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BACKGROUND: The Ca(2+)-activated K(+) channel K(Ca)3.1 is expressed in several structural and inflammatory airway cell types and is proposed to play an important role in the pathophysiology of asthma. The aim of the current study was to determine whether inhibition of K(Ca)3.1 modifies experimental asthma in sheep. METHODOLOGY AND PRINCIPAL FINDINGS: Atopic sheep were administered either 30 mg/kg Senicapoc (ICA-17073), a selective inhibitor of the K(Ca)3.1-channel, or vehicle alone (0.5% methylcellulose) twice daily (orally). Both groups received fortnightly aerosol challenges with house dust mite allergen for fourteen weeks. A separate sheep group received no allergen challenges or drug treatment. In the vehicle-control group, twelve weeks of allergen challenges resulted in a 60±19% increase in resting airway resistance, and this was completely attenuated by treatment with Senicapoc (0.25±12%; n = 10, P = 0.0147). The vehicle-control group had a peak-early phase increase in lung resistance of 82±21%, and this was reduced by 58% with Senicapoc treatment (24±14%; n = 10, P = 0.0288). Senicapoc-treated sheep also demonstrated reduced airway hyperresponsiveness, requiring a significantly higher dose of carbachol to increase resistance by 100% compared to allergen-challenged vehicle-control sheep (20±5 vs. 52±18 breath-units of carbachol; n = 10, P = 0.0340). Senicapoc also significantly reduced eosinophil numbers in bronchoalveolar lavage taken 48 hours post-allergen challenge, and reduced vascular remodelling. CONCLUSIONS: These findings suggest that K(Ca)3.1-activity contributes to allergen-induced airway responses, inflammation and vascular remodelling in a sheep model of asthma, and that inhibition of K(Ca)3.1 may be an effective strategy for blocking allergen-induced airway inflammation and hyperresponsiveness in humans.

Contains fulltext : 70227.pdf (publisher's version ) (Closed access), Asthma is a common disease that causes considerable morbidity. Increased numbers of airway eosinophils are a hallmark of asthma. Mechanisms controlling the entry of eosinophils into asthmatic lung have been intensively investigated, but factors regulating migration within the tissue microenvironment are less well understood. We modeled this by studying chemoattractant and growth factor-mediated human eosinophil migration within a three-dimensional collagen matrix. Stimulation with GM-CSF induced dose-dependent, random migration with a maximum of 77 +/- 4.7% of cells migrating. In contrast, CCL11 and C5a caused a more modest although significant degree of migration (19 +/- 1.8% and 20 +/- 2.6%, respectively). Migration to GM-CSF was partially dependent on Ca(2+) and alpha(M)beta(2) integrins. The Rho family of small GTPases regulates intracellular signaling of cell migration. GM-CSF-induced migration was only partially dependent on Rho kinase/Rho-associated kinase (ROCK) and was independent of RhoA activation. In contrast, CCL11-induced migration was fully dependent on both RhoA and ROCK. Activation of RhoA was therefore neither necessary nor sufficient to cause eosinophil migration in a three-dimensional collagen environment. This study suggests that eosinophil growth factors are likely to be required for eosinophil migration within the bronchial mucosa, and this involves signal transduction pathways distinct from those used by G protein-associated chemoattractants.

BACKGROUND: Analysis of cell-selective gene expression for families of proteins of therapeutic interest is crucial when deducing the influence of genes upon complex traits and disease susceptibility. Presently, there is no convenient tool for examining isoform-selective expression for large gene families. A multigene isoform profiling strategy was developed and used to investigate the inwardly rectifying K+ (Kir) channel family in human leukocytes. Comprised of seven subfamilies, Kir channels have important roles in setting the resting membrane potential in excitable and non-excitable cells. RESULTS: Gene sequence alignment allowed determination of "islands" of amino acid homology, and sub-family "centred" priming permitted simultaneous co-amplification of each family member. Validation and cross-priming analysis was performed against a panel of cognate Kir channel clones. Radiolabelling and diagnostic restriction digestion of pooled PCR products enabled determination of distinct Kir gene expression profiles in pure populations of human neutrophils, eosinophils and lung mast cells, with conservation of Kir2.0 isoforms amongst the leukocyte subsets. We also identified a Kir2.0 channel product, which may potentially represent a novel family member. CONCLUSIONS: We have developed a novel, rapid and flexible strategy for the determination of gene family isoform composition in any cell type with the additional capacity to detect hitherto unidentified family members and verified its application in a study of Kir channel isoform expression in human leukocytes.

Background: Patients with difficult-to-control asthma consume 50–60% of healthcare costs attributed to asthma and cost approximately five-times more than patients with mild stable disease. Recent evidence demonstrates that not all patients with asthma have a typical type 2 (T2)-driven eosinophilic inflammation. These asthmatics have been called ‘T2-low asthma’ and have a minimal response to corticosteroid therapy. Adjustment of corticosteroid treatment using sputum eosinophil counts from induced sputum has demonstrated reduced severe exacerbation rates and optimized corticosteroid dose. However, it has been challenging to move induced sputum into the clinical setting. There is therefore a need to examine novel algorithms to target appropriate levels of corticosteroid treatment in difficult asthma, particularly in T2-low asthmatics. This study examines whether a composite non-invasive biomarker algorithm predicts exacerbation risk in patients with asthma on high-dose inhaled corticosteroids (ICS) (± long-acting beta agonist) treatment, and evaluates the utility of this composite score to facilitate personalized biomarker-specific titration of corticosteroid therapy. Methods/design: Patients recruited to this pragmatic, multi-centre, single-blinded randomised controlled trial are randomly allocated into either a biomarker controlled treatment advisory algorithm or usual care group in a ratio of 4:1. The primary outcome measure is the proportion of patients with any reduction in ICS or oral corticosteroid dose from baseline to week 48. Secondary outcomes include the rate of protocol-defined severe exacerbations per patient per year, time to first severe exacerbation from randomisation, dose of inhaled steroid at the end of the study, cumulative dose of inhaled corticosteroid during the study, proportion of patients on oral corticosteroids at the end of the study, proportion of patients who decline to progress to oral corticosteroids despite composite biomarker score of

