Proteomic, miRNA and bacterial biomarker patterns in atopic dermatitis patients and their course upon anti-IL-4Rα therapy.

Abstract

Identification of biomarkers is required for a systems medicine approach and personalized treatment in atopic dermatitis (AD). These biomarkers may not only aid in diagnosing but also might be suitable to predict the effectiveness of targeted treatment. We aimed to identify proteomic, microbial and miRNA biomarkers in AD patients and investigated their course in relation to the clinical response upon anti-IL-4Rα therapy. Proteomic and miRNA screening was performed in AD patients in comparison to healthy controls. Differentially regulated serum proteins, miRNA and selected skin microbiota were measured consecutively in 50 AD patients before and upon systemic dupilumab treatment. A random forest classifier was used to predict the outcome of dupilumab therapy based on the initial biomarker patterns. We identified 27 proteomic candidates, miRNA and three microbial strains to be dysregulated in AD. CCL17, CCL13, CCL22, E-selectin and BDNF were differently regulated and significantly associated with treatment response. In contrast, neither the microbial composition nor the miRNA pattern was associated with treatment response upon dupilumab treatment. AD patients display defined dysregulations regarding their systemic proteomic serum profile, miRNA patterns and their skin microbiome. The proteomic profile and selected skin bacteria changed profoundly upon anti-IL-4Rα therapy which was associated with an overall clinical response. This was not seen in miRNA-related biomarkers. Our findings support the hypothesis that biomarker profiles reflect treatment responses and may in the future be used to develop a personalized medicine approach for the treatment of AD patients.