Prurigo nodularis (PN) is a chronic, inflammatory skin condition that disproportionately affects African Americans and features intensely pruritic, hyperkeratotic nodules on the extremities and trunk. PN is understudied compared with other inflammatory skin diseases, with the spatial organization of the cutaneous infiltrate in PN yet to be characterized. In this work, we employ spatial imaging mass cytometry to visualize PN lesional skin inflammation and architecture with single-cell resolution through an unbiased machine learning approach. PN lesional skin has increased expression of caspase 3, NF-kB, and phosphorylated signal transducer and activator of transcription 3 compared with healthy skin. Keratinocytes in lesional skin are subdivided into CD14+CD33+, CD11c+, CD63+, and caspase 3-positive innate subpopulations. CD14+ macrophage populations expressing phosphorylated extracellular signal-regulated kinase 1/2 correlate positively with patient-reported itch (P = .006). Hierarchical clustering reveals a cluster of patients with PN with greater atopy, increased NF-kB+ signal transducer and activator of transcription 3-positive phosphorylated extracellular signal-regulated kinase 1/2-positive monocyte-derived myeloid dendritic cells, and increased vimentin expression (P < .05). Neighborhood analysis finds interactions between CD14+ macrophages, CD3+ T cells, monocyte-derived myeloid dendritic cells, and keratinocytes expressing innate immune markers. These findings highlight phosphorylated extracellular signal-regulated kinase-positive CD14+ macrophages as contributors to itch and suggest an epithelial-immune axis in PN pathogenesis.
Keywords: Biomarkers; Imaging mass cytometry; Prurigo nodularis; Single cell; Translational.
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