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Unique patterns of lower respiratory tract microbiota are associated with inflammation and hospital mortality in acute respiratory distress syndrome.

ABSTRACT: BACKGROUND:The lung microbiome maintains the homeostasis of the immune system within the lungs. In acute respiratory distress syndrome (ARDS), the lung microbiome is enriched with gut-derived bacteria; however, the specific microbiome associated with morbidity and mortality in patients with ARDS remains unclear. This study investigated the specific patterns of the lung microbiome that are correlated with mortality in ARDS patients. METHODS:We analyzed the lung microbiome from the bronchoalveolar lavage fluid (BALF) of patients with ARDS and control subjects. We measured the copy numbers of 16S rRNA and the serum and BALF cytokines (interleukin [IL]-6, IL-8, receptor for advanced glycation end products, and angiopoietin-2). RESULTS:We analyzed 47 mechanically ventilated patients diagnosed with (n?=?40) or without (n?=?7; control) ARDS. The alpha diversity was significantly decreased in ARDS patients compared with that of the controls (6.24 vs. 8.07, P?=?0.03). The 16S rRNA gene copy numbers tended to be increased in the ARDS group compared with the controls (3.83?×?106 vs. 1.01?×?105 copies/mL, P?=?0.06). ARDS patients were subdivided into the hospital survivor (n?=?24) and non-survivor groups (n?=?16). Serum IL-6 levels were significantly higher in the non-survivors than in the survivors (567 vs. 214?pg/mL, P?=?0.027). The 16S rRNA copy number was significantly correlated with serum IL-6 levels in non-survivors (r?=?0.615, P?

SUBMITTER: Kyo M

PROVIDER: S-EPMC6836399 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Unique patterns of lower respiratory tract microbiota are associated with inflammation and hospital mortality in acute respiratory distress syndrome.

Kyo Michihito M Nishioka Keisuke K Nakaya Takaaki T Kida Yoshiko Y Tanabe Yuko Y Ohshimo Shinichiro S Shime Nobuaki N

Respiratory research 20191106 1

<h4>Background</h4>The lung microbiome maintains the homeostasis of the immune system within the lungs. In acute respiratory distress syndrome (ARDS), the lung microbiome is enriched with gut-derived bacteria; however, the specific microbiome associated with morbidity and mortality in patients with ARDS remains unclear. This study investigated the specific patterns of the lung microbiome that are correlated with mortality in ARDS patients.<h4>Methods</h4>We analyzed the lung microbiome from the ...[more]

PMID: 31694652

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Project description:The microbiota of the bovine upper respiratory tract has been recently characterized, but no data for the lower respiratory tract are available. A major health problem in bovine medicine is infectious bronchopneumonia, the most common respiratory syndrome affecting cattle. With this study, we used 16S rRNA gene sequencing to characterize and compare the microbial community composition of the upper and lower respiratory tracts in calves.The microbiota of the upper (nasal swab [NS]) and the lower (trans-tracheal aspiration [TTA]) respiratory tracts of 19 post-weaned Piedmontese calves with (8/19) and without (11/19) clinical signs of respiratory disease, coming from six different farms, was characterized by 16S rRNA gene metabarcoding. A total of 29 phyla (29 in NS, 21 in TTA) and 305 genera (289 in NS, 182 in TTA) were identified. Mycoplasma (60.8%) was the most abundant genus identified in both the NS (27.3%) and TTA (76.7%) samples, followed by Moraxella (16.6%) in the NS and Pasteurella (7.3%) in the TTA samples. Pasteurella multocida (7.3% of total operational taxonomic units [OTUs]) was the most abundant species in the TTA and Psychrobacter sanguinis (1.1% of total OTUs) in the NS samples. Statistically significant differences between the NS and the TTA samples were found for both alpha (Shannon index, observed species, Chao1 index, and Simpson index; P?=?0.001) and beta (Adonis; P?=?0.001) diversity. Comparison of the NS and TTA samples by farm origin and clinical signs revealed no statistical difference (P?>?0.05), except for farm origin for the NS samples when compared by the unweighted UniFrac metric (P?=?0.05).Using 16S rRNA gene sequencing, we characterized the microbiota of the upper and lower respiratory tracts of calves, both healthy individuals and those with clinical signs of respiratory disease. Our results suggest that environmental factors may influence the composition of the upper airway microbiota in cattle. While the two microbial communities (upper and lower airways) differed in microbial composition, they shared several OTUs, suggesting that the lung microbiota may be a self-sustaining, more homogeneous ecosystem, influenced by the upper respiratory tract microbiota.

