Abstract

Patients with prurigo nodularis (PN) suffer from intractable itch and dramatic reduction in QOL. Although there is significant clinical heterogeneity in the presentation of PN, disease endotypes remain unknown. We assayed circulating plasma cytokine concentrations in patients with PN (n= 20) along with matched healthy controls and utilized an unsupervised machine learning algorithm to identify disease endotypes. We found two distinct clusters of patients with PN with noninflammatory (cluster 1) and inflammatory (cluster 2) plasma profiles. Cluster 2 had more African Americans (82%, n= 9 vs. 33%, n= 3; P= 0.028), higher Worst Itch Numeric Rating Scale scores (9.5 ± 0.9 vs. 8.3 ± 1.2; P= 0.036), and lower QOL as reflected by higher Dermatology Life Quality Index scores (21.9 ± 6.4 vs. 13.0 ± 4.1; P= 0.015). In addition, cluster 1 had a higher rate of myelopathy (67%, n= 6 vs. 18%, n= 2; P= 0.028). Compared with cluster 1, cluster 2 had higher levels of IL-1α, IL-4, IL-5, IL-6, IL-10, IL-17A, IL-22, IL-25, and IFN-α. With population-level analysis, African American patients with PN had higher erythrocyte sedimentation rate, C-reactive protein, ferritin, and eosinophils and lower transferrin than Caucasian patients with PN. These findings indicate discrete clusters of patients with PN with plasma biomarker profiles corresponding to distinct demographic and clinical characteristics, potentially allowing for precision medicine approaches to treat PN.

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