Research & Early Development, Bristol-Myers Squibb Company, Lawrenceville, NJ, USA.
Rheumatology (Oxford). 2022 Apr 11;61(4):1717-1727. doi: 10.1093/rheumatology/keab580.
SSc is a rheumatic autoimmune disease affecting roughly 20 000 people worldwide and characterized by excessive collagen accumulation in the skin and internal organs. Despite the high morbidity and mortality associated with SSc, there are no approved disease-modifying agents. Our objective in this study was to explore transcriptomic and model-based drug discovery approaches for SSc.
In this study, we explored the molecular basis for SSc pathogenesis in a well-studied mouse model of scleroderma. We profiled the skin and lung transcriptomes of mice at multiple timepoints, analysing the differential gene expression that underscores the development and resolution of bleomycin-induced fibrosis.
We observed shared expression signatures of upregulation and downregulation in fibrotic skin and lung tissue, and observed significant upregulation of key pro-fibrotic genes including GDF15, Saa3, Cxcl10, Spp1 and Timp1. To identify changes in gene expression in responses to anti-fibrotic therapy, we assessed the effect of TGF-β pathway inhibition via oral ALK5 (TGF-β receptor I) inhibitor SB525334 and observed a time-lagged response in the lung relative to skin. We also implemented a machine learning algorithm that showed promise at predicting lung function using transcriptome data from both skin and lung biopsies.
This study provides the most comprehensive look at the gene expression dynamics of an animal model of SSc to date, provides a rich dataset for future comparative fibrotic disease research, and helps refine our understanding of pathways at work during SSc pathogenesis and intervention.
硬皮病(SSc)是一种影响全球约 20000 人的风湿性自身免疫性疾病,其特征是皮肤和内脏器官中胶原过度积聚。尽管 SSc 与高发病率和死亡率相关,但目前尚无批准的疾病修正药物。我们本研究的目的是探索 SSc 的转录组学和基于模型的药物发现方法。
在这项研究中,我们在一个研究充分的硬皮病小鼠模型中探索了 SSc 发病机制的分子基础。我们在多个时间点对小鼠的皮肤和肺转录组进行了分析,分析了阐明博来霉素诱导纤维化发生和消退的差异基因表达。
我们观察到纤维化皮肤和肺组织中上调和下调的共同表达特征,并观察到关键促纤维化基因(包括 GDF15、Saa3、Cxcl10、Spp1 和 Timp1)的显著上调。为了确定抗纤维化治疗反应中基因表达的变化,我们评估了通过口服 ALK5(TGF-β 受体 I)抑制剂 SB525334 抑制 TGF-β 通路的效果,并观察到肺相对于皮肤的时间滞后反应。我们还实施了一种机器学习算法,该算法显示出使用皮肤和肺活检的转录组数据预测肺功能的潜力。
本研究提供了迄今为止对 SSc 动物模型的基因表达动态的最全面观察,为未来的比较纤维化疾病研究提供了丰富的数据集,并有助于我们更深入地了解 SSc 发病机制和干预过程中的作用途径。