4.6 Article

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

期刊

MOLECULAR NEURODEGENERATION
卷 12, 期 -, 页码 -

出版社

BIOMED CENTRAL LTD
DOI: 10.1186/s13024-017-0219-3

关键词

Alzheimer's disease; Oligodendrocyte; Myelin; co-expression network; Causal network; RNA sequencing; Proteomics; Differential expression; CNP; BIN1

资金

  1. NIH [R01AG046170, U01AG052411, RF1AG054014, RF1AG057440, R01AG057907, U01AI111598-01, R01NS067550, P50AG025688, U01AG046161, F30AG052261]
  2. French National Foundation on Alzheimer's disease and related disorders
  3. LABEX (laboratory of excellence program investment for the future) DISTALZ grant
  4. Inserm
  5. Institut Pasteur de Lille
  6. Universite de Lille 2
  7. Lille University Hospital
  8. Medical Research Council [503,480]
  9. Alzheimer's Research UK [503,176]
  10. Wellcome Trust [082604/2/07/Z]
  11. German Federal Ministry of Education and Research (BMBF): Competence Network Dementia (CND) [01GI0102, 01GI0711, 01GI0420]
  12. NIH/NIA [R01 AG033193, U01 AG032984, U24 AG021886, U01 AG016976]
  13. NIA [AG081220]
  14. AGES [N01-AG-12100]
  15. NHLBI [R01 HL105756]
  16. Icelandic Heart Association
  17. Erasmus Medical Center
  18. Erasmus University
  19. Alzheimer's Association [ADGC-10-196,728]

向作者/读者索取更多资源

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.

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