Fibroblast subpopulations in Systemic Sclerosis – Functional implications of individual subpopulations and correlations with clinical features

成纤维细胞 纤维化 生物 人口 病理 真皮成纤维细胞 伤口愈合 免疫学 医学 细胞培养 遗传学 环境卫生
作者
Honglin Zhu,Hui Luo,Brian Skaug,Tracy Tabib,Yinan Li,Yongguang Tao,Alexandru-Emil Matei,Marka A. Lyons,Georg Schett,Robert Lafyatis,Shervin Assassi,Jörg H W Distler
出处
期刊:Journal of Investigative Dermatology [Elsevier]
被引量:1
标识
DOI:10.1016/j.jid.2023.09.288
摘要

Fibroblasts constitute a heterogeneous population of cells. Here, we integrated scRNA-seq and bulk RNA-seq data as well as clinical information to study the role of individual fibroblast populations in Systemic Sclerosis (SSc). SSc skin demonstrated increased abundance of COMP+, COL11A1+, MYOC+, CCL19+, SFRP4/SFRP2+ and PRSS23/SFRP2+ fibroblasts signatures, and decreased proportions of CXCL12+ and PI16+ fibroblast signatures in the PRESS and GENISOS cohorts. Numerical differences were confirmed by multicolor immunofluorescence for selected fibroblast populations. COMP+, COL11A1+, SFRP4/SFRP2+, PRSS23/SFRP2+ and PI16+ fibroblasts were similarly altered between normal wound healing and SSc patients. The proportions of profibrotic COMP+, COL11A1+, SFRP4/SFRP2+ and PRSS23/SFRP2+, and proinflammatory CCL19+ fibroblast signatures were positively correlated with clinical and histopathological parameters of skin fibrosis, whereas signatures of CXCL12+ and PI16+ fibroblasts were inversely correlated. Incorporating the proportions of COMP+, COL11A1+, SFRP4/SFRP2+ and PRSS23/SFRP2+ fibroblast signatures into machine learning models improved the classification of SSc patients into those with progressive versus stable skin fibrosis. In summary, the profound imbalance of fibroblast subpopulations in SSc may drive progression of skin fibrosis. Specific targeting of disease-relevant fibroblast populations may offer the opportunities for the treatment of SSc and other fibrotic diseases.
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