A Transcription Factor Map as Revealed by a Genome-Wide Gene Expression Analysis of Whole-Blood mRNA Transcriptome in Multiple Sclerosis
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Mellor, Drew
Gandhi, Kaushal S
McKay, Fiona C
Cox, Mathew B
Berretta, Regina
Vaezpour, S Yahya
Inostroza-Ponta, Mario
Broadley, Simon A
Heard, Robert N
Vucic, Stephen
Stewart, Graeme J
Williams, David W
Scott, Rodney J
Lechner-Scott, Jeanette
Booth, David R
Moscato, Pablo
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Abstract
Background Several lines of evidence suggest that transcription factors are involved in the pathogenesis of Multiple Sclerosis (MS) but complete mapping of the whole network has been elusive. One of the reasons is that there are several clinical subtypes of MS and transcription factors that may be involved in one subtype may not be in others. We investigate the possibility that this network could be mapped using microarray technologies and contemporary bioinformatics methods on a dataset derived from whole blood in 99 untreated MS patients (36 Relapse Remitting MS, 43 Primary Progressive MS, and 20 Secondary Progressive MS) and 45 age-matched healthy controls. Methodology/Principal Findings We have used two different analytical methodologies: a non-standard differential expression analysis and a differential co-expression analysis, which have converged on a significant number of regulatory motifs that are statistically overrepresented in genes that are either differentially expressed (or differentially co-expressed) in cases and controls (e.g., V
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PloS One
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5
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12
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© 2010 Griffiths et al. This is an Open Access article distributed under the terms of the Creative Commons Attribution License CCAL. (http://www.plos.org/journals/license.html)
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Medical and Health Sciences not elsewhere classified