Fulfilling the Promise of Breathomics: Considerations for the Discovery and Validation of Exhaled Volatile Biomarkers.

The exhaled breath represents an ideal matrix for non-invasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review we will specifically address volatile organic compounds in the breath, with a view towards fulfilling the promise of these as actionable biomarkers, in particular for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward, if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

RATIONALE: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. METHODS: VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). MAIN RESULTS: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). CONCLUSIONS: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

Exhaled Volatile Organic Compounds for Asthma Control Classification in Children with Moderate to Severe Asthma: Results from the SysPharmPediA Study.

RATIONALE: Early identification of children with poorly controlled asthma is imperative for optimizing treatment strategies. The analysis of exhaled volatile organic compounds (VOCs) is an emerging approach to identify prognostic and diagnostic biomarkers in pediatric asthma. OBJECTIVES: To assess the accuracy of gas chromatography-mass spectrometry based exhaled metabolite analysis to differentiate between controlled and uncontrolled pediatric asthma. METHODS: This study encompassed a discovery (SysPharmPediA) and validation phase (U-BIOPRED, PANDA). Firstly, exhaled VOCs that discriminated asthma control levels were identified. Subsequently, outcomes were validated in two independent cohorts. Patients were classified as controlled or uncontrolled, based on asthma control test scores and number of severe attacks in the past year. Additionally, potential of VOCs in predicting two or more future severe asthma attacks in SysPharmPediA was evaluated. MEASUREMENTS AND MAIN RESULTS: Complete data were available for 196 children (SysPharmPediA=100, U-BIOPRED=49, PANDA=47). In SysPharmPediA, after randomly splitting the population into training (n=51) and test sets (n=49), three compounds (acetophenone, ethylbenzene, and styrene) distinguished between uncontrolled and controlled asthmatics. The area under the receiver operating characteristic curve (AUROCC) for training and test sets were respectively: 0.83 (95% CI: 0.65-1.00) and 0.77 (95% CI: 0.58-0.96). Combinations of these VOCs resulted in AUROCCs of 0.74 ±0.06 (UBIOPRED) and 0.68 ±0.05 (PANDA). Attacks prediction tests, resulted in AUROCCs of 0.71 (95% CI 0.51-0.91) and 0.71 (95% CI 0.52-0.90) for training and test sets. CONCLUSIONS: Exhaled metabolites analysis might enable asthma control classification in children. This should stimulate further development of exhaled metabolites-based point-of-care tests in asthma.

Biomarker Predictors of Clinical Efficacy of the Anti-IgE Biologic, Omalizumab, in Severe Asthma in Adults: Results of the SoMOSA Study.

BACKGROUND: The anti-IgE monoclonal, omalizumab, is widely used for severe asthma. This study aimed to identify biomarkers that predict clinical improvement during one year of omalizumab treatment. METHODS: 1-year, open-label, Study of Mechanisms of action of Omalizumab in Severe Asthma (SoMOSA) involving 216 severe (GINA step 4/5) uncontrolled atopic asthmatics (≥2 severe exacerbations in previous year) on high-dose inhaled corticosteroids, long-acting ß-agonists, ± mOCS. It had two phases: 0-16 weeks, to assess early clinical improvement by Global Evaluation of Therapeutic Effectiveness (GETE), and 16-52 weeks, to assess late responses by ≥50% reduction in exacerbations or dose of maintenance oral corticosteroids (mOCS). All participants provided samples (exhaled breath, blood, sputum, urine) before and after 16 weeks of omalizumab treatment. RESULTS: 191 patients completed phase 1; 63% had early improvement. Of 173 who completed phase 2, 69% had reduced exacerbations by ≥50%, while 57% (37/65) on mOCS reduced their dose by ≥50%. The primary outcome 2, 3-dinor-11-ß-PGF2α, GETE and standard clinical biomarkers (blood and sputum eosinophils, exhaled nitric oxide, serum IgE) did not predict either clinical response. Five breathomics (GC-MS) and 5 plasma lipid biomarkers strongly predicted the ≥50% reduction in exacerbations (receiver operating characteristic area under the curve (AUC): 0.780 and 0.922, respectively) and early responses (AUC:0.835 and 0.949, respectively). In independent cohorts, the GC-MS biomarkers differentiated between severe and mild asthma. Conclusions This is the first discovery of omics biomarkers that predict improvement to a biologic for asthma. Their prospective validation and development for clinical use is justified. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Airway hyperresponsiveness in asthma: The role of the epithelium.

