Article

Molecular Neurobiology

, Volume 45, Issue 3, pp 520-535

First online:

Integration of MicroRNA Databases to Study MicroRNAs Associated with Multiple Sclerosis

  • Charlotte AngersteinAffiliated withDepartment of Neurology, Division of Neuroimmunology, University of Rostock
  • , Michael HeckerAffiliated withDepartment of Neurology, Division of Neuroimmunology, University of RostockInstitute of Immunology, University of Rostock Email author 
  • , Brigitte Katrin PaapAffiliated withDepartment of Neurology, Division of Neuroimmunology, University of RostockInstitute of Immunology, University of Rostock
  • , Dirk KoczanAffiliated withInstitute of Immunology, University of Rostock
  • , Madhan ThamilarasanAffiliated withDepartment of Neurology, Division of Neuroimmunology, University of RostockInstitute of Immunology, University of Rostock
  • , Hans-Jürgen ThiesenAffiliated withInstitute of Immunology, University of Rostock
  • , Uwe Klaus ZettlAffiliated withDepartment of Neurology, Division of Neuroimmunology, University of Rostock

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Abstract

MicroRNAs (miRNAs) are small non-coding RNAs which regulate many genes post-transcriptionally. In various contexts of medical science, miRNAs gained increasing attention over the last few years. Analyzing the functions, interactions and cellular effects of miRNAs is a very complex and challenging task. Many miRNA databases with diverse data contents have been developed. Here, we demonstrate how to integrate their information in a reasonable way on a set of miRNAs that were found to be dysregulated in the blood of patients with multiple sclerosis (MS). Using the miR2Disease database, we retrieved 16 miRNAs associated with MS according to four different studies. We studied the predicted and experimentally validated target genes of these miRNAs, their expression profiles in different blood cell types and brain tissues, the pathways and biological processes affected by these miRNAs as well as their regulation by transcription factors. Only miRNA–mRNA interactions that were predicted by at least seven different prediction algorithms were considered. This resulted in a network of 1,498 target genes. In this network, the MS-associated miRNAs hsa-miR-20a-5p and hsa-miR-20b-5p occurred as central hubs regulating about 500 genes each. Strikingly, many of the putative target genes play a role in T cell activation and signaling, and many have transcription factor activity. The latter suggests that miRNAs often act as regulators of regulators with many secondary effects on gene expression. Our present work provides a guideline on how information of different databases can be integrated in the analysis of miRNAs. Future investigations of miRNAs shall help to better understand the mechanisms underlying different diseases and their treatments.

Keywords

Multiple sclerosis MicroRNA Databases Gene regulatory networks