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.

Serum pregnancy-associated plasma protein A (PAPPA) as a predictor of eosinophilic Type-2 high asthmaTo the Editor,Pregnancy-associated plasma protein A (PAPPA), a metalloproteinase that cleaves insulin-like growth factor (IGF)-binding proteins (IGFBPs) to increase IGF availability, is expressed systemically in pregnant women but also in other tissues (1). Higher serum PAPPA levels are reported in patients with newly-diagnosed asthma (1) and allergic rhinitis compared to healthy controls and are decreased following omalizumab treatment (2). We determined whether PAPPA could represent a novel biomarker for Type-2 (T2) asthma by exploring the relationship between asthma severity and phenotypes of severe asthma and PAPPA gene and protein expression (3).We recruited 288 severe non-smoking asthma (NSA), 102 smokers and ex-smokers with severe asthma (SSA), 86 mild/moderate non-smoking asthmatics (MMA) and 95 healthy non-smoking controls (HC) from the U-BIOPRED cohort (NCT01976767) (4) (Table S1 ). Transcriptomic and proteomic profiling of blood and sputum samples and specific serum periostin ELISA were performed (3). Gene set variation analysis (GSVA) was used to calculate the enrichment score (ES) of 34 genes that were upregulated following in vitro stimulation of primary human bronchial epithelial cells with IL-13 (T2_IL-13_IVS) (3). Eosinophilic inflammation was defined by sputum eosinophilia >1.49% (3). Local Ethics Committees of the recruiting centres approved the study and all participants gave written informed consent.Sputum cell PAPPA mRNA was elevated in NSA compared to SSA, MMA and HC subjects particularly in granulocytic asthmatics and in the transcriptomic-associated cluster (TAC)1; an eosinophilic cluster (5) (Figure 1A-C ). This was more pronounced with sputum PAPPA protein analysis according to asthma severity, in eosinophilic and mixed granulocytic asthmatics and in T2-high asthmatics identified by the T2_IL-13_IVS signature (Figure 1D-F ).PAPPA mRNA expression in blood cells was similar across asthma severities, blood granulocytes and molecular phenotypes (Supplementary Figure 1A-C ). However, serum PAPPA protein levels supported the discrimination seen in sputum with significant elevation seen in SA compared to HC, in eosinophilic and mixed granulocytic asthma and in T2-high asthma (SupplementaryFigure 1D-F ).Sputum eosinophil percentages were significantly correlated with sputum (r=0.88, p=10-6) and serum (r=0.41, p=10-6) PAPPA protein levels. Overall, sputum PAPPA protein gave a greater distinction between asthma severity, granulocyte composition and T2-high asthma than with serum although fewer samples were available.These results were validated in sputum from the Airways Disease Endotyping for Personalized Therapeutics (ADEPT) study (6) (Supplementary Figure S2 ). Elevated PAPPA protein in the serum and sputum of severe asthmatics and in eosinophilic compared to non- eosinophilic subjects was seen (SupplementaryFigure S2A-D ). In addition, sputum PAPPA mRNA levels were also elevated in eosinophilic versus non-eosinophilic asthma in the ADEPT cohort (Supplementary Figure S2E ).The ES score of the T2_IL-13_IVS gene signature in bronchial brushings was significantly, but weakly, correlated with blood eosinophil counts (r=0.329, p=10-6), serum PAPPA (r=0.356, p=10-6), but not with serum periostin levels (r=0.07, p-value=0.48). In contrast, the T2 IL-13 IVS ES score was strongly correlated with sputum PAPPA levels (r=0.72, p=10-3). Sputum PAPPA protein levels also significantly correlated with markers of remodelling such as MMP10 (r=0.646, p<10-6) and MET (r=0.429, p<10-6).Receiver-operating characteristics (ROC) curve analysis was performed for sputum eosinophilia (Supplementary Table S2 ). The area under the ROC curve (AUC) for serum indicated that there was no good predictor although blood eosinophilia was the best (0.79) being marginally better than serum PAPPA and exhaled NO (Figure 2A ). In contrast, sputum PAPPA was an excellent predictor of sputum eosinophilia (0.98), better than blood eosinophilia and exhaled nitric oxide levels (Figure 2B ).Therefore, sputum PAPPA is an excellent biomarker for sputum eosinophilia and for T2-high asthma whilst serum PAPPA is as effective as blood eosinophilia in predicting high sputum eosinophil levels and with T2-high 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.

