QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

HOME  |   SEARCH  |   ARCHIVE  |   SUBSCRIBE  |   CONTACT  |   HELP

The Journal of Neuroscience, February 6, 2008, 28(6):1410-1420; doi:10.1523/JNEUROSCI.4098-07.2008

This Article Full Text Full Text (PDF) Supplemental Data Submit an eLetter Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (10) Citing Articles via Google Scholar Google Scholar Articles by Miller, J. A. Articles by Geschwind, D. H. Search for Related Content PubMed PubMed Citation Articles by Miller, J. A. Articles by Geschwind, D. H.

 Previous Article  |  Next Article 

Neurobiology of Disease
A Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging

Jeremy A. Miller,^2,3 Michael C. Oldham,² and Daniel H. Geschwind^1,3

¹Department of Neurology, ²Interdepartmental Program for Neuroscience, and ³Center for Neurobehavioral Genetics, University of California, Los Angeles, Los Angeles, California 90095-1769

Correspondence should be addressed to Daniel H. Geschwind, Department of Neurology, University of California, Los Angeles, 710 Westwood Plaza, Los Angeles, CA 90095-1769. Email: dhg{at}mednet.ucla.edu

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting millions of elderly individuals worldwide. Advances in the genetics of AD have led to new levels of understanding and treatment opportunities. Here, we used a systems biology approach based on weighted gene coexpression network analysis to determine transcriptional networks in AD. This method permits a higher order depiction of gene expression relationships and identifies modules of coexpressed genes that are functionally related, rather than producing massive gene lists. Using this framework, we characterized the transcriptional network in AD, identifying 12 distinct modules related to synaptic and metabolic processes, immune response, and white matter, nine of which were related to disease progression. We further examined the association of gene expression changes with progression of AD and normal aging, and were able to compare functional modules of genes defined in both conditions. Two biologically relevant modules were conserved between AD and aging, one related to mitochondrial processes such as energy metabolism, and the other related to synaptic plasticity. We also identified several genes that were central, or hub, genes in both aging and AD, including the highly abundant signaling molecule 14.3.3 (YWHAZ), whose role in AD and aging is uncharacterized. Finally, we found that presenilin 1 (PSEN1) is highly coexpressed with canonical myelin proteins, suggesting a role for PSEN1 in aspects of glial-neuronal interactions related to neurodegenerative processes.

Key words: microarray; presenilin; systems biology; WGCNA; Alzheimer's disease; aging

---

Received Sept. 6, 2007; revised Nov. 28, 2007; accepted Dec. 6, 2007.

Correspondence should be addressed to Daniel H. Geschwind, Department of Neurology, University of California, Los Angeles, 710 Westwood Plaza, Los Angeles, CA 90095-1769. Email: dhg{at}mednet.ucla.edu

This article has been cited by other articles:

				M. Kayano, I. Takigawa, M. Shiga, K. Tsuda, and H. Mamitsuka Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data Bioinformatics, November 1, 2009; 25(21): 2735 - 2743. [Abstract] [Full Text] [PDF]

				A. Auffret, V. Gautheron, M. Repici, R. Kraftsik, H. T. J. Mount, J. Mariani, and C. Rovira Age-Dependent Impairment of Spine Morphology and Synaptic Plasticity in Hippocampal CA1 Neurons of a Presenilin 1 Transgenic Mouse Model of Alzheimer's Disease J. Neurosci., August 12, 2009; 29(32): 10144 - 10152. [Abstract] [Full Text] [PDF]

				D. J. Pappas, G. Coppola, P. A. Gabatto, F. Gao, D. H. Geschwind, J. R. Oksenberg, and S. E. Baranzini Longitudinal system-based analysis of transcriptional responses to type I interferons Physiol Genomics, August 7, 2009; 38(3): 362 - 371. [Abstract] [Full Text] [PDF]

Home  |   Search  |   Archive  |   Subscribe  |   Contact  |   Help