BACKGROUND:Lung quantitative computed tomography (qCT) severe asthma clusters have been reported, but their replication and underlying disease mechanisms are unknown. We identified and replicated qCT clusters of severe asthma in two independent asthma cohorts and determined their association with molecular pathways, using radiomultiomics, integrating qCT, multiomics and machine learning/artificial intelligence. METHODS:We used consensus clustering on qCT measurements of airway and lung CT scans, performed in 105 severe asthmatic adults from the U-BIOPRED cohort. The same qCT measurements were used to replicate qCT clusters in a subsample of the ATLANTIS asthma cohort (n=97). We performed integrated enrichment analysis using blood, sputum, bronchial biopsies, bronchial brushings and nasal brushings transcriptomics and blood and sputum proteomics to characterise radiomultiomic-associated clusters (RACs). RESULTS:qCT clusters and clinical features in U-BIOPRED were replicated in the matched ATLANTIS cohort. In the U-BIOPRED cohort, RAC1 (n=30) was predominantly female with elevated body mass index, mild airflow limitation, decreased CT lung volume and increased lung density and upregulation of the complement pathway. RAC2 (n=34) subjects had airway wall thickness and a mild degree of airflow limitation, with upregulation of proliferative pathways including neurotrophic receptor tyrosine kinase 2/tyrosine kinase receptor B, and downregulation of semaphorin pathways. RAC3 (n=41) showed increased lung attenuation area and air trapping, severe airflow limitation, hyperinflation, and upregulation of cytokine signalling and signalling by interleukin pathways, and matrix metallopeptidase 1, 2 and 9. CONCLUSIONS:U-BIOPRED severe asthma qCT clusters were replicated in a matched independent asthmatic cohort and associated with specific molecular pathways. Radiomultiomics might represent a novel strategy to identify new molecular pathways in asthma pathobiology.

AbstractBackgroundClustering approaches using single omics platforms are increasingly used to characterise molecular phenotypes of eosinophilic and neutrophilic asthma. Effective integration of multi‐omics platforms should lead towards greater refinement of asthma endotypes across molecular dimensions and indicate key targets for intervention or biomarker development.ObjectivesTo determine whether multi‐omics integration of sputum leads to improved granularity of the molecular classification of severe asthma.MethodsWe analyzed six ‐omics data blocks–microarray transcriptomics, gene set variation analysis of microarray transcriptomics, SomaSCAN proteomics assay, shotgun proteomics, 16S microbiome sequencing, and shotgun metagenomic sequencing–from induced sputum samples of 57 severe asthma patients, 15 mild‐moderate asthma patients, and 13 healthy volunteers in the U‐BIOPRED European cohort. We used Monti consensus clustering algorithm for aggregation of clustering results and Similarity Network Fusion to integrate the 6 multi‐omics datasets of the 72 asthmatics.ResultsFive stable omics‐associated clusters were identified (OACs). OAC1 had the best lung function with the least number of severe asthmatics with sputum paucigranulocytic inflammation. OAC5 also had fewer severe asthma patients but the highest incidence of atopy and allergic rhinitis, with paucigranulocytic inflammation. OAC3 comprised only severe asthmatics with the highest sputum eosinophilia. OAC2 had the highest sputum neutrophilia followed by OAC4 with both clusters consisting of mostly severe asthma but with more ex/current smokers in OAC4. Compared to OAC4, there was higher incidence of nasal polyps, allergic rhinitis, and eczema in OAC2. OAC2 had microbial dysbiosis with abundant Moraxella catarrhalis and Haemophilus influenzae. OAC4 was associated with pathways linked to IL‐22 cytokine activation, with the prediction of therapeutic response to anti‐IL22 antibody therapy.ConclusionMulti‐omics analysis of sputum in asthma has defined with greater granularity the asthma endotypes linked to neutrophilic and eosinophilic inflammation. Modelling diverse types of high‐dimensional interactions will contribute to a more comprehensive understanding of complex endotypes.Key Points Unsupervised clustering on sputum multi‐omics of asthma subjects identified 3 out of 5 clusters with predominantly severe asthma. One severe asthma cluster was linked to type 2 inflammation and sputum eosinophilia while the other 2 clusters to sputum neutrophilia. One severe neutrophilic asthma cluster was linked to Moraxella catarrhalis and to a lesser extent Haemophilus influenzae while the second cluster to activation of IL‐22.

