Multiscale network modeling of oligodendrocytes reveals molecular components of myelin dysregulation in Alzheimer's disease

• Type of Material: Article
• Authors: Andrew T. McKenzie, Icahn School of Medicine at Mount Sinai; Sarah Moyon, Icahn School of Medicine at Mount Sinai; Minghui Wang, Icahn School of Medicine at Mount Sinai; Igor Katsyv, Icahn School of Medicine at Mount Sinai; Won-Min Song, Icahn School of Medicine at Mount Sinai; Xianxiao Zhou, Icahn School of Medicine at Mount Sinai; Eric B Dammer, Emory University; Duc M. Duong, Emory University; Joshua Aaker, University of Chicago; Yongzhong Zhao, Icahn School of Medicine at Mount Sinai; Noam Beckmann, Icahn School of Medicine at Mount Sinai; Pei Wang, Icahn School of Medicine at Mount Sinai; Jun Zhu, Icahn School of Medicine at Mount Sinai; James J Lah, Emory University; Nicholas Seyfried, Emory University; Allan I Levey, Emory University; Pavel Katsel, Icahn School of Medicine at Mount Sinai; Vahram Haroutunian, Icahn School of Medicine at Mount Sinai; Eric E. Schadt, Icahn School of Medicine at Mount Sinai; Brian Popko, University of Chicago; Patrizia Casaccia, Icahn School of Medicine at Mount Sinai; Bin Zhang, Icahn School of Medicine at Mount Sinai
• Language: English
• Date: 2017-11-06
• Publisher: BioMed Central
• Publication Version: Final Published Version
• Copyright Statement: © 2017 The Author(s).
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1186/s13024-017-0219-3
• Title of Journal or Parent Work: Molecular Neurodegeneration
• ISSN: 1750-1326
• Volume: 12
• Issue: 1
• Start Page: 82
• End Page: 82
• Grant/Funding Information: ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association grant ADGC–10–196,728.; CHARGE was partly supported by the NIH/NIA grant R01 AG033193 and the NIA AG081220 and AGES contract N01–AG–12100, the NHLBI grant R01 HL105756, the Icelandic Heart Association, and the Erasmus Medical Center and Erasmus University.; EADI was supported by the LABEX (laboratory of excellence program investment for the future) DISTALZ grant, Inserm, Institut Pasteur de Lille, Université de Lille 2 and the Lille University Hospital.; GERAD was supported by the Medical Research Council (Grant n° 503,480), Alzheimer’s Research UK (Grant n° 503,176), the Wellcome Trust (Grant n° 082604/2/07/Z) and German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) grant n° 01GI0102, 01GI0711, 01GI0420.; R01AG046170 is a component of the AMP-AD Target Discovery and Preclinical Validation Project.; This work was supported by the NIH grants R01AG046170, U01AG052411, RF1AG054014, RF1AG057440, R01AG057907, U01AI111598–01, R01NS067550, P50AG025688, U01AG046161, and F30AG052261.; The i–Select chips was funded by the French National Foundation on Alzheimer’s disease and related disorders.
• Keywords: Neurosciences & Neurology; CNP; RNA sequencing; Alzheimer's disease; UNITED-STATES; AMYLOID PRECURSOR PROTEIN; Science & Technology; Myelin; FAST AXONAL-TRANSPORT; TRANSGENIC MICE; PROTEOLIPID PROTEIN; Neurosciences; co-expression network; Causal network; Oligodendrocyte; Life Sciences & Biomedicine; CNS MYELIN; EXPRESSION DATA; MOUSE MODEL; Differential expression; NERVOUS-SYSTEM; Proteomics; TROPHIC SUPPORT; BIN1
• Research Categories: Biology, Neuroscience; Chemistry, Biochemistry

Abstract

Background: Oligodendrocytes (OLs) and myelin are critical for normal brain function and have been implicated in neurodegeneration. Several lines of evidence including neuroimaging and neuropathological data suggest that Alzheimer's disease (AD) may be associated with dysmyelination and a breakdown of OL-axon communication. Methods: In order to understand this phenomenon on a molecular level, we systematically interrogated OL-enriched gene networks constructed from large-scale genomic, transcriptomic and proteomic data obtained from human AD postmortem brain samples. We then validated these networks using gene expression datasets generated from mice with ablation of major gene expression nodes identified in our AD-dysregulated networks. Results: The robust OL gene coexpression networks that we identified were highly enriched for genes associated with AD risk variants, such as BIN1 and demonstrated strong dysregulation in AD. We further corroborated the structure of the corresponding gene causal networks using datasets generated from the brain of mice with ablation of key network drivers, such as UGT8, CNP and PLP1, which were identified from human AD brain data. Further, we found that mice with genetic ablations of Cnp mimicked aspects of myelin and mitochondrial gene expression dysregulation seen in brain samples from patients with AD, including decreased protein expression of BIN1 and GOT2. Conclusions: This study provides a molecular blueprint of the dysregulation of gene expression networks of OL in AD and identifies key OL- and myelination-related genes and networks that are highly associated with AD.