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      MicroRNA Expression Profiling in Behçet's Disease

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          Abstract

          Background

          Behçet's disease (BD) is a chronic inflammatory multisystem disease characterized by oral and genital ulcers, uveitis, and skin lesions. MicroRNAs (miRNAs) are key regulators of immune responses. Differential expression of miRNAs has been reported in several inflammatory autoimmune diseases; however, their role in BD is not fully elucidated. We aimed to identify miRNA expression signatures associated with BD and to investigate their potential implication in the disease pathogenesis.

          Methods

          miRNA microarray analysis was performed in blood cells of BD patients and healthy controls. miRNA expression profiles were analyzed using Affymetrix arrays with a comprehensive coverage of miRNA sequences. Pathway analyses were performed, and the global miRNA profiling was combined with transcriptoma data in BD. Deregulation of selected miRNAs was validated by real-time PCR.

          Results

          We identified specific miRNA signatures associated with BD patients with active disease. These miRNAs target pathways relevant in BD, such as TNF, IFN gamma, and VEGF-VEGFR signaling cascades. Network analysis revealed several miRNAs regulating highly connected genes within the BD transcriptoma.

          Conclusions

          The combined analysis of deregulated miRNAs and BD transcriptome sheds light on some epigenetic aspects of BD identifying specific miRNAs, which may represent promising candidates as biomarkers and/or for the design of novel therapeutic strategies in BD.

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          Most cited references49

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          FunRich: An open access standalone functional enrichment and interaction network analysis tool.

          As high-throughput techniques including proteomics become more accessible to individual laboratories, there is an urgent need for a user-friendly bioinformatics analysis system. Here, we describe FunRich, an open access, standalone functional enrichment and network analysis tool. FunRich is designed to be used by biologists with minimal or no support from computational and database experts. Using FunRich, users can perform functional enrichment analysis on background databases that are integrated from heterogeneous genomic and proteomic resources (>1.5 million annotations). Besides default human specific FunRich database, users can download data from the UniProt database, which currently supports 20 different taxonomies against which enrichment analysis can be performed. Moreover, the users can build their own custom databases and perform the enrichment analysis irrespective of organism. In addition to proteomics datasets, the custom database allows for the tool to be used for genomics, lipidomics and metabolomics datasets. Thus, FunRich allows for complete database customization and thereby permits for the tool to be exploited as a skeleton for enrichment analysis irrespective of the data type or organism used. FunRich (http://www.funrich.org) is user-friendly and provides graphical representation (Venn, pie charts, bar graphs, column, heatmap and doughnuts) of the data with customizable font, scale and color (publication quality).
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            mirDIP 4.1—integrative database of human microRNA target predictions

            Abstract MicroRNAs are important regulators of gene expression, achieved by binding to the gene to be regulated. Even with modern high-throughput technologies, it is laborious and expensive to detect all possible microRNA targets. For this reason, several computational microRNA–target prediction tools have been developed, each with its own strengths and limitations. Integration of different tools has been a successful approach to minimize the shortcomings of individual databases. Here, we present mirDIP v4.1, providing nearly 152 million human microRNA–target predictions, which were collected across 30 different resources. We also introduce an integrative score, which was statistically inferred from the obtained predictions, and was assigned to each unique microRNA–target interaction to provide a unified measure of confidence. We demonstrate that integrating predictions across multiple resources does not cumulate prediction bias toward biological processes or pathways. mirDIP v4.1 is freely available at http://ophid.utoronto.ca/mirDIP/.
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              MicroRNA in autoimmunity and autoimmune diseases.

              MicroRNAs (miRNAs) are small conserved non-coding RNA molecules that post-transcriptionally regulate gene expression by targeting the 3' untranslated region (UTR) of specific messenger RNAs (mRNAs) for degradation or translational repression. miRNA-mediated gene regulation is critical for normal cellular functions such as the cell cycle, differentiation, and apoptosis, and as much as one-third of human mRNAs may be miRNA targets. Emerging evidence has demonstrated that miRNAs play a vital role in the regulation of immunological functions and the prevention of autoimmunity. Here we review the many newly discovered roles of miRNA regulation in immune functions and in the development of autoimmunity and autoimmune disease. Specifically, we discuss the involvement of miRNA regulation in innate and adaptive immune responses, immune cell development, T regulatory cell stability and function, and differential miRNA expression in rheumatoid arthritis and systemic lupus erythematosus.
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                Author and article information

                Contributors
                Journal
                J Immunol Res
                J Immunol Res
                JIR
                Journal of Immunology Research
                Hindawi
                2314-8861
                2314-7156
                2018
                7 May 2018
                : 2018
                Affiliations
                1Immunology Area, Pediatric Hospital Bambino Gesù, Viale San Paolo 15, 00146 Rome, Italy
                2Department of Experimental Medicine-Section of Histology, University of Genova, Via G.B. Marsano 10, 16132 Genova, Italy
                3Department of Medicine, University of Verona, Piazzale L.A. Scuro 10, 37134 Verona, Italy
                Author notes

                Academic Editor: Andréia M. Cardoso

                Article
                10.1155/2018/2405150
                5964440
                e86627a5-146e-457f-86f8-5aeb9a3232f9
                Copyright © 2018 Antonio Puccetti et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Research Article

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