Multiscale causal networks identify VGF as a key regulator of Alzheimer’s disease

Noam D. Beckmann, Wei Jye Lin, Minghui Wang, Ariella T. Cohain, Alexander W. Charney, Pei Wang, Weiping Ma, Ying Chih Wang, Cheng Jiang, Mickael Audrain, Phillip H. Comella, Amanda K. Fakira, Siddharth P. Hariharan, Gillian M. Belbin, Kiran Girdhar, Allan I. Levey, Nicholas T. Seyfried, Eric B. Dammer, Duc Duong, James J. LahJean Vianney Haure-Mirande, Ben Shackleton, Tomas Fanutza, Robert Blitzer, Eimear Kenny, Jun Zhu, Vahram Haroutunian, Pavel Katsel, Sam Gandy, Zhidong Tu, Michelle E. Ehrlich, Bin Zhang, Stephen R. Salton, Eric E. Schadt

Research output: Contribution to journalArticlepeer-review

47 Scopus citations

Abstract

Though discovered over 100 years ago, the molecular foundation of sporadic Alzheimer’s disease (AD) remains elusive. To better characterize the complex nature of AD, we constructed multiscale causal networks on a large human AD multi-omics dataset, integrating clinical features of AD, DNA variation, and gene- and protein-expression. These probabilistic causal models enabled detection, prioritization and replication of high-confidence master regulators of AD-associated networks, including the top predicted regulator, VGF. Overexpression of neuropeptide precursor VGF in 5xFAD mice partially rescued beta-amyloid-mediated memory impairment and neuropathology. Molecular validation of network predictions downstream of VGF was also achieved in this AD model, with significant enrichment for homologous genes identified as differentially expressed in 5xFAD brains overexpressing VGF. Our findings support a causal role for VGF in protecting against AD pathogenesis and progression.

Original languageEnglish
Article number3942
JournalNature Communications
Volume11
Issue number1
DOIs
StatePublished - 1 Dec 2020

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