Transcriptional analysis of the glial cell differentiation in the diseased and normal central nervous system

The key objective of the research in demyelinating diseases is to find the molecular basis of the diseases and identify targets for future therapeutic approaches. Transcriptome profiling has become a powerful tool in exploratory research and led to essential insights in the complex pathomechanisms of central nervous system disorders. New approaches in knowledge-based data-mining point out the importance of referencing background information. Thus, integrating studies of physiological development and animal models of diseases are a key to identify causal genes or pathways for a specific disease. Therefore, the first part of the study focused on the delineation of oligodendrocyte differentiation and myelination during development. Myelination of the murine spinal cord is an entirely postnatal process, thus it represents a good model system to study mammalian central nervous myelination in vivo. Oligonucleotide microarrays were used to present a detailed exploratory analysis of the postnatal murine spinal cord transcriptome from postnatal day 0 to day 231. This led to the identification of eight highly differentially regulated genes among the group of well-known myelin genes with still unknown function during the myelination process. Furthermore, biological processes were assigned to certain developmental stages and their overlapping significance during several periods of postnatal life was detected. The up-regulated differentially expressed genes (DEGs) exhibited significantly enriched associations to gene ontology terms such as myelination and lipid metabolic transport and down-regulated DEGs to neurogenesis and axonogenesis. Expression values of marker gene signatures for neural stem cells, oligodendrocyte precursor cells, and developing astrocytes were constantly decreasing, whereas expression values of marker gene signitures for myelinating oligodendrocyte and mature astrocyte markers showed a steady increase. The second part of the study was aimed to identify highly conserved and functionally important molecular processes in demyelinating diseases. Integrating the information from multiple studies in multiples sclerosis and its animal models in a comprehensive meta-analysis was suggested to be a powerful approach in detecting commonly affected pathways. ArrayExpress, Gene Expression Omnibus and PubMed databases were screened for microarray gene expression profiling studies of MS and its experimental animal models. Included conditions were multiples sclerosis (MS), myelin oligodendrocyte glycoprotein-induced experimental autoimmune encephalomyelitis (EAE) in rats, proteolipid protein-induced EAE in mice, Theiler's murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD), and a transgenic tumor necrosis factor-overexpressing mouse model (TNFtg). The re-analysis of the data set with consistent methodology on the gene level revealed an intersection of 12 genes related to macrophage function in all studies. Cross-study pathway-analysis revealed interesting commonly affected pathways in MS, EAE, TMEV-IDD, and TNFtg including coagulation and JAK/STAT-signaling. Furthermore the transcriptional changes in the different animal models were examined for their anticipated differences in their pathomechanism. The results of both analyses point out the importance of the integration of multiple knowledge-based data mining methods rather than an exclusive application of highly conservative methods based solely on differentially expressed genes. Conclusively, the novel insights gained from the present data-driven analysis are important to generate novel starting points for further hypothesis-driven studies and thus lead to a better understanding of the cause and consequences of demyelinating diseases.