Abstract
Progressive impairment in lung function caused by chronic polymicrobial airway infection remains the major cause of death in patients with cystic fibrosis (CF). Cross-sectional studies suggest an association between lung function decline and specific lung microbiome ecotypes. However, longitudinal studies on the stability of the airway microbiome are missing for adolescents with CF constituting the age group showing the highest rate of decline in lung function. In this study, we analyzed longitudinal lung function data and sputum samples collected over a period of 3 to 5 years from 12 adolescents with CF. The sputum microbiome was analyzed using 16S rRNA gene sequencing. Our results indicate that the individual course of the lung microbiome is associated with longitudinal lung function. In our cohort, patients with a dynamic, diverse microbiome showed a slower decline of lung function measured by FEV1% predicted, whereas a more stable and less diverse lung microbiome was related to worse outcomes. Specifically, a higher abundance of the phyla Bacteroidetes and Firmicutes was linked to a better clinical outcome, while Proteobacteria were correlated with a decline in FEV1% predicted. Our study indicates that the stability and diversity of the lung microbiome and the abundance of Bacteroidetes and Firmicutes are associated with the lung function decline and are one of the contributing factors to the disease severity.
Highlights
Patients with the autosomal recessive disorder cystic fibrosis (CF) suffer progressive impairment of lung function, which is the most common reason for reduced quality of life and mortality (Bell et al, 2020; Mall et al, 2020)
We observed that the number of intravenous (i.v.) antibiotic therapies per year correlated with the change of FEV1%pred per year: Patients showing a decline in lung function experienced more i.v. antibiotic therapies (Supplementary Figure 1)
Compared to other studies that have been focusing on the impact of clinical state or age on microbiome data from infant to adulthood (Cox et al, 2010; Carmody et al, 2018), we focused on the use of volatility and machine learning to establish the important factors that are associated with the decline in lung function during the period of the life when a fast decline in lung function and an increase of the CF disease’s burden are observed (Szczesniak et al, 2017)
Summary
Patients with the autosomal recessive disorder cystic fibrosis (CF) suffer progressive impairment of lung function, which is the most common reason for reduced quality of life and mortality (Bell et al, 2020; Mall et al, 2020). PRP such as Pseudomonas aeruginosa or Staphylococcus aureus may overgrow the commensal microbiota of the airways causing a decreased microbial diversity in the lung, which is associated with a decrease in lung function and an increase of pulmonary exacerbations in adult CF patients (Boutin et al, 2015; Coburn et al, 2015; O’Neill et al, 2015; Boutin et al, 2017). Analysis of the lung microbiome in cross-sectional studies revealed variable microbial compositions among patients with CF (Coburn et al, 2015). It was demonstrated that patients harbor an individual lung microbiome; longitudinal instead of cross-sectional studies are required to reveal the functional role of microbiome alterations (Whelan et al, 2017)
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