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A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in Multiple Sclerosis

Citation

Riveros, C and Mellor, D and Gandhi, KS and McKay, FC and Cox, MB and Berretta, R and Vaezpour, SY and Inostroza-Ponta, M and Broadley, SA and Heard, RN and Vucic, S and Stewart, GJ and Williams, DW and Scott, RJ and Lechner-Scott, J and Booth, DR and Moscato, P and Bahlo, M and Brown, MA and Browning, BL and Browning, SR and Butzkueven, H and Carroll, WM and Danoy, P and Field, J and Foote, SJ and Griffiths, LR and Kermode, AG and Kilpatrick, TJ and Mason, D and Perreau, VM and Slee, M and Stankovich, J and Taylor, BV and Wiley, J, A transcription factor map as revealed by a genome-wide gene expression analysis of whole-blood mRNA transcriptome in Multiple Sclerosis , P L o S One, 5, (12) EJ ISSN 1932-6203 (2010) [Refereed Article]

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Copyright Statement

Copyright: © 2010 Riveros 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.

Official URL: http://www.plosone.org/

DOI: doi:10.1371/journal.pone.0014176

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$KROX_Q6, p-value ,3.31E-6; V$CREBP1_Q2, p-value ,9.93E-6, V$YY1_02, p-value ,1.65E-5). Conclusions/Significance: Our analysis uncovered a network of transcription factors that potentially dysregulate several genes in MS or one or more of its disease subtypes. The most significant transcription factor motifs were for the Early Growth Response EGR/KROX family, ATF2, YY1 (Yin and Yang 1), E2F-1/DP-1 and E2F-4/DP-2 heterodimers, SOX5, and CREB and ATF families. These transcription factors are involved in early T-lymphocyte specification and commitment as well as in oligodendrocyte dedifferentiation and development, both pathways that have significant biological plausibility in MS causation.

Item Details

Item Type:Refereed Article
Research Division:Medical and Health Sciences
Research Group:Clinical Sciences
Research Field:Medical Genetics (excl. Cancer Genetics)
Objective Division:Health
Objective Group:Clinical Health (Organs, Diseases and Abnormal Conditions)
Objective Field:Immune System and Allergy
UTAS Author:Foote, SJ (Professor Simon Foote)
UTAS Author:Stankovich, J (Dr Jim Stankovich)
UTAS Author:Taylor, BV (Professor Bruce Taylor)
ID Code:67328
Year Published:2010
Web of Science® Times Cited:33
Deposited By:Menzies Institute for Medical Research
Deposited On:2011-03-02
Last Modified:2012-07-02
Downloads:533 View Download Statistics

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