AbstractBackgroundSevere asthma (SA) encompasses several clinical phenotypes with a heterogeneous airway microbiome. We determined the phenotypes associated with a low α‐diversity microbiome.MethodsMetagenomic sequencing was performed on sputum samples from SA participants. A threshold of 2 standard deviations below the mean of α‐diversity of mild‐moderate asthma and healthy control subjects was used to define those with an abnormal abundance threshold as relative dominant species (RDS).FindingsFifty‐one out of 97 SA samples were classified as RDSs with Haemophilus influenzae RDS being most common (n = 16), followed by Actinobacillus unclassified (n = 10), Veillonella unclassified (n = 9), Haemophilus aegyptius (n = 9), Streptococcus pseudopneumoniae (n = 7), Propionibacterium acnes (n = 5), Moraxella catarrhalis (n = 5) and Tropheryma whipplei (n = 5). Haemophilus influenzae RDS had the highest duration of disease, more exacerbations in previous year and greatest number on daily oral corticosteroids. Hierarchical clustering of RDSs revealed a C2 cluster (n = 9) of highest relative abundance of exclusively Haemophilus influenzae RDSs with longer duration of disease and higher sputum neutrophil counts associated with enrichment pathways of MAPK, NF‐κB, TNF, mTOR and necroptosis, compared to the only other cluster, C1, which consisted of 7 Haemophilus influenzae RDSs out of 42. Sputum transcriptomics of C2 cluster compared to C1 RDSs revealed higher expression of neutrophil extracellular trap pathway (NETosis), IL6‐transignalling signature and neutrophil activation.ConclusionWe describe a Haemophilus influenzae cluster of the highest relative abundance associated with neutrophilic inflammation and NETosis indicating a host response to the bacteria. This phenotype of severe asthma may respond to specific antibiotics.

INTRODUCTION:The use and generation of gene signatures have been established as a method to define molecular endotypes in complex diseases such as severe asthma. Bioinformatic approaches have now been applied to large omics datasets to define the various co-existing inflammatory and cellular functional pathways driving or characterizing a particular molecular endotype. AREAS COVERED:Molecular phenotypes and endotypes of Type 2 inflammatory pathways and also of non-Type 2 inflammatory pathways, such as IL-6 trans-signaling, IL-17 activation, and IL-22 activation, have been defined in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes dataset. There has also been the identification of the role of mast cell activation and of macrophage dysfunction in various phenotypes of severe asthma. EXPERT OPINION:Phenotyping on the basis of clinical treatable traits is not sufficient for understanding of mechanisms driving the disease in severe asthma. It is time to consider whether certain patients with severe asthma, such as those non-responsive to current therapies, including Type 2 biologics, would be better served using an approach of molecular endotyping using gene signatures for management purposes rather than the current sole reliance on blood eosinophil counts or exhaled nitric oxide measurements.

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: alpha-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 a-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. alpha-and beta-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.

Background: There is evidence of complement activation in asthma but its role remains unclear. Objective: To analyze the level of complement proteins in sputum by proteomics assay in the Chinese asthma cohort (C-BIOPRED). Method: Weighted gene correlation network analysis was used to define the unique modules that are highly correlated with clinical, physiologic and inflammatory traits. Results: A brown module was positive associated with blood eosinophil percentage (rho=0.38), blood eosinophil counts (rho=0.39), FeNO (rho=0.31), exacerbations (rho=0.13) and sputum eosinophil (%) (rho=0.48).The top enriched pathway of the brown module was complement and coagulation cascades.C5 and the C5 downstream proteins C6, C7, C8B, C8G and C9 were significantly up-regulated in the eosinophil-high group (sputum eosinophil % ≥ 2%). As a validation, sputum C5 and C9 levels were also up-regulated in the severe asthma U-BIOPRED eosinophil-high groups. Conclusion: Complement factors are highly expressed in and correlate with eosinophilic inflammation, supporting a role for the complement cascade in severe eosinophilic asthma.

