Using metabolomics to identify mechanisms of natural variation in aging

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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 conserved, that they will have high translational potential.