Zhao Yang, Jiang Yinyin, Wang Yaxi, Zhang Haiying, Zhu Jun, Jiang Xu, Shen Bo, Chen Yaning, Li Dongfeng, Pan Yang, Han Feng, Zhang Li
Department of Geriatric Neurology, Nanjing Brain Hospital Affiliated to Nanjing Medical University, Nanjing, China.
School of Pharmacy, Nanjing Medical University, Nanjing, China.
Sleep. 2025 Feb 10;48(2). doi: 10.1093/sleep/zsae169.
Numerous observational studies link obstructive sleep apnea (OSA) to inflammatory proteins, yet the directionality of these associations remains ambiguous. Therefore, we aimed to clarify the potential associations of gene-predicted inflammatory proteins with OSA.
Based on genome-wide association study data, we applied Mendelian randomization (MR) to explore potential connections between circulating inflammatory proteins and OSA, primarily using the inverse-variance weighting method for robustness. Cochran's Q test, MR‒Egger intercept test, MR-PRESSO, and leave-one-out method were used to perform sensitivity tests for pleiotropy and heterogeneity. Replication analyses and meta-analyses were performed using other independent data. Steiger tests and multivariate MR assessed the independent effects of exposure factors, and the functional mapping and annotation (FUMA) platform was used to identify key genes to enhance the understanding of genetics.
Our investigation revealed 21 circulating inflammatory proteins significantly associated with OSA-related phenotypes. Notably, IL-10RA, IL-18R1, TNFSF14, CCL23, ADA, and SLAMF1 had significant effects on multiple phenotypes. After FDR correction, IL-18R1, SLAMF1, IL-10RA, and IL-17C were identified as important candidates for OSA, and multivariate MR analysis strengthened the independent heritability of 20 inflammatory factors. The FUMA platform revealed seven overlapping genes: ROBO1, PRIM1, NACA, SHBG, HSD17B6, RBMS2, and WWOX. All reverse MR analyses and sensitivity analyses confirmed the robustness of these associations.
Our results underscore crucial associations between inflammatory proteins and OSA pathogenesis, revealing new correlates and susceptibility genes. These findings advance biomarker identification for OSA risk and highlight the importance of genetic and inflammatory profiles in OSA management.
众多观察性研究将阻塞性睡眠呼吸暂停(OSA)与炎症蛋白联系起来,但这些关联的方向性仍不明确。因此,我们旨在阐明基因预测的炎症蛋白与OSA之间的潜在关联。
基于全基因组关联研究数据,我们应用孟德尔随机化(MR)来探索循环炎症蛋白与OSA之间的潜在联系,主要使用逆方差加权法以确保稳健性。使用 Cochr an's Q检验、MR-Egger截距检验、MR-PRESSO和留一法对多效性和异质性进行敏感性检验。使用其他独立数据进行复制分析和荟萃分析。Steiger检验和多变量MR评估暴露因素的独立效应,并使用功能映射和注释(FUMA)平台识别关键基因,以增进对遗传学的理解。
我们的研究发现21种循环炎症蛋白与OSA相关表型显著相关。值得注意的是,IL-10RA、IL-18R1、TNFSF14、CCL23、ADA和SLAMF1对多种表型有显著影响。经过错误发现率(FDR)校正后,IL-18R1、SLAMF1、IL-10RA和IL-17C被确定为OSA的重要候选蛋白,多变量MR分析强化了20种炎症因子的独立遗传性。FUMA平台揭示了7个重叠基因:ROBO1、PRIM1、NACA、SHBG、HSD17B6、RBMS2和WWOX。所有反向MR分析和敏感性分析均证实了这些关联的稳健性。
我们的结果强调了炎症蛋白与OSA发病机制之间的关键关联,揭示了新的相关性和易感基因。这些发现推进了OSA风险生物标志物的识别,并突出了遗传和炎症特征在OSA管理中的重要性。