Dataset Information

The nasal microbiome in asthma.

ABSTRACT: BACKGROUND:Nasal microbiota may influence asthma pathobiology. OBJECTIVE:We sought to characterize the nasal microbiome of subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls to identify nasal microbiota associated with asthma activity. METHODS:We performed 16S ribosomal RNA sequencing on nasal swabs obtained from 72 primarily adult subjects with exacerbated asthma (n = 20), nonexacerbated asthma (n = 31), and healthy controls (n = 21). Analyses were performed using Quantitative Insights into Microbial (QIIME); linear discriminant analysis effect size (LEfSe); Phylogenetic Investigation of Communities by Reconstruction of Unobserved States; and Statistical Analysis of Metagenomic Profiles (PICRUSt); and Statistical Analysis of Metagenomic Profiles (STAMP). Species found to be associated with asthma activity were validated using quantitative PCR. Metabolic pathways associated with differentially abundant nasal taxa were inferred through metagenomic functional prediction. RESULTS:Nasal bacterial composition significantly differed among subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls (permutational multivariate ANOVA, P = 2.2 × 10-2). Relative to controls, the nasal microbiota of subjects with asthma were enriched with taxa from Bacteroidetes (Wilcoxon-Mann-Whitney, r = 0.33, P = 5.1 × 10-3) and Proteobacteria (r = 0.29, P = 1.4 × 10-2). Four species were differentially abundant based on asthma status after correction for multiple comparisons: Prevotella buccalis, Padj = 1.0 × 10-2; Dialister invisus, Padj = 9.1 × 10-3; Gardnerella vaginalis, Padj = 2.8 × 10-3; Alkanindiges hongkongensis, Padj = 2.6 × 10-3. These phyla and species were also differentially abundant based on asthma activity (exacerbated asthma vs nonexacerbated asthma vs controls). Quantitative PCR confirmed species overrepresentation in asthma relative to controls for Prevotella buccalis (fold change = 130, P = 2.1 × 10-4) and Gardnerella vaginalis (fold change = 160, P = 6.8 × 10-4). Metagenomic inference revealed differential glycerolipid metabolism (Kruskal-Wallis, P = 1.9 × 10-4) based on asthma activity. CONCLUSIONS:Nasal microbiome composition differs in subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls. The identified nasal taxa could be further investigated for potential mechanistic roles in asthma and as possible biomarkers of asthma activity.

SUBMITTER: Fazlollahi M

PROVIDER: S-EPMC6123291 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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The nasal microbiome in asthma.

Fazlollahi Mina M Lee Tricia D TD Andrade Jade J Oguntuyo Kasopefoluwa K Chun Yoojin Y Grishina Galina G Grishin Alexander A Bunyavanich Supinda S

The Journal of allergy and clinical immunology 20180305 3

<h4>Background</h4>Nasal microbiota may influence asthma pathobiology.<h4>Objective</h4>We sought to characterize the nasal microbiome of subjects with exacerbated asthma, nonexacerbated asthma, and healthy controls to identify nasal microbiota associated with asthma activity.<h4>Methods</h4>We performed 16S ribosomal RNA sequencing on nasal swabs obtained from 72 primarily adult subjects with exacerbated asthma (n = 20), nonexacerbated asthma (n = 31), and healthy controls (n = 21). Analyses we ...[more]

PMID: 29518419

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Project description:Perturbation of the microbiome has numerous associations with the phenotypes and progression in chronic airways disease. However, the differences in the nasal microbiome in asthma and allergic rhinitis (AR) have not been defined. We examined whether the nasal microbiome would vary among different comorbidities in asthma and AR and that those differences may be associated with the severity of asthma. Nasal lavage fluid was collected from 110 participants, including 20 healthy controls, 30 subjects with AR, 30 subjects with asthma and 30 subjects with combined asthma + AR. The Asthma Control Questionnaire (ACQ-7) was used to evaluate asthma control status. Using 16S rRNA bacterial gene sequencing, we analyzed nasal microbiome in patients with asthma, AR, combined asthma + AR, and healthy controls. Bacterial diversity was analyzed in corresponding with α diversity indices (Chao and Shannon index). Compared with healthy controls, the Chao index tended to be lower in subjects with AR (P = 0.001), asthma (P = 0.001), and combined asthma + AR (P = 0.001) when compared with healthy controls. Furthermore, the Shannon index was significantly lower in subjects with asthma (P = 0.013) and comorbid asthma with AR (P = 0.004) than the control subjects. Disparity in the structure and composition of nasal bacteria were also observed among the four groups. Furthermore, patients with combined asthma + AR and isolated asthma were divided into two groups according to the level of disease control: partially or well-controlled and uncontrolled asthma. The mean relative abundance observed in the groups mentioned the genera of Pseudoflavonifractor were dominated in patients with well and partially controlled disease, in both isolated asthma and combined asthma + AR. In subjects with uncontrolled asthma and combined asthma + AR, a lower evenness and richness (Shannon index, P = 0.040) was observed in nasal microbiome composition. Importantly, lower evenness and richness in the nasal microbiome may be associated with poor disease control in combined asthma + AR. This study showed the upper airway microbiome is associated with airway inflammation disorders and the level of asthma control.

