|M.Sc Student||Emanuel Meital|
|Subject||Epigenetic and Gene eEpression Modifications in Multiple|
Sclerosis Patients in Response to Glucocorticoid
|Department||Department of Medicine||Supervisors||Professor Ariel Miller|
|Professor Philippa Melamed|
|Full Thesis text|
Multiple Sclerosis (MS) is a chronic immune-mediated disease of the central nervous system, with autoimmune and neurodegenerative components, which is characterized by a relapsing remitting form. Glucocorticoid (GC), a potent anti-inflammatory and immunosuppressive drug, is widely used to reduce the severity and duration of at severe acute MS relapses. Response to therapy might be affected by epigenetic mechanisms that regulate levels of gene expression, through DNA methylation. The goal of our project was to establish a research platform to highlight differentially methylated regions that impact gene expression in MS patients following GC treatment. We employed Illumina whole genome methylation (Infinium? HumanMethylation27?) and whole genome expression (HumanHT-12) arrays, while using qRT-PCR to validate changes in gene expression. Bisulfite sequencing (BS) or pyrosequencing by PyroMark? was used to determine change in methylation. In addition, two different analysis methods were compared: a pure statistical/bioinformatic approach or a more biological approach where the methylation and expression data sets were merged. Several unforeseen challenges were discovered, such as large heterogeneity between patients as well as the small changes in methylation. For the first methodology, both methylation validation methods were found to be lacking. The BS was found incompatible for screening numerous samples and target sites, and lacked sensitivity for small changes; PyroMark? assay success rate was less than 40% of the target sites. Of the two analytical methods, the biological method was more reliable, since the two data sets complement and supports each other. This is especially critical when the number of samples is low and the heterogeneity high, resulting in low statistical power for the study. Despite the limitations and unforeseen challenges, one gene, PRF1, showed promise since both change in methylation and gene expression were successfully validated. In this research we have succeeded in establishing an epigenetic platform to evaluate changes in DNA methylation patterns, and identified PRF1 as being differentially methylated in response to GC treatment in MS patients. Moreover, the research group’s expertise, knowledge with methylation pattern assays and analysis has improved significantly. In addition, several unexpected results, such as difference in methylation between gender, the non CpG methylation sites, and the possible effect of methylation on alternative splicing selection, emphasize the importance of this research field and the gaps in our current knowledge that are yet to be explored in future epigenetic studies in human diseases, and specifically in the context of response to therapy as part of personalized medicine.