Photo Credit: Vshivkova

The following is a summary of “Fibroblast Subpopulations in Systemic Sclerosis: Functional Implications of Individual Subpopulations and Correlations with Clinical Features,” published in the June 2024 issue of Dermatology by Zhu, et al.

For a study, researchers sought to investigate the role of individual fibroblast populations in systemic sclerosis (SSc) by integrating single-cell RNA-sequencing and bulk RNA-sequencing data along with clinical information. Specifically, they examined the abundance and signatures of different fibroblast subpopulations in SSc skin compared to normal skin and their correlation with clinical parameters of skin fibrosis.

The research utilized single-cell RNA-sequencing and bulk RNA-sequencing data, combined with clinical information, to analyze fibroblast populations in SSc skin. Multicolor immunofluorescence is employed to confirm numerical differences in selected fibroblast populations. Machine learning models are utilized to assess the predictive value of fibroblast signatures in classifying patients with SSc based on the progression of skin fibrosis.

SSc skin exhibited an increased abundance of COMP+, COL11A1+, MYOC+, CCL19+, SFRP4/SFRP2+, and PRSS23/SFRP2+ fibroblast signatures, along with decreased proportions of CXCL12+ and PI16+ fibroblast signatures. These numerical differences were validated by multicolor immunofluorescence. Similar alterations in specific fibroblast populations are observed between normal wound healing and patients with SSc. Profibrotic and proinflammatory fibroblast signatures were positively correlated with clinical and histopathological parameters of skin fibrosis, while signatures of CXCL12+ and PI16+ fibroblasts showed inverse correlations. Incorporating the proportions of specific fibroblast signatures into machine-learning models enhanced the classification of patients with SSc based on the progression of skin fibrosis.

The study highlighted a significant imbalance in fibroblast subpopulations in SSc, which may contribute to the progression of skin fibrosis. Targeting disease-relevant fibroblast populations could hold promise for treating SSc and other fibrotic conditions. The findings shed light on potential therapeutic strategies to modulate specific fibroblast populations to mitigate fibrosis progression in SSc.

Reference: sciencedirect.com/science/article/abs/pii/S0022202X23032062