Integrative transcriptomic, network, and genomic analysis of peripheral blood mononuclear cells identifies candidate gene drivers of dupilumab clinical response in atopic dermatitis patients

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 that could predict response to biological therapies. In line with this, we aimed to identify blood biomarkers that could predict 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. Finally, our study highlighted potential genes that could predict outcome in patients with AD who are treated with dupilumab. Moreover, our study represents an incremental contribution to existing knowledge and opens new avenues for research that may ultimately lead to personalized medicine.