Friday, July 26, 2024
7/26/2024
PROJECT SUMMARY In response to NOT-AG-23-031, we propose to use the same approach/technique as in the technology-driven parental application to analyze postmortem dorsolateral prefrontal cortex samples from the spectrum of Alzheimer’s (AD) subjects. Classical single-cell Omics (RNA-seq, ATAC-seq, Cut&Tag) provide information at individual gene/locus level, but the sparse coverage of each cell (particularly for histone modifications profiling using Cut&Tag) limits the predictive power. The imaging approach proposed here, while not resolving individual loci, captures the integral cellular state and the dominant changes in chromatin and epigenetic topography (e.g. ImAge captures the dominant aging changes). Although the importance of cellular heterogeneity in AD has been recognized, most efforts are focused on single cell RNA-sequencing. We propose to focus on the single cell epigenetic topography, taking advantage of a powerful imaging-based chromatin and epigenetic analysis technique recently pioneered by the PI laboratory. Preserving the original framework focused on applying novel imaging-based technology, we will quantitate single cell heterogeneity in AD spectrum brains and associate trajectories of epigenetic changes in major brain cell types with gene expression and cognitive decline of AD. Further, we will determine the connection between aging trajectories during normal brain aging and the pathological progression of AD. We propose to map epigenetic changes across 150 brain samples of AD spectrum with corresponding gene expression and functional readouts to reveal the correlations of epigenetic and expression changes with cognitive decline and AD progression. First, this will enable an accurate assessment of single cell chromatin and epigenetic heterogeneity in the dorsolateral prefrontal cortex (DLPFC) from the spectrum of AD and normal young adult brains. Second, we will interrogate unbiased emergence trajectories and examine their correlation with 80 functional readouts available for each brain sample. Third, we will explore the relationship between the normal aging process and AD progression. We will deliver the proof of feasibility and a unique single cell level epigenetic dataset that will advance AD/ADRD research. The available matching skeletal muscle samples and associated omics datasets could be integrated into the analysis to compare and contrast the trajectories of normal aging and AD progression. Although this proposal employs bulk RNA-seq data, a powerful single cell RNA-seq approach becomes increasingly available and will be integrated in future studies. The availability of PBMC from a subset of the AD cohort enables us in the future to connect the above dependencies to epigenetic signatures in PBMC, which could be assayed longitudinally and used for early diagnosis of AD.
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