Project description:Background: Nasal epithelia are emerging as a proxy measure of gene expression of the airway epithelium in asthma. We hypothesized that epigenetic marks regulate gene expression of the nasal epithelia and consequently may provide a novel target for allergic asthma. Methods: We compared genomic DNA methylation patterns and gene expression in African American children with persistent atopic asthma [N=36] versus healthy controls [N=36]. Results were validated in an independent population of asthmatics [N=30]. Results: We identified 186 genes with significant methylation changes, either as regions (differentially methylated regions [DMRs]) or single CpGs (differentially methylated probes [DMPs]) after adjustment for age, gender, race/ethnicity, batch effects, inflation, and multiple comparisons (false discovery rate-adjusted q<0.05). Genes differentially methylated include those with established roles in asthma and atopy, components of the extracellular matrix, genes related to immunity, cell adhesion, epigenetic regulation, and airway obstruction. The methylation changes are large (median 9.5%, range: 2.6-29.5% methylation change) and similar in magnitude to those observed in malignancies. Hypo- and hyper-methylated genes were associated with increased and decreased gene expression respectively (P<2.8x10-6 for DMRs and P<7.8x10-10 for DMPs). Quantitative analysis of methylation-expression relationships in 53 differentially expressed genes demonstrated that 32 (60%) have significant (q<0.05) methylation-expression relationships within 5kb of the gene. 10 loci selected based on the relevance to asthma, magnitude of methylation change, and asthma specific methylation-expression relationships were validated in an independent cohort of children with asthma. Conclusions: Our findings that epigenetic marks in respiratory epithelia are associated with allergic asthma in inner-city children provide new targets for biomarker development, and novel approaches to understanding disease pathogenesis. case control design with nasal epithelial cells from 36 atopic asthmatic and 36 nonatopic nonasthmatic children from the inner city

Project description:BackgroundGiven the strong environmental influence on both epigenetic marks and allergic asthma in children, the epigenetic alterations in respiratory epithelia might provide insight into allergic asthma.ObjectiveWe sought to identify DNA methylation and gene expression changes associated with childhood allergic persistent asthma.MethodsWe compared genomic DNA methylation patterns and gene expression in African American children with persistent atopic asthma (n = 36) versus healthy control subjects (n = 36). Results were validated in an independent population of asthmatic children (n = 30) by using a shared healthy control population (n = 36) and in an independent population of white adult atopic asthmatic patients (n = 12) and control subjects (n = 12).ResultsWe identified 186 genes with significant methylation changes, differentially methylated regions or differentially methylated probes, after adjustment for age, sex, race/ethnicity, batch effects, inflation, and multiple comparisons. Genes differentially methylated included those with established roles in asthma and atopy and genes related to extracellular matrix, immunity, cell adhesion, epigenetic regulation, and airflow obstruction. The methylation changes were substantial (median, 9.5%; range, 2.6% to 29.5%). Hypomethylated and hypermethylated genes were associated with increased and decreased gene expression, respectively (P < 2.8 × 10-6 for differentially methylated regions and P < 7.8 × 10-10 for differentially methylated probes). Quantitative analysis in 53 differentially expressed genes demonstrated that 32 (60%) have significant methylation-expression relationships within 5 kb of the gene. Ten loci selected based on the relevance to asthma, magnitude of methylation change, and methylation-expression relationships were validated in an independent cohort of children with atopic asthma. Sixty-seven of 186 genes also have significant asthma-associated methylation changes in nasal epithelia of adult white asthmatic patients.ConclusionsEpigenetic marks in respiratory epithelia are associated with allergic asthma and gene expression changes in inner-city children.

Dataset Information

The nasal microbiome in asthma.

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The nasal microbiome in asthma.

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