阻塞性睡眠呼吸暂停中睡眠结构破坏与炎症及细胞外基质生物标志物的协同模式：一项横断面研究
Sleep architecture disruption and coordinated patterns of inflammatory and extracellular matrix biomarkers in obstructive sleep apnea: a cross-sectional study.
文献信息
| PMID | 42966814 |
|---|---|
| 原文 | 在 PubMed 查看原文 ↗ |
| 发表日期 | 2026 |
| 作者 | Gülşah Köse |
| 作者单位 | Department of Medical Biochemistry, Faculty of Medicine, Recep Tayyip Erdoğan University, Rize, Türkiye. |
| 期刊 | European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery |
| SCI 分区 | Q1 |
| IF | 2.3 |
| 研究类型 | 临床研究 · 临床 |
| 所属专科 | 耳科 |
中文摘要
目的： 本研究旨在探讨循环炎症、细胞外基质（ECM）和氧化应激生物标志物与不同严重程度阻塞性睡眠呼吸暂停（OSA）的多导睡眠图参数之间的关联，并对体重指数（BMI）进行调整。
方法： 70名确诊OSA的成人根据呼吸暂停低通气指数（AHI）分为轻至中度或重度。采用ELISA或分光光度法测定血清TNF-α、IL-6、MMP-2、MMP-9、锁链素、细胞纤连蛋白（cFN）、syndecan-1（SDC-1）、谷胱甘肽（GSH）和丙二醛（MDA）水平。生物标志物浓度经自然对数转换以满足正态性假设；组间比较采用ANCOVA并对BMI进行调整。生物标志物与临床变量之间的关联采用Spearman相关、BMI调整的偏相关和网络分析进行评估。
结果： 与轻至中度OSA相比，重度OSA与更高水平的TNF-α、IL-6、MMP-2、MMP-9、锁链素和cFN相关（均p < 0.05）。SDC-1在BMI调整后达到统计学显著性（p = 0.009）。这些生物标志物与AHI、氧减饱和指数（ODI）、减饱和次数以及SpO₂ <90%的时间（T90）呈正相关，与N3睡眠持续时间呈负相关。BMI调整后，强的生物标志物间偏相关（r = 0.831-0.921，p < 0.001）形成一个连接密集的炎症-ECM簇；该模式在使用未调整Spearman相关（ρ = 0.427-0.655，p < 0.001）的敏感性分析中仍然显著，尽管幅度更为温和。GSH和MDA显示出较弱且更孤立的关联。
结论： OSA严重程度与炎症和ECM相关生物标志物之间的协同模式相关，这些模式与缺氧负荷和睡眠结构变化相平行。相比之下，全身氧化应激标志物似乎在这些模式中整合程度较低。这些发现支持多生物标志物方法在反映疾病相关生理改变方面的潜在效用，这些改变可能源于全身和上气道局部组织过程。
英文摘要
PURPOSE: This study aimed to investigate the associations between circulating inflammatory, extracellular matrix (ECM), and oxidative stress biomarkers and polysomnographic parameters across different severity levels of obstructive sleep apnea (OSA), with adjustment for body mass index (BMI).
METHODS: Seventy adults with confirmed OSA were categorized as mild-to-moderate or severe based on apnea-hypopnea index (AHI). Serum levels of TNF-α, IL-6, MMP-2, MMP-9, desmosine, cellular fibronectin (cFN), syndecan-1 (SDC-1), glutathione (GSH), and malondialdehyde (MDA) were measured using ELISA or spectrophotometric methods. Biomarker concentrations were natural-log transformed to satisfy normality assumptions; between-group comparisons were adjusted for BMI using ANCOVA. Associations among biomarkers and clinical variables were assessed using Spearman correlation, BMI-adjusted partial correlation, and network analysis.
RESULTS: Severe OSA was associated with higher levels of TNF-α, IL-6, MMP-2, MMP-9, desmosine, and cFN compared with mild-to-moderate OSA (all p < 0.05). SDC-1 reached statistical significance after BMI adjustment (p = 0.009). These biomarkers were positively associated with AHI, oxygen desaturation index (ODI), desaturation count, and time spent with SpO₂ <90% (T90), and inversely associated with N3 sleep duration. After adjustment for BMI, strong inter-biomarker partial correlations (r = 0.831-0.921, p < 0.001) formed a densely connected inflammatory-ECM cluster; this pattern remained significant, albeit more modest in magnitude, in sensitivity analyses using unadjusted Spearman correlations (ρ = 0.427-0.655, p < 0.001). GSH and MDA showed weaker and more isolated associations.
CONCLUSION: OSA severity is associated with coordinated patterns among inflammatory and ECM-related biomarkers that parallel hypoxic burden and sleep architecture changes. In contrast, systemic oxidative stress markers appear less integrated within these patterns. These findings support the potential utility of multi-biomarker approaches in reflecting disease-related physiological alterations, potentially arising from both systemic and local upper airway tissue processes.