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

> **NIH NIH U01** · DUKE UNIVERSITY · 2020 · $125,041

## Abstract

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.

## Key facts

- **NIH application ID:** 10084547
- **Project number:** 3U01AG061359-02S1
- **Recipient organization:** DUKE UNIVERSITY
- **Principal Investigator:** Rima F Kaddurah-Daouk
- **Activity code:** U01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $125,041
- **Award type:** 3
- **Project period:** 2020-01-13 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10084547

## Citation

> US National Institutes of Health, RePORTER application 10084547, Metabolomic Signatures for Disease Sub-classification and Target Prioritization in AMP-AD (3U01AG061359-02S1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10084547. Licensed CC0.

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