Background: Previous cluster analyses have identified subgroups of asthma. However, only a few studies included parameters of small airways disease (SAD), or gene expression profiles reflecting underlying disease mechanisms. We aimed to identify clinically distinct asthma phenotypes using available data from the ATLANTIS study which focused on identifying the prevalence of SAD in asthma and its role asthma control, exacerbations and quality of life. Methods: The ATLANTIS study included 773 asthma patients (mean age 44 years, 58% female, 76% never-smoker, GINA 1-5). Subjects were extensively characterized, including symptoms, parameters of large and small airways disease, blood and sputum differential cell counts, and genome-wide gene expression profiling from nasal brushes. Clusters were generated using the Self-Organizing Map-Ward’s method. Results: Four distinct clusters were identified: A (N=62; 8%) characterized by the most frequent exacerbations, lower post-bronchodilator FEV 1 %predicted, more small airways disease, higher sputum and blood eosinophils and high expression of asthma related genes. B (N=206; 27%) consisting of atopic patients with early-onset asthma, uncontrolled symptoms, and normal lung function and bronchial hyperresponsiveness along with higher nasal expression of asthma-related genes. C (N=277; 36%), predominantly male former smokers, with well-controlled asthma and sputum neutrophilia. D (N=228; 29%), with normal lung function and low blood and sputum eosinophils. Conclusions: Four distinct clusters were identified, where the presence of SAD was associated with high type 2 inflammation lower lung function and frequent exacerbations. SAD may be a marker of poorly controlled asthma and should be considered as an important clinical trait.