Hebei General Hospital, Shijiazhuang, Hebei, China.
Hebei North University, Zhangjiakou, Hebei, China.
Front Immunol. 2024 Sep 16;15:1416870. doi: 10.3389/fimmu.2024.1416870. eCollection 2024.
Obstructive sleep apnea (OSA) is a common sleep disorder. Inflammatory factors and plasma metabolites are important in assessing its progression. However, the causal relationship between them and OSA remains unclear, hampering early clinical diagnosis and treatment decisions.
We conducted a large-scale study using data from the FinnGen database, with 43,901 cases and 366,484 controls for our discovery MR analysis. We employed 91 plasma proteins from 11 cohorts (totaling 14,824 participants of European descent) as instrumental variables (IVs). Additionally, we conducted a GWAS involving 13,818 cases and 463,035 controls to replicate the MR analysis. We primarily used the IVW method, supplemented by MR Egger, weighted median, simple mode, and weighted mode methods. Meta-analysis was used to synthesize MR findings, followed by tests for heterogeneity, pleiotropy, and sensitivity analysis (LOO). Reverse MR analysis was also performed to explore causal relationships.
The meta-analysis showed a correlation between elevated Eotaxin levels and an increased risk of OSA (OR=1.050, 95% CI: 1.008-1.096; p < 0.05). Furthermore, we found that the increased risk of OSA could be attributed to reduced levels of X-11849 and X-24978 (decreases of 7.1% and 8.4%, respectively). Sensitivity analysis results supported the reliability of these findings.
In this study, we uncovered a novel biomarker and identified two previously unknown metabolites strongly linked to OSA. These findings underscore the potential significance of inflammatory factors and metabolites in the genetic underpinnings of OSA development and prognosis.
阻塞性睡眠呼吸暂停（OSA）是一种常见的睡眠障碍。炎症因子和血浆代谢物在评估其进展中很重要。然而，它们与 OSA 之间的因果关系尚不清楚，这阻碍了早期的临床诊断和治疗决策。
我们使用 FinnGen 数据库中的数据进行了一项大规模研究，在发现性 MR 分析中，我们使用了 43901 例病例和 366484 例对照。我们使用了来自 11 个队列的 91 种血浆蛋白（总计 14824 名欧洲血统的参与者）作为工具变量（IVs）。此外，我们进行了一项涉及 13818 例病例和 463035 例对照的 GWAS 来复制 MR 分析。我们主要使用 IVW 方法，同时辅以 MR Egger、加权中位数、简单模式和加权模式方法。使用 Meta 分析综合了 MR 研究结果，然后进行了异质性、多效性和敏感性分析（LOO）检验。还进行了反向 MR 分析来探索因果关系。
Meta 分析显示，Eotaxin 水平升高与 OSA 风险增加相关（OR=1.050，95%CI：1.008-1.096；p<0.05）。此外，我们发现 OSA 风险的增加可归因于 X-11849 和 X-24978 水平的降低（分别降低了 7.1%和 8.4%）。敏感性分析结果支持了这些发现的可靠性。
在这项研究中，我们发现了一种新的生物标志物，并确定了两个以前未知的与 OSA 强烈相关的代谢物。这些发现强调了炎症因子和代谢物在 OSA 发展和预后的遗传基础中的潜在重要性。
