Long-Term Tracking of Cerebral Microvascular Structural and Functional Alterations between Normal and Alzheimer's Aging

长期跟踪正常衰老和阿尔茨海默病衰老之间的脑微血管结构和功能变化

• 批准号: 10613561
• 负责人: Jonghwan Lee
• 金额: $ 36.67万
• 依托单位: BROWN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-30 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10613561
• 关键词: Address; Affect; Age; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Amyloid; Animal Husbandry; Behavioral; Biological Markers; Biological Models; Biomedical Engineering; Blood Vessels; Blood capillaries; Blood flow; Caregiver Burden; Cause of Death; Cerebrum; Clinical Research; Computer Models; Consensus; Data; Defect; Dementia; Development; Diagnosis; Dietary Intervention; Disease; Early Diagnosis; Early treatment; Economic Burden; Epidemic; Etiology; Failure; Functional disorder; Hyperemia; Image; Imaging technology; Impaired cognition; Individual; Knowledge; Laboratory Animals; Longevity; Measures; Medical History; Microcirculation; Modeling; Mus; Nerve Degeneration; Neurodegenerative Disorders; Neurons; Neurosciences; Optical Coherence Tomography; Oxygen; Pathogenesis; Pathology; Persons; Pharmaceutical Preparations; Play; Population; Process; Property; Public Health; Research Project Grants; Resolution; Risk Factors; Role; Senile Plaques; Structure; System; Techniques; Technology; Testing; Thinness; Three-Dimensional Image; Time; United States; abeta accumulation; age related; cerebral microvasculature; clinically relevant; comorbidity; computer framework; cost; exercise intervention; gene therapy; human old age (65+); hypoperfusion; image processing; improved; in vivo; in vivo imaging; insight; interest; mouse model; neuron loss; neurovascular coupling; new technology; normal aging; pharmacologic; psychologic; response; simulation; social; therapeutic target; tool; vascular factor

SUMMARY Alzheimer’s disease (AD), a progressive neurodegenerative disorder affecting millions of people worldwide, is currently incurable. As the population ages, AD and related dementia are becoming the biggest epidemic in medical history: the number of people aged 65 and older with AD is projected to increase between two- and three-fold by 2050. As shown by imaging and biomarker studies, age is a major risk factor for developing dementia, and the pathophysiological processes of AD begin more than a decade before the diagnosis of dementia. However, AD is a heterogeneous and multifactorial disease; thus, it is challenging to fully understand how the multiple etiologies and age-related prodromal processes contribute to its pathophysiology. Among other factors, deficits in cerebral microvascular structures and functions may play a key role in the onset and development of AD. Despite its importance for early diagnosis and as a therapeutic target, it is still unclear whether they are a causal factor for AD pathogenesis or an early consequence of multifactorial conditions that lead to AD at a later stage. Especially, two critical knowledge gaps exist: (1) Temporal relationships between vascular and other key factors during the onset and development of AD are not clear; (2) Little has been studied about how individual defects in various microvascular structural and functional properties distinctly correlate with and/or contribute to neuronal degeneration. Here, we will develop, optimize, and integrate experimental and computational technologies for the lifespan tracking and analysis of progressive microvascular alterations in AD versus normal aging in model mice. First, we will optimize our optical coherence tomography imaging and 3D image processing techniques to track the time-course of 32 vascular and non-vascular measures longitudinally over the mouse’s lifespan, including microvascular structure, microcirculation, functional reactivity, Aβ plaque accumulation, neuronal loss, and cognitive decline (Aim 1). These unprecedentedly comprehensive temporal dynamics data and advanced statistical/correlation analyses will enable us to determine whether the microvascular deficits precede neuronal loss or Aβ accumulation, and how those alterations are correlated, directly addressing the first knowledge gap. In Aim 2, we will improve our computational model of microvascular flow and functional hyperemia, and then combine the model with the experimental data of Aim 1 to investigate complicated cause- effect relationships. Our computational model will enable us to essentially “turn on” and “turn off” each microvascular deficit (e.g., thinner vessels, tortuous capillaries, hypoperfusion, capillary stalling) and test its effect on oxygen delivery to neurons, which is difficult and sometimes impossible to achieve experimentally. This combined approach will provide a powerful and unique strategy for testing the role of vascular deficits in neuronal degeneration, directly addressing the second knowledge gap, and informing future research for diagnosis and therapeutic target development.

概括 阿尔茨海默病 (AD) 是一种影响数百万人的进行性神经退行性疾病 在世界范围内，随着人口老龄化，AD 和相关痴呆症正在成为最严重的疾病。 医学史上的流行病：预计 65 岁及以上患有 AD 的人数将在 到 2050 年，这一数字将增加两倍和三倍。影像学和生物标志物研究表明，年龄是一个主要风险因素 发展为痴呆，AD 的病理生理过程早在 10 多年前就开始了。 然而，AD 是一种异质性、多因素的疾病，因此，诊断痴呆症具有挑战性。 充分了解多种病因和与年龄相关的前驱过程如何导致其 除其他因素外，脑微血管结构和功能的缺陷可能起到一定的作用。 尽管它对于早期诊断和治疗很重要，但它在 AD 的发生和发展中发挥着关键作用。 目标，目前尚不清楚它们是 AD 发病机制的因果因素还是 AD 的早期后果 特别是，存在两个关键的知识差距：(1) AD 发生和发展过程中血管与其他关键因素之间的时间关系是 (2)关于各种微血管结构和个体缺陷如何发生的研究很少； 功能特性与神经变性明显相关和/或促成神经变性。 在这里，我们将开发、优化和集成实验和计算技术 AD 模型中与正常衰老相比进行性微血管改变的寿命跟踪和分析 首先，我们将优化我们的光学相干断层扫描成像和 3D 图像处理技术。 纵向跟踪小鼠一生中 32 项血管和非血管测量的时间进程， 包括微血管结构、微循环、功能反应性、Aβ斑块积累、神经元 损失和认知能力下降（目标 1）。 先进的统计/相关分析将使我们能够确定微血管缺陷是否 先于神经损失或 Aβ 积累，以及这些改变如何相关，直接解决 第一个知识差距在目标 2 中，我们将改进微血管流动和功能的计算模型。 充血，然后将模型与目标1的实验数据结合起来，调查复杂的原因- 我们的计算模型将使我们能够从本质上“打开”和“关闭”每个效果关系。 微血管缺陷（例如，血管变细、毛细血管曲折、灌注不足、毛细血管停滞）并测试其 对神经元氧气输送的影响，这很难甚至有时不可能通过实验实现。 这种组合方法将为测试血管缺陷的作用提供强大而独特的策略。 神经退化，直接解决第二个知识差距，并为未来的研究提供信息 诊断和治疗目标的制定。