Metabolomic analysis of aging and longevity
Hoffman, Jessica Marie
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Recent advances in the biology of aging have uncovered many genetic and environmental factors that influence aging and longevity. However, even with these discoveries, we can still only explain a small proportion of the variance seen in longevity within and among species. My thesis attempts to close this gap by employing metabolomics, the study of all the small molecules in an organism. I first examine how the metabolome changes with age, sex, and genotype in the fruit fly Drosophila melanogaster. I find the metabolome is highly variable (and predictive of) all three factors, and I find dramatic age related changes occurring in metabolic pathways associated with monoamine neurotransmitters. I then take a comparative approach across the Drosophila genus to determine how the metabolome is associated with longevity and resistance to oxidative stress in the largest comparative metabolomics study to date. I find that the metabolome varies considerably among species, and that much of the variability is explained by interspecific variation in body weight. Within sexes, a large fraction of the metabolome is associated with species differences in longevity and oxidative stress resistance. Despite these strong correlations, the metabolome appears to contain only a very weak phylogenetic signal. Finally, while Drosophila studies have the potential to give many new insights into the basic biology of aging, results in the species can be limited in their translational impact to humans. In this light, I attempt to understand the metabolome’s association with age in a non-human primate, the common marmoset. I use a longitudinal approach and find the metabolome is highly predictive of age, and I can identify metabolites that show consistent age-related trajectories within individuals. Many of these changes are associated with oxidative stress and xenobiotic metabolism, both of which are already known to be associated with age in other model organisms. This suggests that the association between age and specific metabolic pathways might be conserved across millions of years of evolution. Taken together, the results of this thesis demonstrate the powerful potential metabolomics has to discover the underlying biochemical pathways influencing natural variation in aging and longevity.