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.

项目摘要/摘要 阿尔茨海默氏病（AD）是痴呆症的最常见原因，其特征是 老年斑块和神经纤维缠结。广告风险可能受众多遗传和 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的蛋白质和脂质代谢， 作为炎症，血管和氧化机制。导致广告及其的一系列风险因素 在AD患者中，下游影响可能是异质的，这使人们更加复杂 在任何给定的AD患者中，药物靶标，生物标志物及其潜在的下游有益用途。为了这 原因，药物靶标和生物标志物的发现工作必须集中于两个分子的识别 AD患者通常会扰动的机制以及可能是基础的机制 广告中的异质性。为了克服这一巨大挑战，团队科学的努力，包括NIH计划， 加速药物合作伙伴关系（AMP-AD）和AD血管病因的分子机制 （M2ove-ad）财团，已经从良好的 表型人类人群和模型系统。这些联盟旨在整合多摩斯和临床 构建AD模型的内表型数据，该模型捕获了这些常见和异质的模型 病理机理。我们的团队是AMP-AD和M2OVE-AD的领先参与者。初始发现 从这些联盟中揭示了AD受试者中表达基因和蛋白质网络的一致变化 和模型系统，具有生物学意义。尽管取得了这种进步，并广泛地分享了 这些程序生成的数据，可用的–omics数据中仍然存在巨大差距，以及能够 集成，协调和注释这些数据集。我们的建议是对RFA-AG-17-054的回应， 旨在缩小这些差距。在此提案中，我们保持了父母资助的M2ove-AD的总体目标 项目（RF1 AG51504），即确定apoE和性别依赖性效应，并发现新基因 以及影响衰老，AD和其他痴呆症的血管风险的途径。我们的具体目标是：1。 人脑的综合功能基因组分析，发现AD中的新途径。 2。集成 前瞻性队列中的功能基因组分析，以验证和发现AD途径。 3。调查 APOE基因型和性别对转录网络和模型系统中代谢组的影响。 4。 执行单细胞分析以注释来自AMP-AD和M2OVE-AD的转录组数据。这些研究 将在人和转录组中添加关键的表观遗传数据（H3K9AC和RRB甲基甲基）以及 代谢组学数据到鼠标队列，生成人和小鼠单细胞转录组数据，以及 执行集成的网络分析。我们希望这一建议能够填补知识的关键空白，进一步 在其药物和生物标志物发现目标中增强AMP-AD和M2OVE-AD计划。