Selective Neuronal Vulnerability in Alzheimer’s Disease: A Network-Based Analysis

• Published in: Neuron (Cambridge, Mass.) Vol. 107; no. 5; pp. 821 - 835.e12
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: Cambridge Elsevier Inc 09.09.2020; Elsevier Limited
• Subjects: Age; Aging; Alzheimer's disease; Artificial chromosomes; bacTRAP; Brain; Disease; Gene expression; Genomes; machine learning; Molecular modelling; network; Neurodegeneration; Neurodegenerative diseases; Neurons; Pathology; Proteins; PTBP1; Quantitative genetics; selective neuronal vulnerability; PTBP1; bacTRAP; machine learning; Alzheimer's disease; selective neuronal vulnerability; network
• ISSN: 0896-6273; 1097-4199; 1097-4199
• DOI: 10.1016/j.neuron.2020.06.010

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. •Ribosomal profiling of AD vulnerable/resistant neurons in 5-, 12-, 24-month old mice•Using human neuron-type functional networks and GWASs to model vulnerability•Identification of axon plasticity genes linking Aß, aging, tau in vulnerable neurons•PTB, regulator of tau exon 10 splicing, might contribute to selective vulnerability Neurons display different levels of vulnerability to Alzheimer’s pathology. Roussarie et al. experimentally profile and computationally model several relevant neuron types. Using a mouse-human framework, they identify genes linking Aß, aging, and tau in vulnerable neurons. Finally, they show experimentally that PTB, a regulator of tau splicing, contributes to vulnerability.