PROJECT SUMMARY/ABSTRACT New submission for PA-20-185 (NOT-AG-21-020: Maximizing the Scientific Value of Secondary Analyses of Existing Cohorts and Datasets in Order to Address Research Gaps and Foster Additional Opportunities in Aging Research). Over the last decade, there have been increased efforts to improve early detection of Alzheimer’s disease and related dementias (AD/ADRD), with most of these efforts focused on pathological and biomarker changes. However, there also continues to be critical gaps in our understanding of cognitive changes in the early stages of AD/ADRD, despite cognitive and subsequent functional changes ultimately having the greatest direct impact on the lives of people living with AD/ADRD and their loved ones. Specifically, little work has comprehensively investigated the cognitive heterogeneity within older adults who do not yet meet criteria for mild cognitive impairment (MCI), but who may be showing subtle cognitive difficulties. This subtle cognitive decline/pre-MCI phase may be a critical window of opportunity for early intervention and planning, so refining our understanding of the earliest cognitive changes associated with AD/ADRD is crucial. Our work using a data-driven approach to understand the heterogeneity of MCI has shown specific subtypes beyond the traditional amnestic/non-amnestic distinction that show unique patterns of cortical thinning, AD biomarker profiles, and rates of cognitive decline and progression to dementia. In this project, we will leverage the rich longitudinal data from the Atherosclerosis Risk in Communities (ARIC) Study and Baltimore Longitudinal Study of Aging (BLSA) and use a data-driven approach to characterize the cognitive heterogeneity in older adults who do not yet show cognitive impairments consistent with MCI or dementia. The ARIC Study and BLSA include diverse samples recruited from the community, which will allow for greater generalization of results beyond the typical memory clinic samples. The aims of this project include: 1) Derive cognitive phenotypes among cognitively unimpaired older adults (i.e., no MCI or dementia) using latent profile analysis of individual neuropsychological measures, 2) Determine the mid- and late-life vascular risk factors (diabetes, hypertension), physical activity levels, and AD biomarkers (e.g., plasma, MRI) that predict membership to the cognitive phenotype groups (e.g., low-memory, low-executive, etc.), and 3) Examine the longitudinal outcomes associated with the cognitive phenotypes, including rates of progression to MCI/dementia, rates of cognitive/functional decline, and rates of brain atrophy and white matter hyperintensity volume changes. Results from this study have the potential to improve our understanding of the types of cognitive profiles that emerge as the earliest changes associated with AD/ADRD. Determining these unique subtle cognitive decline subtypes plus associated biomarker and risk/resilience profiles and risk of progression...