Background/Purpose:

Vascular injury is a hallmark event in the pathogenesis of Systemic Sclerosis (SSc). Endothelial dysfunction happens early in the course of the disease and drives some of the most prominent clinical manifestations of scleroderma, including Raynaud’s phenomenon, telangiectasias and gastric antral vascular ectasias, pulmonary arterial hypertension and scleroderma renal crisis. The exact mechanisms that lead to endothelial cell injury and propagate the vasculopathy in scleroderma are not well understood. Single cell RNA sequencing provides a robust platform for cellular identification, allows gene expression analysis at the single cell level and accounts for cellular heterogeneity.

Methods:

The study was completed in the Scleroderma Center of UPMC in collaboration with the Scleroderma Research Center of Boston University and the Broad Institute of Boston. We implemented single cell sorting and subsequent RNA sequencing of cells isolated from scleroderma and healthy control skin. The analysis was performed using R software. We used t-distributed stochastic neighbor embedding (t-SNE) with k-means clustering to identify the various cell types. We performed pathway analysis using Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA). Finally, we independently verified distinct markers using immunohistochemistry on skin biopsies and qPCR in primary endothelial cells isolated from skin of scleroderma patients and healthy controls.

Results:

In order to visualize and ultimately define the various cell subsets in the single cell RNA sequencing dataset, we used t-SNE analysis, a method of unsupervised learning for dimensionality reduction. 2D projection of the t-SNE coupled with k-means clustering effectively reduced the dimensionality of the data. By combining the t-SNE analysis with the expression of known endothelial cell markers, including VWF, PECAM1 and CDH5, we were able to positively identify the endothelial cells among the sorted single cells from healthy and scleroderma skin. Subsequently, we analyzed the differential expression profile between the endothelial cells from healthy and scleroderma skin. Using GSEA and IPA analysis, we were able to demonstrate that the SSc endothelial cell expression profile is enriched in processes associated with extracellular matrix generation, negative regulation of angiogenesis and epithelial-to-mesenchymal transition. Finally, two of the top differentially expressed genes, HSPG2 and APLNR, were independently verified. Primary endothelial cells isolated from scleroderma skin expressed higher levels of APLNR mRNA compared to endothelial cells isolated from healthy skin. Immunohistochemistry studies of skin biopsies revealed that HSPG2 showed increased expression in the perivascular area of scleroderma skin compared to healthy skin.

Conclusion:

Using single cell RNA sequencing we were able to identify an endothelial cell gene signature in scleroderma skin. Differential gene expression and pathway analysis revealed that endothelial cells from scleroderma patients exhibit a pattern of endothelial injury and activation as well as increased extracellular matrix generation and negative regulation of angiogenesis.

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ACR Meeting Abstracts - https://acrabstracts.org/abstract/single-cell-rna-sequencing-reveals-a-signature-of-endothelial-injury-in-scleroderma-skin/