Airway hyperresponsiveness (AHR) is a key clinical feature of asthma. The presence of AHR in people with asthma provides the substrate for bronchoconstriction in response to numerous diverse stimuli, contributing to airflow limitation and symptoms including breathlessness, wheeze, and chest tightness. Dysfunctional airway smooth muscle significantly contributes to AHR and is displayed as increased sensitivity to direct pharmacologic bronchoconstrictor stimuli, such as inhaled histamine and methacholine (direct AHR), or to endogenous mediators released by activated airway cells such as mast cells (indirect AHR). Research in in vivo human models has shown that the disrupted airway epithelium plays an important role in driving inflammation that mediates indirect AHR in asthma through the release of cytokines such as thymic stromal lymphopoietin and IL-33. These cytokines upregulate type 2 cytokines promoting airway eosinophilia and induce the release of bronchoconstrictor mediators from mast cells such as histamine, prostaglandin D2, and cysteinyl leukotrienes. While bronchoconstriction is largely due to airway smooth muscle contraction, airway structural changes known as remodeling, likely mediated in part by epithelial-derived mediators, also lead to airflow obstruction and may enhance AHR. In this review, we outline the current knowledge of the role of the airway epithelium in AHR in asthma and its implications on the wider disease. Increased understanding of airway epithelial biology may contribute to better treatment options, particularly in precision medicine.

A single extraction 96-well method for LC-MS/MS quantification of urinary eicosanoids, steroids and drugs.

Urinary eicosanoid concentrations reflect inflammatory processes in multiple diseases and have been used as biomarkers of disease as well as suggested for patient stratification in precision medicine. However, implementation of urinary eicosanoid profiling in large-scale analyses is restricted due to sample preparation limits. Here we demonstrate a single solid-phase extraction of 300 µL urine in 96-well-format for prostaglandins, thromboxanes, isoprostanes, cysteinyl-leukotriene E4 and the linoleic acid-derived dihydroxy-octadecenoic acids (9,10- and 12,13-DiHOME). A simultaneous screening protocol was also developed for cortisol/cortisone and 7 exogenous steroids as well as 3 cyclooxygenase inhibitors. Satisfactory performance for quantification of eicosanoids with an appropriate internal standard was demonstrated for intra-plate analyses (CV = 8.5-15.1%) as well as for inter-plate (n = 35) from multiple studies (CV = 22.1-34.9%). Storage stability was evaluated at - 20 °C, and polar tetranors evidenced a 50% decrease after 5 months, while the remaining eicosanoids evidenced no significant degradation. All eicosanoids were stable over 3.5-years in urine stored at - 80 °C. This method will facilitate the implementation of urinary eicosanoid quantification in large-scale screening.

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

BACKGROUND: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. OBJECTIVE: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. METHODS: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. RESULTS: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. CONCLUSION: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

Identifying and appraising outcome measures for severe asthma: a systematic review.

