Single cell resolution expression profiling of prurigo nodularis highlights enhanced cell-cell interactions and IL-31 signaling modulations in keratinocytes

Summary: Abstract Body: Spatial expression profiling at single-cell resolution provides complementing information for the widely used scRNA-seq. This approach enhances our understanding of tissue architecture and cellular interactions in both healthy and diseased states. Here, we spatially profile three prurigo nodularis (PN) and two control samples using the 10X Genomics Xenium platform, and generated high-resolution cell type projection using fully annotated scRNA-seq. We conducted differential ligand-receptor (LR) signaling analysis, highlighting increased LR signals in PN skin. Notably, keratinocytes harbor the most differential LR interactions, including profibrotic signals involving TGFβ2-TGFβR1 (FC = 9.0, p = 1.2×10-4), and TGFβ3-TGFβR1 (FC = 4.1, p = 9.6×10-10), with primary source of ligands from fibroblasts and T cells. In addition, vascular growth factor interactions were prominent in PN skin including VEGFB-FLT1 (FC = 12.2, p = 7.1×10-73) and VEGFA-EPHB2 (FC = 30.0, p = 7.3×10-19), with fibroblasts and endothelial cells serving as main target cell population. We also captured interactions involving nerve cells in PN skin, relating to angiogenesis and neurogenic inflammation, involving VEGFB-FLT1 (FC = 5.0, p = 3.8×10-2), TGFβ3-TGFβR1 (FC = 4.1, p = 7.3×10-7), and PDGFB-PGFRB (FC = 5.5, p = 2.9×10-2). By computing a module score incorporating IL-31 induced genes available in the xenium panel, we then assessed the spatial distribution of IL-31 responses in keratinocytes. This revealed prominent and highly enriched module score for keratinocyte - T-cell interactions, with the highest module score for keratinocytes neighboring Th2 cells (p = 6.4×10-16). Our study underscores the pivotal role of spatial transcriptomics in uncovering candidate LR signaling pathways specific to PN and elucidating the critical interactions among keratinocytes, nerve, and T cells, offering novel insights into the pathophysiology of PN and potential therapeutic targets. Haihan Zhang¹, He Zhang¹, Yuli Cai¹, Rachael Bogle¹, Matthew Patrick¹, Johann E. Gudjonsson¹, Lam C. Tsoi¹ 1. University of Michigan, Ann Arbor, MI, United States. Bioinformatics, Computational Biology, and Imaging