Roussarie, Jean-PierreYao, VickyRodriguez-Rodriguez, PatriciaOughtred, RoseRust, JenniferPlautz, ZakaryKasturia, ShirinAlbornoz, ChristianWang, WeiSchmidt, Eric F.Dannenfelser, RuthTadych, AlicjaBrichta, LarsBarnea-Cramer, AlonaHeintz, NathanielHof, Patrick R.Heiman, MyriamDolinski, KaraFlajolet, MarcTroyanskaya, Olga G.Greengard, Paul2020-10-162020-10-162020Roussarie, Jean-Pierre, Yao, Vicky, Rodriguez-Rodriguez, Patricia, et al.. "Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis." <i>Neuron,</i> 107, no. 5 (2020) Elsevier: 821-835.e12. https://doi.org/10.1016/j.neuron.2020.06.010.https://hdl.handle.net/1911/109419A 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.engThis is an open access article under the CC BY licenseJournal articleAlzheimer's diseaseselective neuronal vulnerabilitybacTRAPnetworkmachine learningPTBP1https://doi.org/10.1016/j.neuron.2020.06.010