BACKGROUND: Valid outcome measures are imperative to evaluate treatment response, yet the suitability of existing end-points for severe asthma is unclear. This review aimed to identify outcome measures for severe asthma and appraise the quality of their measurement properties. METHODS: A literature search was performed to identify "candidate" outcome measures published between 2018 and 2020. A modified Delphi exercise was conducted to select "key" outcome measures within healthcare professional, patient, pharmaceutical and regulatory stakeholder groups. Initial validation studies for "key" measures were rated against modified quality criteria from COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). The evidence was discussed at multi-stakeholder meetings to ratify "priority" outcome measures. Subsequently, four bibliographic databases were searched from inception to 20 July 2020 to identify development and validation studies for these end-points. Two reviewers screened records, extracted data, assessed their methodological quality and graded the evidence according to COSMIN. RESULTS: 96 outcome measures were identified as "candidates", 55 as "key" and 24 as "priority" for severe asthma, including clinical, healthcare utilisation, quality of life, asthma control and composite. 32 studies reported measurement properties of 17 "priority" end-points from the latter three domains. Only the Severe Asthma Questionnaire and Childhood Asthma Control Test were developed with input from severe asthma patients. The certainty of evidence was "low" to "very low" for most "priority" end-points across all measurement properties and none fulfilled all quality standards. CONCLUSIONS: Only two outcome measures had robust developmental data for severe asthma. This review informed development of core outcome measures sets for severe asthma.

Development of Core Outcome Measures sets for paediatric and adult Severe Asthma (COMSA).

BACKGROUND: Effectiveness studies with biological therapies for asthma lack standardised outcome measures. The COMSA (Core Outcome Measures sets for paediatric and adult Severe Asthma) Working Group sought to develop Core Outcome Measures (COM) sets to facilitate better synthesis of data and appraisal of biologics in paediatric and adult asthma clinical studies. METHODS: COMSA utilised a multi-stakeholder consensus process among patients with severe asthma, adult and paediatric clinicians, pharmaceutical representatives, and health regulators from across Europe. Evidence included a systematic review of development, validity and reliability of selected outcome measures plus a narrative review and a pan-European survey to better understand patients' and carers' views about outcome measures. It was discussed using a modified GRADE (Grading of Recommendations Assessment, Development and Evaluation) Evidence to Decision framework. Anonymous voting was conducted using predefined consensus criteria. RESULTS: Both adult and paediatric COM sets include forced expiratory volume in 1 s (FEV1) as z-scores, annual frequency of severe exacerbations and maintenance oral corticosteroid use. Additionally, the paediatric COM set includes the Paediatric Asthma Quality of Life Questionnaire and Asthma Control Test or Childhood Asthma Control Test, while the adult COM set includes the Severe Asthma Questionnaire and Asthma Control Questionnaire-6 (symptoms and rescue medication use reported separately). CONCLUSIONS: This patient-centred collaboration has produced two COM sets for paediatric and adult severe asthma. It is expected that they will inform the methodology of future clinical trials, enhance comparability of efficacy and effectiveness of biological therapies, and help assess their socioeconomic value. COMSA will inform definitions of non-response and response to biological therapy for severe asthma.

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 ß-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.

The role of inflammation in anxiety and depression in the European U-BIOPRED asthma cohorts.

BACKGROUND: Growing evidence indicates high comorbid anxiety and depression in patients with asthma. However, the mechanisms underlying this comorbid condition remain unclear. The aim of this study was to investigate the role of inflammation in comorbid anxiety and depression in three asthma patient cohorts of the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project. METHODS: U-BIOPRED was conducted by a European Union consortium of 16 academic institutions in 11 European countries. A subset dataset from subjects with valid anxiety and depression measures and a large blood biomarker dataset were analysed, including 198 non-smoking patients with severe asthma (SAn), 65 smoking patients with severe asthma (SAs), 61 non-smoking patients with mild-to-moderate asthma (MMA), and 20 healthy non-smokers (HC). The Hospital Anxiety and Depression Scale was used to measure anxiety and depression and a series of inflammatory markers were analysed by the SomaScan v3 platform (SomaLogic, Boulder, Colo). ANOVA and the Kruskal-Wallis test were used for multiple-group comparisons as appropriate. RESULTS: There were significant group effects on anxiety and depression among the four cohort groups (p < 0.05). Anxiety and depression of SAn and SAs groups were significantly higher than that of MMA and HC groups (p < 0.05. There were significant differences in serum IL6, MCP1, CCL18, CCL17, IL8, and Eotaxin among the four groups (p < 0.05). Depression was significantly associated with IL6, MCP1, CCL18 level, and CCL17; whereas anxiety was associated with CCL17 only (p < 0.05). CONCLUSIONS: The current study suggests that severe asthma patients are associated with higher levels of anxiety and depression, and inflammatory responses may underlie this comorbid condition.

