Skin Gene Expression Is Prognostic for the Trajectory of Skin Disease in Patients With Diffuse Cutaneous Systemic Sclerosis

皮肤基因表达可预测弥漫性皮肤系统性硬化症患者的皮肤疾病发展轨迹

阅读:1

Abstract

OBJECTIVE: At present, there are no clinical or laboratory measures that accurately forecast the progression of skin fibrosis and organ involvement in patients with systemic sclerosis (SSc). The goal of this study was to identify skin biomarkers that could be prognostic for the progression of skin fibrosis in patients with early diffuse cutaneous SSc (dcSSc). METHODS: We analyzed clinical data and gene expression in skin biopsy samples from 38 placebo-treated patients, part of the Roche Safety and Efficacy of Subcutaneous Tocilizumab in Adults with Systemic Sclerosis (FASSCINATE) phase II study of tocilizumab in SSc. RNA samples were analyzed using nCounter. A trajectory model based on a modified Rodnan skin thickness score was used to describe 3 skin disease trajectories over time. We examined the association of skin gene expression with skin score trajectory groups, by chi-square test. Logistic regression was used to examine the prognostic power of each gene identified. RESULTS: We found that placebo-treated patients with high expression of messenger RNA for CD14, SERPINE1, IL13RA1, CTGF, and OSMR at baseline were more likely to have progressive skin score trajectories. We also found that those genes were prognostic for the risk of skin progression and that IL13RA1, OSMR, and SERPINE1 performed the best. CONCLUSION: Skin gene expression of biomarkers associated with macrophages (CD14, IL13RA1) and transforming growth factor β activation (SERPINE1, CTGF, OSMR) are prognostic for progressive skin disease in patients with dcSSc. These biomarkers may provide guidance in decision-making about which patients should be considered for aggressive therapies and/or for clinical trials.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。