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）临床试验的失败要求研究范式的转变。AMP-AD具有 中心目标是缩短发现潜在药物靶点和 开发治疗AD的新药。六个参与财团产生的大量数据， 发现了20多个新药发现的潜在靶点。下一个挑战是提供 对涉及的共同途径和关键酶的更深入的分子理解， 转运蛋白和信号分子，最适合药物发现和铅 识别. AD代谢组学联盟（ADMC）作为AMP-AD和M2 OVE-AD的一部分，开始 通过建立全面的代谢组学数据库和 AD的Atlas。代谢组学特征用作捕获（epi）遗传的净影响的读数。 变异、蛋白质表达、肠道微生物组以及环境和生活方式差异。 代谢特征可以告知疾病机制、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， 监测疾病的基本工具，如糖尿病中葡萄糖和胆固醇的测量， 心血管疾病，并导致针对这些疾病的关键药物的开发。 定义那些有AD风险和患有AD的人的代谢轨迹同样可以使药物发现成为可能。 在AMP-AD I期，ADMC分析了来自AD神经影像学检查的1，600个基线样本， ADNI计划使用8个代谢组学平台测量800多种代谢物。我们确定 与AD病理生理学标志物相关的AD代谢特征，包括 认知，以及肠道衍生的代谢产物参与胆固醇清除相关的脑 影像改变和认知能力下降。作为患者子分层的第一步，我们 研究了性别和APOE特异性代谢特征。在正在开发的地图集中，我们 将AD代谢组学特征与基因组联系起来。利用这些代谢特征， 注释的AMP-AD靶点与相关的代谢途径，说明了 代谢，为药物开发提供信息。 对于AMP-AD第二阶段，我们建议更彻底地应对挑战，以便 加速AMPAD向新药发现的进展。我们将连接中央和外围 代谢变化解决了外周代谢对脑健康和疾病的贡献， 使AMPAD合作伙伴能够获得生化读数，将他们的发现与已知的 可用于药物发现的生物化学途径;定义可以 提供有关致病机制和早期干预的见解;使用代谢型， 基因型，以确定临床亚型，以支持精准医学方法治疗AD;以及 确定可能重新利用现有药物治疗AD的先导化合物。