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

描述(申请人提供)：K23候选人的目标是建立一个高质量的神经成像独立研究计划，特别是在改进分子成像的网络分析技术和研究神经退行性疾病方面。痴呆症，包括阿尔茨海默病(AD)，是一种网络退行性疾病。例如，众所周知，阿尔茨海默病的病理沿着神经元网络内的分布式大脑系统传播。然而，目前还没有直接的活体方法来可视化痴呆患者个体中大规模的网络退化和传播。因此，迫切需要开发新的、全面的分析方法来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论工具来可视化和研究临床前-即由于年龄较高而有AD风险的正常老年人-和临床AD受试者的BPN，使用正电子发射断层扫描(PET)。特别是，我们将使用多元回归模型和来自两个关键AD病理放射配基的PET图像来构建组水平的脑图：1)11C标记的匹兹堡化合物-B(11C-PIB)，它结合纤维淀粉样β蛋白(A？)斑块；以及2)F18-T807，它结合TAU神经纤维缠结(目标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、功能连接障碍和神经心理学特征的关系(目标3)。我们相信，这项研究可以极大地提高我们对AD和痴呆患者体内网络变性的检测和可视化能力。旨在表征BPN的神经成像方法--作为网络退化的代用品--有望改善痴呆症的诊断和治疗反应监测，这反过来可能会对背负这些毁灭性疾病负担的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发展成为一名独立的研究员奠定基础，通过在分子PET成像方面的严格培训来补充候选人之前的技能。候选人将利用其合作机构的尖端设施和世界级的教育机会。在K23奖项期间，候选人将得到Keith A.Johnson教授和Thomas Brady教授的宝贵支持和指导。相关性：这项建议有可能通过提高PET早期诊断和监测痴呆症的能力来改善公众健康。

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.