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 FcεR1-stimulated and IFN-γ-stimulated signatures were enriched in SA. A FcεR1-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-κB (nuclear factor-κB), and IL-1ß/TNF-α (tumor necrosis factor-α) pathway activation. The IFN-γ-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.

Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation.

RATIONALE: Asthma phenotyping requires novel biomarker discovery. OBJECTIVES: To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs). METHODS: An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED. RESULTS: In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-ß and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation. CONCLUSIONS: The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.

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.

A novel non-invasive method allowing for discovery of pathologically relevant proteins from small airways.

BACKGROUND: There is a lack of early and precise biomarkers for personalized respiratory medicine. Breath contains an aerosol of droplet particles, which are formed from the epithelial lining fluid when the small airways close and re-open during inhalation succeeding a full expiration. These particles can be collected by impaction using the PExA® method (Particles in Exhaled Air), and are derived from an area of high clinical interest previously difficult to access, making them a potential source of biomarkers reflecting pathological processes in the small airways. RESEARCH QUESTION: Our aim was to investigate if PExA method is useful for discovery of biomarkers that reflect pathology of small airways. METHODS AND ANALYSIS: Ten healthy controls and 20 subjects with asthma, of whom 10 with small airway involvement as indicated by a high lung clearance index (LCI ≥ 2.9 z-score), were examined in a cross-sectional design, using the PExA instrument. The samples were analysed with the SOMAscan proteomics platform (SomaLogic Inc.). RESULTS: Two hundred-seven proteins were detected in up to 80% of the samples. Nine proteins showed differential abundance in subjects with asthma and high LCI as compared to healthy controls. Two of these were less abundant (ALDOA4, C4), and seven more abundant (FIGF, SERPINA1, CD93, CCL18, F10, IgM, IL1RAP). sRAGE levels were lower in ex-smokers (n = 14) than in never smokers (n = 16). Gene Ontology (GO) annotation database analyses revealed that the PEx proteome is enriched in extracellular proteins associated with extracellular exosome-vesicles and innate immunity. CONCLUSION: The applied analytical method was reproducible and allowed identification of pathologically interesting proteins in PEx samples from asthmatic subjects with high LCI. The results suggest that PEx based proteomics is a novel and promising approach to study respiratory diseases with small airway involvement.

Activation of succinate receptor 1 boosts human mast cell reactivity and allergic bronchoconstriction.

BACKGROUND: SUCNR1 is a sensor of extracellular succinate, a Krebs cycle intermediate generated in excess during oxidative stress and has been linked to metabolic regulation and inflammation. While mast cells express SUCNR1, its role in mast cell reactivity and allergic conditions such as asthma remains to be elucidated. METHODS: Cord blood-derived mast cells and human mast cell line LAD-2 challenged by SUCNR1 ligands were analyzed for the activation and mediator release. Effects on mast cell-dependent bronchoconstriction were assessed in guinea pig trachea and isolated human small bronchi challenged with antigen and anti-IgE, respectively. RESULTS: SUCNR1 is abundantly expressed on human mast cells. Challenge with succinate, or the synthetic non-metabolite agonist cis-epoxysuccinate, renders mast cells hypersensitive to IgE-dependent activation, resulting in augmented degranulation and histamine release, de novo biosynthesis of eicosanoids and cytokine secretion. The succinate-potentiated mast cell reactivity was attenuated by SUCNR1 knockdown and selective SUCNR1 antagonists and could be tuned by pharmacologically targeting protein kinase C and extracellular signal-regulated kinase. Both succinate and cis-epoxysuccinate dose-dependently potentiated antigen-induced contraction in a mast cell-dependent guinea pig airway model, associated with increased generation of cysteinyl-leukotrienes and histamine in trachea. Similarly, cis-epoxysuccinate aggravated IgE-receptor-induced contraction of human bronchi, which was blocked by SUCNR1 antagonism. CONCLUSION: SUCNR1 amplifies IgE-receptor-induced mast cell activation and allergic bronchoconstriction, suggesting a role for this pathway in aggravation of allergic asthma, thus linking metabolic perturbations to mast cell-dependent inflammation.

