Multi-omic Brain Cell Atlas of Alzheimer's Disease Progression

项目摘要/摘要 阿尔茨海默病(AD)是老年人中最常见的痴呆症，影响着500多万人 美国人，以及他们的家人和照顾者。不幸的是，全球人口老龄化只是 使AD“流行病”恶化，因为预计到2050年发病率将增加两倍。尽管进行了密集的研究，但仍有 目前还没有治愈这种毁灭性的神经退行性疾病的方法。因此，理解内在的分子 推动AD病理和进展的机制对于设计有效的治疗方法至关重要。尸检 对人类大脑的检查发现，与AD相关的神经病理，如神经原纤维缠结 (NFTS)和神经退行性变，通常以保守的时空模式发生，影响经鼻 首先是区域，然后延伸到边缘和等皮质区域。细胞的分子和神经化学基础 长期以来，人们一直在追求这种选择性神经元脆弱性(SNV)，因为它们是疾病进展和 可能掌握着理解神经变性的分子基础的关键，但到目前为止 机制仍然难以捉摸。在这里，尖端的单细胞技术将被用来产生 阿尔茨海默病易感脑区不同阶段细胞类型的综合多组学图谱 疾病。假设受AD病理影响最大的特定细胞类型是易感的 大脑区域由不同的分子通路(转录因子、信号级联、基因 网络)，推动SNV。此外，这些路径是以连续的时空模式执行的 通过染色质结构和基因调控元件的变化。追踪显示的分子变化 通过这些AD病理连续体中的神经细胞群将更好地定义AD的发病和进展， 并可能显示出新的治疗靶点。尸检脑组织样本将从健康的 对照组，或死亡时表现出不同阶段AD病理的患者，即早期(Braak III/IV)或晚期 (布拉克V/VI)。将对AD进展不同阶段发生的变化进行分析，以确定细胞类型 以及对AD相关病理的启动和传播最为关键的分子途径。分析的地区将 包括海马区(CA1/SUB)、下颞叶皮质(BA20)、额叶皮质(BA9)和视皮层(AD- 抗性区域)。在目标1中，将对来自对照对象的样本进行单细胞分析以表征 甲基组和染色质结构联合(sn-m3c-seq)，以及染色质的可及性 转录组(配对序列)，在阿尔茨海默病易患脑区的细胞类型。这些数据集的集成将 创建相关细胞类型的多基因组图谱，作为了解AD发病和治疗的基础 进步。在目标2中，这些分析将扩展到AD患者。比较不同大脑区域的数据集 疾病分期将揭示AD中受影响最大的特定细胞类型以及分子途径 (基于甲基化模式、染色质结构等的变化)在AD(Aim3)中驱动SNV。

PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is the most common form of dementia in the elderly, affecting more than 5 million Americans, as well as their families and caregivers. Unfortunately, aging of the global population is only worsening the AD “epidemic”, as incidence is projected to triple by 2050. Despite intense research, there is currently no cure for this devastating neurodegenerative disorder. Thus, understanding the intrinsic molecular mechanisms that drive AD pathology and progression is critical to devising effective treatments. Postmortem examination of human brains has revealed that AD-associated neuropathologies, such as neurofibrillary tangles (NFTs) and neurodegeneration, generally arise in a conserved spatio-temporal pattern, affecting transentorhinal regions first, and later extending to limbic and isocortical areas. The molecular and neurochemical bases for such selective neuronal vulnerability (SNV) have long been pursued, as they underlie disease progression and may hold the key to understanding the molecular underpinnings of neurodegeneration, but to date these mechanisms remain elusive. Here, cutting-edge, single-cell technologies will be used to generate a comprehensive, multi-omic atlas of cell types within AD-vulnerable brain regions across different stages of disease. The hypothesis is that specific cell types most dramatically affected by AD pathology within susceptible brain regions are characterized by distinct molecular pathways (transcription factors, signaling cascades, gene networks) that drive SNV. Moreover, that these pathways are executed in a sequential spatio-temporal pattern by changes in chromatin architecture and gene regulatory elements. Tracking the molecular changes exhibited by these neuronal cell populations in the continuum of AD pathology will better define AD onset and progression, and potentially indicate new therapeutic targets. Postmortem brain samples will be obtained from healthy controls, or patients who at death exhibited different stages of AD pathology, namely early (Braak III/IV), or late (Braak V/VI). Changes occurring at different stages of AD progression will be analyzed to identify the cell types and molecular pathways most critical for the initiation and spread of AD-related pathology. Regions analyzed will be hippocampus (CA1/sub), inferior temporal cortex (BA20), frontal cortex (BA9), and visual cortex (an AD- resistant region). In Aim 1, samples from control subject will be subjected to single cell analyses to characterize the methylome and chromatin architecture jointly (sn-m3C-seq), as well as chromatin accessibility together with transcriptome (Paired-seq), of cell types within AD-vulnerable brain regions. Integration of these datasets will create a multi-omic atlas of relevant cell types that will serve as the foundation for understanding AD onset and progression. In Aim 2, these analyses will be extended to AD patients. Comparing data sets across brain regions and disease stages will reveal the specific cell types most affected in AD, as well as the molecular pathways (based on changes in methylation patterns, chromatin architecture, etc.) that drive SNV in AD (Aim3).