Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis. Author Jean-Pierre Roussarie, Vicky Yao, Patricia Rodriguez-Rodriguez, Rose Oughtred, Jennifer Rust, Zakary Plautz, Shirin Kasturia, Christian Albornoz, Wei Wang, Eric Schmidt, Ruth Dannenfelser, Alicja Tadych, Lars Brichta, Alona Barnea-Cramer, Nathaniel Heintz, Patrick Hof, Myriam Heiman, Kara Dolinski, Marc Flajolet, Olga Troyanskaya, Paul Greengard Publication Year 2020 Type Journal Article 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. Keywords Animals, Mice, Gene Expression Profiling, Humans, Neurons, Aging, Alzheimer Disease, Transcriptome, Gene Regulatory Networks, Machine Learning Journal Neuron Volume 107 Issue 5 Pages 821-835.e12 Date Published 2020 Sep 09 ISSN Number 1097-4199 DOI 10.1016/j.neuron.2020.06.010 Alternate Journal Neuron PMCID PMC7580783 PMID 32603655 PubMedPubMed CentralGoogle ScholarBibTeXEndNote X3 XML