Impacts of hurricanes and social buffering on biological aging in a free-ranging animal model Natural disasters are deeply damaging to human health and welfare. Such disasters have the potential to accelerate the aging process, which is the primary risk factor for most diseases. Identifying age-accelerating consequences of natural disasters and mitigating their impacts is therefore critical. However, natural disasters do not affect all individuals equally - there is abundant variation in individual health outcomes. Evidence suggests that social support is a critical buffer against the consequences of adversity, including natural disasters. But precisely how social support gets under the skin to mitigate disaster-linked declines in health and lifespan remains elusive. Gaps in understanding are partly the result of ethical and logistical challenges to the study of humans in disaster zones, including the availability of baseline data, and our ability to quantify aging across more than a few domains (e.g., molecular markers in blood, physical frailty). Humans are also very long-lived, impeding longitudinal study of accelerated aging within individuals, and they tend to emigrate away from environmental catastrophes, biasing subject pools toward certain members of affected populations. These difficulties can be overcome by studying shorter-lived nonhuman primates, which share much of their biology and behavior with humans, exposed to natural disasters. The objective of this proposal is to leverage pilot data generated by a 1-year R56 (R56- AG071023) in our long-term study of aging in the rhesus macaque population of Cayo Santiago island, Puerto Rico, which was heavily impacted by Hurricanes Maria in 2017 and Fiona in 2022. Our objective is to use this natural experimental model to quantify how natural disasters affect biological age in multiple aging domains (molecular, physiological, physical), and to test if social support buffers these effects. We will quantify the effects of natural disasters on biological age and the pace of aging (Aim 1) in three ways: (a) Using data, particularly post-mortem tissues, across individuals, we will test if animals that experienced a hurricane exhibit older biological ages for their chronological age than those who did not; (b) Using longitudinal data in the same living individuals we will test if their pace at which they are aging is accelerated by a hurricane; (c) Comparing across Hurricanes Maria and Fiona, we will quantify the cumulative age effects of natural disasters, predicting individuals that lived through two disasters will appear biologically older for their chronological age, and have a faster pace of aging, than individuals that only lived through one. We will then quantify the extent to which social support buffers against the effects of natural disasters on biological age (Aim 2), using data across aging domains. We predict that individuals with greater social support will exhibit lower biological age...