Sputum ACE2, TMPRSS2 and FURIN gene expression in severe neutrophilic asthma

Background Patients with severe asthma may have a greater risk of dying from COVID-19 disease. Angiotensin converting enzyme-2 (ACE2) and the enzyme proteases, transmembrane protease serine 2 (TMPRSS2) and FURIN, are needed for viral attachment and invasion into host cells. Methods We examined microarray mRNA expression of ACE2, TMPRSS2 and FURIN in sputum, bronchial brushing and bronchial biopsies of the European U-BIOPRED cohort. Clinical parameters and molecular phenotypes, including asthma severity, sputum inflammatory cells, lung functions, oral corticosteroid (OCS) use, and transcriptomic-associated clusters, were examined in relation to gene expression levels. Results ACE2 levels were significantly increased in sputum of severe asthma compared to mild-moderate asthma. In multivariate analyses, sputum ACE2 levels were positively associated with OCS use and male gender. Sputum FURIN levels were significantly related to neutrophils (%) and the presence of severe asthma. In bronchial brushing samples, TMPRSS2 levels were positively associated with male gender and body mass index, whereas FURIN levels with male gender and blood neutrophils. In bronchial biopsies, TMPRSS2 levels were positively related to blood neutrophils. The neutrophilic molecular phenotype characterised by high inflammasome activation expressed significantly higher FURIN levels in sputum than the eosinophilic Type 2-high or the pauci-granulocytic oxidative phosphorylation phenotypes. Conclusion Levels of ACE2 and FURIN may differ by clinical or molecular phenotypes of asthma. Sputum FURIN expression levels were strongly associated with neutrophilic inflammation and with inflammasome activation. This might indicate the potential for a greater morbidity and mortality outcome from SARS-CoV-2 infection in neutrophilic severe asthma

Pathways linked to unresolved inflammation and airway remodelling characterize the transcriptome in two independent severe asthma cohorts

Background and objective Severe asthma (SA) is a heterogeneous disease. Transcriptomic analysis contributes to the understanding of pathogenesis necessary for developing new therapies. We sought to identify and validate mechanistic pathways of SA across two independent cohorts. Methods Transcriptomic profiles from U-BIOPRED and Australian NOVocastrian Asthma cohorts were examined and grouped into SA, mild/moderate asthma (MMA) and healthy controls (HCs). Differentially expressed genes (DEGs), canonical pathways and gene sets were identified as central to SA mechanisms if they were significant across both cohorts in either endobronchial biopsies or induced sputum. Results Thirty-six DEGs and four pathways were shared across cohorts linking to tissue remodelling/repair in biopsies of SA patients, including SUMOylation, NRF2 pathway and oxidative stress pathways. MMA presented a similar profile to HCs. Induced sputum demonstrated IL18R1 as a shared DEG in SA compared with healthy subjects. We identified enrichment of gene sets related to corticosteroid treatment; immune-related mechanisms; activation of CD4+ T cells, mast cells and IL18R1; and airway remodelling in SA. Conclusion Our results identified differentially expressed pathways that highlight the role of CD4+ T cells, mast cells and pathways linked to ongoing airway remodelling, such as IL18R1, SUMOylation and NRF2 pathways, as likely active mechanisms in the pathogenesis of SA

Haemophilus influenzae and Moraxella catarrhalis in sputum of severe asthma with inflammasome and neutrophil activation

BACKGROUND: Because of altered airway microbiome in asthma, we analysed the bacterial species in sputum of patients with severe asthma. METHODS: Whole genome sequencing was performed on induced sputum from non-smoking (SAn) and current or ex-smoker (SAs/ex) severe asthma patients, mild/moderate asthma (MMA) and healthy controls (HC). Data were analysed by asthma severity, inflammatory status and transcriptome-associated clusters (TACs). RESULTS: α-diversity at the species level was lower in SAn and SAs/ex, with an increase in Haemophilus influenzae and Moraxella catarrhalis, and Haemophilus influenzae and Tropheryma whipplei, respectively, compared to HC. In neutrophilic asthma, there was greater abundance of Haemophilus influenzae and Moraxella catarrhalis and in eosinophilic asthma, Tropheryma whipplei was increased. There was a reduction in α-diversity in TAC1 and TAC2 that expressed high levels of Haemophilus influenzae and Tropheryma whipplei, and Haemophilus influenzae and Moraxella catarrhalis, respectively, compared to HC. Sputum neutrophils correlated positively with Moraxella catarrhalis and negatively with Prevotella, Neisseria and Veillonella species and Haemophilus parainfluenzae. Sputum eosinophils correlated positively with Tropheryma whipplei which correlated with pack-years of smoking. α- and β-diversities were stable at one year. CONCLUSIONS: Haemophilus influenzae and Moraxella catarrhalis were more abundant in severe neutrophilic asthma and TAC2 linked to inflammasome and neutrophil activation, while Haemophilus influenzae and Tropheryma whipplei were highest in SAs/ex and in TAC1 associated with highest expression of IL-13 type 2 and ILC2 signatures with the abundance of Tropheryma whipplei correlating positively with sputum eosinophils. Whether these bacterial species drive the inflammatory response in asthma needs evaluation

Determinants of expression of SARS-CoV-2 entry-related genes in upper and lower airways.

