Life-space, isolation, and functional exposome study in preclinical Alzheimer's disease and cognitive environments (LIFESPACE)

PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) is a global public health priority as nearly 55 million of the world’s population live with dementia, with cases projected to triple to 150 million by 2050. Dementia prevalence varies across populations, and differences are due to complex relationships across demographic and social determinants of health (SDOH). Social isolation may lead to decreased cognitive stimulation, more stress and depression, higher physical inactivity, and increased neuroinflammation among older adults (OA). The overarching goal of this study is to examine and improve the validity and the generalizability of digital signals collected from everyday life, ranging from driving to other activities of daily living, in identifying biological AD using a large, diverse cohort. Our Specific Aims will (1) Determine the ability of digital markers of social isolation (smartwatch) and life space (datalogger) to cross-sectionally distinguish between OA with/without preclinical AD and cognitive impairment, (2) Model longitudinal trajectories as a function of driving behavior and physical activity to determine if OA with preclinical AD experiences greater life space constriction and social isolation over time, (3) Explore the effects of S/SDOH factors, including air pollution (PM2.5), neighborhood deprivation, green space, and cognitive stimulation on social isolation and life space. To accomplish this, a multidisciplinary team of experts will jointly assemble cohorts representing two geographically distinct and socio-cultural diverse sites (St. Louis, Greenville). We will capitalize on existing institutional infrastructure to longitudinally follow 350 cognitively normal older adults in St. Louis and 150 cognitively normal older adults in Greenville. This study will prospectively collect cross-sectional data on molecular plasma biomarkers, SDOH, and longitudinal digital markers, including naturalistic driving and physical activity/mobility for three to five years. This proposal is one of the first to examine preclinical AD, the natural environment, and longitudinal data on life space and social mobility. Once obtained, this knowledge can be used to map digital signals from daily life as a neurobehavioral biomarker that may be monitored and used for clinical trials and interventions throughout the disease progression of AD.