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New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project

Several predictive models have been proposed to understand the microbial risk factors associated with cystic fibrosis (CF) progression. Very few have integrated fungal airways colonisation, which is increasingly recognized as a key player regarding CF progression. To assess the association between t...

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Autores principales: Francis, Florence, Enaud, Raphael, Soret, Perrine, Lussac-Sorton, Florian, Avalos-Fernandez, Marta, Bui, Stéphanie, Fayon, Michael, Thiébaut, Rodolphe, Delhaes, Laurence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8396880/
https://www.ncbi.nlm.nih.gov/pubmed/34442021
http://dx.doi.org/10.3390/jcm10163725
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author Francis, Florence
Enaud, Raphael
Soret, Perrine
Lussac-Sorton, Florian
Avalos-Fernandez, Marta
Bui, Stéphanie
Fayon, Michael
Thiébaut, Rodolphe
Delhaes, Laurence
author_facet Francis, Florence
Enaud, Raphael
Soret, Perrine
Lussac-Sorton, Florian
Avalos-Fernandez, Marta
Bui, Stéphanie
Fayon, Michael
Thiébaut, Rodolphe
Delhaes, Laurence
author_sort Francis, Florence
collection PubMed
description Several predictive models have been proposed to understand the microbial risk factors associated with cystic fibrosis (CF) progression. Very few have integrated fungal airways colonisation, which is increasingly recognized as a key player regarding CF progression. To assess the association between the percent predicted forced expiratory volume in 1 s (ppFEV1) change and the fungi or bacteria identified in the sputum, 299 CF patients from the “MucoFong” project were included and followed-up with over two years. The relationship between the microorganisms identified in the sputum and ppFEV1 course of patients was longitudinally analysed. An adjusted linear mixed model analysis was performed to evaluate the effect of a transient or chronic bacterial and/or fungal colonisation at inclusion on the ppFEV1 change over a two-year period. Pseudomonas aeruginosa, Achromobacter xylosoxidans, Stenotrophomonas maltophilia, and Candida albicans were associated with a significant ppFEV1 decrease. No significant association was found with other fungal colonisations. In addition, the ppFEV1 outcome in our model was 11.26% lower in patients presenting with a transient colonisation with non-pneumoniae Streptococcus species compared to other patients. These results confirm recently published data and provide new insights into bacterial and fungal colonisation as key factors for the assessment of lung function decline in CF patients.
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spelling pubmed-83968802021-08-28 New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project Francis, Florence Enaud, Raphael Soret, Perrine Lussac-Sorton, Florian Avalos-Fernandez, Marta Bui, Stéphanie Fayon, Michael Thiébaut, Rodolphe Delhaes, Laurence J Clin Med Article Several predictive models have been proposed to understand the microbial risk factors associated with cystic fibrosis (CF) progression. Very few have integrated fungal airways colonisation, which is increasingly recognized as a key player regarding CF progression. To assess the association between the percent predicted forced expiratory volume in 1 s (ppFEV1) change and the fungi or bacteria identified in the sputum, 299 CF patients from the “MucoFong” project were included and followed-up with over two years. The relationship between the microorganisms identified in the sputum and ppFEV1 course of patients was longitudinally analysed. An adjusted linear mixed model analysis was performed to evaluate the effect of a transient or chronic bacterial and/or fungal colonisation at inclusion on the ppFEV1 change over a two-year period. Pseudomonas aeruginosa, Achromobacter xylosoxidans, Stenotrophomonas maltophilia, and Candida albicans were associated with a significant ppFEV1 decrease. No significant association was found with other fungal colonisations. In addition, the ppFEV1 outcome in our model was 11.26% lower in patients presenting with a transient colonisation with non-pneumoniae Streptococcus species compared to other patients. These results confirm recently published data and provide new insights into bacterial and fungal colonisation as key factors for the assessment of lung function decline in CF patients. MDPI 2021-08-21 /pmc/articles/PMC8396880/ /pubmed/34442021 http://dx.doi.org/10.3390/jcm10163725 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Francis, Florence
Enaud, Raphael
Soret, Perrine
Lussac-Sorton, Florian
Avalos-Fernandez, Marta
Bui, Stéphanie
Fayon, Michael
Thiébaut, Rodolphe
Delhaes, Laurence
New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
title New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
title_full New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
title_fullStr New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
title_full_unstemmed New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
title_short New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
title_sort new insights in microbial species predicting lung function decline in cf: lessons from the mucofong project
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8396880/
https://www.ncbi.nlm.nih.gov/pubmed/34442021
http://dx.doi.org/10.3390/jcm10163725
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