阿尔茨海默病的不同病因、遗传关联、生物标志物和治疗方案 疾病，迫切需要有效的工具来帮助对痴呆亚型进行分类， 病理生理过程的最早可检测阶段。为了解决这一未满足的需求 Advanced Brain 监测（ABM）建议利用昼夜评估技术来创建一个综合的 用于痴呆亚型内表型分类的神经认知和睡眠行为分析仪 (INSPECDS) 来分析阿尔茨海默病和其他痴呆症。 INSPECDS 平台的核心组件将 警觉性和记忆分析器 (AMP)、睡眠分析器以及集成的机器学习、分类 算法，托管在安全的、基于云的基础设施上，用于自动数据处理、分析和 报告。 AMP 的开发和验证最初是为了检测神经认知效应 被诊断患有阻塞性睡眠呼吸暂停的成年人睡眠不足的情况，但最近被应用于 评估阿尔茨海默病和帕金森病。 AMP 在神经认知测试平台中是独一无二的 它是唯一一款集成了先进的电生理测量（例如 24 通道、无线 脑电图和心电图）在计算机化神经认知任务的执行过程中被证明是有效的 阿尔茨海默病认知能力下降的特征。这种先进的功能使研究人员能够探索真实的 警觉性波动、离散认知功能和特定神经过程之间的时间关系 据信可以改善阿尔茨海默氏症和其他痴呆症中观察到的表现缺陷。睡眠分析仪是 一种经 FDA 批准、易于使用的无线脑电图设备，专为测量睡眠而开发和验证 使用颏下（下巴）肌电图和无线加速度计进行监测的家庭睡眠研究架构 头部和肢体运动来量化快速眼动睡眠行为障碍 (RBD) 的特征，被认为是 是突触核蛋白病的前驱表现。此外，应用先进的机器 学习、分类算法将简化这些数据的处理和分析，以得出统计数据 阿尔茨海默病和其他痴呆亚型的概率。当前直接阶段的总体目标 II、SBIR项目将最终实现一个安全的、基于云的基础设施来编译数据 从 AMP 和睡眠分析器获得的数据，训练分类算法来区分阿尔茨海默病 和其他痴呆症亚型，验证诊断准确性，并在云中集成优化的分类器 基于架构。一旦完成，INSPECDS 系统将成为同类中第一个临床研究工具 并在大学研究环境和制药行业临床中立即得到应用 帮助阿尔茨海默病和其他痴呆症的内表型分层的试验。