Integrative translational discovery of vascular risk factors in aging and dementia

项目摘要/摘要 阿尔茨海默病(AD)是导致痴呆症的最常见原因，其特征是大脑中 老年斑和神经原纤维缠结。AD风险可能受多种遗传因素和 环境风险因素及其复杂的相互作用，从而导致下游的级联 病理生理事件，包括但不限于异常蛋白平衡和脂类代谢 炎症、血管和氧化机制。导致AD的一系列风险因素及其 在AD患者中，下游影响可能是不同的，这使得寻找 任何特定AD患者的药物靶点、生物标记物及其潜在的下游有益用途。为了这个 AD的原因、药物靶点和生物标记物的发现工作必须集中在这两个分子的鉴定上 阿尔茨海默病患者通常受到干扰的机制，以及可能存在的机制 AD的异质性。为了克服这一巨大的挑战，团队科学努力，包括国家卫生研究院的倡议， 促进药物伙伴关系-AD(AMP-AD)与AD血管发病的分子机制 (M2OVE-AD)财团已经启动了从油井中大规模生成和分析多组学数据的工作。 表型人类队列和模型系统。这些联盟的目标是整合多组学和临床 用内表型数据构建AD模型(S)，捕捉这些共同和异质性 病理机制。我们的团队是AMP-AD和M20VE-AD的主要参与者。初步调查结果 从这些联合体中发现AD患者表达基因和蛋白质网络的协同变化 和模型系统，具有生物学意义。尽管取得了这一进展，并立即广泛分享了 由这些计划生成的数据，在可用的组学数据中仍然存在显著差距，并且有能力 整合、协调和注释这些数据集。我们的建议是对RFA-AG-17-054的回应，其中 旨在弥合这些差距。在这份提案中，我们维持了母公司资助的M20VE-AD的总体目标 项目(RF1 AG51504)，该项目旨在确定载脂蛋白E和性别依赖的效应，并发现新的基因 以及影响衰老、阿尔茨海默病和其他痴呆症血管风险的途径。我们的具体目标是：1. 人类大脑的综合功能基因组分析，以发现AD的新途径。2.融合式 在前瞻性队列中进行功能基因组分析，以验证和发现AD途径。3.调查 模型系统中载脂蛋白E基因和性别对转录网络和代谢组的影响。4. 执行单细胞图谱以注释AMP-AD和M2OVE-AD的转录组数据。这些研究 将关键的表观遗传学数据(H3K9Ac和RRBS甲基组)添加到人类和转录组中，并 代谢组学数据到小鼠队列，产生人类和小鼠单细胞转录组数据，以及 执行综合网络分析。我们希望这项建议将填补知识方面的关键空白，并进一步 加强AMP-AD和M2OVE-AD在药物和生物标记物发现目标中的倡议。

PROJECT SUMMARY/ABSTRACT Alzheimer's disease (AD) is the most common cause of dementia characterized by brain accumulation of senile plaques and neurofibrillary tangles. AD risk is likely influenced by a multitude of genetic and environmental risk factors and their complex interplay, which subsequently lead to cascades of downstream pathophysiologic events that include but are not limited to aberrant proteostasis and lipid metabolism, as well as inflammatory, vascular, and oxidative mechanisms. The array of risk factors that lead to AD and their downstream influences are likely to be heterogeneous amongst AD patients, which complicates the search for drug targets, biomarkers and their potential downstream beneficial use in any given AD patient. For this reason, drug target and biomarker discovery efforts in AD have to focus on identification of both molecular mechanisms that are commonly perturbed in AD patients, as well as those mechanisms that may underlie heterogeneity in AD. To overcome this massive challenge, team-science efforts, including the NIH initiatives, Accelerating Medicines Partnership-AD (AMP-AD) and Molecular Mechanisms of the Vascular Etiology of AD (M2OVE-AD) Consortia, have launched large-scale generation and analyses of multi-omics data from well- phenotyped human cohorts and model systems. These consortia aim to integrate multi-omics and clinical endophenotype data to build a model(s) of AD that captures these common and heterogeneous pathomechanisms. Our teams are leading participants of both AMP-AD and M2OVE-AD. The initial findings from these consortia reveal concerted changes in networks of expressed genes and proteins in AD subjects and model systems, with biological significance. Despite this progress and wide and immediate sharing of the data generated by these programs, significant gaps remain in the available –omics data, and the ability to integrate, harmonize and annotate these datasets. Our proposal is in response to the RFA-AG-17-054, which aims to close these gaps. In this proposal, we maintain the overall objective of our parent funded M2OVE-AD project (RF1 AG51504), which is to determine APOE- and sex-dependent effects, and uncover novel genes and pathways that influence vascular risk in aging, AD and other dementias. Our specific aims are: 1. Integrative functional genomic analysis of human brains to discover novel pathways in AD. 2. Integrative functional genomic analysis in a prospective cohort to validate and discover AD pathways. 3. Investigate the impact of APOE genotype and sex on transcriptional networks and the metabolome in model systems. 4. Perform single-cell profiling to annotate the transcriptome data from AMP-AD and M2OVE-AD. These studies will add key epigenetic data (H3K9Ac and RRBS methylome) to the human and transcriptome and metabolomics data to the mouse cohorts, generate human and mouse single cell transcriptome data, and perform integrative network analyses. We expect this proposal to fill key gaps in knowledge and further enhance the AMP-AD and M2OVE-AD initiatives in their drug and biomarker discovery goals.