Pathogenesis and treatment of chronic pulmonary disease

Urinary metabotype of severe asthma evidences decreased carnitine metabolism independent of oral corticosteroid treatment in the U-BIOPRED study

Introduction Asthma is a heterogeneous disease with poorly defined phenotypes. Patients with severe asthma often receive multiple treatments including oral corticosteroids (OCS). Treatment may modify the observed metabotype, rendering it challenging to investigate underlying disease mechanisms. Here, we aimed to identify dysregulated metabolic processes in relation to asthma severity and medication. Methods Baseline urine was collected prospectively from healthy participants (n=100), patients with mild-to-moderate asthma (n=87) and patients with severe asthma (n=418) in the cross-sectional U-BIOPRED cohort; 12–18-month longitudinal samples were collected from patients with severe asthma (n=305). Metabolomics data were acquired using high-resolution mass spectrometry and analysed using univariate and multivariate methods. Results A total of 90 metabolites were identified, with 40 significantly altered (p<0.05, false discovery rate <0.05) in severe asthma and 23 by OCS use. Multivariate modelling showed that observed metabotypes in healthy participants and patients with mild-to-moderate asthma differed significantly from those in patients with severe asthma (p=2.6×10−20), OCS-treated asthmatic patients differed significantly from non-treated patients (p=9.5×10−4), and longitudinal metabotypes demonstrated temporal stability. Carnitine levels evidenced the strongest OCS-independent decrease in severe asthma. Reduced carnitine levels were associated with mitochondrial dysfunction via decreases in pathway enrichment scores of fatty acid metabolism and reduced expression of the carnitine transporter SLC22A5 in sputum and bronchial brushings. Conclusions This is the first large-scale study to delineate disease- and OCS-associated metabolic differences in asthma. The widespread associations with different therapies upon the observed metabotypes demonstrate the need to evaluate potential modulating effects on a treatment- and metabolite-specific basis. Altered carnitine metabolism is a potentially actionable therapeutic target that is independent of OCS treatment, highlighting the role of mitochondrial dysfunction in severe asthma

Determinants of SARS-CoV-2 receptor gene expression in upper and lower airways

The recent outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19), has led to a worldwide pandemic. One week after initial symptoms develop, a subset of patients progresses to severe disease, with high mortality and limited treatment options. To design novel interventions aimed at preventing spread of the virus and reducing progression to severe disease, detailed knowledge of the cell types and regulating factors driving cellular entry is urgently needed. Here we assess the expression patterns in genes required for COVID-19 entry into cells and replication, and their regulation by genetic, epigenetic and environmental factors, throughout the respiratory tract using samples collected from the upper (nasal) and lower airways (bronchi). Matched samples from the upper and lower airways show a clear increased expression of these genes in the nose compared to the bronchi and parenchyma. Cellular deconvolution indicates a clear association of these genes with the proportion of secretory epithelial cells. Smoking status was found to increase the majority of COVID-19 related genes including ACE2 and TMPRSS2 but only in the lower airways, which was associated with a significant increase in the predicted proportion of goblet cells in bronchial samples of current smokers. Both acute and second hand smoke were found to increase ACE2 expression in the bronchus. Inhaled corticosteroids decrease ACE2 expression in the lower airways. No significant effect of genetics on ACE2 expression was observed, but a strong association of DNA- methylation with ACE2 and TMPRSS2- mRNA expression was identified in the bronchus

Systems biology in asthma.

The application of mathematical and computational analysis, together with the modelling of biological and physiological processes, is transforming our understanding of the pathophysiology of complex diseases. This systems biology approach incorporates large amounts of genomic, transcriptomic, proteomic, metabolomic, breathomic, metagenomic and imaging data from disease sites together with deep clinical phenotyping, including patient-reported outcomes. Integration of these datasets will provide a greater understanding of the molecular pathways associated with severe asthma in each individual patient and determine their personalised treatment regime. This chapter describes some of the data integration methods used to combine data sets and gives examples of the results obtained using single datasets and merging of multiple datasets (data fusion and data combination) from several consortia including the severe asthma research programme (SARP) and the Unbiased Biomarkers Predictive of Respiratory Disease Outcomes (U-BIOPRED) consortia. These results highlight the involvement of several different immune and inflammatory pathways and factors in distinct subsets of patients with severe asthma. These pathways often overlap in patients with distinct clinical features of asthma, which may explain the incomplete or no response in patients undergoing specific targeted therapy. Collaboration between groups will improve the predictions obtained using a systems medicine approach in severe asthma