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Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol
Many studies have investigated misregulation of miRNAs relevant to multiple sclerosis (MS) pathogenesis. Abnormal miRNAs can be used both as candidate biomarker for MS diagnosis and understanding the disease miRNA-mRNA regulatory network. In this comprehensive study, misregulated miRNAs related to M...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Shiraz University
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5640895/ https://www.ncbi.nlm.nih.gov/pubmed/29071282 http://dx.doi.org/10.22099/mbrc.2017.24861.1256 |
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author | Ehya, Farveh Abdul Tehrani, Hossein Garshasbi, Masoud Nabavi, Seyed Masood |
author_facet | Ehya, Farveh Abdul Tehrani, Hossein Garshasbi, Masoud Nabavi, Seyed Masood |
author_sort | Ehya, Farveh |
collection | PubMed |
description | Many studies have investigated misregulation of miRNAs relevant to multiple sclerosis (MS) pathogenesis. Abnormal miRNAs can be used both as candidate biomarker for MS diagnosis and understanding the disease miRNA-mRNA regulatory network. In this comprehensive study, misregulated miRNAs related to MS were collected from existing literature, databases and via in silico prediction. A multi-staged data integration strategy (including the construction of miRNA-mRNA regulatory network and systematic data analysis) was conducted in order to investigate MS related miRNAs and their regulatory networks. The final outcome was a bi-layer MS related regulatory network constructed with 27 miRNAs (seven of them were novel) and 59 mRNA targets. To verify the accuracy of the bioinformatics strategy three novel and five previously reported miRNAs from the network model were selected for experimental validation using the real-time PCR assay. The obtained results proved the accuracy of the network. The expression of themiR-24 and miR-137(as novel MS candidate biomarker) and miR-16, and miR-181 (as previously reported MS candidate biomarker) showed significant deregulation in 33 MS patients compared to the control. The optimized data integration strategy conducted in this study found two miRNAs (miR-24and miR-16)that can be considered as candidate biomarkers for MS and also has the potential to generate a regulatory network to aid in further understanding the mechanisms underlying this disease. |
format | Online Article Text |
id | pubmed-5640895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Shiraz University |
record_format | MEDLINE/PubMed |
spelling | pubmed-56408952017-10-25 Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol Ehya, Farveh Abdul Tehrani, Hossein Garshasbi, Masoud Nabavi, Seyed Masood Mol Biol Res Commun Original Article Many studies have investigated misregulation of miRNAs relevant to multiple sclerosis (MS) pathogenesis. Abnormal miRNAs can be used both as candidate biomarker for MS diagnosis and understanding the disease miRNA-mRNA regulatory network. In this comprehensive study, misregulated miRNAs related to MS were collected from existing literature, databases and via in silico prediction. A multi-staged data integration strategy (including the construction of miRNA-mRNA regulatory network and systematic data analysis) was conducted in order to investigate MS related miRNAs and their regulatory networks. The final outcome was a bi-layer MS related regulatory network constructed with 27 miRNAs (seven of them were novel) and 59 mRNA targets. To verify the accuracy of the bioinformatics strategy three novel and five previously reported miRNAs from the network model were selected for experimental validation using the real-time PCR assay. The obtained results proved the accuracy of the network. The expression of themiR-24 and miR-137(as novel MS candidate biomarker) and miR-16, and miR-181 (as previously reported MS candidate biomarker) showed significant deregulation in 33 MS patients compared to the control. The optimized data integration strategy conducted in this study found two miRNAs (miR-24and miR-16)that can be considered as candidate biomarkers for MS and also has the potential to generate a regulatory network to aid in further understanding the mechanisms underlying this disease. Shiraz University 2017-09 /pmc/articles/PMC5640895/ /pubmed/29071282 http://dx.doi.org/10.22099/mbrc.2017.24861.1256 Text en This is an Open Access article distributed under the terms of the Creative Commons Attribution License, (http://creativecommons.org/licenses/by/3.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Ehya, Farveh Abdul Tehrani, Hossein Garshasbi, Masoud Nabavi, Seyed Masood Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol |
title | Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol |
title_full | Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol |
title_fullStr | Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol |
title_full_unstemmed | Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol |
title_short | Identification of miR-24 and miR-137 as novel candidate multiple sclerosis miRNA biomarkers using multi-staged data analysis protocol |
title_sort | identification of mir-24 and mir-137 as novel candidate multiple sclerosis mirna biomarkers using multi-staged data analysis protocol |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5640895/ https://www.ncbi.nlm.nih.gov/pubmed/29071282 http://dx.doi.org/10.22099/mbrc.2017.24861.1256 |
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