Recent findings in the genetics underlying Alzheimer's disease (AD), the leading cause of late- onset dementia, suggest that AD pathophysiology is driven primarily by four biological processes: cholesterol metabolism, immune response, endosomal trafficking, and cytoskeletal systems. Among these, endosomal trafficking has received relatively less attention. Underscoring its potential importance to AD development is that a substantial number of variants associated with familial AD and sporadic or late-onset AD have direct or indirect functional connections to endosomal trafficking. However, there is currently no clear picture of the molecular and cellular players and to what extent their participation in endosomal trafficking contribute to AD pathophysiology. In this application, we propose to leverage our computational and experimental expertise to build upon our recent unexpected findings of the roles of AD risk variants in endosome trafficking to provide a detailed picture at the molecular, cellular, and gene-clusters network levels for how endosomal trafficking impacts AD pathophysiology. We integrate highly innovative in-house bioinformatics platform, with single-cell transcriptomics of human postmortem AD samples, and the powerful genetics of yeast and human induced stem cells (iPSCs) to identify, validate, and illuminate the biological consequences of AD risk endosomal genes. Our multimodal strategy will shed light on how disruptions in endosomal trafficking could contribute to AD pathogenesis, opening up new avenues for novel therapeutic targeting toward the search for effective treatments.
Alzheimer?s disease (AD) is the most common neurodegenerative disease, affecting 1 in 8 people older than 65 in the US. Converging lines of evidence point to defects in endosomal trafficking as an important factor contributing to the development of AD, but we have a relatively poor understanding of the mechanisms by which endosomal pathway disruptions impact AD pathophysiology. Here, we leverage our computational and experimental expertise to identify novel AD-associated endosomal gene candidates and generate a detailed picture for how disrupted functions of known and novel AD-associated endosomal genes operate at the genetic, molecular, cellular, and organoid levels and give rise to AD pathophysiology.
