综合性多组学分析揭示了与疾病进展相关的新型异常性肺纤维化内型
Peifeng Ruan1, Jamie L Todd2,3, Hongyu Zhao1
1Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA.
Respiratory research
|June 21, 2023
概括
整合多个omics的血液数据,确定了两种异常性肺纤维化 (IPF) 的分子亚型. 一种亚型显示出更严重的疾病和更短的无进展生存期,有助于未来的IPF临床试验丰富.
科学领域:
- 肺部医学 肺部医学
- 基因组学就是基因组学.
- 蛋白质组学是指蛋白质组学.
背景情况:
- 异形性肺纤维化 (IPF) 是一种进展性肺病,其特征是细胞外矩阵积累.
- 目前对IPF异质性的理解有限,阻碍了针对性的治疗策略.
研究的目的:
- 整合多omics数据 (蛋白质组学,总RNA,微RNA) 来识别IPF患者的不同分子内型.
- 评估已确定分子亚型的临床相关性和预后价值.
主要方法:
- 从IPF-PRO注册表 (NCT01915511) 收集未来的数据.
- 在血液样本上进行多omics (proteomics,toRNA,miRNA) 分析.
- 类似性网络融合和光谱聚类用于分子亚型识别.
- 考克斯的比例危险模型用于评估生存结果.
主要成果:
- 在232名受试者中发现了两种不同的IPF分子亚型.
- 1亚型,包括45.3%的患者,表现出更严重的疾病和明显更短的无进展生存期.
- 蛋白质和微RNA,而不是总RNA,是亚型分类的关键驱动因素,在纤维化相关途径 (例如mTOR,VEGF) 中进行丰富.
结论:
- 多omics数据集成成功确定了IPF的临床上有意义的分子内型.
- 这些内型可以帮助识别患有更高进展风险的患者,并改善临床试验设计.
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