alexa An Exploratory Analysis of Conservation of Co-Expressed Genes across Alzheimer's disease Progression | OMICS International | Abstract
ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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Research Article

An Exploratory Analysis of Conservation of Co-Expressed Genes across Alzheimer's disease Progression

Pradeep Chowriappa*, Prerna Dua and Walter J Lukiw

Department of Computer Science, 241 Nethken Hall, Louisiana Tech University, Ruston, LA - 71272, USA

*Corresponding Author:
Pradeep C
Department of Computer Science
241 Nethken Hall
Louisiana Tech University
Ruston, LA - 71272, USA
Tel: +001-31-82574612
Fax: +001-31-82574922
E-mail: [email protected]

Received date: August 07, 2013; Accepted date: August 26, 2013; Published date: August 31, 2013

Citation: Pradeep C, Prerna D, Lukiw WJ (2013) An Exploratory Analysis of Conservation of Co-Expressed Genes across Alzheimer’s disease Progression. J Comput Sci Syst Biol 6:215-227. doi:10.4172/jcsb.1000119

Copyright: © 2013 Pradeep C, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Alzheimer’s disease (AD) is a complex disease where the analysis of gene expression patterns relies on computational techniques to understand the cause and progression of the disease. Evidence postulates that the complexity of AD stems from the overlap of early-stage markers with normal aging. Furthermore, there is increasing evidence suggesting that gene co-regulation in AD plays a vital role in the progression of the disease. The aim of this work is to identify and track co-regulated genes from incipient to severe cases of AD i.e. samples that exhibited progression of AD. We hypothesize that co-expressed genes associated with two markers of AD (the cognitive marker-mini mental state examination (MMSE) and the pathological marker Neurofibrillary Tangles (NFT)), are conserved across AD progression. For our analysis we used the Blalock dataset and the prominent tool weighted correlation network analysis (WGCNA). Through our analysis we observed that genes GNA11 and MAP2K2 were consistently ranked through the progression of AD. The functional analysis of the identified co-regulated genes at the incipient stages of AD includes RNA and cofactor binding. Through this exploratory study we conclude that from incipient to severe stages of AD the gamut of co-regulated genes vary rather than being conserved across disease severity.


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