Cognitively Defined Alzheimer's Subgroups: Natural history, neuropathology, and life course ramifications

Clinical heterogeneity is common in late-onset Alzheimer's disease (AD). This heterogeneity leads to the question of whether there are biologically distinct subsets of people with Alzheimer's disease. Precision medicine strategies can categorize people with a condition into subgroups and treat each subgroup differently to improve overall treatment success. Project 2 addresses whether cognitive data can be used to similarly categorize “Alzheimer's disease.” The investigators use cognitive testing data from the time of Alzheimer's diagnosis to define subgroups. They use scores from memory, executive functioning, language, and visuospatial functioning and compare those scores to each other. The modal pattern has all scores relatively similar to each other (AD-No Domains). There are four groups where scores in one domain are much worse than the other domains – AD-Memory, AD-Executive Functioning, AD-Language, and AD-Visuospatial. There are people who have multiple domains with worse scores (AD-Multiple Domains). The investigators have previously found important genetic, clinical, and imaging differences that correspond to these subgroups. The overall goal of Project 2 is to leverage Adult Changes in Thought (ACT) U19 Research Program resources to further scientific understanding of cognitively defined Alzheimer's disease subgroups. Specific Aims are: Aim 1. Define the evolution of regional brain atrophy across cognitively-defined subgroups. The investigators will leverage clinical MRI scans, research MRI scans including some obtained for this project, ex vivo scans, and 3D brain data derived from digital photographs of brain slices at autopsy. Aim 2. Determine neuropathological change across cognitively-defined subgroups. The investigators will leverage ACT's tremendous neuropathology resources, including extensive new sampling, digital slide scanning, and approaches that robustly quantify neuropathology findings including deep learning methods. Aim 3. Determine the clinical, functional, living situation, caregiver network, and economic ramifications of cognitively defined subgroups. The investigators will leverage ACT's infrastructure to collect data from extensive medical records, collect new data from people with Alzheimer's and their families and caregivers, and perform careful quantitative and qualitative analyses to determine whether there are differences across subgroups in clinical, functional, living situation, caregiver network, or economic implications. Taken together, these investigations will more firmly establish the implications of cognitively defined subgroups, furthering our progress towards personalized medicine approaches to ameliorate the scourge of Alzheimer's disease.