Title |
Multiscale network modeling of oligodendrocytes reveals molecular components of myelin dysregulation in Alzheimer’s disease
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Published in |
Molecular Neurodegeneration, November 2017
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DOI | 10.1186/s13024-017-0219-3 |
Pubmed ID | |
Authors |
Andrew T. McKenzie, Sarah Moyon, Minghui Wang, Igor Katsyv, Won-Min Song, Xianxiao Zhou, Eric B. Dammer, Duc M. Duong, Joshua Aaker, Yongzhong Zhao, Noam Beckmann, Pei Wang, Jun Zhu, James J. Lah, Nicholas T. Seyfried, Allan I. Levey, Pavel Katsel, Vahram Haroutunian, Eric E. Schadt, Brian Popko, Patrizia Casaccia, Bin Zhang |
Abstract |
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. 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. 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. 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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Finland | 1 | 17% |
United States | 1 | 17% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
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Scientists | 3 | 50% |
Members of the public | 2 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 129 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 29 | 22% |
Researcher | 26 | 20% |
Student > Master | 16 | 12% |
Student > Bachelor | 10 | 8% |
Student > Doctoral Student | 6 | 5% |
Other | 18 | 14% |
Unknown | 24 | 19% |
Readers by discipline | Count | As % |
---|---|---|
Neuroscience | 28 | 22% |
Biochemistry, Genetics and Molecular Biology | 27 | 21% |
Agricultural and Biological Sciences | 21 | 16% |
Computer Science | 4 | 3% |
Medicine and Dentistry | 4 | 3% |
Other | 18 | 14% |
Unknown | 27 | 21% |