Atopic dermatitis (AD) is among the most common chronic inflammatory diseases. Due to the heterogeneous presentation of AD, patient response to treatment may differ considerably. Therefore, there is a pressing need for biomarkers associated with response to biological therapies. Thus, we aimed to identify blood-based candidate biomarkers associated with response in patients treated with dupilumab. The present study applied a multi-stage integrative analytical framework combining transcriptomic profiling, functional enrichment, co-expression network analysis, and genomic variant analysis to identify potential biomarkers. Eighteen dupilumab-naïve patients were enrolled in the transcriptomic analysis, with blood samples collected at baseline and after 16–18 weeks of therapy; five patients were identified as non-responders. Additionally, genotyping was performed in 34 patients. We identified a set of candidate genes (RPL18A, RPS28, FAU, MASTL, AURKA, TAF2, BUB1B, and RNF135) and genomic variants that may reflect underlying biological mechanisms influencing therapeutic response. However, given the limited sample size, these findings should be considered exploratory and hypothesis-generating. Finally, our study identified exploratory candidate genes potentially associated with variability in dupilumab treatment response. Moreover, our study represents an incremental contribution to existing knowledge, opening avenues for research that may ultimately lead to personalized medicine.
Krušič et al. (Fri,) studied this question.