• Kian Fan Chung.
• Airway Disease Section, National Heart and Lung Institute, Imperial College London, London, UK.
• J. Intern. Med. 2016 Feb 1; 279 (2): 192-204.

AbstractAsthma is a common heterogeneous disease with a complex pathophysiology that carries a significant mortality rate and high morbidity. Current therapies based on inhaled corticosteroids and long-acting β-agonists remain effective in a large proportion of patients with asthma, but ~10% (considered to have 'severe asthma') do not respond to these treatments even at high doses or with the use of oral corticosteroids. Analytical clustering methods have revealed phenotypes that include dependence on high-dose corticosteroid treatment, severe airflow obstruction and recurrent exacerbations associated with an allergic background and late onset of disease. One severe phenotype is eosinophilic inflammation-predominant asthma, with late-onset disease, rhinosinusitis, aspirin sensitivity and exacerbations. Blood and sputum eosinophilia have been used to distinguish patients with high Th2 inflammation and to predict therapeutic response to treatments targeted towards Th2-associated cytokines. New therapies in the form of humanized antibodies against Th2 targets, such as anti-IgE, anti-IL4Rα, anti-IL-5 and anti-IL-13 antibodies, have shown encouraging results in terms of reduction in exacerbations and improvement in airflow in patients with a 'Th2-high' expression profile and blood eosinophilia. Research efforts are now focusing on elucidating the phenotypes underlying the non-Th2-high (or Th2-low) group, which constitutes ~50% of severe asthma cases. There is an increasing need to use biomarkers to indicate the group of patients who will respond to a specifically targeted treatment. The use of improved tools to measure activity of disease, a better definition of severe asthma and the delineation of inflammatory pathways with omics analyses using computational tools, will lead to better-defined phenotypes for specific therapies.© 2015 The Association for the Publication of the Journal of Internal Medicine.

32 keywords...

hide…