Publication Details

AFRICAN RESEARCH NEXUS

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Microbiome balance in sputum determined by PCR stratifies COPD exacerbations and shows potential for selective use of antibiotics

PLoS ONE, Volume 12, No. 8, Article e0182833, Year 2017

Background: While a subgroup of patients with exacerbations of chronic obstructive pulmonary disease (COPD) clearly benefit from antibiotics, their identification remains challenging. We hypothesised that selective assessment of the balance between the two dominant bacterial groups (Gammaproteobacteria (G) and Firmicutes (F)) in COPD sputum samples might reveal a subgroup with a bacterial community structure change at exacerbation that was restored to baseline on recovery and potentially reflects effective antibiotic treatment. Methods: Phylogenetically specific 16S rRNA genes were determined by quantitative real time PCR to derive a G:F ratio in serial sputum samples from 66 extensively-phenotyped COPD exacerbation episodes. Results: Cluster analysis based on Euclidean distance measures, generated across the 4 visit times (stable and exacerbation day: 0,14 and 42) for the 66 exacerbation episodes, revealed three subgroups designated HG, HF, and GF reflecting predominance or equivalence of the two target bacterial groups. While the other subgroups showed no change at exacerbation, the HG cluster (n = 20) was characterized by G:F ratios that increased significantly at exacerbation and returned to baseline on recovery (p<0.00001); ratios in the HG group also correlated positively with inflammatory markers and negatively with FEV1. At exacerbation G:F showed a significant receiver-operator-characteristic curve to identify the HG subgroup (AUC 0.90, p<0.0001). Conclusions: The G:F ratio at exacerbation can be determined on a timescale compatible with decisions regarding clinical management. We propose that the G:F ratio has potential for use as a biomarker enabling selective use of antibiotics in COPD exacerbations and hence warrants further clinical evaluation.
Statistics
Citations: 34
Authors: 13
Affiliations: 6
Identifiers
Research Areas
Noncommunicable Diseases
Study Approach
Quantitative