A prospective, longitudinal perspective on gut microbiome aging and health in a non-human primate model

University Of Notre Dame, Notre Dame IN

Investigators

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Abstract

Summary The structure and function of the gut microbiome is linked to several major human health risks during development and aging, including malnutrition, obesity, diabetes, and frailty. As such, many scientists have proposed that longitudinal changes in the gut microbiome across the life course may serve as a bellwether of healthy development, healthy aging, and lifespan. Testing this hypothesis requires prospective, longitudinal, population-based research. However, nearly all population-based research on the human microbiome is cross- sectional. Indeed, to our knowledge, there are no prospective, longitudinal data on human gut microbial variation in adults or the elderly. Yet without these data, we cannot leverage the power of prospective, longitudinal approaches to link the dynamics of gut microbiome communities to major human health outcomes. Our objective is to use a prospective, longitudinal data set in an animal model to test whether individual variation in gut microbial development and aging predict endocrinological and biodemographic components of health, including age at maturity, endocrinological aging, and longevity. To accomplish this objective, we will leverage an unprecedented, pre-existing data set with 15,621 gut microbiome bacterial profiles from 501 individually known baboons. Each baboon is the subject of individual-based research by the Amboseli Baboon Research Project, which has been collecting detailed demographic and behavioral data on known wild baboons in the Amboseli ecosystem in Kenya since 1971. Our central hypothesis is that age-related changes in gut microbial composition, diversity, and stability serve as harbingers of developmental milestones, physical aging, and mortality. In Aim 1 we test how gut microbial composition, diversity, and stability vary among individuals from birth to death. In Aim 2, we use our prospective, longitudinal data to test whether individual variation in these traits predicts biodemographic and endocrinological components of development and aging. By identifying age-specific definitions of healthy microbiomes, our results will provide a target for interventions aimed at sustaining microbiome health in healthy populations and improving health for people with microbiome-related disease. Our animal model will allow us, for the first time, to measure: (i) individual variation in gut microbial aging, (ii) lifelong patterns of gut microbial diversity, and (iii) multiple dimensions of gut microbial stability?all of which are thought to indicate gut microbiome health and cannot be measured in existing data on human subjects. At its conclusion, this developmental proposal will have built the first-ever full lifespan, prospective, longitudinal model of gut microbial dynamics, with exceptional promise to help harness the gut microbiome to predict and improve human health.