Effects of non-steroidal anti-inflammatory drugs and other eicosanoid pathway modifiers on antiviral and allergic responses: EAACI task force on eicosanoids consensus report in times of COVID-19.

Non-steroidal anti-inflammatory drugs (NSAIDs) and other eicosanoid pathway modifiers are among the most ubiquitously used medications in the general population. Their broad anti-inflammatory, antipyretic, and analgesic effects are applied against symptoms of respiratory infections, including SARS-CoV-2, as well as in other acute and chronic inflammatory diseases that often coexist with allergy and asthma. However, the current pandemic of COVID-19 also revealed the gaps in our understanding of their mechanism of action, selectivity, and interactions not only during viral infections and inflammation, but also in asthma exacerbations, uncontrolled allergic inflammation, and NSAIDs-exacerbated respiratory disease (NERD). In this context, the consensus report summarizes currently available knowledge, novel discoveries, and controversies regarding the use of NSAIDs in COVID-19, and the role of NSAIDs in asthma and viral asthma exacerbations. We also describe here novel mechanisms of action of leukotriene receptor antagonists (LTRAs), outline how to predict responses to LTRA therapy and discuss a potential role of LTRA therapy in COVID-19 treatment. Moreover, we discuss interactions of novel T2 biologicals and other eicosanoid pathway modifiers on the horizon, such as prostaglandin D2 antagonists and cannabinoids, with eicosanoid pathways, in context of viral infections and exacerbations of asthma and allergic diseases. Finally, we identify and summarize the major knowledge gaps and unmet needs in current eicosanoid research.

Urinary Leukotriene E4 and Prostaglandin D2 Metabolites Increase in Adult and Childhood Severe Asthma Characterized by Type 2 Inflammation. A Clinical Observational Study.

Rationale: New approaches are needed to guide personalized treatment of asthma.Objectives: To test if urinary eicosanoid metabolites can direct asthma phenotyping.Methods: Urinary metabolites of prostaglandins (PGs), cysteinyl leukotrienes (CysLTs), and isoprostanes were quantified in the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Diseases Outcomes) study including 86 adults with mild-to-moderate asthma (MMA), 411 with severe asthma (SA), and 100 healthy control participants. Validation was performed internally in 302 participants with SA followed up after 12-18 months and externally in 95 adolescents with asthma.Measurement and Main Results: Metabolite concentrations in healthy control participants were unrelated to age, body mass index, and sex, except for the PGE2 pathway. Eicosanoid concentrations were generally greater in participants with MMA relative to healthy control participants, with further elevations in participants with SA. However, PGE2 metabolite concentrations were either the same or lower in male nonsmokers with asthma than in healthy control participants. Metabolite concentrations were unchanged in those with asthma who adhered to oral corticosteroid treatment as documented by urinary prednisolone detection, whereas those with SA treated with omalizumab had lower concentrations of LTE4 and the PGD2 metabolite 2,3-dinor-11ß-PGF2α. High concentrations of LTE4 and PGD2 metabolites were associated with lower lung function and increased amounts of exhaled nitric oxide and eosinophil markers in blood, sputum, and urine in U-BIOPRED participants and in adolescents with asthma. These type 2 (T2) asthma associations were reproduced in the follow-up visit of the U-BIOPRED study and were found to be as sensitive to detect T2 inflammation as the established biomarkers.Conclusions: Monitoring of urinary eicosanoids can identify T2 asthma and introduces a new noninvasive approach for molecular phenotyping of adult and adolescent asthma.Clinical trial registered with www.clinicaltrials.gov (NCT01976767).