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 was 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.

Sputum transcriptomic analysis of air pollutant signatures: link to asthma severity and phenotype Background: Air pollution could increase the risk of asthma exacerbations but those who are most at risk remain undefined. Aim: To determine the prevalence of gene signatures induced by exposure to components of air pollution in sputum transcriptomics of the U-BIOPRED cohort. Methods: Enrichment scores(ES) in sputum cells from 61 non-smokers severe asthma(SAns), 20 mild-moderate asthma(MMA) patients and 16 healthy-volunteers(HV) were analyzed for published signatures after ozone, SO2, NO2, NOx, PM2.5, and PM10 exposure(acute:<24 hours, short-term:1-21 days, mid-term:3 weeks-6 months or chronic:6 months-5 years). Using gene set variation analysis(GSVA), we calculated ES across severity, inflammatory phenotype, exacerbation frequency(≥3/year), and airflow limitation(FEV1/FVC<0.7). Results: Most pollutant gene signatures were enriched in SAns vs MMA/HV with significant differences for acute exposure to ozone and SO2(all p<0.02), mid-term exposure to ozone and PM2.5(all p<0.03) and chronic exposure to PM2.5 and NOx(all p<0.04).Acute and mid-term exposures were associated with a mixed/neutrophilic inflammation(all p<0.02), whereas chronic exposure with mixed/eosinophilic phenotypes(all p<0.01).No pollutants were associated with an exacerbation-prone phenotype. Only acute exposure to ozone and chronic exposure to PM2.5 or NOx were associated with airflow limitation(all p<0.03). Conclusions: Chronic exposure to constituents of air pollution may be linked to the development of more severe asthma, both neutrophilic as well as eosinophilic inflammation and to airflow obstruction, but not to exacerbations.

An amendment to this paper has been published and can be accessed via the original article.

SummaryBackgroundPatients with severe asthma may have a greater risk of dying from COVID-19 disease caused by SARS-CoV-2 virus. Angiotensin converting enzyme 2 (ACE2) receptor and enzyme proteases, transmembrane protease, serine 2 (TMPRSS2) and furin are needed for the attachment and invasion of the virus into host cells. We determined whether their expression in the airways of severe asthma patients is increased.MethodWe examined the microarray mRNA expression of ACE2, TMPRSS2 and furin in the sputum, bronchial brush and bronchial biopsies of participants in the European U-BIOPRED cohort.ResultsACE2 and furin sputum gene expression was significantly increased in severe non-smoking asthma compared to mild-moderate asthma and healthy volunteers. By contrast, TMPRSS2 expression in bronchial biopsy and bronchial brushings was increased in severe smoking and ex-smoking asthmatics, and so was furin expression in bronchial brushings. Several clinical parameters including male gender, oral steroid use and nasal polyps were positively associated with ACE2, TMPRSS2 and furin expression levels. There was a higher expression of ACE2 and furin in the sputum neutrophilic molecular phenotype with inflammasome activation compared to the eosinophilic Type2-high or paucigranulocytic phenotypes. The enrichment score of the IL-13-Type2 gene signature was positively correlated with ACE2, TMPRSS2 and furin levels.ConclusionThese key determinants of virus entry into the lungs may contribute to the poorer outcomes from COVID-19 disease in patients with severe asthma.“take home” messageIn severe asthma, gene expression of ACE, TMPRSS2 and furin are elevated compared to mild-moderate asthma and healthy volunteers, particularly in neutrophilic asthma. This might explain the increased risk of death in severe asthma afflicted with COVID19.