Computer Science

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Browsing Computer Science by Subject "bacTRAP"

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    Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis
    (Elsevier, 2020) Roussarie, Jean-Pierre; Yao, Vicky; Rodriguez-Rodriguez, Patricia; Oughtred, Rose; Rust, Jennifer; Plautz, Zakary; Kasturia, Shirin; Albornoz, Christian; Wang, Wei; Schmidt, Eric F.; Dannenfelser, Ruth; Tadych, Alicja; Brichta, Lars; Barnea-Cramer, Alona; Heintz, Nathaniel; Hof, Patrick R.; Heiman, Myriam; Dolinski, Kara; Flajolet, Marc; Troyanskaya, Olga G.; Greengard, Paul
    A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerability, a key characteristic of the disease. Here, we present a framework integrating high-quality neuron-type-specific molecular profiles across the lifetime of the healthy mouse, which we generated using bacTRAP, with postmortem human functional genomics and quantitative genetics data. We demonstrate human-mouse conservation of cellular taxonomy at the molecular level for neurons vulnerable and resistant in AD, identify specific genes and pathways associated with AD neuropathology, and pinpoint a specific functional gene module underlying selective vulnerability, enriched in processes associated with axonal remodeling, and affected by amyloid accumulation and aging. We have made all cell-type-specific profiles and functional networks available at http://alz.princeton.edu. Overall, our study provides a molecular framework for understanding the complex interplay between A?, aging, and neurodegeneration within the most vulnerable neurons in AD.