Commentary: The Next Era of Opportunity in Psoriasis: Spatial Transcriptomics

Ma and colleagues² present findings supporting a ground-breaking role for skin fibroblasts in promoting psoriasis lesion development.  Fibroblasts represent another understudied cell type in psoriasis pathogenesis, and the work presented in this publication demonstrates a critical role for psoriasis fibroblasts in amplifying skin inflammation alone and in synergy with keratinocytes and immune cells.  SFRP2+ fibroblasts localized to the upper dermis produce CCL13, CCL19, and CXCL12 that directly interact with CXCR4+ keratinocytes, CCR2+ myeloid cells, CCR7+LAMP3+ dendritic cells and CXCR4+ CD8+Tc17 cells and contribute to self-sustaining inflammation by recruiting immune cells to sites of active inflammation. SFRP2+ fibroblasts also secrete cathepsin S, a protease known to cleave and activate IL-36G, in supraspinous layer keratinocytes and contribute to the synergistic amplification of IL-17A and TNF. Other critical findings in this work include a demonstration of stratified gene expression changes in keratinocytes throughout the epidermal layers and a distinct separation of keratinocyte gene expression changes between PP and PN and NS keratinocytes consistent with a major change in epidermal function in lesional psoriatic skin.  Whereas IFN elicits its effects primarily in basal layers, TNF, IL17A, and IL36G are more active in the supraspinous layers.  CD8+Tc17 cells, not CD4+Tc17 cells, were determined to be the major cellular source of Il-17A in PP skin, and these cells also produce IFNG and localize to the DEJ and tips of the dermal papillae, regions of dense immune cell infiltrate and fibroblasts.  This work also integrates in vitro primary keratinocyte-Crispr-Cas9 knockout cell RNAseq data with in vivo spatial and scRNA-seq data to demonstrate specific mechanisms of action in the absence of specific cytokines. Whether targeting fibroblast-specific factors, the interactions between fibroblasts and immune cells, or fibroblasts and keratinocytes, will provide new targets for therapeutic development and will likely be a focus of new and ongoing research. 

The groups involved in this work, led by Dr. Johann Gudjonsson, used the bioinformatic tools Seurat and SeqScope to identify cell populations, CellPhone DB to identify ligand-receptor interactions, and Monocle to complete the Pseudotime trajectories.

The independent confirmation of findings by different groups, using different patient samples and bioinformatic approaches, validates findings and interpretation. The future will allow the comparison of different approaches and identify the strengths and limitations of different R codes and software analytic tools.

Together, these groups, many working collaboratively, utilize new cutting-edge sequencing and imaging approaches and demonstrate that there is still much to learn about psoriasis pathogenesis. The capacity to use these deep datasets in the future will likely uncover additional paradigm-shifting findings and add new insight into psoriasis pathogenesis for years to come.