Integrative modelling of transcriptional regulation in response to interferon β multiple sclerosis treatment

The purpose of this study was to characterize the transcriptional effects induced by an interferon-β-1a (IFN-b) treatment regime (Avonex; weekly 30 mcg intramuscular) in patients with relapsing-remitting form of multiple sclerosis (MS). IFN-b effectively decreases the frequency of clinical exacerbations in most MS patients, but the specifically modulated genes and mechanisms by which IFN-b exerts its effects have not been fully elucidated.

DNA microarrays were used to obtain genome-wide transcriptional profiles of peripheral blood mononuclear cells of 24 MS patients within the first four weeks of IFN-b administration. We identified a set of 121 genes as being significantly regulated in particular during first week of therapy. Most of them are known to control the human body's immune response. 11 transcription factor binding sites (TFBS) were found overrepresented in the promoter regions of these genes, including the IFN-stimulated response element. We then applied TILAR, a novel method for deriving gene regulatory networks from gene expression data by integrating information on TFBS, to reconstruct a complex network of gene regulatory interactions. The network model exhibits a scale-free, self-regulating and massively parallel architecture and provides new and testable hypotheses about the drug's mechanisms of action.

We demonstrate that integrating different types of biological data in a systems biological model strongly supports the investigation of immunomodulatory therapies for MS. Besides, we show, that the inferred molecular network structures could find applicability in dissecting clinical heterogeneity.