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Author Notes:

Correspondence: Patrizia.Casaccia@mssm.edu

Conceptualization, ATM, SM, BZ and PC

Methodology, ATM, SM, BZ and PC

Software, ATM, MW, IK, W-MS, XZ, ED, JZ and BZ

Investigation, ATM, SM, BZ and PC

Resources, ATM, SM, BP, JA, K-A N, ED, DD, JL, NS, AL, EE, B.Z and PC

Writing – Original Draft, ATM

Writing – Review & Editing All Authors

Supervision, BZ and PC

Funding Acquisition, BZ and PC.

All authors read and approved the final manuscript.

We would like to thank members of the Zhang and Casaccia labs for many fruitful discussions.

We thank the International Genomics of Alzheimer’s Project (IGAP) for providing summary results data for these analyses.

IGAP was made possible by the generous participation of the control subjects, the patients, and their families.

The authors declare that they have no competing interests.

Subjects:

Research Funding:

This work was supported by the NIH grants R01AG046170, U01AG052411, RF1AG054014, RF1AG057440, R01AG057907, U01AI111598–01, R01NS067550, P50AG025688, U01AG046161, and F30AG052261.

R01AG046170 is a component of the AMP-AD Target Discovery and Preclinical Validation Project.

The i–Select chips was funded by the French National Foundation on Alzheimer’s disease and related disorders.

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.

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.

ADGC was supported by the NIH/NIA grants: U01 AG032984, U24 AG021886, U01 AG016976, and the Alzheimer’s Association grant ADGC–10–196,728.

Keywords:

  • Science & Technology
  • Life Sciences & Biomedicine
  • Neurosciences
  • Neurosciences & Neurology
  • Alzheimer's disease
  • Oligodendrocyte
  • Myelin
  • co-expression network
  • Causal network
  • RNA sequencing
  • Proteomics
  • Differential expression
  • CNP
  • BIN1
  • AMYLOID PRECURSOR PROTEIN
  • FAST AXONAL-TRANSPORT
  • PROTEOLIPID PROTEIN
  • NERVOUS-SYSTEM
  • CNS MYELIN
  • TRANSGENIC MICE
  • TROPHIC SUPPORT
  • EXPRESSION DATA
  • UNITED-STATES
  • MOUSE MODEL

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

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Journal Title:

Molecular Neurodegeneration

Volume:

Volume 12, Number 1

Publisher:

, Pages 82-82

Type of Work:

Article | Final Publisher PDF

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.

Copyright information:

© 2017 The Author(s).

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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