Current opinion in allergy and clinical immunology
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Severe asthma remains a debilitating disease and a challenge for the clinicians. Novel therapies have been introduced and have greatly improved asthma control and more are under development or in clinical studies. These include anti-IL5/IL5R, anti-IL4/IL4R, anti IL13, anti- thymic stromal lymphopoietin (TSLP) and more, and severe asthma is currently managed in personalized medicine approach. However, there is still an unmet need to discover new, clinically available biomarkers and targeted therapies for a large group of severe asthma patients, particularly those with T2-low asthma. In this review, we briefly present the phenotypes and endotypes of severe asthma, the omics technologies in asthma as well as current and future treatments for both T2-high and T2-low asthma. ⋯ Novel anti-IL5 agents have changed the management of T2-high asthma resulting in improved disease control, QoL and lung function and importantly, fewer exacerbations. Nevertheless, there is still the need to find new treatments, particularly for T2-low asthma, which remains a challenge.
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Curr Opin Allergy Clin Immunol · Apr 2020
ReviewChildhood asthma in the new omics era: challenges and perspectives.
Childhood asthma is a heterogeneous inflammatory disease comprising different phenotypes and endotypes and, particularly in its severe forms, has a large impact on the quality-of-life of patients and caregivers. The application of advanced omics technologies provides useful insights into underlying asthma endotypes and may provide potential clinical biomarkers to guide treatment and move towards a precision medicine approach. ⋯ Until now, omics studies have largely expanded our view on asthma heterogeneity, helped understand cellular processes underlying asthma, and brought us closer towards identifying (bio)markers that will allow the prediction of treatment responsiveness and disease progression. There is a clinical need for biomarkers that will guide treatment at the individual level, particularly in the field of biologicals. The integration of multiomics data together with clinical data could be the next promising step towards development individual risk prediction models to guide treatment. However, this requires large-scale collaboration in a multidisciplinary setting.