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Microbial and Host Immune Factors as Drivers of COPD

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Microbial and Host Immune Factors as Drivers of COPD

Moana Mika et al. ERJ Open Res.

Abstract

Compartmentalisation of the respiratory tract microbiota in patients with different chronic obstructive pulmonary disease (COPD) severity degrees needs to be systematically investigated. In addition, it is unknown if the inflammatory and emphysematous milieux in patients with COPD are associated with changes in the respiratory tract microbiota and host macrophage gene expression. We performed a cross-sectional study to compare non-COPD controls (n=10) to COPD patients (n=32) with different disease severity degrees. Samples (n=187) were obtained from different sites of the upper and lower respiratory tract. Microbiota analyses were performed by 16S ribosomal RNA gene sequencing and host gene expression analyses by quantitative real-time PCR of distinct markers of bronchoalveolar lavage cells. Overall, the microbial communities of severe COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade 3/4) patients clustered significantly differently to controls and less severe COPD (GOLD 1/2) patients (permutational multivariate ANOVA (MANOVA), p=0.001). However, we could not detect significant associations between the different sampling sites in the lower airways. In addition, the chosen set of host gene expression markers significantly separated COPD GOLD 3/4 patients, and we found correlations between the composition of the microbiota and the host data. In conclusion, this study demonstrates associations between host gene expression and microbiota profiles that may influence the course of COPD.

Conflict of interest statement

Conflict of interest: None declared.

Figures

FIGURE 1
FIGURE 1
Bacterial community comparison of samples with the most abundant bacterial families (>0.5% mean relative abundance). Illustrated are the samples for the upper lobe (UL), middle lobe (ML), lower lobe (LL), main bronchus (mBr), bronchoalveolar lavage (BAL), lingula, trachea and oropharynx. Samples were grouped according to the site of the respiratory tract and disease status (controls, Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade 1/2 and GOLD 3/4). The tree was produced with hierarchical clustering (hclust from the stats package in R using the ward method). Bacterial composition of chronic obstructive pulmonary disease (COPD) GOLD 3/4 patients (mBr, UL, LL, BAL, pharynx and trachea) differed significantly from samples of controls and GOLD 1/2 patients, as measured by permutational multivariate ANOVA (adonis function of the vegan package in R) (p=0.001, stress 0.196).
FIGURE 2
FIGURE 2
β-diversity analyses between sampling sites. β-diversity was calculated using the abundance-based operational taxonomic unit table as input. a–c) Relative abundance-based Jaccard dissimilarity values were graphically represented using nonmetric multidimensional scaling (NMDS) as ordination method. Stress values are indicated. Arrows indicate clustering of samples according to the sampling site and were fitted using the envfit function of R. UL: upper lobe; ML: middle lobe; LL: lower lobe; mBr: main bronchus; BAL: bronchoalveolar lavage. a) No significant difference in overall microbiota composition between the different sites of controls using permutational multivariate ANOVA (MANOVA). b) Samples from pharynx clustered significantly differently in chronic obstructive pulmonary disease (COPD) Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade 1/2 patients (permutational MANOVA, p=0.05). c) Samples from pharynx clustered significantly differently in COPD GOLD 3/4 patients (permutational MANOVA, p=0.04). d–f) Between-subject dissimilarity was measured by comparison of BAL samples from all patients within the corresponding group. Within-subject dissimilarity represents all dissimilarity values of a subject within the corresponding group. Within-subject dissimilarity was significantly lower in all three groups than the between-subject dissimilarity. #: p<0.0001, Mann–Whitney test.
FIGURE 3
FIGURE 3
Expression of bronchoalveolar lavage cell markers. The relative abundances of inflammatory (red), immunomodulatory (blue) and remodelling/scavenging receptor (green) markers are shown. Results are shown according to a) controls, b) chronic obstructive pulmonary disease (COPD) Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade 1/2 patients and c) COPD GOLD 3/4 patients. p-values (Mann–Whitney tests) of GOLD 3/4 patients compared to controls are indicated in (c). In addition, d) principal component analysis (PCA) based on the selected gene targets is shown. Mean values of the three groups were received and the highest mean value of each cell marker was set as 100% while the other values are relative means. A clear separation of GOLD 3/4 patients (3/4) from the controls (0) is illustrated (red surface). Arrows indicate clustering of samples according to the severity of COPD (i.e. controls (0), COPD GOLD 1/2 (1/2) and COPD GOLD 3/4 (3/4)). COX: cyclo-oxygenase; TIMP: tissue inhibitor of metalloproteinase; PDGF: platelet-derived growth factor; MMP: matrix metallopeptidase; DCSIGN: dendritic cell-specific intracellular adhesion molecule-3-grabbing non-integrin; MRC: mannose receptor C; IL1RN: interleukin-1 receptor antagonist; IL: interleukin; IDO: indoleamine 2,3-dioxygenase; TNF: tumour necrosis factor; PC: principal component.
FIGURE 4
FIGURE 4
Correlation of expression values of bronchoalveolar lavage cell markers with α-diversity measurements: Shannon Diversity Index (SDI) and richness (S). Illustrated are the cell markers with significant correlations with α-diversity, namely a) cyclo-oxygenase (COX)2, b) mannose receptor C (MRC)1, c) interleukin (IL)-10 and d) IL-1 receptor antagonist (IL1RN) (p-values are derived from Pearson correlation). The linear regressions (solid lines) with 95% confidence intervals (dotted lines) are indicated. Only significant p-values are shown (i.e. p<0.05).

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