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 阿尔茨海默氏病（AD）临床试验的失败要求进行研究范式转变。 Amp-ad有 缩短发现潜在药物靶标之间时间的核心目标和 开发AD的新药。六个参与财团生成的大数据 确定了20多个新型药物发现的潜在靶标。下一个挑战是提供 对所涉及的公共途径和关键酶的更深入的分子理解， 最适合药物发现和铅的转运蛋白和信号分子 鉴别。 作为AMP-AD和M2OVE-AD的一部分，广告代谢组学联盟（ADMC）开始 通过构建全面的代谢组学数据库来应对这些挑战和其他挑战 Atlas for Ad。代谢组签名是捕获（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。基本的生化知识影响了医学领域并提供了 监测疾病的基本工具，例如糖尿病中的葡萄糖和胆固醇的措施 心血管疾病，导致针对这些疾病的关键药物的发展。 定义有风险和AD风险的人的代谢轨迹可以类似地发现药物。 在AMP-AD阶段，ADMC介绍了来自AD神经影像学的1,600个基线样品 倡议（ADNI），使用8个代谢组学平台，测量超过800个代谢产物。我们确定了 与AD病理生理标记相关的AD代谢特征 认知以及与大脑有关的胆固醇清除率涉及的肠道衍生代谢产物 成像变化和认知能力下降。作为迈向患者子分层的第一步，我们 研究了性别和特异性的代谢特征。在开发的地图集中，我们 将AD代谢组信号与基因组联系起来。利用这些代谢特征我们 带有牵涉代谢途径的注释的AMP-AD目标，说明了 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 加速AMPAD朝着新的药物发现前进。我们将连接中央和周边 代谢变化解决周围代谢对大脑健康和疾病的贡献， 启用AMPAD合作伙伴与生化读数，将其发现与已知的发现联系起来 可以针对药物发现的生化途径；定义可以的早期变化 提供有关因果机制和早期干预措施的见解；使用代谢型和 鉴定临床亚型以支持Precision Medicine AD方法的基因型；和 识别铅化合物，有可能重新利用现有药物进行AD。