Single-cell analysis reveals key differences between early-stage and late-stage systemic sclerosis skin across autoantibody subgroups

单细胞分析揭示了早期和晚期系统性硬化症皮肤在不同自身抗体亚组间的关键差异

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作者:Kristina Elizabeth Neergaard Clark ,Shiwen Xu ,Moustafa Attah ,Voon H Ong ,Christopher Dominic Buckley ,Christopher P Denton

Abstract

Objectives: The severity of skin involvement in diffuse cutaneous systemic sclerosis (dcSSc) depends on stage of disease and differs between anti-RNA-polymerase III (ARA) and anti-topoisomerase antibody (ATA) subsets. We have investigated cellular differences in well-characterised dcSSc patients compared with healthy controls (HCs). Methods: We performed single-cell RNA sequencing on 4 mm skin biopsy samples from 12 patients with dcSSc and HCs (n=3) using droplet-based sequencing (10× genomics). Patients were well characterised by stage (>5 or <5 years disease duration) and autoantibody (ATA+ or ARA+). Analysis of whole skin cell subsets and fibroblast subpopulations across stage and ANA subgroup were used to interpret potential cellular differences anchored by these subgroups. Results: Fifteen forearm skin biopsies were analysed. There was a clear separation of SSc samples, by disease, stage and antibody, for all cells and fibroblast subclusters. Further analysis revealed differing cell cluster gene expression profiles between ATA+ and ARA+ patients. Cell-to-cell interaction suggest differing interactions between early and late stages of disease and autoantibody. TGFβ response was mainly seen in fibroblasts and smooth muscle cells in early ATA+dcSSc skin samples, whereas in early ARA+dcSSc patient skin samples, the responding cells were endothelial, reflect broader differences between clinical phenotypes and distinct skin score trajectories across autoantibody subgroups of dcSSc. Conclusions: We have identified cellular differences between the two main autoantibody subsets in dcSSc (ARA+ and ATA+). These differences reinforce the importance of considering autoantibody and stage of disease in management and trial design in SSc.

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