Background: Asthma is characterized by a heterogeneous inflammatory profile and can be subdivided into T(h) 2-high and T(h) 2-low airway inflammation. Profiling of a broader panel of airway cytokines in large unselected patient cohorts is lacking. Methods: Patients (n = 205) were defined as being "cytokine-low/high" if sputum mRNA expression of a particular cytokine was outside the respective 10th/90th percentile range of the control group (n = 80). Unsupervised hierarchical clustering was used to determine clusters based on sputum cytokine profiles. Results: Half of patients (n = 108; 52.6%) had a classical T(h) 2-high ("IL-4-, IL-5-and/or IL-13-high") sputum cytokine profile. Unsupervised cluster analysis revealed 5 clusters. Patients with an "IL-4-and/or IL-13-high"pattern surprisingly did not cluster but were equally distributed among the 5 clusters. Patients with an "IL-5-, IL-17A-/F-and IL-25-high"profile were restricted to cluster 1 (n = 24) with increased sputum eosinophil as well as neutrophil counts and poor lung function parameters at baseline and 2 years later. Four other clusters were identified: "IL-5-high or IL-10-high"(n = 16), "IL-6-high"(n = 8), "IL-22-high"(n = 25). Cluster 5 (n = 132) consists of patients without "cytokine-high"pattern or patients with only high IL-4 and/or IL-13. Conclusion: We identified 5 unique asthma molecular phenotypes by biological clustering. Type 2 cytokines cluster with non-type 2 cytokines in 4 out of 5 clusters. Unsupervised analysis thus not supports a priori type 2 versus non-type 2 molecular phenotypes.