Cargando…
Integrated transcriptomic correlation network analysis identifies COPD molecular determinants
Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous syndrome. Network-based analysis implemented by SWIM software can be exploited to identify key molecular switches - called “switch genes” - for the disease. Genes contributing to common biological processes or defining given...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042269/ https://www.ncbi.nlm.nih.gov/pubmed/32099002 http://dx.doi.org/10.1038/s41598-020-60228-7 |
_version_ | 1783501275704328192 |
---|---|
author | Paci, Paola Fiscon, Giulia Conte, Federica Licursi, Valerio Morrow, Jarrett Hersh, Craig Cho, Michael Castaldi, Peter Glass, Kimberly Silverman, Edwin K. Farina, Lorenzo |
author_facet | Paci, Paola Fiscon, Giulia Conte, Federica Licursi, Valerio Morrow, Jarrett Hersh, Craig Cho, Michael Castaldi, Peter Glass, Kimberly Silverman, Edwin K. Farina, Lorenzo |
author_sort | Paci, Paola |
collection | PubMed |
description | Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous syndrome. Network-based analysis implemented by SWIM software can be exploited to identify key molecular switches - called “switch genes” - for the disease. Genes contributing to common biological processes or defining given cell types are usually co-regulated and co-expressed, forming expression network modules. Consistently, we found that the COPD correlation network built by SWIM consists of three well-characterized modules: one populated by switch genes, all up-regulated in COPD cases and related to the regulation of immune response, inflammatory response, and hypoxia (like TIMP1, HIF1A, SYK, LY96, BLNK and PRDX4); one populated by well-recognized immune signature genes, all up-regulated in COPD cases; one where the GWAS genes AGER and CAVIN1 are the most representative module genes, both down-regulated in COPD cases. Interestingly, 70% of AGER negative interactors are switch genes including PRDX4, whose activation strongly correlates with the activation of known COPD GWAS interactors SERPINE2, CD79A, and POUF2AF1. These results suggest that SWIM analysis can identify key network modules related to complex diseases like COPD. |
format | Online Article Text |
id | pubmed-7042269 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-70422692020-03-03 Integrated transcriptomic correlation network analysis identifies COPD molecular determinants Paci, Paola Fiscon, Giulia Conte, Federica Licursi, Valerio Morrow, Jarrett Hersh, Craig Cho, Michael Castaldi, Peter Glass, Kimberly Silverman, Edwin K. Farina, Lorenzo Sci Rep Article Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous syndrome. Network-based analysis implemented by SWIM software can be exploited to identify key molecular switches - called “switch genes” - for the disease. Genes contributing to common biological processes or defining given cell types are usually co-regulated and co-expressed, forming expression network modules. Consistently, we found that the COPD correlation network built by SWIM consists of three well-characterized modules: one populated by switch genes, all up-regulated in COPD cases and related to the regulation of immune response, inflammatory response, and hypoxia (like TIMP1, HIF1A, SYK, LY96, BLNK and PRDX4); one populated by well-recognized immune signature genes, all up-regulated in COPD cases; one where the GWAS genes AGER and CAVIN1 are the most representative module genes, both down-regulated in COPD cases. Interestingly, 70% of AGER negative interactors are switch genes including PRDX4, whose activation strongly correlates with the activation of known COPD GWAS interactors SERPINE2, CD79A, and POUF2AF1. These results suggest that SWIM analysis can identify key network modules related to complex diseases like COPD. Nature Publishing Group UK 2020-02-25 /pmc/articles/PMC7042269/ /pubmed/32099002 http://dx.doi.org/10.1038/s41598-020-60228-7 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as 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 images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Paci, Paola Fiscon, Giulia Conte, Federica Licursi, Valerio Morrow, Jarrett Hersh, Craig Cho, Michael Castaldi, Peter Glass, Kimberly Silverman, Edwin K. Farina, Lorenzo Integrated transcriptomic correlation network analysis identifies COPD molecular determinants |
title | Integrated transcriptomic correlation network analysis identifies COPD molecular determinants |
title_full | Integrated transcriptomic correlation network analysis identifies COPD molecular determinants |
title_fullStr | Integrated transcriptomic correlation network analysis identifies COPD molecular determinants |
title_full_unstemmed | Integrated transcriptomic correlation network analysis identifies COPD molecular determinants |
title_short | Integrated transcriptomic correlation network analysis identifies COPD molecular determinants |
title_sort | integrated transcriptomic correlation network analysis identifies copd molecular determinants |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7042269/ https://www.ncbi.nlm.nih.gov/pubmed/32099002 http://dx.doi.org/10.1038/s41598-020-60228-7 |
work_keys_str_mv | AT pacipaola integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT fiscongiulia integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT contefederica integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT licursivalerio integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT morrowjarrett integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT hershcraig integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT chomichael integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT castaldipeter integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT glasskimberly integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT silvermanedwink integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants AT farinalorenzo integratedtranscriptomiccorrelationnetworkanalysisidentifiescopdmoleculardeterminants |