Motor Profiles as Novel Biomarker for Alzheimer’s Disease

项目总结/摘要 已建立的阿尔茨海默病（AD）生物标志物，如用PET测量的淀粉样β蛋白，价格昂贵 和侵略性。具有成本效益、快速且易于管理的运动措施，如握力和步行 速度，已经显示出在AD的认知症状之前几年。相对于单一措施， 结合动态和力量测量可以提高AD的预测价值。这表明一个复合物 运动轮廓评分，衡量功能跨越运动域的广度将有最佳的预测 动力.已知早期退化的认知和运动脑区域（例如，海马和 穹窿）和后来的AD疾病过程（例如，小脑、（前）运动皮质和皮质脊髓束） 预测轻度认知障碍（MCI）和AD中运动功能障碍的候选者。的目标 这个K 01建议是双重的：1）通过一系列指导，进一步发展申请人的研究技能 活动，和2）确定MCI和AD的行为和神经运动概况，目的是开发 一个强大而有效的风险评分算法。我们的中心假设是运动行为综合评分 和神经运动轮廓评分区分MCI和AD个体与健康对照受试者， 与已建立的AD生物标志物（淀粉样蛋白负荷、海马体积和APOE e4状态）相关。项目 有三个具体目标：1）量化MCI和AD中的行为和神经运动功能障碍; 2）识别 行为和神经运动综合评分作为新的AD生物标志物;和3）复制运动综合评分 评分作为AD生物标志物在一个大的独立样本从越南时代双胞胎研究老化。 培训计划的目的是在对候选人进行培训至关重要的领域建立专门知识， 建议的研究，并成为在AD领域的独立调查员。以下培训目标 在与指导团队的密切合作下，已经确定了：a）建立临床观点， 在MCI和AD中实施有效研究所需的概念框架; B）发展以下方面的专业知识 与预测建模相关的机器学习; c）深入了解神经运动 症状和功能的MCI和AD;和d）发展AD生物标志物及其在AD中的感知作用的专业知识 病因学培训将由AD的临床专家（Duff博士）和AD领域的领导者密切监督。 衰老中的神经运动功能障碍（Rosano博士），AD生物标志物（Foster博士），MCI风险因素（Kremen博士），以及 机器学习（Tasdizen博士）。候选人的最佳制度环境进一步确保了成功 为R 01应用于预测MCI至AD提供数据的培训和研究计划 从运动概况综合评分的转变。这项研究做出了重大贡献。 致力于开发新的具有成本效益的AD生物标志物，这些生物标志物可以丰富临床试验， 诊断目的，与NIA的使命一致。

PROJECT SUMMARY / ABSTRACT Established biomarkers for Alzheimer's disease (AD), such as amyloid beta measured with PET, are expensive and invasive. Cost-efficient, quick, and easy-to-administer motor measures, such as grip strength and walking speed, have shown to precede the cognitive symptoms of AD by several years. Relative to single measures, combining ambulatory and strength measures boosts predictive value for AD. This suggests that a composite motor profile score that weighs functions spanning the breadth of motor domains will have optimal predictive power. Cognitive and motor brain regions that are known to degenerate early (e.g., the hippocampus and fornix) and later in the AD disease process (e.g., the cerebellum, (pre)motor cortex, and corticospinal tract) are candidates for the prediction of motor dysfunction in mild cognitive impairment (MCI) and AD. The objective of this K01 proposal is two-fold: 1) to further develop the research skills of the applicant with a series of mentored activities, and 2) to identify the behavioral and neural motor profiles of MCI and AD with the aim of developing a robust and valid risk scoring algorithm. Our central hypothesis is that a motor behavioral composite score and neural motor profile score distinguish individuals with MCI and AD from healthy control subjects, and are related to established AD biomarkers (amyloid burden, hippocampal volume, and APOE e4 status). The project has three specific aims: 1) Quantify behavioral and neural motor dysfunction in MCI and AD; 2) Identify behavioral and neural motor composite scores as novel AD biomarkers; and 3) Replicate a motor composite score as AD biomarker in a large independent sample from the Vietnam Era Twin Study of Aging. The training plan aims to establish expertise in areas that are crucial for the candidate to conduct the proposed research and to become an independent investigator in the field of AD. The following training goals have been identified in close collaboration with the mentoring team: a) establishing a clinical perspective and the conceptual framework required to implement effective research in MCI and AD; b) develop expertise in machine learning relevant to prediction modeling; c) gaining an in-depth understanding of neurological motor signs and function in MCI and AD; and d) develop expertise on AD biomarkers and their perceived role in AD etiology. The training will be closely supervised by clinical experts of AD (Dr. Duff), and leaders in the field of neural motor dysfunction in aging (Dr. Rosano), AD biomarkers (Dr. Foster), MCI risk factors (Dr. Kremen), and machine learning (Dr. Tasdizen). The candidate's optimal institutional environment further ensures the success of the training and research plan that will provide data for an R01 application on the prediction of MCI to AD transition from a motor profile composite score. The proposed research makes a significant contribution towards the development of novel cost-efficient AD biomarkers that can serve to enrich clinical trials and for diagnostic purposes, consistent with the mission of the NIA.