Metabolic Network Analysis of Biochemical Trajectories in Alzheimer's Disease

阿尔茨海默病生化轨迹的代谢网络分析

• 批准号: 9422730
• 负责人: Rima F Kaddurah-Daouk
• 金额: $ 350.95万
• 依托单位: DUKE UNIVERSITY
• 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 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9422730
• 关键词: Adoption; Affect; Aging; Alzheimer' s Disease; Alzheimer' s disease risk; Amyloid beta-Protein; Analytical Chemistry; Area; Atlases; Biochemical; Biochemical Pathway; Biological Markers; Blood; Blood specimen; Brain; Cerebrospinal Fluid; Cholesterol; Clinical Trials; Cognition; Cognitive; Communities; Comorbidity; Data; Data Analyses; Databases; Diabetes Mellitus; Disease; Disease Progression; Disease susceptibility; Early Intervention; Environment; Enzymes; Epidemic; European; Failure; Functional Imaging; Functional disorder; Funding; Genes; Genetic; Genetic Code; Genetic Heterogeneity; Genetic Risk; Genome; Genotype; Health; Human; Image; Impaired cognition; Institutes; Investments; Knowledge; Link; Lipids; Maps; Measurement; Measures; Membrane Microdomains; Membrane Structure and Function; Metabolic; Metabolic Diseases; Metabolic Pathway; Metabolism; Mitochondria; Modeling; Molecular; Pathology; Pathway Analysis; Pathway interactions; Peripheral; Phagocytosis; Pharmaceutical Preparations; Phospholipids; Physiology; Play; Positioning Attribute; Process; Proteomics; Regulation; Research; Resources; Role; Sampling; Sphingomyelins; System; Systems Analysis; Time; Tissues; United States National Institutes of Health; Variant; brain volume; clinically relevant; cohort; computer framework; disease heterogeneity; disease phenotype; drug development; drug discovery; enzyme pathway; follow-up; gene function; genetic risk factor; genetic variant; genome-wide; gut microbiome; immune function; indexing; insight; lipid metabolism; metabolic engineering; metabolome; metabolomics; multiple omics; network models; neuroimaging; novel; novel therapeutics; phenotypic data; prevent; reconstruction; stoichiometry; symposium; synaptic failure; tau Proteins; transcriptomics

METABOLIC NETWORK ANALYSIS OF BIOCHEMCIAL TRAJECTORIES IN ALZHEIMER'S DISEASE ABSTRACT Despite advances, clinical trials have not yielded therapies to prevent or slow progression of Alzheimer's Disease (AD) with recent failures highlighting our incomplete knowledge of disease mechanisms. Accumulating evidence suggests the synaptic failure in AD is associated with dysregulation in multiple networks and that AD is not a singular condition but may be a combination of altered networks calling for a systems approach. AD susceptibility is likely influenced by many different common and rare genomic variants spread across hundreds of genes. Such genetic heterogeneity poses enormous challenges in defining disease mechanisms and approaches for drug development. Increasing evidence supports that AD is a metabolic disease with diabetes co-morbidity and a range of metabolic perturbations occurring early in disease. APOE4 is the strongest genetic risk factor for AD. APOE functions in lipid metabolism and presence of the APOE4 variant is correlated with higher cholesterol levels in the blood, suggesting again an important role for metabolism in AD. In addition, most of the genes that have recently been implicated in AD suggest a role for lipid processing, immune function regulation and phagocytosis that are all related to metabolic functions. Yet, a detailed mapping of interconnected metabolic networks that fail in AD are not defined. Metabolomics allows simultaneous measurement of 100's to 1000's of metabolites for mapping perturbations into metabolic networks, enabling a systems approach to the study of AD. The metabolome captures net influences of the genome, gut microbiome and environment in AD. Metabolomics data provides a functional readout of effects of genetic variants on metabolism, reducing the complexity of genetics to common effects on metabolic pathways that are implicated in disease. As part of NIA's large initiatives AMP-AD and MOVE-AD, we have established the AD Metabolomics Consortium (ADMC) aiming at building a comprehensive metabolomics database for AD for interrogation of global metabolic failures in disease and to define metabolic pathways that are implicated in cognitive decline. By leveraging large NIH investments in the AD Neuroimaging Initiative (ADNI), ADMC, AMP- AD and MOVE-AD and by adding experts in metabolic reconstruction and modeling we will frame the metabolic basis for AD progression. In Aim 1, we propose to profile longitudinal samples from ADNI cohorts where deep phenotype data exists that enables us to track early biochemical changes related to both CSF amyloid-beta and tau pathology and across the trajectory of disease. Through imaging data we will link peripheral metabolic changes to changes in the brain. In Aim 2, we propose to create an integrated molecular Atlas for AD. This resource for the AD community will connect genotypes and metabotypes, providing a functional readout of genetic variants implicated in AD. In Aim 3, we propose to build the first genome-scale model of metabolic changes underlying AD progression. Together, this effort will provide a biochemical roadmap towards effective early interventions for AD.

