Integrative translational discovery of vascular risk factors in aging and dementia

衰老和痴呆血管危险因素的综合转化发现

• 批准号: 9421402
• 负责人: GUOJUN BU
• 金额: $ 357.77万
• 依托单位: MAYO CLINIC JACKSONVILLE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-15 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9421402
• 关键词: Address; Age; Aging; Alleles; Alzheimer' s Disease; Alzheimer' s Disease Pathway; Alzheimer' s disease risk; Amyloid beta-Protein; Apolipoprotein E; Autopsy; Biochemical; Biological; Biological Models; Blood Vessels; Brain; Brain Diseases; Cells; ChIP-seq; Chromatin; Clinic; Clinical; Cognitive; Complex; Data; Data Set; Dementia; Disease; Drug Targeting; Elderly; Environmental Risk Factor; Epigenetic Process; Etiology; Event; Funding; Gene Proteins; Generations; Genes; Genetic; Genetic Risk; Genetic Transcription; Genotype; Goals; Gonadal Steroid Hormones; Grant; Heterogeneity; Human; Inflammatory; Knowledge; Lead; Measurement; Measures; Medicine; Meta-Analysis; Methylation; Modeling; Molecular; Mus; Nerve Degeneration; Neurofibrillary Tangles; Outcome; Parents; Participant; Pathologic; Pathway Analysis; Pathway interactions; Patients; Phenotype; Plasma; Prospective cohort; Protein Isoforms; RNA Sequences; Risk; Risk Factors; Role; Sampling; Science; Senile Plaques; Testing; Tissue Sample; Tissues; United States National Institutes of Health; apolipoprotein E-3; biomarker discovery; cohort; data sharing; drug discovery; endophenotype; functional genomics; functional outcomes; genome-wide; human data; lipid metabolism; metabolome; metabolomics; methylome; mouse model; network models; neuroimaging; neuropathology; new therapeutic target; novel; parent grant; programs; proteostasis; response; sex; targeted biomarker; tau Proteins; transcriptome

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.

项目总结/摘要 阿尔茨海默氏病（AD）是痴呆的最常见原因，其特征在于脑内积聚的 老年斑和神经纤维缠结。AD风险可能受到多种遗传因素的影响， 环境风险因素及其复杂的相互作用，随后导致下游的级联 病理生理事件，包括但不限于异常蛋白质稳态和脂质代谢，以及 炎症、血管和氧化机制。导致AD的一系列风险因素及其 下游影响在AD患者中可能是异质性的，这使得寻找 药物靶标、生物标志物及其在任何给定AD患者中的潜在下游有益用途。为此 因此，AD中的药物靶点和生物标志物发现工作必须集中在识别两种分子 这些机制通常在AD患者中受到干扰，以及那些可能导致 AD的异质性。为了克服这个巨大的挑战，团队科学的努力，包括国家卫生研究院的倡议， 加速药物合作-AD（AMP-AD）和AD血管病因的分子机制 （M2 OVE-AD）联盟，已经启动了大规模的多组学数据的生成和分析， 表型确定的人类群组和模型系统。这些联盟旨在整合多组学和临床 内表型数据来构建AD模型，该模型捕获这些常见和异质的 病理机制我们的团队是AMP-AD和M2 OVE-AD的主要参与者。初步结果 揭示了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，并广泛和立即分享了 尽管这些计划产生的数据，但可用的组学数据仍存在重大差距， 整合、协调和注释这些数据集。我们的提案是对RFA-AG-17-054的回应， 旨在缩小这些差距。在本提案中，我们保持了母公司资助的M2 OVE-AD的总体目标 项目（RF 1 AG 51504），该项目旨在确定APOE和性别依赖性效应，并发现新基因 以及影响衰老、AD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.综合 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.探讨 APOE基因型和性别对模型系统中转录网络和代谢组的影响。4. 进行单细胞分析以注释来自AMP-AD和M2 OVE-AD的转录组数据。这些研究 将为人类和转录组添加关键的表观遗传数据（H3 K9 Ac和RRBS甲基化组）， 将代谢组学数据提供给小鼠群组，生成人和小鼠单细胞转录组数据，以及 进行综合网络分析。我们希望这一提议能够填补知识方面的关键空白，并进一步 加强AMP-AD和M2 OVE-AD在其药物和生物标志物发现目标方面的举措。