Project description:OBJECTIVES:In pediatric acute respiratory distress syndrome, lung injury is mediated by immune activation and severe inflammation. Therefore, we hypothesized that patients with elevated pro- and anti-inflammatory cytokines would have higher mortality rates and that these biomarkers could improve risk stratification of poor outcomes. DESIGN:Multicenter prospective observational study. SETTING:We enrolled patients from five academic PICUs between 2008 and 2015. PATIENTS:Patients were 1 month to 18 years old, used noninvasive or invasive ventilation, and met the American European Consensus Conference definition of acute respiratory distress syndrome. INTERVENTIONS:Eight proinflammatory and anti-inflammatory cytokines were measured on acute respiratory distress syndrome day 1 and correlated with mortality, ICU morbidity as measured by survivor Pediatric Logistic Organ Dysfunction score, and biomarkers of endothelial injury, including angiopoietin-2, von Willebrand Factor, and soluble thrombomodulin. MEASUREMENTS AND MAIN RESULTS:We measured biomarker levels in 194 patients, including 38 acute respiratory distress syndrome nonsurvivors. Interleukin-6, interleukin-8, interleukin-10, interleukin-18, and tumor necrosis factor-R2 were each strongly associated with all-cause mortality, multiple markers of ICU morbidity, and endothelial injury. A multiple logistic regression model incorporating oxygenation index, interleukin-8, and tumor necrosis factor-R2 was superior to a model of oxygenation index alone in predicting the composite outcome of mortality or severe morbidity (area under the receiver operating characteristic, 0.77 [0.70-0.83] vs 0.70 [0.62-0.77]; p = 0.042). CONCLUSIONS:In pediatric acute respiratory distress syndrome, pro- and anti-inflammatory cytokines are strongly associated with mortality, ICU morbidity, and biochemical evidence of endothelial injury. These cytokines significantly improve the ability of the oxygenation index to discriminate risk of mortality or severe morbidity and may allow for identification and enrollment of high-risk subgroups for future studies.

Project description:BackgroundLower respiratory tract infections (LRTIs) are a leading cause of childhood morbidity and mortality. Potentially pathogenic organisms are present in the respiratory tract in both symptomatic and asymptomatic children, but their presence does not necessarily indicate disease. We aimed to assess the concordance between upper and lower respiratory tract microbiota during LRTIs and the use of nasopharyngeal microbiota to discriminate LRTIs from health.MethodsFirst, we did a prospective study of children aged between 4 weeks and 5 years who were admitted to the paediatric intensive care unit (PICU) at Wilhelmina Children's Hospital (Utrecht, Netherlands) for a WHO-defined LRTI requiring mechanical ventilation. We obtained paired nasopharyngeal swabs and deep endotracheal aspirates from these participants (the so-called PICU cohort) between Sept 10, 2013, and Sept 4, 2016. We also did a matched case-control study (1:2) with the same inclusion criteria in children with LRTIs at three Dutch teaching hospitals and in age-matched, sex-matched, and time-matched healthy children recruited from the community. Nasopharyngeal samples were obtained at admission for cases and during home visits for controls. Data for child characteristics were obtained by questionnaires and from pharmacy printouts and medical charts. We used quantitative PCR and 16S rRNA-based sequencing to establish viral and bacterial microbiota profiles, respectively. We did sparse random forest classifier analyses on the bacterial data, viral data, metadata, and the combination of all three datasets to distinguish cases from controls.Findings29 patients were enrolled in the PICU cohort. Intra-individual concordance in terms of viral microbiota profiles (96% agreement [95% CI 93-99]) and bacterial microbiota profiles (58 taxa with a median Pearson's r 0·93 [IQR 0·62-0·99]; p<0·05 for all 58 taxa) was high between nasopharyngeal and endotracheal aspirate samples, supporting the use of nasopharyngeal samples as proxy for lung microbiota during LRTIs. 154 cases and 307 matched controls were prospectively recruited to our case-control cohort. Individually, bacterial microbiota (area under the curve 0·77), viral microbiota (0·70), and child characteristics (0·80) poorly distinguished health from disease. However, a classification model based on combined bacterial and viral microbiota plus child characteristics distinguished children with LRTIs from their matched controls with a high degree of accuracy (area under the curve 0·92).InterpretationOur data suggest that the nasopharyngeal microbiota can serve as a valid proxy for lower respiratory tract microbiota in childhood LRTIs, that clinical LRTIs in children result from the interplay between microbiota and host characteristics, rather than a single microorganism, and that microbiota-based diagnostics could improve future diagnostic and treatment protocols.FundingSpaarne Gasthuis, University Medical Center Utrecht, and the Netherlands Organization for Scientific Research.

