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Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis

BACKGROUND: Membranous glomerulonephritis (MGN) is the most common cause of nephrotic syndrome in adult patients. Despite extensive evidences suggested that many immune-related genes could serve as effective biomarkers in MGN, the potential has not been sufficiently understood because of most previo...

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Autores principales: Zhang, Chengwei, Leng, Lei, Zhang, Xiaoming, Zhao, Yao, Li, Zhaozheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056925/
https://www.ncbi.nlm.nih.gov/pubmed/30041664
http://dx.doi.org/10.1186/s12967-018-1586-4
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author Zhang, Chengwei
Leng, Lei
Zhang, Xiaoming
Zhao, Yao
Li, Zhaozheng
author_facet Zhang, Chengwei
Leng, Lei
Zhang, Xiaoming
Zhao, Yao
Li, Zhaozheng
author_sort Zhang, Chengwei
collection PubMed
description BACKGROUND: Membranous glomerulonephritis (MGN) is the most common cause of nephrotic syndrome in adult patients. Despite extensive evidences suggested that many immune-related genes could serve as effective biomarkers in MGN, the potential has not been sufficiently understood because of most previous studies have concentrated on individual gene and not the entire interaction network. METHODS: Here, we integrated multiple levels of data containing immune-related genes, MGN-related genes, protein–protein interaction (PPI) networks and gene expression profiling data to construct an immune or MGN-directed neighbor network (IOMDN network) and an MGN-related genes-directed network (MGND network). RESULTS: Our analysis suggested that immune-related genes in the PPI network have special topological characteristics and expression pattern related to MGN. We also identified five network modules which showed tighter network structure and stronger correlation of expression. In addition, functional and drug target analyses of genes in modules indicated that the potential mechanism for MGN. CONCLUSIONS: Collectively, these results indicated that the strong associations between immune and MGN and showed the potential of immune-related genes as novel diagnostic and therapeutic targets for MGN. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-018-1586-4) contains supplementary material, which is available to authorized users.
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spelling pubmed-60569252018-07-30 Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis Zhang, Chengwei Leng, Lei Zhang, Xiaoming Zhao, Yao Li, Zhaozheng J Transl Med Research BACKGROUND: Membranous glomerulonephritis (MGN) is the most common cause of nephrotic syndrome in adult patients. Despite extensive evidences suggested that many immune-related genes could serve as effective biomarkers in MGN, the potential has not been sufficiently understood because of most previous studies have concentrated on individual gene and not the entire interaction network. METHODS: Here, we integrated multiple levels of data containing immune-related genes, MGN-related genes, protein–protein interaction (PPI) networks and gene expression profiling data to construct an immune or MGN-directed neighbor network (IOMDN network) and an MGN-related genes-directed network (MGND network). RESULTS: Our analysis suggested that immune-related genes in the PPI network have special topological characteristics and expression pattern related to MGN. We also identified five network modules which showed tighter network structure and stronger correlation of expression. In addition, functional and drug target analyses of genes in modules indicated that the potential mechanism for MGN. CONCLUSIONS: Collectively, these results indicated that the strong associations between immune and MGN and showed the potential of immune-related genes as novel diagnostic and therapeutic targets for MGN. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12967-018-1586-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-07-24 /pmc/articles/PMC6056925/ /pubmed/30041664 http://dx.doi.org/10.1186/s12967-018-1586-4 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Zhang, Chengwei
Leng, Lei
Zhang, Xiaoming
Zhao, Yao
Li, Zhaozheng
Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis
title Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis
title_full Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis
title_fullStr Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis
title_full_unstemmed Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis
title_short Comprehensive identification of immune-associated biomarkers based on network and mRNA expression patterns in membranous glomerulonephritis
title_sort comprehensive identification of immune-associated biomarkers based on network and mrna expression patterns in membranous glomerulonephritis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6056925/
https://www.ncbi.nlm.nih.gov/pubmed/30041664
http://dx.doi.org/10.1186/s12967-018-1586-4
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