Abstract
BackgroundSeveral 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 FindingsWe 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/SignificanceOur 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.
Highlights
Multiple Sclerosis (MS) [1] is an autoimmune disease characterised by chronic inflammatory demyelination of the central nervous system
All differential expression or co-expression analysis here are performed on individual probe identifiers, while transcription factor overrepresentation are performed based on the target genes identifiers
Other transcription factors that need to be added to this model are those which we have found very relevant in our analysis such as 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. doi:10.1371/journal.pone.0014176.g016
Summary
Multiple Sclerosis (MS) [1] is an autoimmune disease characterised by chronic inflammatory demyelination of the central nervous system. The disorder affects millions of people worldwide and is the most common chronic disease of the central nervous system that begins in early to middle adult life [2] (its prevalence in the USA is 0.9 per 1,000 [3]). MS is a multifactorial and heterogeneous disease, and its causes are currently unknown it is increasingly clear that both genetic and environmental factors contribute to susceptibility [2,4,5,6]. 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. 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
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