/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.

Public Health Relevance

Knowledge about metabolism contributes to all aspects of drug discovery and drug development and has led to development of most commonly used drug as statin for prevention and treatment of cardiovascular disease and 5-fluorouracil for treating cancer. In addition, metabolism data led to development of biomarkers used routinely in daily clinical testing such as glucose and cholesterol. Our Alzheimer Disease Metabolomics Consortium is creating a comprehensive metabolomics database and an Atlas for the Alzheimer community that will provides a deep understanding of metabolic failures in AD and a roadmap for drug discovery. We provide an intermediate layer of information to AMPAD partners that is close to clinical phenotypes and that is a readout for large omics data they are creating informing them about common pathways implicated in disease and highlighting enzymes and transporters as targets for drug development.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Research Project--Cooperative Agreements (U01)
Project #
Application #
Study Section
Program Officer
Petanceska, Suzana
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Duke University
Schools of Medicine
United States
Zip Code