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Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD

OBJECTIVE: Novel biomarkers related to main clinical hallmarks of Chronic obstructive pulmonary disease (COPD), a heterogeneous disorder with pulmonary and extra-pulmonary manifestations, were investigated by profiling the serum levels of 1305 proteins using Slow Off-rate Modified Aptamers (SOMA)sca...

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Autores principales: Dagher, Rania, Fogel, Paul, Wang, Jingya, Soussan, David, Chiang, Chia-Chien, Kearley, Jennifer, Muthas, Daniel, Taillé, Camille, Berger, Patrick, Bourdin, Arnaud, Chenivesse, Cécile, Leroy, Sylvie, Anderson, Gary, Humbles, Alison A., Aubier, Michel, Kolbeck, Roland, Pretolani, Marina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731494/
https://www.ncbi.nlm.nih.gov/pubmed/36480517
http://dx.doi.org/10.1371/journal.pone.0277357
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author Dagher, Rania
Fogel, Paul
Wang, Jingya
Soussan, David
Chiang, Chia-Chien
Kearley, Jennifer
Muthas, Daniel
Taillé, Camille
Berger, Patrick
Bourdin, Arnaud
Chenivesse, Cécile
Leroy, Sylvie
Anderson, Gary
Humbles, Alison A.
Aubier, Michel
Kolbeck, Roland
Pretolani, Marina
author_facet Dagher, Rania
Fogel, Paul
Wang, Jingya
Soussan, David
Chiang, Chia-Chien
Kearley, Jennifer
Muthas, Daniel
Taillé, Camille
Berger, Patrick
Bourdin, Arnaud
Chenivesse, Cécile
Leroy, Sylvie
Anderson, Gary
Humbles, Alison A.
Aubier, Michel
Kolbeck, Roland
Pretolani, Marina
author_sort Dagher, Rania
collection PubMed
description OBJECTIVE: Novel biomarkers related to main clinical hallmarks of Chronic obstructive pulmonary disease (COPD), a heterogeneous disorder with pulmonary and extra-pulmonary manifestations, were investigated by profiling the serum levels of 1305 proteins using Slow Off-rate Modified Aptamers (SOMA)scan technology. METHODS: Serum samples were collected from 241 COPD subjects in the multicenter French Cohort of Bronchial obstruction and Asthma to measure the expression of 1305 proteins using SOMAscan proteomic platform. Clustering of the proteomics was applied to identify disease subtypes and their functional annotation and association with key clinical parameters were examined. Cluster findings were revalidated during a follow-up visit, and compared to those obtained in a group of 47 COPD patients included in the Melbourne Longitudinal COPD Cohort. RESULTS: Unsupervised clustering identified two clusters within COPD subjects at inclusion. Cluster 1 showed elevated levels of factors contributing to tissue injury, whereas Cluster 2 had higher expression of proteins associated with enhanced immunity and host defense, cell fate, remodeling and repair and altered metabolism/mitochondrial functions. Patients in Cluster 2 had a lower incidence of exacerbations, unscheduled medical visits and prevalence of emphysema and diabetes. These protein expression patterns were conserved during a follow-up second visit, and substanciated, by a large part, in a limited series of COPD patients. Further analyses identified a signature of 15 proteins that accurately differentiated the two COPD clusters at the 2 visits. CONCLUSIONS: This study provides insights into COPD heterogeneity and suggests that overexpression of factors involved in lung immunity/host defense, cell fate/repair/ remodelling and mitochondrial/metabolic activities contribute to better clinical outcomes. Hence, high throughput proteomic assay offers a powerful tool for identifying COPD endotypes and facilitating targeted therapies.
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spelling pubmed-97314942022-12-09 Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD Dagher, Rania Fogel, Paul Wang, Jingya Soussan, David Chiang, Chia-Chien Kearley, Jennifer Muthas, Daniel Taillé, Camille Berger, Patrick Bourdin, Arnaud Chenivesse, Cécile Leroy, Sylvie Anderson, Gary Humbles, Alison A. Aubier, Michel Kolbeck, Roland Pretolani, Marina PLoS One Research Article OBJECTIVE: Novel biomarkers related to main clinical hallmarks of Chronic obstructive pulmonary disease (COPD), a heterogeneous disorder with pulmonary and extra-pulmonary manifestations, were investigated by profiling the serum levels of 1305 proteins using Slow Off-rate Modified Aptamers (SOMA)scan technology. METHODS: Serum samples were collected from 241 COPD subjects in the multicenter French Cohort of Bronchial obstruction and Asthma to measure the expression of 1305 proteins using SOMAscan proteomic platform. Clustering of the proteomics was applied to identify disease subtypes and their functional annotation and association with key clinical parameters were examined. Cluster findings were revalidated during a follow-up visit, and compared to those obtained in a group of 47 COPD patients included in the Melbourne Longitudinal COPD Cohort. RESULTS: Unsupervised clustering identified two clusters within COPD subjects at inclusion. Cluster 1 showed elevated levels of factors contributing to tissue injury, whereas Cluster 2 had higher expression of proteins associated with enhanced immunity and host defense, cell fate, remodeling and repair and altered metabolism/mitochondrial functions. Patients in Cluster 2 had a lower incidence of exacerbations, unscheduled medical visits and prevalence of emphysema and diabetes. These protein expression patterns were conserved during a follow-up second visit, and substanciated, by a large part, in a limited series of COPD patients. Further analyses identified a signature of 15 proteins that accurately differentiated the two COPD clusters at the 2 visits. CONCLUSIONS: This study provides insights into COPD heterogeneity and suggests that overexpression of factors involved in lung immunity/host defense, cell fate/repair/ remodelling and mitochondrial/metabolic activities contribute to better clinical outcomes. Hence, high throughput proteomic assay offers a powerful tool for identifying COPD endotypes and facilitating targeted therapies. Public Library of Science 2022-12-08 /pmc/articles/PMC9731494/ /pubmed/36480517 http://dx.doi.org/10.1371/journal.pone.0277357 Text en © 2022 Dagher et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Dagher, Rania
Fogel, Paul
Wang, Jingya
Soussan, David
Chiang, Chia-Chien
Kearley, Jennifer
Muthas, Daniel
Taillé, Camille
Berger, Patrick
Bourdin, Arnaud
Chenivesse, Cécile
Leroy, Sylvie
Anderson, Gary
Humbles, Alison A.
Aubier, Michel
Kolbeck, Roland
Pretolani, Marina
Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD
title Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD
title_full Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD
title_fullStr Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD
title_full_unstemmed Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD
title_short Proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in COPD
title_sort proteomic profiling of serum identifies a molecular signature that correlates with clinical outcomes in copd
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9731494/
https://www.ncbi.nlm.nih.gov/pubmed/36480517
http://dx.doi.org/10.1371/journal.pone.0277357
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