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Severe asthma is associated with significant morbidity and mortality despite the maximal use of inhaled corticosteroids and additional controller medications, and has a high economic burden. Biologic therapies are recommended for the management of severe, uncontrolled asthma to help to prevent exacerbations and to improve symptoms and health-related quality of life. The effective management of severe asthma requires consideration of clinical heterogeneity that is driven by varying clinical and inflammatory phenotypes, which are reflective of distinct underlying disease mechanisms. Phenotyping patients using a combination of clinical characteristics such as the age of onset or comorbidities and biomarker profiles, including blood eosinophil counts and levels of fractional exhaled nitric oxide and serum total immunoglobulin E, is important for the differential diagnosis of asthma. In addition, phenotyping is beneficial for risk assessment, selection of treatment, and monitoring of the treatment response in patients with asthma. This review describes the clinical and inflammatory phenotypes of asthma, provides an overview of biomarkers routinely used in clinical practice and those that have recently been explored for phenotyping, and aims to assess the value of phenotyping in severe asthma management in the current era of biologics., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Asthma and chronic obstructive pulmonary disease are currently diagnosed and treated after the demonstration of variable airflow limitation and symptoms. Under this framework, undiagnosed and unchecked airway inflammation is associated with recurrent acute attacks, airway remodeling, airflow limitation, adverse effects of corticosteroids, and impaired quality of life, ultimately leading to the collection of side effects termed "people remodeling." This one-size-fits-all damage control approach aims to control symptoms and treat exacerbations rather than modify the underlying disease process. The advent of highly effective therapies targeting proximal drivers of airway inflammation calls for a paradigm shift; upstream-acting therapies offer potential to alter the disease course and achieve clinical remission. We propose moving away from downstream firefighting and toward a "predict and prevent" model, measuring inflammation and providing anti-inflammatory therapy early, without waiting for further clinical deterioration. Much in the same way that high blood pressure and cholesterol are used to predict and prevent heart attacks, in asthma, elevated blood eosinophils and/or exhaled nitric oxide can be used to predict and prevent asthma attacks. We also advocate moving research further upstream by identifying patients with subclinical airway inflammation or disease who may be at risk of progressing to airflow limitation and associated morbidities and intervening early to prevent them. In summary, we call for a predict and prevent approach in obstructive airway disease., (Copyright © 2023 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Introduction: In asthma, lung function measures are often discordant with clinical features such as disease activity or control., Methods: We investigated a novel technique that provides a measure (σCL) of unevenness (inhomogeneity) in lung inflation/deflation. In particular, we compared σCL with FEV 1 % predicted (FEV 1 %pred) as measures of disease activity in the asthmatic lung., Results: σCL correlated modestly with FEV 1 %pred. However, σCL is not simply a proxy for FEV 1 %pred as the effects of salbutamol on the two parameters were unrelated. Importantly, σCL reflected disease control better than FEV 1 ., Discussion: We conclude that σCL shows promise as an objective measure of disease activity in asthma., Competing Interests: Competing interests: Oxford University Innovation, a wholly owned subsidiary of the University of Oxford, owns the IP and holds/has filed patents in relation to the technology. JC, GH, GADR and PAR have an interest in one or more of these patents/filings., (© Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY. Published by BMJ.)