Background Although genome-wide association studies (GWAS) represent the most powerful approach for identifying genes that influence asthma, no studies have established the genetic susceptibility to asthma in the Korean population. To identify genetic variants associated with adult Korean asthmatics and compare them with the significant single nucleotide polymorphisms (SNPs) of UK asthmatics from UK Biobank. Methods Asthmatic patients were defined as having asthma if they were diagnosed by a doctor or taking medications for asthma. Controls were defined as having no asthma and chronic obstructive pulmonary disease. We performed the quality controls, genotype imputation, GWAS, and PrediXcan analysis. In GWAS, P value < 5×10-8 is considered significant. We compared significant SNPs between Korean asthmatics and UK asthmatics. Results A total of 1,386 asthmatic patients and 5,205 controls were analyzed. The SNP rs1770, located near human leukocyte antigen (HLA)-DQB1, was the most significant SNP (P=4.5×10-10). In comparison with 24 SNPs in GWAS of UK asthmatics, 6 SNPs were significant with the same odds ratio direction, including signals related to type 2 inflammation (e.g., IL1RL1, TSLP, and GATA3) and mucus plugging (e.g., MUC5AC). HLA-DQA1 showed an opposite odds ratio direction. HLA-DQB1 gene demonstrated significant imputed mRNA expression levels for lung tissue and whole blood. Conclusions The SNP rs1770 of HLA-DQB1 was the most significant SNP in Korean asthmatics. There were similarities and discrepancies in genetic variants between Korean and UK asthmatics. The GWAS of Korean asthmatics should be replicated and compared with those of GWAS of other ethnicities.

Objectives: We determined the clinical and imaging features of patients with severe COVID-19 that were associated with survival. Methods: Sixty-seven patients hospitalised with severe laboratory-confirmed COVID-19, were consecutively enrolled. Clinical data, blood measurements and chest computed tomographic (CT) scans were analyzed. Results: We compared the findings between 39 survivors and 28 non-survivors. At admission, although there were no differences in white blood cell (WBC) and platelet (PLT) counts, there was an increase of WBC, neutrophil, platelet distribution width and mean platelet volume with a marked decrease of lymphocyte, monocyte, eosinophil and PLT in non-survivor group on their last day compared to survivors (P < 0.05). Non-survivors had higher ratios of peak creatinine(P<0.05) and peak lactate dehydrogenase (LDH) (P<0.05). Compared to survivors, the incremental rate of total lesion area, ground-glass opacity (GGO) area and consolidation area on CT scans was increased in non-survivors (P<0.05).The deceleration rate of total lung volume was greater in non-survivors than survivors(P<0.05). Using the univariate survival analysis, the following were predictive of non-survival: time from admission to peak of D-dimer (D2D)<16 days , initial pro-BNP>319.0 pg/ml, peak procalcitonin (PCT) ≥0.19 ng/ml, peak creatinine>96.5 μmol/l ,peak alkaline phosphatase (ALP)>81.5 u/l, median time from admission to peak ALP<18 days, the acceleration rate of total lesional area> -11.5 cm3 /day, incremental rate of GGO area> 2.4 cm3 /day and the acceleration of consolidation area> 2.3 cm3 /day. Conclusion: Hematological counts, serum analytes and radiological indicators, the latter assessed by artificial intelligence, are robust predictors of survival outcome in COVID-19.