单细胞与转录组学综合分析揭示阻塞性睡眠呼吸暂停中与缺氧、代谢重编程和动脉粥样硬化相关的致病网络及潜在生物标志物
Comprehensive analysis of the single-cell and transcriptomics uncovers the pathogenic network and potential biomarkers related to hypoxia, metabolic reprogramming and atherosclerosis in obstructive sleep apnoea.
文献信息
| PMID | 42821729 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Huiqian Yang |
| 作者单位 | Department of Otolaryngology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, P. R. China. |
| 期刊 | Artificial cells, nanomedicine, and biotechnology |
| SCI 分区 | Q1 |
| IF | 4.3 |
| 研究类型 | 基础研究 · 基础／转化 |
| 所属专科 | 鼻科 |
中文摘要
本研究旨在通过分析RNA-seq（GSE75097： 6例对照和42例OSA）和单细胞RNA-seq（GSE214865：11例对照和11例OSA）数据集，识别阻塞性睡眠呼吸暂停（OSA）的关键生物标志物。差异表达分析揭示了OSA组与对照组之间的575个差异表达基因（DEGs）。使用加权基因共表达网络分析（WGCNA）结合机器学习方法（随机森林、SVM-RFE和LASSO），我们识别出四个枢纽基因（C17ORF91、HBEGF、PGBD2和ZNF616）作为候选生物标志物，显示出探索性的区分性能（AUC > 0.7）。基因集富集分析（GSEA）显示，这些基因与缺氧反应、动脉粥样硬化和代谢重编程相关通路（NES低至-2.049，adj. p < .05）以及免疫调节（NES高达1.932，adj. p < .05）相关。单细胞RNA测序分析进一步表明，cMonocytes在OSA进展中发挥核心作用，在缺氧、代谢功能障碍和动脉粥样硬化风险方面表现出最高评分。一个包含这些枢纽基因的探索性列线图在发现队列中显示出良好的内部性能。这些发现提供了关于OSA相关分子特征的假设生成性见解，并将这些基因识别为需要独立外部和功能验证的候选生物标志物。对这些基因的进一步验证可能为评估其在OSA中的潜在诊断和治疗相关性提供基础。
英文摘要
This study aimed to identify key biomarkers for obstructive sleep apnoea (OSA) by analysing RNA-seq (GSE75097: 6 control and 42 OSA) and single-cell RNA-seq (GSE214865: 11 control and 11 OSA) datasets. Differential expression analysis revealed 575 DEGs between OSA and control groups. Using weighted gene co-expression network analysis (WGCNA) combined with machine learning approaches (Random Forest, SVM-RFE and LASSO), we identified four hub genes (C17ORF91, HBEGF, PGBD2 and ZNF616) as candidate biomarkers, showing exploratory discriminatory performance (AUC > 0.7). Gene set enrichment analysis (GSEA) revealed that these genes are associated with pathways related to hypoxia response, atherosclerosis and metabolic reprogramming (NES as low as -2.049, adj. p < .05), as well as immune regulation (NES up to 1.932, adj. p < .05). Single-cell RNA sequencing analysis further demonstrated that cMonocytes play a central role in OSA progression, exhibiting the highest scores for hypoxia, metabolic dysfunction and atherosclerosis risk. An exploratory nomogram incorporating these hub genes showed favourable internal performance within the discovery cohort. These findings provide hypothesis-generating insights into the molecular features associated with OSA and identify these genes as candidate biomarkers that require independent external and functional validation. Further validation of these genes may provide a basis for evaluating their potential diagnostic and therapeutic relevance in OSA.