Fu Wenhui, Liu Yangli, Li Renjie, Jin Haiying
Department of Respiratory Medicine, Jinyun People's Hospital, Lishui, Zhejiang, 321400, People's Republic of China.
Int J Chron Obstruct Pulmon Dis. 2025 Sep 12;20:3187-3202. doi: 10.2147/COPD.S524381. eCollection 2025.
Chronic obstructive pulmonary disease (COPD) involves progressive lung function decline, with hypoxia playing a key pathogenic role. However, systematic investigations focusing on hypoxia-related genes (HRGs) in COPD remain limited.
We applied machine learning to identify HRG-associated diagnostic biomarkers and evaluated their performance via Receiver Operating Characteristic (ROC) analysis. Mendelian randomization (MR) was conducted to assess causal relationships between candidate genes and COPD. A nomogram model was constructed to evaluate clinical utility, and a ceRNA network was developed using ENCORI database.
Six HRG-based diagnostic biomarkers were identified, including , which demonstrated strong diagnostic value (AUC > 0.8). MR analysis revealed a significant causal effect of expression on COPD risk (OR = 1.32, 95% CI: 1.02-1.71, P < 0.05). Functional evidence suggests promotes hypoxia-induced metabolic reprogramming in airway epithelial cells. The constructed nomogram showed good clinical applicability. ceRNA analysis highlighted , , and as potential upstream regulators.
Our findings identify as a causal and diagnostically relevant gene in COPD, offering novel insight into hypoxia-driven disease mechanisms and supporting future personalized therapeutic strategies.
慢性阻塞性肺疾病（COPD）涉及肺功能进行性下降，缺氧在其发病机制中起关键作用。然而，针对COPD中缺氧相关基因（HRGs）的系统研究仍然有限。
我们应用机器学习来识别与HRG相关的诊断生物标志物，并通过受试者工作特征（ROC）分析评估其性能。进行孟德尔随机化（MR）以评估候选基因与COPD之间的因果关系。构建列线图模型以评估临床实用性，并使用ENCORI数据库开发ceRNA网络。
鉴定出6种基于HRG的诊断生物标志物，包括 ，其显示出强大的诊断价值（AUC>0.8）。MR分析显示 表达对COPD风险有显著因果效应（OR = 1.32，95%CI：1.02 - 1.71，P < 0.05）。功能证据表明 促进气道上皮细胞中缺氧诱导的代谢重编程。构建的列线图显示出良好的临床适用性。ceRNA分析突出了 、 和 作为潜在的上游调节因子。
我们的研究结果确定 是COPD中的一个因果相关且与诊断相关的基因，为缺氧驱动的疾病机制提供了新的见解，并支持未来的个性化治疗策略。