阿尔茨海默病生化代谢途径的代谢网络分析 摘要 尽管取得了进展，但临床试验还没有产生预防或减缓阿尔茨海默氏症进展的疗法 疾病（AD）与最近的失败，突出了我们的疾病机制的不完整的知识。积累 有证据表明，AD中的突触失效与多种网络的失调有关， AD不是一个单一的条件，但可能是一个改变网络的组合，需要一个系统的方法。 AD易感性可能受到许多不同的常见和罕见基因组变异的影响， 数百个基因。这种遗传异质性对确定疾病机制提出了巨大挑战 和药物开发的方法。越来越多的证据支持AD是一种代谢性疾病， 糖尿病合并症和疾病早期发生的一系列代谢紊乱。APOE 4是 AD的最强遗传风险因素。APOE在脂质代谢中起作用，APOE 4变体的存在是 与血液中较高的胆固醇水平相关，再次表明代谢在AD中的重要作用。 此外，最近发现的与AD有关的大多数基因都表明了脂质加工的作用， 免疫功能调节和吞噬作用，这些都与代谢功能有关。一个详细的 没有定义在AD中失效的相互连接的代谢网络的映射。代谢组学允许 同时测量100到1000个代谢物， 网络，使系统的方法来研究AD。代谢组学捕获了代谢产物的净影响， AD的基因组、肠道微生物组和环境。代谢组学数据提供了一个功能读数的影响， 遗传变异对代谢的影响，减少遗传学对代谢途径的共同影响的复杂性 与疾病有关的基因作为NIA大型计划AMP-AD和MOVE-AD的一部分，我们已经建立了 AD代谢组学联盟（ADMC）旨在建立一个全面的AD代谢组学数据库 用于询问疾病中的整体代谢失败，并定义与疾病相关的代谢途径， 认知能力下降通过利用NIH在AD神经影像学倡议（ADNI）、ADMC、AMP中的大量投资， AD和MOVE-AD，通过增加代谢重建和建模方面的专家，我们将构建 AD进展的代谢基础。在目标1中，我们建议对ADNI队列的纵向样本进行分析 其中存在深层表型数据，使我们能够跟踪与CSF相关的早期生化变化， 淀粉样蛋白-β和tau病理学以及疾病的轨迹。通过成像数据我们将 外周代谢变化到大脑变化。在目标2中，我们建议创建一个整合的分子 AD的Atlas。AD社区的这一资源将连接基因型和代谢型， 与AD有关的遗传变异的功能读出。在目标3中，我们建议建立第一个基因组规模 AD进展基础的代谢变化模型。总之，这一努力将提供一个生化 为AD的有效早期干预制定路线图。

项目成果

CORUM: the comprehensive resource of mammalian protein complexes-2019.

• DOI: 10.1093/nar/gky973
• 发表时间: 2019-01-08
• 期刊: Nucleic acids research
• 影响因子: 14.9
• 作者: Giurgiu M;Reinhard J;Brauner B;Dunger-Kaltenbach I;Fobo G;Frishman G;Montrone C;Ruepp A
• 通讯作者: Ruepp A