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（通过应用程序证明）：K23候选者的目标是在改善分子成像的网络分析技术方面建立高质量的独立计划。疾病。 。来自两个关键的AD病理放射线：1）11C标记的匹兹堡化合物B（11C-PIB）结合了纤维化淀粉样蛋白β（AN）斑块的F18-T807； ，我们将开发图理论，以估计组级A.D A.D Tau BPN中的网络传播模式（AIM 2）。我们认为，这项研究可以急剧提高我们对AD和痴呆症的体内网络变性的检测能力。这些毁灭性的疾病。 - 合作学院的教育机会。