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: 8766289
• 负责人: Jorge Sepulcre
• 金额: $ 15.66万
• 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/8766289
• 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; 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; Metric; 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; public health relevance; 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（由申请人提供）：K23候选人的目标是建立一个高质量的神经影像学独立研究计划，特别是改善分子成像的网络分析技术和研究神经退行性疾病。痴呆症，包括阿尔茨海默病（AD），是网络退行性疾病。例如，众所周知，AD病理学沿着神经元网络内的分布式脑系统传播。然而，目前还没有直接的体内方法来可视化患有痴呆症的个体中的大规模网络退化和传播。因此，迫切需要开发新的和全面的分析方法，准确地检测大脑病理网络（BPN）。 在这项提案中，我们的目标是开发图形理论工具来可视化和研究BPN在临床前-即，正常的老年人在AD的风险凭借先进的年龄-和临床AD受试者使用正电子发射断层扫描（PET）。特别地，我们将使用多元回归模型和来自两种关键AD病理性放射性配体的PET图像构建组水平的脑图：1）结合纤维状淀粉样蛋白-β（A）斑块的11 C-标记的匹兹堡化合物-B（11 C-PIB）;和2）结合TAU神经元缠结的F18-T807（Aim 1）。然后，我们将开发图论度量来估计组级A？和TAU BPN中的网络传播模式（目标2）。最后，我们将研究BPN的个体映射及其与AD个体风险、功能连接崩溃和神经心理学特征的关系（目的3）。我们相信这项研究可以大大提高我们对AD和痴呆症体内网络退化的检测和可视化能力。旨在表征BPN的神经成像方法-作为网络退化的代理-有望改善痴呆症的诊断和治疗反应的监测，这反过来可能会对美国医疗保健系统产生积极影响。此外，完成拟议的奖项将为候选人作为独立研究者的发展奠定基础，通过严格的分子PET成像培训补充候选人的先前技能。候选人将利用尖端的设施，以及在其合作机构的世界一流的教育机会。在K23得奖期间，候选人将得到基思A教授的宝贵支持和指导。约翰逊和托马斯布雷迪教授。相关性：该提案有可能通过提高PET早期诊断和监测痴呆症的能力来改善公共卫生。