Patterns of Natural Aging and the Role of Senescence Registry

The primary purpose of this registry is to collect aging biomarker data in a general population across the entire lifespan (Aging Cohort). The investigators will then build several computational models of aging in order to better understand senescence in the context of general aging or specific aging associate diseases. As a secondary goal, The investigators will determine the association between biomarkers of aging and health characteristics (defined through blood chemistry panels and specific functional measures). Central to these computational models is the measurement of a biomarker of aging/senescence, p16INK4 (hereafter referred to as p16) in peripheral blood T cells. The primary aim of this registry is to determine if p16 mRNA expression measured in T cells reflects total organismal senescent load. The secondary aim is to determine if senescence dynamics are affected by age-associated chronic diseases. The exploratory aim is to determine the ability of computational models of senescence to predict clinical and functional status. Active participation in the study will end at the completion of the study questionnaires and assessments, but The investigators will ask permission to recontact participants at a later date for longitudinal sample collection. Despite the prominence of senescence as an aging mechanism and target of geroscience-based therapies, little is known about the dynamics of senescent cells in humans. Understanding the process of senescence, including its regulation, dynamics, and contribution to physiologic or pathologic processes, is essential for an understanding of aging. In this registry, the investigators will assess the contribution of senescence, co-morbidities, functional performance, and quality of life to aging. The investigators will determine the ability of these factors to aid in the development of a new stochastic model that will be formulated specifically in the context of T-cell turnover and senescence, thereby providing a cell level description of p16 accumulation and a mechanistic model with parameters characterizing relevant physiological processes. The development of this new model will thus enable a quantitative, predictive, mechanistic study of the role of senescence in aging at both organismal and cellular levels