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Modular Transcriptional Activity Characterizes the Initiation and Progression of Autoimmune Encephalomyelitis¹

Sergio E. Baranzini^2,*, Claude C. A. Bernard and Jorge R. Oksenberg^*

^* Department of Neurology, School of Medicine, University of California, San Francisco, CA 94143; and Neuroimmunology Laboratory, School of Biochemistry and Genetics, LaTrobe University, Bundoora, Victoria, Australia

Murine experimental autoimmune encephalomyelitis is a well-established model that recapitulates many clinical and physiopathological aspects of multiple sclerosis (MS). An important conceptual development in the understanding of both experimental autoimmune encephalomyelitis and MS pathogenesis has been the compartmentalization of the mechanistic process into two distinct but overlapping and connected phases, inflammatory and neurodegenerative. However, the dynamics of CNS transcriptional changes that underlie the development and regression of the phenotype are not well understood. Our report presents the first high frequency longitudinal study looking at the earliest transcriptional changes in the CNS of NOD mice immunized with myelin oligodendrocyte glycoprotein 35–55 in CFA. Microarray-based gene expression profiling and histopathological analysis were performed from spinal cord samples obtained at 13 time points around the first clinical symptom (every other day until day 11 and every day onward until day 19 postimmunization). Advanced statistics and data-mining algorithms were used to identify expression signatures that correlated with disease stage and histological profiles. Discrete phases of neuroinflammation were accompanied by distinctive expression signatures, in which altered immune to neural gene expression ratios were observed. By using high frequency gene expression analysis we captured expression profiles that were characteristic of the transition from innate to adaptive immune response in this experimental paradigm between days 11 and 12 postimmunization. Our study demonstrates the utility of large-scale transcriptional studies and advanced data mining to decipher complex biological processes such as those involved in MS and other neurodegenerative disoders.

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