Targeting the Wnt signaling pathway through R-spondin 3 identifies an anti-fibrosis treatment strategy for multiple organs

The Wnt/β-catenin signaling pathway has been implicated in human proliferative diseases such as cancer and fibrosis. The functions of β-catenin and several other components of this pathway have been investigated in fibrosis. However, the potential role of R-spondin proteins (RSPOs), enhancers of the Wnt/β-catenin signaling, has not been described. A specific interventional strategy targeting this pathway for fibrosis remains to be defined. We developed monoclonal antibodies against members of the RSPO family (RSPO1, 2, and 3) and probed their potential function in fibrosis in vivo. We demonstrated that RSPO3 plays a critical role in the development of fibrosis in multiple organs. Specifically, an anti-RSPO3 antibody, OMP-131R10, when dosed therapeutically, attenuated fibrosis in carbon tetrachloride (CCl4)-induced liver fibrosis, bleomycin-induced pulmonary and skin fibrosis models. Mechanistically, we showed that RSPO3 induces multiple pro-fibrotic chemokines and cytokines in Kupffer cells and hepatocytes. We found that the anti-fibrotic activity of OMP-131R10 is associated with its inhibition of β-catenin activation in vivo. Finally, RSPO3 was found to be highly elevated in the active lesions of fibrotic tissues in mouse models of fibrosis and in patients with idiopathic pulmonary fibrosis (IPF) and nonalcoholic steatohepatitis (NASH). Together these data provide an anti-fibrotic strategy for targeting the Wnt/β-catenin pathway through RSPO3 blockade and support that OMP-131R10 could be an important therapeutic agent for fibrosis

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.</p

Is atrial fibrillation in HFpEF a distinct phenotype? Insights from multiparametric MRI and circulating biomarkers.

Heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF) frequently co-exist. There is a limited understanding on whether this coexistence is associated with distinct alterations in myocardial remodelling and mechanics. We aimed to determine if patients with atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF) represent a distinct phenotype.In this secondary analysis of adults with HFpEF (NCT03050593), participants were comprehensively phenotyped with stress cardiac MRI, echocardiography and plasma fibroinflammatory biomarkers, and were followed for the composite endpoint (HF hospitalisation or death) at a median of 8.5 years. Those with AF were compared to sinus rhythm (SR) and unsupervised cluster analysis was performed to explore possible phenotypes.136 subjects were included (SR = 75, AF = 61). The AF group was older (76 ± 8 vs. 70 ± 10 years) with less diabetes (36% vs. 61%) compared to the SR group and had higher left atrial (LA) volumes (61 ± 30 vs. 39 ± 15 mL/m2, p  Background Methods Results Conclusions</p

Correction to: Sputum ACE2, TMPRSS2 and FURIN gene expression in severe neutrophilic asthma (Respiratory Research, (2021), 22, 1, (10), 10.1186/s12931-020-01605-8)

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

Is atrial fibrillation in HFpEF a distinct phenotype? Insights from multiparametric MRI and circulating biomarkers.

Heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF) frequently co-exist. There is a limited understanding on whether this coexistence is associated with distinct alterations in myocardial remodelling and mechanics. We aimed to determine if patients with atrial fibrillation (AF) and heart failure with preserved ejection fraction (HFpEF) represent a distinct phenotype.In this secondary analysis of adults with HFpEF (NCT03050593), participants were comprehensively phenotyped with stress cardiac MRI, echocardiography and plasma fibroinflammatory biomarkers, and were followed for the composite endpoint (HF hospitalisation or death) at a median of 8.5 years. Those with AF were compared to sinus rhythm (SR) and unsupervised cluster analysis was performed to explore possible phenotypes.136 subjects were included (SR = 75, AF = 61). The AF group was older (76 ± 8 vs. 70 ± 10 years) with less diabetes (36% vs. 61%) compared to the SR group and had higher left atrial (LA) volumes (61 ± 30 vs. 39 ± 15 mL/m2, p  Background Methods Results Conclusions</p

Association of differential mast cell activation with granulocytic inflammation in severe asthma

