Characterization of Microbiota in Bronchiectasis Patients with Different Disease Severities.
Sang Hoon LeeYeonJoo LeeJong Sun ParkYoung-Jae ChoHo Il YoonChoon-Taek LeeJae Ho LeePublished in: Journal of clinical medicine (2018)
The applications of the 16S rRNA gene pyrosequencing has expanded our knowledge of the respiratory tract microbiome originally obtained using conventional, culture-based methods. In this study, we employed DNA-based molecular techniques for examining the sputum microbiome in bronchiectasis patients, in relation to disease severity. Of the sixty-three study subjects, forty-two had mild and twenty-one had moderate or severe bronchiectasis, which was classified by calculating the FACED score, based on the FEV₁ (forced expiratory volume in 1 s, %) (F, 0⁻2 points), age (A, 0⁻2 points), chronic colonization by Pseudomonas aeruginosa (C, 0⁻1 point), radiographic extension (E, 0⁻1 point), and dyspnoea (D, 0⁻1 point). Bronchiectasis was defined as mild, at 0⁻2 points, moderate at 3⁻4 points, and severe at 5⁻7 points. The mean age was 68.0 ± 9.3 years; thirty-three patients were women. Haemophilus (p = 0.005) and Rothia (p = 0.043) were significantly more abundant in the mild bronchiectasis group, whereas Pseudomonas (p = 0.031) was significantly more abundant in the moderate or severe group. However, in terms of the alpha and beta diversity, the sputum microbiota of the two groups did not significantly differ, i.e., the same dominant genera were found in all samples. Further large-scale studies are needed to investigate the sputum microbiome in bronchiectasis.
Keyphrases
- cystic fibrosis
- pseudomonas aeruginosa
- end stage renal disease
- ejection fraction
- chronic kidney disease
- newly diagnosed
- mycobacterium tuberculosis
- biofilm formation
- respiratory tract
- prognostic factors
- peritoneal dialysis
- early onset
- healthcare
- metabolic syndrome
- pregnant women
- patient reported outcomes
- drug resistant
- copy number
- pulmonary tuberculosis
- type diabetes
- dna methylation
- intensive care unit
- genome wide
- polycystic ovary syndrome
- pregnancy outcomes
- case control
- genome wide analysis