Bile Acid Signal Molecules Associate Temporally with Respiratory Inflammation and Microbiome Signatures in Clinically Stable Cystic Fibrosis Patients.
Stephanie FlynnF Jerry ReenJose A Caparros-MartinDavid F WoodsJörg PepliesSarath C RanganathanStephen M StickFergal O'GaraPublished in: Microorganisms (2020)
Cystic fibrosis (CF) is a congenital disorder resulting in a multisystemic impairment in ion homeostasis. The subsequent alteration of electrochemical gradients severely compromises the function of the airway epithelia. These functional changes are accompanied by recurrent cycles of inflammation-infection that progressively lead to pulmonary insufficiency. Recent developments have pointed to the existence of a gut-lung axis connection, which may modulate the progression of lung disease. Molecular signals governing the interplay between these two organs are therefore candidate molecules requiring further clinical evaluation as potential biomarkers. We demonstrate a temporal association between bile acid (BA) metabolites and inflammatory markers in bronchoalveolar lavage fluid (BALF) from clinically stable children with CF. By modelling the BALF-associated microbial communities, we demonstrate that profiles enriched in operational taxonomic units assigned to supraglottic taxa and opportunistic pathogens are closely associated with inflammatory biomarkers. Applying regression analyses, we also confirmed a linear link between BA concentration and pathogen abundance in BALF. Analysis of the time series data suggests that the continuous detection of BAs in BALF is linked to differential ecological succession trajectories of the lung microbiota. Our data provide further evidence supporting a role for BAs in the early pathogenesis and progression of CF lung disease.
Keyphrases
- cystic fibrosis
- pseudomonas aeruginosa
- oxidative stress
- lung function
- clinical evaluation
- end stage renal disease
- ejection fraction
- electronic health record
- microbial community
- newly diagnosed
- chronic kidney disease
- big data
- young adults
- peritoneal dialysis
- pulmonary hypertension
- gold nanoparticles
- depressive symptoms
- gene expression
- climate change
- prognostic factors
- antibiotic resistance genes
- patient reported outcomes
- genome wide
- antimicrobial resistance
- ionic liquid
- data analysis
- machine learning
- candida albicans
- risk assessment
- deep learning
- dna methylation
- human health
- mass spectrometry
- chronic obstructive pulmonary disease
- single molecule
- artificial intelligence
- molecularly imprinted
- air pollution