Proteomic, miRNA and bacterial biomarker patterns in atopic dermatitis
patients and their course upon anti-IL-4Rα therapy
Abstract
Background: Identification of biomarkers is required for a
systems medicine approach and personalized treatment in AD. These
biomarkers may not only aid in diagnosing but also might be suitable to
predict the effectiveness of targeted treatment. Objective: We
aimed to identify proteomic, microbial, and miRNA biomarkers in atopic
dermatitis patients and investigated their course in relation to the
clinical response upon anti-IL-4Rα therapy. Methods: 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. Results: We identified 27 proteomic
candidates, miRNA, and 3 microbial strains to be dysregulated in AD.
Besides the well-known chemokine CCL17 other proteins i.e., CCL13,
CCL22, E-selectin and BDNF were differently regulated and significantly
associated with treatment response. By contrast neither the microbial
changes nor the miRNA pattern were found to be associated with treatment
response upon dupilumab treatment. Conclusion: AD patients
display defined dysregulations regarding their systemic proteomic serum
profile, miRNA patterns, and their skin microbiome. The proteomic
profile and selekted 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 atopic dermatitis patients.