PROJECT SUMMARY
The goal of this project is to identify epigenetic pathways underlying the effects of social
connectedness on aging-related morbidity and mortality. We propose to examine the potential
pathogenic and protective consequences of individuals’ habitual patterns of interaction with
members of their egocentric, or personal, social networks (i.e., their social signatures). Meta-
analyses have identified beneficial effects of social connectedness on all-cause mortality that are
robust and larger in magnitude than the adverse effects associated with smoking, alcohol
consumption, sedentary lifestyle, and obesity. However, the biological processes underlying
these patterns have received insufficient empirical study relative to behavioral mechanisms, and
little attention has focused on longer-term physiological or pathogenic mechanisms. To address
these gaps, we examine the implications of social signatures for DNA methylation (DNAm), a
biomarker of accelerated biological aging and an early predictor of later-life onset of diabetes,
cardiovascular disease (CVD), stroke, dementia, and other complex diseases. We leverage a
large, omnibus health survey, the Person to Person (P2P) Health Interview Study (N˜3,050),
administered face-to-face to a stratified household probability sample. As part of this effort, DNA
was extracted from saliva samples (n˜2,600) for future analysis. We address the following specific
aims: Aim 1 examines associations between social signatures and DNA methylation-based
profiles, including epigenetic age acceleration and polyepigenetic scores. Aim 2 assesses
whether social signatures attenuate documented associations between early life, mid-life, and
chronic exposures to stressful conditions and DNA methylation-based profiles. Aim 3 explores
associations between social signatures and targeted DNA methylation sites documented to affect
risk for obesity, inflammation, Alzheimer’s disease, and other specific complex diseases
associated with aging. The proposed study is interdisciplinary, combines leading-edge methods
from the social and biomedical sciences, and leverages considerable existing data and research
infrastructure. By increasing our understanding of the specific biological pathways underlying the
effects of social connectedness that unfold over the life course, this study could help identify novel
targets for earlier social or biological intervention in aging-related complex diseases.
