| Literature DB >> 32603655 |
Jean-Pierre Roussarie1, Vicky Yao2, Patricia Rodriguez-Rodriguez3, Rose Oughtred4, Jennifer Rust4, Zakary Plautz5, Shirin Kasturia5, Christian Albornoz5, Wei Wang5, Eric F Schmidt6, Ruth Dannenfelser7, Alicja Tadych4, Lars Brichta5, Alona Barnea-Cramer5, Nathaniel Heintz6, Patrick R Hof8, Myriam Heiman9, Kara Dolinski4, Marc Flajolet5, Olga G Troyanskaya10, Paul Greengard5.
Abstract
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 Aβ, aging, and neurodegeneration within the most vulnerable neurons in AD.Entities:
Keywords: Alzheimer's disease; PTBP1; bacTRAP; machine learning; network; selective neuronal vulnerability
Mesh:
Year: 2020 PMID: 32603655 PMCID: PMC7580783 DOI: 10.1016/j.neuron.2020.06.010
Source DB: PubMed Journal: Neuron ISSN: 0896-6273 Impact factor: 17.173