Identification of Asthma Subtypes Using Clustering Methodologies. Issue 1 (June 2016)

• Record Type: Journal Article
• Authors: Deliu, Matea; Sperrin, Matthew; Belgrave, Danielle; Custovic, Adnan
• Is Part Of: Pulmonary therapy. Volume 2:Issue 1(2016)
• Page Start: 19
• Page End: 41
• Publication Date: 2016-06
• Subjects: Adult asthma -- Asthma -- Clustering -- Endotypes -- Paediatric asthma -- Phenotypes; Respiratory organs -- Diseases -- Treatment -- Periodicals; Respiratory therapy -- Periodicals; 616.20046
• DOI: 10.1007/s41030-016-0017-z
• Languages: English
• ISSNs: 2364-1754

Abstract

Abstract Asthma is a heterogeneous disease comprising a number of subtypes which may be caused by different pathophysiologic mechanisms (sometimes referred to as endotypes) but may share similar observed characteristics (phenotypes). The use of unsupervised clustering in adult and paediatric populations has identified subtypes of asthma based on observable characteristics such as symptoms, lung function, atopy, eosinophilia, obesity, and age of onset. Here we describe different clustering methods and demonstrate their contributions to our understanding of the spectrum of asthma syndrome. Precise identification of asthma subtypes and their pathophysiological mechanisms may lead to stratification of patients, thus enabling more precise therapeutic and prevention approaches.