Grant: Summer Program in Aging

Alzheimer's disease (AD) affects the brain years, if not decades, before symptoms emerge. As such, we want to find factors that predict the later onset or relative severity of the disease. Reduced sociality predicts later negative symptoms of AD such as poorer memory. What is not known, however, is whether objective social isolation (e.g., how many people you interact with) or the subjective experience of social isolation (e.g., how lonely you feel) have differential impacts on AD progression. By understanding their unique impacts, we can develop more targeted interventions for reducing disease burden. A unique challenge to this work is that AD affects the brain and behavior at different points in time, necessitating models that effectively integrate longitudinal and multi-method (brain + behavior) evaluations. Therefore, we will conduct analyses on two datasets from individuals at high-risk for developing AD. The Rush AD Center Memory and Aging Project (1997-, N=2177) has a larger sample size and more annual timepoints per person. We will thus leverage it to develop models of the temporal sequencing of changes in clinical, cognitive, and objective and subjective social isolation. For example, we hypothesize that increases in subjective social isolation, controlling for objective social isolation, will predict cognitive declines that characterize the pre-symptomatic to symptomatic phases of AD. We will then test those models in the PREVENT-AD dataset (2011-, N=385) that has the added advantage of longitudinal neuroimaging and in-vivo AD pathology measures of brain health. As such, we will have a more sensitive characterization of when social factors influence older adults' brain health than a clinical diagnosis, usually based on cognitive changes, alone. Taken together, this work will make significant scientific and translational contributions by identifying social risk factors for the more rapid development of AD symptoms.