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.