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Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods

BACKGROUND: Exacerbations of chronic obstructive pulmonary disease (COPD), characterized by acute deterioration in symptoms, may be due to bacterial or viral infections, environmental exposures, or unknown factors. Exacerbation frequency may be a stable trait in COPD patients, which could imply gene...

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Autores principales: Morrow, Jarrett D, Qiu, Weiliang, Chhabra, Divya, Rennard, Stephen I, Belloni, Paula, Belousov, Anton, Pillai, Sreekumar G, Hersh, Craig P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302028/
https://www.ncbi.nlm.nih.gov/pubmed/25582225
http://dx.doi.org/10.1186/s12920-014-0072-y
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author Morrow, Jarrett D
Qiu, Weiliang
Chhabra, Divya
Rennard, Stephen I
Belloni, Paula
Belousov, Anton
Pillai, Sreekumar G
Hersh, Craig P
author_facet Morrow, Jarrett D
Qiu, Weiliang
Chhabra, Divya
Rennard, Stephen I
Belloni, Paula
Belousov, Anton
Pillai, Sreekumar G
Hersh, Craig P
author_sort Morrow, Jarrett D
collection PubMed
description BACKGROUND: Exacerbations of chronic obstructive pulmonary disease (COPD), characterized by acute deterioration in symptoms, may be due to bacterial or viral infections, environmental exposures, or unknown factors. Exacerbation frequency may be a stable trait in COPD patients, which could imply genetic susceptibility. Observing the genes, networks, and pathways that are up- and down-regulated in COPD patients with differing susceptibility to exacerbations will help to elucidate the molecular signature and pathogenesis of COPD exacerbations. METHODS: Gene expression array and plasma biomarker data were obtained using whole-blood samples from subjects enrolled in the Treatment of Emphysema With a Gamma-Selective Retinoid Agonist (TESRA) study. Linear regression, weighted gene co-expression network analysis (WGCNA), and pathway analysis were used to identify signatures and network sub-modules associated with the number of exacerbations within the previous year; other COPD-related phenotypes were also investigated. RESULTS: Individual genes were not found to be significantly associated with the number of exacerbations. However using network methods, a statistically significant gene module was identified, along with other modules showing moderate association. A diverse signature was observed across these modules using pathway analysis, marked by differences in B cell and NK cell activity, as well as cellular markers of viral infection. Within two modules, gene set enrichment analysis recapitulated the molecular signatures of two gene expression experiments; one involving sputum from asthma exacerbations and another involving viral lung infections. The plasma biomarker myeloperoxidase (MPO) was associated with the number of recent exacerbations. CONCLUSION: A distinct signature of COPD exacerbations may be observed in peripheral blood months following the acute illness. While not predictive in this cross-sectional analysis, these results will be useful in uncovering the molecular pathogenesis of COPD exacerbations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-014-0072-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-43020282015-01-22 Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods Morrow, Jarrett D Qiu, Weiliang Chhabra, Divya Rennard, Stephen I Belloni, Paula Belousov, Anton Pillai, Sreekumar G Hersh, Craig P BMC Med Genomics Research Article BACKGROUND: Exacerbations of chronic obstructive pulmonary disease (COPD), characterized by acute deterioration in symptoms, may be due to bacterial or viral infections, environmental exposures, or unknown factors. Exacerbation frequency may be a stable trait in COPD patients, which could imply genetic susceptibility. Observing the genes, networks, and pathways that are up- and down-regulated in COPD patients with differing susceptibility to exacerbations will help to elucidate the molecular signature and pathogenesis of COPD exacerbations. METHODS: Gene expression array and plasma biomarker data were obtained using whole-blood samples from subjects enrolled in the Treatment of Emphysema With a Gamma-Selective Retinoid Agonist (TESRA) study. Linear regression, weighted gene co-expression network analysis (WGCNA), and pathway analysis were used to identify signatures and network sub-modules associated with the number of exacerbations within the previous year; other COPD-related phenotypes were also investigated. RESULTS: Individual genes were not found to be significantly associated with the number of exacerbations. However using network methods, a statistically significant gene module was identified, along with other modules showing moderate association. A diverse signature was observed across these modules using pathway analysis, marked by differences in B cell and NK cell activity, as well as cellular markers of viral infection. Within two modules, gene set enrichment analysis recapitulated the molecular signatures of two gene expression experiments; one involving sputum from asthma exacerbations and another involving viral lung infections. The plasma biomarker myeloperoxidase (MPO) was associated with the number of recent exacerbations. CONCLUSION: A distinct signature of COPD exacerbations may be observed in peripheral blood months following the acute illness. While not predictive in this cross-sectional analysis, these results will be useful in uncovering the molecular pathogenesis of COPD exacerbations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12920-014-0072-y) contains supplementary material, which is available to authorized users. BioMed Central 2015-01-13 /pmc/articles/PMC4302028/ /pubmed/25582225 http://dx.doi.org/10.1186/s12920-014-0072-y Text en © Morrow et al.; licensee BioMed Central. 2015 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Article
Morrow, Jarrett D
Qiu, Weiliang
Chhabra, Divya
Rennard, Stephen I
Belloni, Paula
Belousov, Anton
Pillai, Sreekumar G
Hersh, Craig P
Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
title Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
title_full Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
title_fullStr Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
title_full_unstemmed Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
title_short Identifying a gene expression signature of frequent COPD exacerbations in peripheral blood using network methods
title_sort identifying a gene expression signature of frequent copd exacerbations in peripheral blood using network methods
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4302028/
https://www.ncbi.nlm.nih.gov/pubmed/25582225
http://dx.doi.org/10.1186/s12920-014-0072-y
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