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| Funder | NATIONAL INSTITUTE ON AGING |
|---|---|
| Recipient Organization | University of Exeter |
| Country | United Kingdom |
| Start Date | Sep 15, 2024 |
| End Date | Aug 31, 2029 |
| Duration | 1,811 days |
| Number of Grantees | 4 |
| Roles | Principal Investigator; Co-Investigator |
| Data Source | NIH (US) |
| Grant ID | 10933581 |
Social Modifiers of Primate Lifespan People who are socially isolated or low socioeconomic status suffer from poorer health and shorter lives. Social factors also impact the survival of other primates, suggesting that social health gradients are part of the human evolutionary legacy. Yet whether social factors shape
how long primate species live, and how this interspecific variation is encoded at a molecular level, are unknown. Gaps in understanding stem from challenges posed by collecting data on lifespan, the social environment, and the pace of aging across large numbers of primates. Information-rich comparative social and life-history datasets with high-quality biological samples
are thus needed. The objective of this proposal is to leverage three unique assets developed by our research team: a Bayesian life-history model; the largest primate social network database to date; and a generalizable epigenetic aging clock. We aim to use these resources to estimate lifespan for a large number of primate species, to test if the social environment predicts how long different
primates live, and if lifespan and social variation are reflected in molecular signatures of aging. We will optimize our newly developed Bayesian Life-History Estimator for primate data and will apply it to available cross-sectional age-structured data - i.e., snapshots of the distribution of ages in a population - from over 70 primate species (Aim 1). In doing so, we will create the
largest database of primate lifespan values to date. We will test if social support elongates and social inequality truncates lifespans in the largest best-studied genera of primates, the macaques (Aim 2). Macaque species share many aging-relevant traits, yet vary in lifespan and social regimes. We will leverage our MacaqueNet
database, home to behavioral data for over half the 25 species in the genus Macaca to quantify social support and social inequality. We predict that species with high levels of social support and low levels of social inequality live longer. Using MacaqueNet and the robust biomedical infrastructure that supports macaque research,
we will develop a generalizable epigenetic aging clock for multiple macaque species (Aim 3). We predict that longer lived macaques age at a slower pace than shorter lived macaques, and that macaques with more social support or lower levels of social inequality age more slowly. Our study will vastly increase availability of fundamental primate longevity data, will provide
insights into the eco-evolutionary contexts underpinning human lifespans, and into the social modifiers of aging and longevity in the most human-relevant cross-species comparative system for the study of health, disease, and aging – the genus Macaca.
University of Exeter
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