Alzheimer’s disease (AD), the leading cause of dementia in the elderly, is a progressive and fatal neurodegenerative disease that affects 40-50 million people worldwide1. Pathologically, AD is characterized by intracellular hyperphosphorylated tau aggregates and extracellular-amyloid plaques, which coincide with the activation of innate immunity, gliosis induced by activated microglia and reactive astrocytes, white matter degeneration, dysfunctions in oligodendrocytes, and neuronal loss2-5. Genome-wide association studies (GWAS) have identified >30 AD genetic risk loci, many of which are related to innate immunity and microglial function, including APOE and TREM2 variants, which are associated with high genetic risks for sporadic AD6-10. Numerous studies have shown that AD pathology spreads from regions like the medial temporal lobe to the cortex11,12. However, the molecular mechanisms underlying the cell- and region-specific distribution of AD pathology during AD progression are still not fully elucidated. The transcriptome of the AD brain can pinpoint key differences in disease that may be crucial for elucidating the pathogenesis of AD and for developing disease-modifying therapeutics for the prevention and treatment of AD. To develop effective cell therapies for AD, it is necessary to know the spatial distribution of different immune and glial cells in AD brains and how they interact with neuronal cells during AD. Such precise knowledge is required for precision medicine and therapeutic development of small molecules and their delivery to a specific tissue domain. This project addresses key computational challenges in the analysis of spatial transcriptomics, single-cell/single-nucleus RNA-seq data, and single-cell ATAC-seq data generated from Alzheimer’s disease studies.
In collaboration with: Bing Yao, Yangping Li