In Vivo Visualization of TAU and Amyloid-Beta Networks for Early AD Detection

用于早期 AD 检测的 TAU 和淀粉样蛋白网络的体内可视化

• 批准号: 8898795
• 负责人: Jorge Sepulcre
• 金额: $ 15.44万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8898795
• 关键词: Affinity; Aging; Alzheimer disease detection; Alzheimer' s Disease; Alzheimer' s disease risk; Amyloid beta-Protein; Appearance; Area; Award; Binding; Brain; Brain Mapping; Brain region; Clinical; Complement; Complex; Data; Data Set; Degenerative Disorder; Dementia; Deposition; Detection; Development; Diagnosis; Diffusion; Disease; Early Diagnosis; Elderly; Evolution; Exhibits; Foundations; Funding; Goals; Graph; Health; Healthcare Systems; Histopathology; Image; Image Analysis; Imagery; Imaging Techniques; Individual; Institution; Investigation; Label; Learning; Magnetic Resonance; Magnetic Resonance Imaging; Maps; Mentored Patient-Oriented Research Career Development Award; Mentorship; Methods; Modeling; Molecular; Monitor; Nerve Degeneration; Network-based; Neurodegenerative Disorders; Neurofibrillary Tangles; Neurons; Pathology; Pathway interactions; Pattern; Pittsburgh Compound-B; Positron-Emission Tomography; Proxy; Public Health; Research; Research Personnel; Research Project Grants; Rest; Seeds; Signal Transduction; System; Techniques; Therapeutic; Time; Tracer; Training; United States National Institutes of Health; aging brain; analytical method; analytical tool; base; blood oxygen level dependent; clinically relevant; cost effective; design; detector; imaging modality; improved; in vivo; molecular imaging; neuroimaging; neuropsychological; novel; pre-clinical; programs; radioligand; response; skills; spatiotemporal; theories; tool

DESCRIPTION (provided by applicant): The goal of the K23 candidate is to establish a high-quality independent research program on neuroimaging, particularly on improving network analytical techniques of molecular imaging and to study neurodegenerative disorders. Dementias, including Alzheimer's disease (AD), are network degenerative disorders. For instance, it is well known that AD pathology spreads along distributed brain systems within neuronal networks. However, at present there is no direct in vivo method to visualize large-scale network degeneration and propagation in individuals suffering from dementia. Hence there is a critical need for developing novel and comprehensive analytical methods that accurately detect brain pathological networks (BPNs). In this proposal, we aim to develop graph theoretical tools to visualize and study BPNs in preclinical - that is, normal older individuals at risk for AD by virtue of advanced age- and clinical AD subjects using positron emission tomography (PET). Particularly, we will construct group-level brain graphs using multi- regression models and PET images from two key AD pathological radioligands: 1) 11C-labeled Pittsburgh Compound-B (11C-PIB) that binds fibrillar amyloid-beta (A�) plaques; and 2) F18-T807 that binds TAU neurofibrillary tangles (Aim 1). Then, we will develop graph theory metrics to estimate network propagation patterns in group-level A� and TAU BPNs (Aim 2). Finally, we will investigate individual mapping of BPNs and its relationship with individual risk for AD, functional connectivity breakdown, and neuropsychological profiles (Aim 3). We believe this research can dramatically improve our detection and visualization capabilities of in vivo network degeneration in AD and dementia. Neuroimaging methods designed to characterize BPNs -as a proxy of network degeneration- promise to improve diagnosis and monitoring of therapeutic response in dementia, which might in turn positively impact the U.S. health care system burdened by these devastating disorders. Moreover, completion of the proposed award will provide the foundation for the candidate's development as an independent investigator, complementing the candidate's prior skills with rigorous training in molecular PET imaging. The candidate will take advantage of the cutting-edge facilities, as well as the world- class educational opportunities at its collaborating institutions. During the K23 award, the candidate will have the valuable support and mentorship of Prof. Keith A. Johnson and Prof. Thomas Brady. Relevance: This proposal has the potential to improve public health through advancement of the PET capabilities to early diagnose and monitor dementia.

描述（由适用提供）：K23候选者的目标是建立有关神经影像学高质量的独立研究计划，尤其是在改善分子成像的网络分析技术和研究神经退行性疾病方面。包括阿尔茨海默氏病（AD）在内的痴呆症是网络退行性疾病。例如，众所周知，AD病理沿着神经元网络中的分布式大脑系统扩散。但是，目前尚无直接的体内方法来可视化患有痴呆症患者的大规模网络变性和传播。因此，需要准确检测到脑病理网络（BPN）的新型和全面的分析方法的迫切需要。在此提案中，我们旨在开发图理论工具来可视化和研究临床前的BPN，也就是说，使用极性发射断层扫描（PET）的高级年龄和临床AD受试者，正常的老年人有可能出现AD的风险。特别是，我们将使用来自两个关键的AD病理放射性配体的多回归模型和PET图像构建组级脑图：1）11C标记的匹兹堡化合物B（11C-PIB）结合了纤维状淀粉样蛋白β（a）斑块; 2）结合Tau神经原纤维缠结的F18-T807（AIM 1）。然后，我们将开发图理论指标，以估计组级A和Tau BPN中的网络传播模式（AIM 2）。最后，我们将研究BPN的单个映射及其与AD的个人风险，功能连通性崩溃和神经心理学概况的关系（AIM 3）。我们认为，这项研究可以大大提高AD和痴呆症体内网络变性的检测和可视化功能。旨在表征BPN的神经影像学方法 - 作为网络变性的代理 - 有望改善痴呆症中治疗反应的诊断和监测，这反过来又可能对这些毁灭性疾病燃烧的美国医疗保健系统产生积极影响。此外，拟议奖项的完成将为候选人作为独立研究者的发展提供基础，并通过在分子宠物成像中进行严格的培训来完成候选人的先前技能。候选人将利用其合作机构的尖端设施以及世界一流的教育机会。在K23奖上，候选人将获得基思·A·约翰逊教授和托马斯·布雷迪教授的宝贵支持和心态。相关性：该提案有可能通过提高宠物能力来提高早期诊断和监测痴呆症的能力来改善公共卫生。