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| Funder | NATIONAL INSTITUTE ON AGING |
|---|---|
| Recipient Organization | Duke University |
| Country | United States |
| Start Date | Sep 30, 2021 |
| End Date | May 31, 2026 |
| Duration | 1,704 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10885032 |
Project Summary Social support and social integration are some of the most robust predictors of morbidity and mortality identified to date. This relationship arises from increased susceptibility to several of the top causes of death in the United States, including major diseases of aging such as heart disease and cancer. Recent studies
suggest that a signature of social relationships is also detectable in data on gene regulation, highlighting a potential pathway through which social ties get “under the skin” to influence health. However, despite abundant evidence that the health effects of social relationships begin early in life, no studies have related the full life
course trajectory of social relationships to data on gene regulation, or used these data to investigate why some individuals appear more susceptible to social isolation than others. The goal of this study is to address these gaps by linking fine-grained, longitudinal data on social relationships to unbiased surveys of the molecular signature of social experience. To do so, we will leverage
an established model for social relationships and health in natural animal populations, the baboons of the Amboseli ecosystem of Kenya. This population has been the subject of longitudinal study for up to 9 generations, revealing that social isolation predicts shortened lifespan in a manner highly analogous to
humans. We propose to link annual measures of social relationships, from birth through adulthood, with gene expression and chromatin accessibility data collected both at baseline and following ex vivo challenge with bacterial and viral mimics. This strategy will allow us to investigate the types of social relationships that matter
most, the timing of their effects on gene regulation, and their relevance for immune function, a primary contributor to variation in health during aging. Using these data, we will address three aims. First, we will characterize the gene regulatory signature of variation in social relationships across the life course. We will investigate the relative roles of early life,
cumulative experience, and social relationships close to the time of biological sample collection, as well as the relative importance of social relationship quantity versus quality. Second, we will assess whether individuals vary in their sensitivity to social environments based on genotype, by identifying gene-social relationship
interactions that affect gene expression. Finally, we will test the consequences of social relationship-associated gene regulation for immune defense and lifespan. In doing so, this work will shed important light on whether gene regulatory signatures of social relationships are likely to be mechanistically implicated in the link between
social relationships and health, or instead serve as passive biomarkers. Together, our results will provide the most comprehensive window into the functional genomic signature of social relationships available to date. By revealing when, how, and for whom social relationships matter most, they will therefore address three
questions of outstanding importance to understanding the role of the social environment in human health.
Duke University
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