Metabolomic Signatures for Disease Sub-classification and Target Prioritization in AMP-AD

AMP-AD 中疾病亚分类和目标优先级的代谢组学特征

• 批准号: 10084547
• 负责人: Rima F Kaddurah-Daouk
• 金额: $ 12.5万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-13 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10084547
• 关键词: Address; Alzheimer' s Disease; Alzheimer' s disease model; Amines; Animals; Atlases; Bile Acids; Binding; Biochemical; Biochemical Pathway; Biological Markers; Biological Models; Blood specimen; Brain; Brain Diseases; Brain imaging; Branched-Chain Amino Acids; Cardiovascular Diseases; Chemicals; Cholesterol; Classification; Clinical; Clinical Trials; Cognition; Cognitive; Communities; Data; Databases; Development; Diabetes Mellitus; Disease; Drug Targeting; Drug usage; Early Intervention; Enzymes; Failure; Fluorouracil; Framingham Heart Study; Functional disorder; Gene Expression; Genetic; Genetic Variation; Genome; Genotype; Glucose; Glutamates; Goals; Heterogeneity; Human; Impaired cognition; Knowledge; Lead; Lecithin; Life Style; Link; Malignant Neoplasms; Measures; Medical; Metabolic; Metabolic Pathway; Metabolism; Molecular; Monitor; Network-based; Neurotransmitters; Pathogenesis; Pathway interactions; Patients; Peripheral; Pharmaceutical Preparations; Phase; Prevention; Proxy; Research; Risk; Risk Factors; Role; Sampling; Signal Transduction; Signaling Molecule; Sphingomyelins; Stratification; Structure; Symptoms; Time; Translations; Tryptophan; Tyrosine; Vertebral column; Work; biomarker development; brain health; clinical phenotype; clinical subtypes; cohort; cytotoxic; disease phenotype; disorder subtype; drug development; drug discovery; gut microbiome; insight; metabolic phenotype; metabolomics; network models; neuroimaging; new therapeutic target; novel therapeutics; precision medicine; protein expression; research clinical testing; sex; tool; treatment response

Abstract/Scope of Work Failures of Alzheimer disease (AD) clinical trials calls for a research paradigm shift. AMP-AD has the central goal of shortening the time between the discovery of potential drug targets and development of new drugs for AD. Large data generated by the six participating consortia has identified over 20 potential targets for novel drug discovery. The next challenge is to provide deeper molecular understanding of common pathways implicated and the key enzymes, transporters and signaling molecules that are most amenable for drug discovery and for lead identification. The AD Metabolomics Consortium (ADMC), as part of AMP-AD and M2OVE-AD, began to address these and other challenges by building a comprehensive metabolomics database and an Atlas for AD. Metabolomic signatures serve as a readout capturing net influences of (epi)genetic variation, protein expression, gut microbiome and environmental and lifestyle differences. Metabolic signatures can inform about disease mechanisms, progression, heterogeneity and treatment response. Basic biochemical knowledge has impacted the medical field and provided basic tools for monitoring disease such as measures of glucose and cholesterol in diabetes and cardiovascular diseases and resulted in development of key drugs targeting these disorders. Defining metabolic trajectories of those at risk for and with AD can similarly enable drug discovery. In AMP-AD Phase I, the ADMC profiled 1,600 baseline samples from the AD Neuroimaging Initiative (ADNI) using 8 metabolomics platforms measuring over 800 metabolites. We identified metabolic signatures for AD that correlate with markers of AD pathophysiology including cognition, as well as gut-derived metabolites involved in cholesterol clearance related to brain imaging changes and cognitive decline. As a first step towards patient sub-stratification, we investigated sex- and APOE-specific metabolic signatures. Within an atlas being developed, we connect AD metabolomic signatures with the genome. Utilizing these metabolic signatures we annotated AMP-AD targets with implicated metabolic pathways, illustrating the power of metabolism to inform drug development. For Phase II of AMP-AD, we propose to more thoroughly address challenges in order to accelerate AMPAD progress toward novel drug discovery. We will connect central and peripheral metabolic changes addressing contributions of peripheral metabolism to brain health and disease, enable AMPAD partners with biochemical readouts that connect their findings to known biochemical pathways that can be targeted for drug discovery; define early changes that can provide insights about causative mechanisms and early interventions; use metabotypes and genotypes to identify clinical subtypes to support a precision medicine approach to AD; and identify lead compounds with the possibility to repurpose existing drugs for AD.

摘要/工作范围 阿尔茨海默病(AD)临床试验的失败需要研究范式的转变。AMP-AD有 缩短发现潜在药物靶点之间的时间和 开发治疗AD的新药。由六个参与财团产生的大量数据 确定了20多个潜在的新药发现目标。下一个挑战是提供 对所涉及的常见途径和关键酶有更深入的分子理解， 最适合药物发现和铅的转运体和信号分子 身份证明。 AD代谢组学联合会(ADMC)作为AMP-AD和M2OVE-AD的一部分，开始 通过建立全面的代谢组学数据库和 AD的地图集。代谢组特征作为一个读数来捕捉(Epi)遗传的净影响 变异、蛋白质表达、肠道微生物群以及环境和生活方式的差异。 代谢特征可以告知疾病的机制、进展、异质性和 治疗反应。基本的生物化学知识影响了医学领域，并为 监测疾病的基本工具，如糖尿病和糖尿病患者的血糖和胆固醇测量 并导致针对这些疾病的关键药物的开发。 确定阿尔茨海默病风险人群和AD患者的代谢轨迹同样可以促进药物发现。 在AMP-AD第一阶段，ADMC分析了来自AD神经成像的1600个基线样本 首创(ADNI)使用8个代谢组学平台，测量超过800种代谢物。我们确认了 与AD病理生理学标志物相关的AD代谢特征，包括 认知以及与大脑相关的与胆固醇清除相关的肠源性代谢物 影像改变和认知能力下降。作为患者细分的第一步，我们 调查了性别和载脂蛋白E特定的代谢特征。在正在开发的地图册中，我们 将AD代谢特征与基因组联系起来。利用这些代谢特征，我们 用隐含的代谢途径注释AMP-AD靶点，说明了 新陈代谢为药物开发提供信息。 对于AMP-AD的第二阶段，我们建议更彻底地应对挑战，以便 加快Ampad在新药发现方面的进展。我们将连接中央和外围设备 针对外周代谢对大脑健康和疾病的贡献的代谢变化， 为AMPAD合作伙伴提供生化读数，将他们的发现与已知 可以作为药物发现目标的生化途径；定义可以 提供关于致病机制和早期干预的见解；使用代谢物类型和 确定临床亚型的基因类型，以支持AD的精确医学方法；以及 确定先导化合物，有可能改变现有药物治疗AD的目的。