Epigenetic Aging and Cognitive Health: A Pilot Study

Chronological age is the strongest risk factor for disease, disability, and death. However, same-aged individuals may be differentially at risk because chronological time is an imperfect proxy of a person’s biological age. One promising approach to quantify biological aging is epigenetic biomarkers that use DNA methylation data to derive a person’s “epigenetic age”. Older epigenetic age, above and beyond chronological age, has been associated with increased risk of premature mortality and morbidity, however, links between epigenetic and cognitive aging are less well characterized, despite the burden of cognitive decline and dementia. The proposed pilot study aims to gather preliminary data in support of an external grant application that examines the longitudinal associations between epigenetic and cognitive aging across midlife, while addressing previous limitations in measuring epigenetic and cognitive aging. This project will leverage an existing longitudinal cohort of midlife adults with two waves of data collected 10-16 years apart to test whether accelerated epigenetic aging is predictive of future cognitive decline. In order to be competitive for this larger grant, preliminary data are needed to establish whether and to what degree (1) cognitive function and (2) epigenetic age change over the length of the 10-16 year follow-up provided by this cohort, and (3) to provisionally test in a subset of participants whether changes in epigenetic age are associated with changes in cognitive function over the follow-up interval. This pilot study, designed to provide the needed preliminary data, will examine cognitive and epigenetic aging using an extreme groups approach to identify two subgroups of individuals with different cognition trajectories over 10-16 years, and will use stored blood samples to quantify DNA methylation to estimate epigenetic age. A final aim of this project is to provide a rich training experience for undergraduates by immersing them in cutting-edge, hypothesis-driven health and aging research