title: Identification of Asthma Subtypes Using Clustering Methodologies.
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.
authors: Centre for Health Informatics, Institute of Population Health, University of Manchester, Manchester, UK.
authors: Matea
authors: M
authors: Deliu
authors: Centre for Health Informatics, Institute of Population Health, University of Manchester, Manchester, UK.
authors: Matthew
authors: M
authors: Sperrin
authors: Department of Paediatrics, Imperial College London, London, UK.
authors: Danielle
authors: D
authors: Belgrave
authors: Department of Paediatrics, Imperial College London, London, UK.
authors: Adnan
authors: A
authors: Custovic
keywords: Adult asthma; Asthma; Clustering; Endotypes; Paediatric asthma; Phenotypes