胸部计算机断层扫描成像和基因表达的深度学习整合确定了COPD的新方面
Junxiang Chen1, Zhonghui Xu2, Li Sun1
1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.
Chronic obstructive pulmonary diseases (Miami, Fla.)
|July 6, 2023
概括
这项研究将慢性阻塞性肺病 (COPD) 中的肺结构变化与血液基因表达模式联系起来. 研究人员在COPD患者中确定了两种与肺和呼吸道疾病相关的不同的炎症特征.
科学领域:
- 肺部医学 肺部医学
- 基因组学就是基因组学.
- 放射学 放射学是一门学科.
背景情况:
- 慢性阻塞性肺病 (COPD) 涉及肺部结构变化和炎症,但与血液基因表达的联系尚不清楚.
- 了解这些联系对于诊断和治疗COPD亚型至关重要.
研究的目的:
- 发现肺部结构变化 (CT扫描) 和血液转录组模式 (RNA-seq) 之间的新型关系.
- 在COPD中识别成像和基因表达之间的共享炎症方面.
主要方法:
- 深度学习分析了1223名COPDGene研究参与者的胸部CT扫描和血液RNA测序数据.
- 图像表达轴 (IEA) 的开发,以表示共享的炎症和结构变化.
- 回归和考克斯比例危险模型将IEAs与COPD测量和结果联系起来.
- 途径丰富分析以确定与IEAs相关的生物途径.
主要成果:
- 确定了两个不同的IEA:IEA (肺主导) 和IEA (气道主导).
- IEA与肺重度相关,与肺功能和BMI负相关.
- IEA气道与气道壁厚度和BMI相关,并且与肺气有负相关.
- 在两种IEA中都发现了显著的途径丰富,突出了不同的生物过程.
结论:
- 结合CT成像和血液RNA-seq数据,发现了两个IEA.
- 这些IEA代表了与肺和气道占主导地位的COPD相关的独特炎症过程.
- 这种方法为COPD异质性和潜在的治疗目标提供了新的见解.
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