Influence of a dietary-induced hypercholesterolemia on the pathogenesis of Theiler´s murine encephalomyelitis with special emphasis on transcriptional changes

In multiples sclerosis (MS), an immune-mediated disease of the central nervous system (CNS), inflammation, demyelination and axonal degeneration are responsible for the variety of neurological disabilities. The basis for the disease progression is ongoing myelin destruction and a failure of remyelination resulting in progressive axonal damage with limited capacity to regenerate. Therefore, one of the main objectives in multiples sclerosis research is to identify the molecular mechanisms leading to a failure of remyelination and to identify potential targets for future therapeutic approaches. Transcriptional profiling has become a powerful tool in exploratory research and led to essential insights in the complex pathomechanisms of demyelinating diseases. Transcriptional analysis in demyelinating diseases suggested an involvement of cholesterol metabolism as a possible cause for inadequate remyelination in progressive demyelinating diseases. Therefore, the first part of this study addresses the possible interaction of dyslipidemia or disturbances of the cholesterol metabolism in Theiler's murine encephalomyelitis (TME), an experimentally, virus-induced, inflammatory, demyelinating disease of the spinal cord in susceptible mouse strains. Consequently, expression of genes associated to cholesterol biosynthesis and metabolism, composition of the body's major lipid repositories and diet-induced, systemic hypercholesterolemia were examined in TME using histology, immunohistochemistry, serum clinical chemistry, microarray analysis and high-performance thin layer chromatography. TME-virus (TMEV)-infected mice showed progressive loss of motor performance and demyelinating leukomyelitis. Gene expression associated with cholesterol biosynthesis was overall down-regulated in the spinal cord of TMEV-infected animals. Spinal cord levels of galactocerebroside and sphingomyelin were reduced on day 196 post TMEV infection. Paigen diet induced serum hypercholesterolemia and hepatic lipidosis. However, high dietary fat and cholesterol intake led to no significant differences in clinical course, inflammatory response, astrocytosis, and the amount of demyelination and remyelination in the spinal cord of TMEV-infected animals. The results suggest that down-regulation of cholesterol biosynthesis is a transcriptional marker for demyelination, quantitative loss of myelin-specific lipids, but not cholesterol occurs late in chronic demyelination, and serum hypercholesterolemia exhibited no significant effect on TMEV infection. As the results of the first part of this thesis have shown, gene expression profiling using microarray technology represents a potent method to discover novel relationships and interactions in complex diseases. The large-scale data sets generated by microarrays help to understand complex signaling pathways and pathomechanistic processes in different somatic cell types and tissues, under various extrinsic and intrinsic conditions. Because microarray analysis became a sensitive, reliable and robust method during the last few years a vast amount of microarray gene expression data sets were produced and are available through public repositories. New possibilities lay in the re-analysis or combination of the freely and easily accessible information. To explore the potential of this data, a basic knowledge of possible methods and applications is crucial. Therefore, the second part of the study presents an application-oriented introduction to microarray data analysis techniques for users without detailed bioinformatic knowledge from the point of few of a veterinary pathologist. In particular, the present report aims to clarify, which data analysis techniques are available and what are the most appropriate methods for a specific research purpose. A main goal of the second part of the study is to assist the reader in the transformation of the huge amount of information obtained by a single experiment into biological knowledge and to point out important challenges and pitfalls by presenting real representative data that illustrate common problems in data analysis. Both parts of this thesis highlight the great potential of novel high-throughput technologies in both, data-driven analysis for the generation of new hypothesis, and hypothesis-driven approaches to study particular signaling pathways and regulatory interactions. By means of these methodologies an interesting novel association of cholesterol metabolism and demyelination was found.