# Using metabolomics to identify mechanisms of natural variation in aging

> **NIH NIH R56** · UNIVERSITY OF WASHINGTON · 2022 · $318,745

## Abstract

Project Summary
Molecular studies of aging have uncovered numerous, evolutionarily conserved mechanisms associated with
aging in laboratory organisms. However, we have still yet to determine to what extent these mechanisms account
for the enormous variation in rates of aging and age-related disease that we find among individuals within
populations. This leaves a significant gap in our ability to understand and improve healthy aging in natural
populations. To close this gap, researchers have tried to map the genetic basis of this variation using genome-
wide association studies. However, the genes identified, while highly statistically significant, typically have very
small effect sizes. In our work on the fruit fly, Drosophila melanogaster, we have shown that much of this variation
can be accounted for by measuring the intermediate ‘endophenotypes’ that lie between genotype and
downstream phenotype. We have focused in particular on the metabolome. The metabolome consists of the
small molecules (< ~1,500 Da) that make up the structural and functional building blocks of all organisms. Our
previous studies have shown that i) metabolome profiles can predict complex traits in genetically variable
populations; ii) that metabolomics can reveal easily validated mechanisms associated with this variation; iii) that
a metabolomic clock can predict lifespan; and iv) that network analysis can reveal otherwise hidden explanatory
modules combining genes, metabolites, and complex traits of interest. Our previous findings have led us to
formulate our central hypotheses that the metabolome can provide deep insight into the mechanisms that explain
variation within and between species in aging, and variation in the response to interventions that can increase
healthspan. Here we propose to test these hypotheses by incorporating in-depth metabolomic profiling into
studies of aging within a naturally variable population of a single fly species through two aims. First, in studies of
the Drosophila Genetic Reference Panel, we have established considerable genetic variation for the response
to rapamycin, a promising focus of healthspan-promoting interventions. Based on results from this screen, we
will test three putative mechanisms associated with variation in sensitivity to rapamycin. Given the central role
of phosphorylation in mTOR complex activity, Aim 1 also includes proteomic and phosphoproteomic analysis.
Second, we have developed a metabolome clock capable of predicting lifespan in flies. In Aim 2, we will test
putative mechanisms by which this novel clock works, we will test the ability of the clock to predict response to
a lifespan intervention in diverse genetic backgrounds, and we will create a second-generation metabolome
clock that is sex-specific and longitudinal. The rationale for the proposed studies is not only that they will shed
light on fundamental mechanisms of aging, but also, given that central metabolic pathways are deeply
evolutionarily conserve...

## Key facts

- **NIH application ID:** 10674251
- **Project number:** 2R56AG049494-06A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** Daniel Edward Promislow
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $318,745
- **Award type:** 2
- **Project period:** 2022-09-15 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10674251

## Citation

> US National Institutes of Health, RePORTER application 10674251, Using metabolomics to identify mechanisms of natural variation in aging (2R56AG049494-06A1). Retrieved via AI Analytics 2026-06-01 from https://api.ai-analytics.org/grant/nih/10674251. Licensed CC0.

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