Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls.
Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of di...
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Public Library of Science (PLoS)
2009
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oai:doaj.org-article:b176492969e8419abaa966f7b6329bb42021-11-25T06:28:47ZMultiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls.1932-620310.1371/journal.pone.0007440https://doaj.org/article/b176492969e8419abaa966f7b6329bb42009-10-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/19823682/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS.Andreas KellerPetra LeidingerJulia LangeAnne BorriesHannah SchroersMatthias SchefflerHans-Peter LenhofKlemens RuprechtEckart MeesePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 4, Iss 10, p e7440 (2009) |
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Medicine R Science Q |
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Medicine R Science Q Andreas Keller Petra Leidinger Julia Lange Anne Borries Hannah Schroers Matthias Scheffler Hans-Peter Lenhof Klemens Ruprecht Eckart Meese Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| description |
Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system, which is heterogenous with respect to clinical manifestations and response to therapy. Identification of biomarkers appears desirable for an improved diagnosis of MS as well as for monitoring of disease activity and treatment response. MicroRNAs (miRNAs) are short non-coding RNAs, which have been shown to have the potential to serve as biomarkers for different human diseases, most notably cancer. Here, we analyzed the expression profiles of 866 human miRNAs. In detail, we investigated the miRNA expression in blood cells of 20 patients with relapsing-remitting MS (RRMS) and 19 healthy controls using a human miRNA microarray and the Geniom Real Time Analyzer (GRTA) platform. We identified 165 miRNAs that were significantly up- or downregulated in patients with RRMS as compared to healthy controls. The best single miRNA marker, hsa-miR-145, allowed discriminating MS from controls with a specificity of 89.5%, a sensitivity of 90.0%, and an accuracy of 89.7%. A set of 48 miRNAs that was evaluated by radial basis function kernel support vector machines and 10-fold cross validation yielded a specificity of 95%, a sensitivity of 97.6%, and an accuracy of 96.3%. While 43 of the 165 miRNAs deregulated in patients with MS have previously been related to other human diseases, the remaining 122 miRNAs are so far exclusively associated with MS. The implications of our study are twofold. The miRNA expression profiles in blood cells may serve as a biomarker for MS, and deregulation of miRNA expression may play a role in the pathogenesis of MS. |
| format |
article |
| author |
Andreas Keller Petra Leidinger Julia Lange Anne Borries Hannah Schroers Matthias Scheffler Hans-Peter Lenhof Klemens Ruprecht Eckart Meese |
| author_facet |
Andreas Keller Petra Leidinger Julia Lange Anne Borries Hannah Schroers Matthias Scheffler Hans-Peter Lenhof Klemens Ruprecht Eckart Meese |
| author_sort |
Andreas Keller |
| title |
Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| title_short |
Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| title_full |
Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| title_fullStr |
Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| title_full_unstemmed |
Multiple sclerosis: microRNA expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| title_sort |
multiple sclerosis: microrna expression profiles accurately differentiate patients with relapsing-remitting disease from healthy controls. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2009 |
| url |
https://doaj.org/article/b176492969e8419abaa966f7b6329bb4 |
| work_keys_str_mv |
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