RT Journal Article
T1 Identification of Asthma Phenotypes in the Spanish MEGA Cohort Study Using Cluster Analysis
A1 Matabuena, Marcos
A1 Salgado Castro, Francisco Javier
A1 Nieto Fontarigo, Juan José
A1 Álvarez-Puebla, María J.
A1 Arismendi, Ebymar
A1 Barranco, Pilar
A1 Bobolea, Irina
A1 Caballero, María L.
A1 Cañas, José Antonio
A1 Cárdaba, Blanca
A1 Cruz, María Jesús
A1 Curto, Elena
A1 Domínguez-Ortega, Javier
A1 Luna, Juan Alberto
A1 Martínez-Rivera, Carlos
A1 Mullol, Joaquim
A1 Muñoz, Xavier
A1 Rodríguez-García, Javier
A1 Olaguibel, José María
A1 Picado, César
A1 Plaza, Vicente
A1 Quirce, Santiago
A1 Rial, Manuel J.
A1 Romero-Mesones, Christian
A1 Sastre, Beatriz
A1 Soto-Retes, Lorena
A1 Valero, Antonio
A1 Valverde-Monge, Marcela
A1 Pozo, Victoria del
A1 Sastre, Joaquín
A1 González Barcala, Francisco Javier
K1 Asthma
K1 Asthma phenotypes
K1 Asthma endotypes
K1 Clustering analysis
AB IntroductionThe definition of asthma phenotypes has not been fully established, neither there are cluster studies showing homogeneous results to solidly establish clear phenotypes. The purpose of this study was to develop a classification algorithm based on unsupervised cluster analysis, identifying clusters that represent clinically relevant asthma phenotypes that may share asthma-related outcomes.MethodsWe performed a multicentre prospective cohort study, including adult patients with asthma (N=512) from the MEGA study (Mechanisms underlying the Genesis and evolution of Asthma). A standardised clinical history was completed for each patient. Cluster analysis was performed using the kernel k-groups algorithm.ResultsFour clusters were identified. Cluster 1 (31.5% of subjects) includes adult-onset atopic patients with better lung function, lower BMI, good asthma control, low ICS dose, and few exacerbations. Cluster 2 (23.6%) is made of adolescent-onset atopic asthma patients with normal lung function, but low adherence to treatment (59% well-controlled) and smokers (48%). Cluster 3 (17.1%) includes adult-onset patients, mostly severe non-atopic, with overweight, the worse lung function and asthma control, and receiving combination of treatments. Cluster 4 (26.7%) consists of the elderly-onset patients, mostly female, atopic (64%), with high BMI and normal lung function, prevalence of smokers and comorbidities.ConclusionWe defined four phenotypes of asthma using unsupervised cluster analysis. These clusters are clinically relevant and differ from each other as regards FEV1, age of onset, age, BMI, atopy, asthma severity, exacerbations, control, social class, smoking and nasal polyps.
PB Elsevier
SN 0300-2896
YR 2023
FD 2023-01-18
LK https://hdl.handle.net/10347/46479
UL https://hdl.handle.net/10347/46479
LA eng
NO This study has been supported by Sanofi [02/055], the Health Research Fund (Fondo de Investigación Sanitaria – FIS [PI15/00803]), [PI15/01900], the Merck Health Foundation, 6CIBER (Biomedical Research Centre Network) Respiratory Diseases (Centro de Investigación Biomédica en Red – Enfermedades Res- piratorias [CIBERES]), a Carlos III Institute of Health Initiative, and European Regional Development Funds (ERDF). Dr. Nieto-Fontarigo is recipient of a Sara Borrell Fellowship from Instituto de Salud Carlos III (European Social Fund, ESF+).
DS Minerva
RD 19 may 2026