Distinct plasma biomarkers confirm the diagnosis of mastocytosis and identify increased risk of anaphylaxis.

BACKGROUND: Mastocytosis encompasses a heterogeneous group of disorders characterized by accumulation of clonal mast cells (MCs) in the skin and/or internal organs. Patients typically present with a broad variety of recurrent mediator-related clinical symptoms, including severe anaphylaxis. However, not all patients with mastocytosis experience anaphylactic reactions. OBJECTIVE: We sought to identify disease-specific biomarkers in plasma that could be used to predict patients with mastocytosis with increased risk of anaphylaxis. METHODS: Nineteen patients (≥18 years) and 2 control groups (11 subjects with allergic asthma and 13 healthy volunteers without history of atopy) were recruited. In total, 248 plasma proteins were analyzed by Proximity Extension Assay using Olink Proseek Multiplex panels. RESULTS: We identified 4 novel proteins, in addition to tryptase, E-selectin, adrenomedullin, T-cell immunoglobulin, and mucin domain 1, and CUB domain-containing protein 1/CD138 to be significantly increased in patients with mastocytosis compared with both patients with asthma and healthy controls. Furthermore, we investigated whether we could discriminate between patients with mastocytosis with or without anaphylaxis. In addition to tryptase, we identified 3 novel proteins, that is, allergin-1, pregnancy-associated plasma protein-A, and galectin-3, with significantly different levels in patients with mastocytosis with anaphylaxis compared with those without anaphylaxis. CONCLUSIONS: Newly identified proteomic biomarkers may be used to predict patients with mastocytosis with increased risk of anaphylaxis.

Sputum microbiome profiles identify severe asthma phenotypes of relative stability at 12 to 18 months.

BACKGROUND: Asthma is a heterogeneous disease characterized by distinct phenotypes with associated microbial dysbiosis. OBJECTIVES: Our aim was to identify severe asthma phenotypes based on sputum microbiome profiles and assess their stability after 12 to 18 months. A further aim was to evaluate clusters' robustness after inclusion of an independent cohort of patients with mild-to-moderate asthma. METHODS: In this longitudinal multicenter cohort study, sputum samples were collected for microbiome profiling from a subset of the Unbiased Biomarkers in Prediction of Respiratory Disease Outcomes adult patient cohort at baseline and after 12 to 18 months of follow-up. Unsupervised hierarchical clustering was performed by using the Bray-Curtis ß-diversity measure of microbial profiles. For internal validation, partitioning around medoids, consensus cluster distribution, bootstrapping, and topological data analysis were applied. Follow-up samples were studied to evaluate within-patient clustering stability in patients with severe asthma. Cluster robustness was evaluated by using an independent cohort of patients with mild-to-moderate asthma. RESULTS: Data were available for 100 subjects with severe asthma (median age 55 years; 42% males). Two microbiome-driven clusters were identified; they were characterized by differences in asthma onset, smoking status, residential locations, percentage of blood and/or sputum neutrophils and macrophages, lung spirometry results, and concurrent asthma medications (all P values < .05). The cluster 2 patients displayed a commensal-deficient bacterial profile that was associated with worse asthma outcomes than those of the cluster 1 patients. Longitudinal clusters revealed high relative stability after 12 to 18 months in those with severe asthma. Further inclusion of an independent cohort of 24 patients with mild-to-moderate asthma was consistent with the clustering assignments. CONCLUSION: Unbiased microbiome-driven clustering revealed 2 distinct robust phenotypes of severe asthma that exhibited relative overtime stability. This suggests that the sputum microbiome may serve as a biomarker for better characterizing asthma phenotypes.