Effects of a Major Natural Disaster on the Pace of Aging in a Nonhuman Primate Model

Effects of a Major Natural Disaster on the Pace of Aging in a Nonhuman Primate Model Extreme environmental effects on the pace of aging Environmental disasters are deeply damaging to the health and welfare of the human population. Major hurricanes in 2017 (Irma, Harvey, and Maria) cost thousands of lives and caused $265 billion worth of damage. These traumas have the potential to impact on the pace at which individuals age, the primary risk factor for most diseases. Identifying age-related outcomes of environmental disasters and mitigating their impact is therefore critical. But ethical and logistical considerations in human studies limit the availability of pre-disaster baseline data, as well as the ability to quantify aging across more than a few domains, e.g., molecular markers in blood, physical frailty. Disasters may acutely alter aging rates but may also result in persistent, cumulative, effects across the lifespan. Yet uncovering long-term disaster-linked aging is also challenging because humans are so long-lived. These difficulties can be overcome by using biologically-relevant nonhuman primate models living in naturalistic settings that have been exposed to natural disasters. Here, we propose to leverage our long-term cross-institutional study of aging in the rhesus macaque population of Cayo Santiago island, Puerto Rico, which was decimated by Hurricane Maria. Damage to Cayo Santiago included destruction of all man-made structures, the death of >95% of vegetation, and submergence of all lower parts of the island. Nonetheless, almost all of our long-term study subjects survived. Our objective is to use this unique natural experiment to quantify how an extreme natural disaster affects the pace of aging across domains (molecular, physiological, physical, and social) (Aim 1) and to test if these effects persist across the lifespan (Aim 2). We posit that natural disasters increase the pace of aging across domains and that these effects persist for years after the initial event. We will compare aging rates before and after the hurricane across multiple tissue types (Aim 1a) and within individuals that lived through the storm (Aim 1b), and will quantify aging rates after the storm for up to half of the lifespan of subjects (Aim 2).