Clinical phenotypes of difficult-to-treat and mild asthma defined by cluster analysis

Background Cluster modelling has demonstrated asthma heterogeneity across disease severities, but contemporary data integrating difficult-to-treat and mild asthma with systematic assessment of comorbidity-focused treatable traits remain limited. Objective To identify and characterise difficult-to-treat and mild asthma clusters in two UK cohorts: Wessex AsThma CoHort of Difficult Asthma (WATCH-DA) and a mild-asthma cohort from the Epigenetics of Severe Asthma study (EOSA-MA). Methods Separate K-means clustering was applied to WATCH-DA ( n = 498; 11 variables) and EOSA-MA ( n = 67; 12 variables). Post-hoc comparisons evaluated demographic, inflammatory, physiological, comorbidity and patient-reported outcome profiles. Results Six difficult-to-treat and two mild asthma clusters were identified respectively, all Type-2 (T2)-predominant. Difficult-to-treat asthma clusters differed by sex, age of asthma-onset, body mass index (BMI) and comorbidities. Two clinically controlled clusters, cluster-1 (Early-onset atopic controlled) and cluster-4 (Late-adult-onset non-atopic controlled), showed distinct comorbidity patterns despite lower overall morbidity. Three severe, exacerbation-prone, adult-onset, female predominant difficult-to-treat clusters (Adult-onset eosinophilic exacerbator [cluster-2], Young-adult-onset high-risk exacerbator [cluster-5], Adult-onset obese multimorbid symptomatic [cluster-6]) varied by blood eosinophil counts (BEC), spirometry, BMI, treatment needs, comorbidities, and quality of life. An Adolescent-onset obese atopic obstructive (cluster-3) showed fewer exacerbations but high BEC with worst spirometry and poor asthma control. In mild asthma, cluster-1 (Early-onset atopic mild) showed worse pathophysiological indices and asthma control than cluster-2 (Adolescent-onset mild) but similarly high comorbidity prevalence. Conclusion Characterisation of difficult-to-treat and mild asthma clusters reveals diverse associated clinical traits and outcomes across the asthma severity spectrum. Recognition of these clusters and their associated comorbidities should prompt early personalised asthma management to address both airway-centric and comorbid disease aspects.