Confirmation of multiple endotypes in atopic dermatitis based on serum biomarkers.

Abstract Background Atopic dermatitis (AD) is a highly heterogeneous disease, both clinically and biologically, whereas patients are still treated according the “one-size-fits-all” approach. Stratification of patients into biomarker-based endotypes is important for future development of personalized therapies. Objective To confirm previously defined serum biomarker-based patient clusters in a new cohort of AD patients. Methods A panel of 143 biomarkers was measured using Luminex technology in serum samples of 146 severe AD patients (median EASI 28.3, IQR 25.2-35.3). Principal components analysis followed by unsupervised k-means cluster analysis of the biomarker data was used to identify patient clusters. A prediction model was built based on a previous cohort to predict in which of the four previously identified clusters the patients of our new cohort would belong. Results Cluster analysis identified four serum biomarker-based clusters of which three (cluster B, C and D) were comparable to the previously identified clusters. Cluster A (33.6%) could be distinguished from other clusters as being “skin-homing chemokines/IL-1R1 dominant” cluster, cluster B (18.5%) as “Th1/Th2/Th17 dominant” cluster C (18.5%) as “Th2/Th22/PARC dominant” and cluster D (29.5%) as “Th2/eosinophil inferior” cluster. Additionally, using a prediction model based on our previous cohort we accurately assigned the new cohort to the four previously identified clusters by including only 10 selected serum biomarkers. Conclusion We confirmed that AD is heterogeneous on the immuno-pathological level and identified four distinct biomarker-based clusters of which three were comparable with previously identified clusters. Cluster membership could be predicted with a model including 10 serum biomarkers.