Background: Patients with difficult-to-control asthma consume 50–60% of healthcare costs attributed to asthma and cost approximately five-times more than patients with mild stable disease. Recent evidence demonstrates that not all patients with asthma have a typical type 2 (T2)-driven eosinophilic inflammation. These asthmatics have been called ‘T2-low asthma’ and have a minimal response to corticosteroid therapy. Adjustment of corticosteroid treatment using sputum eosinophil counts from induced sputum has demonstrated reduced severe exacerbation rates and optimized corticosteroid dose. However, it has been challenging to move induced sputum into the clinical setting. There is therefore a need to examine novel algorithms to target appropriate levels of corticosteroid treatment in difficult asthma, particularly in T2-low asthmatics. This study examines whether a composite non-invasive biomarker algorithm predicts exacerbation risk in patients with asthma on high-dose inhaled corticosteroids (ICS) (± long-acting beta agonist) treatment, and evaluates the utility of this composite score to facilitate personalized biomarker-specific titration of corticosteroid therapy. Methods/design: Patients recruited to this pragmatic, multi-centre, single-blinded randomised controlled trial are randomly allocated into either a biomarker controlled treatment advisory algorithm or usual care group in a ratio of 4:1. The primary outcome measure is the proportion of patients with any reduction in ICS or oral corticosteroid dose from baseline to week 48. Secondary outcomes include the rate of protocol-defined severe exacerbations per patient per year, time to first severe exacerbation from randomisation, dose of inhaled steroid at the end of the study, cumulative dose of inhaled corticosteroid during the study, proportion of patients on oral corticosteroids at the end of the study, proportion of patients who decline to progress to oral corticosteroids despite composite biomarker score of

Background: Patients with difficult-to-control asthma consume 50–60% of healthcare costs attributed to asthma and cost approximately five-times more than patients with mild stable disease. Recent evidence demonstrates that not all patients with asthma have a typical type 2 (T2)-driven eosinophilic inflammation. These asthmatics have been called ‘T2-low asthma’ and have a minimal response to corticosteroid therapy. Adjustment of corticosteroid treatment using sputum eosinophil counts from induced sputum has demonstrated reduced severe exacerbation rates and optimized corticosteroid dose. However, it has been challenging to move induced sputum into the clinical setting. There is therefore a need to examine novel algorithms to target appropriate levels of corticosteroid treatment in difficult asthma, particularly in T2-low asthmatics. This study examines whether a composite non-invasive biomarker algorithm predicts exacerbation risk in patients with asthma on high-dose inhaled corticosteroids (ICS) (± long-acting beta agonist) treatment, and evaluates the utility of this composite score to facilitate personalized biomarker-specific titration of corticosteroid therapy. Methods/design: Patients recruited to this pragmatic, multi-centre, single-blinded randomised controlled trial are randomly allocated into either a biomarker controlled treatment advisory algorithm or usual care group in a ratio of 4:1. The primary outcome measure is the proportion of patients with any reduction in ICS or oral corticosteroid dose from baseline to week 48. Secondary outcomes include the rate of protocol-defined severe exacerbations per patient per year, time to first severe exacerbation from randomisation, dose of inhaled steroid at the end of the study, cumulative dose of inhaled corticosteroid during the study, proportion of patients on oral corticosteroids at the end of the study, proportion of patients who decline to progress to oral corticosteroids despite composite biomarker score of

Background: Patients with difficult-to-control asthma consume 50–60% of healthcare costs attributed to asthma and cost approximately five-times more than patients with mild stable disease. Recent evidence demonstrates that not all patients with asthma have a typical type 2 (T2)-driven eosinophilic inflammation. These asthmatics have been called ‘T2-low asthma’ and have a minimal response to corticosteroid therapy. Adjustment of corticosteroid treatment using sputum eosinophil counts from induced sputum has demonstrated reduced severe exacerbation rates and optimized corticosteroid dose. However, it has been challenging to move induced sputum into the clinical setting. There is therefore a need to examine novel algorithms to target appropriate levels of corticosteroid treatment in difficult asthma, particularly in T2-low asthmatics. This study examines whether a composite non-invasive biomarker algorithm predicts exacerbation risk in patients with asthma on high-dose inhaled corticosteroids (ICS) (± long-acting beta agonist) treatment, and evaluates the utility of this composite score to facilitate personalized biomarker-specific titration of corticosteroid therapy. Methods/design: Patients recruited to this pragmatic, multi-centre, single-blinded randomised controlled trial are randomly allocated into either a biomarker controlled treatment advisory algorithm or usual care group in a ratio of 4:1. The primary outcome measure is the proportion of patients with any reduction in ICS or oral corticosteroid dose from baseline to week 48. Secondary outcomes include the rate of protocol-defined severe exacerbations per patient per year, time to first severe exacerbation from randomisation, dose of inhaled steroid at the end of the study, cumulative dose of inhaled corticosteroid during the study, proportion of patients on oral corticosteroids at the end of the study, proportion of patients who decline to progress to oral corticosteroids despite composite biomarker score of