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Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes
BACKGROUND: MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4124764/ https://www.ncbi.nlm.nih.gov/pubmed/24103777 http://dx.doi.org/10.1186/1752-0509-7-101 |
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author | Shi, Hongbo Xu, Juan Zhang, Guangde Xu, Liangde Li, Chunquan Wang, Li Zhao, Zheng Jiang, Wei Guo, Zheng Li, Xia |
author_facet | Shi, Hongbo Xu, Juan Zhang, Guangde Xu, Liangde Li, Chunquan Wang, Li Zhao, Zheng Jiang, Wei Guo, Zheng Li, Xia |
author_sort | Shi, Hongbo |
collection | PubMed |
description | BACKGROUND: MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed. RESULTS: We developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms. CONCLUSIONS: In this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis. |
format | Online Article Text |
id | pubmed-4124764 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41247642014-08-12 Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes Shi, Hongbo Xu, Juan Zhang, Guangde Xu, Liangde Li, Chunquan Wang, Li Zhao, Zheng Jiang, Wei Guo, Zheng Li, Xia BMC Syst Biol Research Article BACKGROUND: MicroRNAs (miRNAs) are important post-transcriptional regulators that have been demonstrated to play an important role in human diseases. Elucidating the associations between miRNAs and diseases at the systematic level will deepen our understanding of the molecular mechanisms of diseases. However, miRNA-disease associations identified by previous computational methods are far from completeness and more effort is needed. RESULTS: We developed a computational framework to identify miRNA-disease associations by performing random walk analysis, and focused on the functional link between miRNA targets and disease genes in protein-protein interaction (PPI) networks. Furthermore, a bipartite miRNA-disease network was constructed, from which several miRNA-disease co-regulated modules were identified by hierarchical clustering analysis. Our approach achieved satisfactory performance in identifying known cancer-related miRNAs for nine human cancers with an area under the ROC curve (AUC) ranging from 71.3% to 91.3%. By systematically analyzing the global properties of the miRNA-disease network, we found that only a small number of miRNAs regulated genes involved in various diseases, genes associated with neurological diseases were preferentially regulated by miRNAs and some immunological diseases were associated with several specific miRNAs. We also observed that most diseases in the same co-regulated module tended to belong to the same disease category, indicating that these diseases might share similar miRNA regulatory mechanisms. CONCLUSIONS: In this study, we present a computational framework to identify miRNA-disease associations, and further construct a bipartite miRNA-disease network for systematically analyzing the global properties of miRNA regulation of disease genes. Our findings provide a broad perspective on the relationships between miRNAs and diseases and could potentially aid future research efforts concerning miRNA involvement in disease pathogenesis. BioMed Central 2013-10-08 /pmc/articles/PMC4124764/ /pubmed/24103777 http://dx.doi.org/10.1186/1752-0509-7-101 Text en Copyright © 2013 Shi et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Shi, Hongbo Xu, Juan Zhang, Guangde Xu, Liangde Li, Chunquan Wang, Li Zhao, Zheng Jiang, Wei Guo, Zheng Li, Xia Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes |
title | Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes |
title_full | Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes |
title_fullStr | Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes |
title_full_unstemmed | Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes |
title_short | Walking the interactome to identify human miRNA-disease associations through the functional link between miRNA targets and disease genes |
title_sort | walking the interactome to identify human mirna-disease associations through the functional link between mirna targets and disease genes |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4124764/ https://www.ncbi.nlm.nih.gov/pubmed/24103777 http://dx.doi.org/10.1186/1752-0509-7-101 |
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