Bioinformatics approach to identifying molecular biomarkers and networks in multiple sclerosis

Abstract

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS) white matter mediated by an autoimmune process triggered by a complex interplay between genetic and environmental factors, in which the precise molecular pathogenesis remains to be comprehensively characterized. The global analysis of genome, transcriptome, proteome and metabolome, collectively termed omics, promotes us to characterize the genome-wide molecular basis of MS. However, as omics studies produce high-throughput experimental data at one time, it is often difficult to find out the meaningful biological implications from huge datasets. Recent advances in bioinformatics and systems biology have made major breakthroughs by illustrating the cell-wide map of complex molecular interactions with the aid of the literature-based knowledgebase of molecular pathways. The integration of omics data derived from the disease-affected cells and tissues with underlying molecular networks provides a rational approach not only to identifying the disease-relevant molecular markers and pathways, but also to designing the network-based effective drugs for MS. (Clin. Exp. Neuroimmunol. doi: 10.1111/j.1759-1961.2010.00013.x, 2010)