Project description:BACKGROUND:Lower respiratory tract (LRT) microbiome has been reported to associate with pulmonary diseases. Unregulated inflammation is an underlying cause of variable lung diseases. The lung microbiome may play an important role in the smoking-induced inflammatory lung diseases. What's more, the function of microbiome may be more important for understanding how microbes interact with host. Our study aims to explore the effects of smoking on the lower respiratory tract microbiome, the association between variation of lower respiratory tract microbiome and inflammation and whether smoking exposure changes the function of lower respiratory tract microbime. METHODS:Forty male mice were randomly divided into smoking group and non-smoking group, and the smoking group was exposed to cigarette smoke for 2?h per day for 90?days. After experiment, the blood samples were collected to measure the concentration of interleukin-6 (IL-6) and C reactive protein (CRP) by ELISA. Lung tissue samples were used to detect the community and diversity of lower respiratory tract microbiome through 16S rRNA gene quantification and sequencing technology. ANOSIM and STAMP were performed to analyze the differences of the microbial community structure between smoking group and non-smoking group. SPSS 24.0 software was used to analyze the correlations between microbiome and inflammation mediators through scatter plots and Spearman correlation coefficient. Microbial metabolic function was predicted by PICRUSt based on the 16?s rRNA gene quantification and sequencing results. PATRIC database was searched for the potential pathogenic bacteria in lower respiratory tract. RESULTS:Our results suggested that smoking had markedly effects on the microbiota structure of lower respiratory tract based on Bray-Curtis distance (R2?=?0.084, p?=?0.005) and on unweighted uniFrac distance (R2?=?0.131, p?=?0.002). Smoking mainly affected the abundance of microbiome which belong to Proteobacteria phyla and Firmicutes phyla. Moreover, our results also found that smoking increased the abundance of Acinetobacter, Bacillus and Staphylococcus, which were defined as pathogenic bacteria. Inflammatory mediators were observed to associate with certain microbiome at every level. Most of microbiome which were associated with inflammation belonged to Proteobacteria phyla or Firmicutes phyla. Moreover, we found that the decreased microbiome in smoking group, including Oceanospirillales, Desulfuromonadales, Nesterenkonia, and Lactobacillaceae, all were negatively correlated with IL-6 or CRP. Based on the level of inflammation, the abundance of microbiome differs. At genus level, Lactobacillus, Pelagibacterium, Geobacter and Zoogloea were significantly higher in smoking group with lower IL-6 concentration. The abundance of microbiome was not observed any statistical difference in subgroups with different weight. Three dominant genus, defined as pathogen, were found higher in the smoking group. The microbial functional prediction analysis revealed that ABC-type transport systems, transcription factors, amino acide transport and metabolism, arginine and proline metabolism et al. were distinctively decreased in smoking group, while the proportions of replication, recombination and repair, ribosome, DNA repair and recombination proteins were increased in smoking group (q?<?0.05). CONCLUSIONS:Members of Proteobacteria phyla and Firmicutes phyla played an important role in the microbial community composition and keeping a relatively balanced homeostasis. Microbiome dysbiosis might break the balance of immune system to drive lung inflammation. There might exist potential probiotics in lower respiratory tract, such as Lactobacillaceae. The altered function of Lower respiratory tract microbiome under smoking exposure may affect the physiological homeostasis of host.

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Unique patterns of lower respiratory tract microbiota are associated with inflammation and hospital mortality in acute respiratory distress syndrome.

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Unique patterns of lower respiratory tract microbiota are associated with inflammation and hospital mortality in acute respiratory distress syndrome.

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