PT  - JOURNAL ARTICLE
AU  - V. Siroux
AU  - X. Basagaña
AU  - A. Boudier
AU  - I. Pin
AU  - J. Garcia-Aymerich
AU  - A. Vesin
AU  - R. Slama
AU  - D. Jarvis
AU  - J.M. Anto
AU  - F. Kauffmann
AU  - J. Sunyer
TI  - Identifying adult asthma phenotypes using a clustering approach
AID  - 10.1183/09031936.00120810
DP  - 2011 Aug 01
TA  - European Respiratory Journal
PG  - 310--317
VI  - 38
IP  - 2
4099  - http://erj.ersjournals.com/content/38/2/310.short
4100  - http://erj.ersjournals.com/content/38/2/310.full
SO  - Eur Respir J2011 Aug 01; 38
AB  - There is a need to improve asthma characterisation by integrating multiple aspects of the disease. The aim of the present study was to identify distinct asthma phenotypes by applying latent class analysis (LCA), a model-based clustering method, to two large epidemiological studies. Adults with asthma who participated in the follow-up of the Epidemiological Study on the Genetics and Environment of Asthma (EGEA2) (n = 641) and the European Community Respiratory Health Survey (ECRHSII) (n = 1,895) were included. 19 variables covering personal characteristics, asthma symptoms, exacerbations and treatment, age of asthma onset, allergic characteristics, lung function and airway hyperresponsiveness were considered in the LCA. Four asthma phenotypes were distinguished by the LCA in each sample. Two phenotypes were similar in EGEA2 and ECRHSII: active treated allergic childhood-onset asthma and active treated adult-onset asthma. The other two phenotypes were composed of subjects with inactive or mild untreated asthma, who differed by atopy status and age of asthma onset (childhood or adulthood). The phenotypes clearly discriminated populations in terms of quality of life, and blood eosinophil and neutrophil counts. The LCAs revealed four distinct asthma phenotypes in each sample. Considering these more homogeneous phenotypes in future studies may lead to a better identification of risk factors for asthma.