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Commentary: The Next Era of Opportunity in Psoriasis: Spatial Transcriptomics
Nicole Ward, PhD
Vanderbilt University Medical Center
Nashville, Tennessee, United States
BioPUBLICATIONS
Spatial Transcriptomics Stratifies Psoriatic Disease Severity by Emergent Cellular Ecosystems. Castillo RL, Sidhu I, Dolgalev I, et al. Sci Immunol. 2023 Jun 8;8(84):eabq7991. doi: 10.1126/sciimmunol.abq7991. Epub 2023 Jun 2.PMID: 37267384.
Single Cell and Spatial Sequencing Define Processes by Which Keratinocytes and Fibroblasts Amplify Inflammatory Responses in Psoriasis. Ma F, Plazyo O, Billi AC, et al. Nat Commun. 2023 Jun 12;14(1):3455. doi: 10.1038/s41467-023-39020-4. PMID: 37308489.
Why this article was chosen
Seldom is there a paradigm shift in psoriatic disease research methodology that can impact our field in new, exciting ways. GWAS was one of these, as was the advent of Biologics. This month, we highlight two papers that utilize cutting-edge Spatial Transcriptomics and Single Cell Sequencing to study psoriasis patient skin and point out new and exciting cellular players long thought not to play a critical role in psoriasis pathogenesis. These new methods will likely lead to identifying new cellular and molecular pathways, novel targets for drug development, and will continue to help move the Psoriasis field of research and medicine forward.
Commentary
Two papers1,2, presented in chronological order below, came out in June, highlighting the enormous capacity of spatial transcriptomics and single-cell sequencing for identifying innovative new cellular players and pathways in psoriasis pathogenesis, and promise for an exciting future moving forward in learning how these new cell types and pathways contribute to psoriatic disease.
B Cells in Psoriatic Skin
Castillo and colleagues1 identify the presence of B cells in psoriasis skin and epidermal-dermal “interactomes” critical for psoriatic inflammation, including dermal B cell-fibroblast interactions. B cells were located to the dermal-epidermal junction (DEJ) in lesional psoriasis skin (PP), in the dermis in nonlesional (PN) skin, and were absent in healthy skin (NS). B cell-related KEGG pathway analyses identified “regulation of cytokine production,” “antigen processing and presentation,” “IkB, NFkB signaling,” “TLR-like receptor signaling,” “IL-6 production”, and “IL-10 production” as top pathways. They also determine that changes in gene expression and interactomes correlate with skin disease severity and not systemic comorbidity, supporting a skin-centered inflammatory response. These findings suggest that B cells, an understudied cell in psoriasis pathogenesis, may also contribute to skin lesion development and/or maintenance and could explain recent case reports showing psoriatic arthritis remission following treatment with the B cell targeted therapy, rituximab 3-8, but also paradoxical psoriasis development in patients being treated for other B cell-specific diseases (reviewed in 9). Indeed, the “yin-yang” findings following B cell inhibition imply a B cell subtype-specific response, such that B cells may restrain inflammation indirectly through its effects on T cells and IL-17A production, via the production of IL-10 and Bregs, and promote inflammation and increase in IL-17A, via production of IL-6 and Beffs. Thus, B cell blockade may improve existent psoriasis via inhibition of Beffs and IL-6 or elicit psoriasis (via inhibition of Bregs and IL-10) in patients with genetic susceptibility. The future looks exciting for this area of research and delineating a pathogenic role for B cells in psoriatic disease pathogenesis. Other critical findings in this work included a clear demonstration that changes in skin inflammation stratify with disease severity, and their patient cohort does not appear to predict or align with PsA.
The teams of Drs. Shruti Naik, Jose Sher, and collaborators used the bioinformatic tools Space Ranger, Seurat, and SpaceFold to study and identify unique cell populations and NicheNet to perform their ligand-receptor interaction queries.
Fibroblasts as Critical Regulators of Inflammation
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.
References
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