Genetic Profiles of the Spatiotemporal Causality of Tau and Amyloid in the Elderly Brain

项目摘要(摘要) 异常的tau和淀粉样蛋白β(Aβ)蛋白沿神经元回路的进展现象 对于了解阿尔茨海默病(AD)的病理基础至关重要。个体发育迟缓的风险 发作性阿尔茨海默病与导致异常和进行性痴呆易感性的生物学和遗传学特征有关 Tau和Aβ在大脑中的积累。多模式神经影像和遗传生物标记物的研究进展 为发现阿尔茨海默病的早期阶段和研究其网络性质和遗传学提供了新的前景 支撑点。然而，这一领域的一个主要研究挑战是整合和执行 神经影像和遗传数据的综合联合分析。因此，迫切需要新的战略。 检测Tau相关和Aβ相关蓄积的传播途径和遗传机制 人脑。对进展和发展的个体神经成像特征的详细描述的组合 遗传脆弱性风险将提高AD轨迹的可检测性。这一建议旨在解决 这些新出现的挑战集中在识别tau和Aβ沉积的体内扩散途径上 以及他们在哈佛老龄化大脑老年参与者纵向样本中的遗传脆弱性 研究(哈布斯)。在目标1中，我们将开发定制的图论指标来检测病理进展 横截面和纵向PET图像中的网络级别。在AIM2中，我们将专注于构建个性化 使用PET成像基于病理进展和扩散模式的分期框架，我们将 将分期估计与临床和神经心理学特征相关联。在目标3中，我们将描述 在艾伦人脑图谱的帮助下，与赤潮有关的遗传大脑转录组 神经影像传播特征。在此提案结束时，我们将能够发现和识别早期和 体内分子成像和遗传特征使老年人对阿尔茨海默病易感性。

Project Summary (Abstract) The progression phenomenon of abnormal tau and amyloid-β (Aβ) proteins along neuronal circuits is critical to understand the foundations of Alzheimer's disease (AD) pathology. The individual risk to develop late onset AD relates to the biological and genetic profiles that confer susceptibility for abnormal and progressive accumulation of tau and Aβ in the brain. Recent advances in multi-modal neuroimaging and genetic biomarkers provide new prospects to detect very early stages of AD and to study its network nature and genetic underpinnings. However, a major research challenge in this field has been to integrate and perform comprehensive joint analysis of neuroimaging and genetic data. Thus, there is a critical need for new strategies to detect the spreading pathways and genetic mechanisms of tau-related and Aβ-related accumulation in the human brain. The combination of detailed descriptions of individual neuroimaging profiles of progression and genetic vulnerability risk will offer enhanced detectability of AD trajectories. This proposal purposes to solve these emerging challenges by focusing on identification of in vivo spreading pathways of tau and Aβ deposits and their genetic vulnerabilities in a longitudinal sample of elderly participants from the Harvard Aging Brain Study (HABS). In Aim 1, we will develop customized graph theory metrics to detect progression of pathology at the network level in cross-sectional and longitudinal PET images. In Aim2, we will focus on building individualized staging frameworks based on progression and spreading patterns of pathology using PET imaging, and we will correlate staging estimates with clinical and neuropsychological profiles. In Aim 3, we will characterize the genetic brain transcriptome –assisted by the Allen Human Brain Atlas- that are associated to the HABS neuroimaging spreading profiles. At the end of this proposal, we will be able to detect and identify the early and in vivo molecular imaging and genetic features that confer AD susceptibility in elderly individuals.