Imaging Mass Cytometry Reveals Predominant Innate Immune Signature and Endothelial-Immune Cell Interaction in Juvenile Myositis Compared to Lupus Skin

Abstract

Objective: Cutaneous inflammation can signal disease in juvenile dermatomyositis (DM) and childhood-onset systemic lupus erythematosus (cSLE), but we do not fully understand cellular mechanisms of cutaneous inflammation. In this study, we used imaging mass cytometry to characterize cutaneous inflammatory cell populations and cell-cell interactions in juvenile DM as compared to cSLE.

Methods: We performed imaging mass cytometry analysis on skin biopsy samples from juvenile DM patients (n = 6) and cSLE patients (n = 4). Tissue slides were processed and incubated with metal-tagged antibodies for CD14, CD15, CD16, CD56, CD68, CD11c, HLA-DR, blood dendritic cell antigen 2, CD20, CD27, CD138, CD4, CD8, E-cadherin, CD31, pan-keratin, and type I collagen. Stained tissue was ablated, and raw data were acquired using the Hyperion imaging system. We utilized the Phenograph unsupervised clustering algorithm to determine cell marker expression and permutation test by histoCAT to perform neighborhood analysis.

Results: We identified 14 cell populations in juvenile DM and cSLE skin, including CD14+ and CD68+ macrophages, myeloid and plasmacytoid dendritic cells (pDCs), CD4+ and CD8+ T cells, and B cells. Overall, cSLE skin had a higher inflammatory cell infiltrate, with increased CD14+ macrophages, pDCs, and CD8+ T cells and immune cell-immune cell interactions. Juvenile DM skin displayed a stronger innate immune signature, with a higher overall percentage of CD14+ macrophages and prominent endothelial cell-immune cell interaction.

Conclusion: Our findings identify immune cell population differences, including CD14+ macrophages, pDCs, and CD8+ T cells, in juvenile DM skin compared to cSLE skin, and highlight a predominant innate immune signature and endothelial cell-immune cell interaction in juvenile DM, providing insight into candidate cell populations and interactions to better understand disease-specific pathophysiology.