Department of Rheumatology and Immunology, Xiangya Hospital, Central South University, Changsha, China; Department of Internal Medicine 3, Friedrich-Alexander University (FAU) Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
Department of Rheumatology and Immunology, Xiangya Hospital, Central South University, Changsha, China; National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China.
J Invest Dermatol. 2024 Jun;144(6):1251-1261.e13. doi: 10.1016/j.jid.2023.09.288. Epub 2023 Dec 24.
Fibroblasts constitute a heterogeneous population of cells. In this study, we integrated single-cell RNA-sequencing and bulk RNA-sequencing data as well as clinical information to study the role of individual fibroblast populations in systemic sclerosis (SSc). SSc skin demonstrated an 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 Prospective Registry of Early Systemic Sclerosis and Genetics versus Environment in Scleroderma Outcome Study 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 patients with SSc. 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 patients with SSc into those with progressive versus stable skin fibrosis. In summary, the profound imbalance of fibroblast subpopulations in SSc may drive the progression of skin fibrosis. Specific targeting of disease-relevant fibroblast populations may offer opportunities for the treatment of SSc and other fibrotic diseases.
成纤维细胞构成了一个异质性的细胞群体。在这项研究中,我们整合了单细胞 RNA 测序和批量 RNA 测序数据以及临床信息,以研究单个成纤维细胞群体在系统性硬化症 (SSc) 中的作用。SSc 皮肤表现出 COMP+、COL11A1+、MYOC+、CCL19+、SFRP4/SFRP2+和 PRSS23/SFRP2+成纤维细胞特征的丰度增加,以及 CXCL12+和 PI16+成纤维细胞特征的比例降低,在早期系统性硬化症前瞻性注册研究和硬皮病结局研究中的遗传学与环境队列中。通过对选定的成纤维细胞群体进行多色免疫荧光染色,证实了数值差异。COMP+、COL11A1+、SFRP4/SFRP2+、PRSS23/SFRP2+和 PI16+成纤维细胞在正常伤口愈合和 SSc 患者之间也发生了类似的改变。促纤维化 COMP+、COL11A1+、SFRP4/SFRP2+和 PRSS23/SFRP2+和成炎症性 CCL19+成纤维细胞特征的比例与皮肤纤维化的临床和组织病理学参数呈正相关,而 CXCL12+和 PI16+成纤维细胞特征的比例则呈负相关。将 COMP+、COL11A1+、SFRP4/SFRP2+和 PRSS23/SFRP2+成纤维细胞特征的比例纳入机器学习模型,可提高 SSc 患者中皮肤纤维化进展与稳定患者的分类。总之,SSc 中成纤维细胞亚群的严重失衡可能推动了皮肤纤维化的进展。针对与疾病相关的成纤维细胞群体的特定靶向治疗可能为 SSc 和其他纤维化疾病的治疗提供机会。