Rationale: mast cells (MCs) play a role in inflammation and both innate and adaptive immunity, but their involvement in severe asthma (SA) remains undefined. Objectives: we investigated the phenotypic characteristics of the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) asthma cohort by applying published MC activation signatures to the sputum cell transcriptome. Methods: eighty-four participants with SA, 20 with mild/moderate asthma (MMA), and 16 healthy participants without asthma were studied. We calculated enrichment scores (ESs) for nine MC activation signatures by asthma severity, sputum granulocyte status, and three previously defined sputum molecular phenotypes or transcriptome-associated clusters (TACs) 1, 2, and 3 using gene set variation analysis. Measurements and Main Results: MC signatures except unstimulated, repeated FceR1-stimulated and IFN-g–stimulated signatures were enriched in SA. A FceR1-IgE–stimulated and a single-cell signature from asthmatic bronchial biopsies were highly enriched in eosinophilic asthma and in the TAC1 molecular phenotype. Subjects with a high ES for these signatures had elevated sputum amounts of similar genes and pathways. IL-33– and LPS-stimulated MC signatures had greater ES in neutrophilic and mixed granulocytic asthma and in the TAC2 molecular phenotype. These subjects exhibited neutrophil, NF-kB (nuclear factor-kB), and IL-1b/TNF-a (tumor necrosis factor-a) pathway activation. The IFN-g–stimulated signature had the greatest ES in TAC2 and TAC3 that was associated with responses to viral infection. Similar results were obtained in an independent ADEPT (Airway Disease Endotyping for Personalized Therapeutics) asthma cohort. Conclusions: gene signatures of MC activation allow the detection of SA phenotypes and indicate that MCs can be induced to take on distinct transcriptional phenotypes associated with specific clinical phenotypes. IL-33–stimulated MC signature was associated with severe neutrophilic asthma, whereas IgE-activated MC was associated with an eosinophilic phenotype.</p

Validated and longitudinally stable asthma phenotypes based on cluster analysis of the ADEPT study

BACKGROUND: Asthma is a disease of varying severity and differing disease mechanisms. To date, studies aimed at stratifying asthma into clinically useful phenotypes have produced a number of phenotypes that have yet to be assessed for stability and to be validated in independent cohorts. The aim of this study was to define and validate, for the first time ever, clinically driven asthma phenotypes using two independent, severe asthma cohorts: ADEPT and U-BIOPRED. METHODS: Fuzzy partition-around-medoid clustering was performed on pre-specified data from the ADEPT participants (n = 156) and independently on data from a subset of U-BIOPRED asthma participants (n = 82) for whom the same variables were available. Models for cluster classification probabilities were derived and applied to the 12-month longitudinal ADEPT data and to a larger subset of the U-BIOPRED asthma dataset (n = 397). High and low type-2 inflammation phenotypes were defined as high or low Th2 activity, indicated by endobronchial biopsies gene expression changes downstream of IL-4 or IL-13. RESULTS: Four phenotypes were identified in the ADEPT (training) cohort, with distinct clinical and biomarker profiles. Phenotype 1 was "mild, good lung function, early onset", with a low-inflammatory, predominantly Type-2, phenotype. Phenotype 2 had a "moderate, hyper-responsive, eosinophilic" phenotype, with moderate asthma control, mild airflow obstruction and predominant Type-2 inflammation. Phenotype 3 had a "mixed severity, predominantly fixed obstructive, non-eosinophilic and neutrophilic" phenotype, with moderate asthma control and low Type-2 inflammation. Phenotype 4 had a "severe uncontrolled, severe reversible obstruction, mixed granulocytic" phenotype, with moderate Type-2 inflammation. These phenotypes had good longitudinal stability in the ADEPT cohort. They were reproduced and demonstrated high classification probability in two subsets of the U-BIOPRED asthma cohort. CONCLUSIONS: Focusing on the biology of the four clinical independently-validated easy-to-assess ADEPT asthma phenotypes will help understanding the unmet need and will aid in developing tailored therapies. TRIAL REGISTRATION: NCT01274507 (ADEPT), registered October 28, 2010 and NCT01982162 (U-BIOPRED), registered October 30, 2013

U-BIOPRED clinical adult asthma clusters linked to a subset of sputum omics

Background: Asthma is a heterogeneous disease in which there is a differential response to asthma treatments. This heterogeneity needs to be evaluated so that a personalized management approach can be provided. Objectives: We stratified patients with moderate-to-severe asthma based on clinicophysiologic parameters and performed an omics analysis of sputum. Methods: Partition-around-medoids clustering was applied to a training set of 266 asthmatic participants from the European Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes (U-BIOPRED) adult cohort using 8 prespecified clinic-physiologic variables. This was repeated in a separate validation set of 152 asthmatic patients. The clusters were compared based on sputum proteomics and transcriptomics data. Results: Four reproducible and stable clusters of asthmatic patients were identified. The training set cluster T1 consists of patients with well-controlled moderate-to-severe asthma, whereas cluster T2 is a group of patients with late-onset severe asthma with a history of smoking and chronic airflow obstruction. Cluster T3 is similar to cluster T2 in terms of chronic airflow obstruction but is composed of nonsmokers. Cluster T4 is predominantly composed of obese female patients with uncontrolled severe asthma with increased exacerbations but with normal lung function. The validation set exhibited similar clusters, demonstrating reproducibility of the classification. There were significant differences in sputum proteomics and transcriptomics between the clusters. The severe asthma clusters (T2, T3, and T4) had higher sputum eosinophilia than cluster T1, with no differences in sputum neutrophil counts and exhaled nitric oxide and serum IgE levels. Conclusion: Clustering based on clinicophysiologic parameters yielded 4 stable and reproducible clusters that associate with different pathobiological pathways