A major issue with the current management of psoriasis is our inability to predict treatment response.
Our aim was to evaluate the ability to use baseline molecular expression profiling to assess treatment outcome for psoriatic patients.
We conducted a longitudinal study of 46 patients with chronic plaque psoriasis treated with anti-TNF agent etanercept, and molecular profiles were assessed in over 200 RNA-seq samples.
We demonstrated correlation between clinical response and molecular changes during the course of the treatment, particularly for genes responding to IL-17A/TNF in keratinocytes. Intriguingly, baseline gene expressions in non-lesional, but not lesional skin, were the best marker of treatment response at week 12. We identified USP18, a known regulator of IFN responses, as positively correlated with PASI improvement (p=9.8×10) and demonstrate its role in regulating IFN/TNF responses in keratinocytes. Consistently, cytokine gene signatures enriched in baseline non-lesional skin expression profiles had strong correlations with PASI improvement. Using this information, we developed a statistical model for predicting PASI 75 (i.e. 75% of PASI improvement) at week 12, achieving AUC=0.75 and up to 80% accurate PASI75 prediction among the top predicted responders.
Our results illustrate feasibility of assessing drug response in psoriasis utilizing non-lesional skin and implicate involvement of IFN regulators in anti-TNF responses.

Copyright © 2021. Published by Elsevier Inc.