Integrating Single-Cell Genomics for Pathways to Protection and Resilience Against Alzheimer’s Disease

Until recently, postmortem observation of amyloid beta and tau neurofibrillary tangles has been sufficient for a definitive diagnosis of Alzheimer’s disease (AD). A significant proportion of individuals preserve cognitive function despite meeting neuropathological criteria for AD at autopsy, known as cognitive resilience. Studying these exceptional individuals to understand the underlying molecular mechanisms of resilience can provide a powerful suite of targets for therapeutic intervention. With the aim of defining the molecular and cellular signatures of cognitive resilience against AD, this study integrates single-cell genomics, pathway analysis, and rare variant-associated genes to identify sets of molecules (“signatures”) that confer protection against AD. To define these systems of protection—and, consequently, establish powerful, prioritized targets for treating AD—we need to identify and characterize their molecular signatures and biological pathways. By examining single-cell genomic (“scRNA-seq”) expression of genes found in each individual cell in diseased and resilient postmortem brain tissue, we can precisely map functions across cellular populations, revealing pathogenic and protective pathways. Our approach builds on a treasure trove of data from the Cure Alzheimer’s Fund CIRCUITS consortium and the Alzheimer’s Genome Project, integrating multimodal omics to create a comprehensive functional map of AD. This map will guide the development of precise 3D cellular models for drug discovery and mechanistic exploration. Key insights from rare variant-associated genes will further pinpoint critical neuronal sub-populations involved in AD protection. These rich but complex datasets will be managed through the Genedex platform (developed by our laboratory), facilitating the application of these signatures in Alzheimer’s-in-a–dish models. Our integrated approach aims to improve our understanding of AD resilience mechanisms and to exploit this knowledge to find effective disease-modifying therapies.