Zhao Mingyu, Huang Xu, Zheng Hu, Cai Yuhang, Han Wenjia, Wang Yuanyin, Chen Ran
Key Laboratory of Oral Diseases Research of Anhui Province, College & Hospital of Stomatology, Anhui Medical University, Hefei, China.
Front Neurol. 2024 Dec 10;15:1420391. doi: 10.3389/fneur.2024.1420391. eCollection 2024.
The causal relationship between hypothyroidism and obstructive sleep apnea (OSA) remains controversial. Therefore, our research used a bidirectional Mendelian randomization (MR) method in an attempt to determine the causal relationship between hypothyroidism and OSA.
From the publicly accessible genome-wide association analysis (GWAS) summary database, we obtained single nucleotide polymorphism (SNPs) data pertaining to hypothyroidism and OSA. Inverse variance weighting (IVW) was the principal method of analysis utilized, with validation also conducted via weighted median, MR-Egger, simple model, and weighted model approaches. To further evaluate the robustness of the results, heterogeneity testing, pleiotropy testing, and the "leave-one-out" sensitivity analysis were performed. Differentially expressed genes (DEGs) from the OSA dataset (GSE135917) and hypothyroidism dataset (GSE176153) derived from the Gene Expression Omnibus (GEO) database were screened using the "limma" package. The "clusterProfiler" and "GO plot" packages were used for further enrichment analysis in order to validate the findings of the MR study. The Cytoscape software was utilized to build a protein-protein interaction (PPI) network of DEGs and to screen for hub genes.
The MR analysis showed that genetically predicted hypothyroidism was associated with an increased risk of OSA [IVW odds ratio (OR) = 1.734; 95% confidence interval (CI) = 1.073-2.801; = 0.025]. The trend of the outcomes of the other approaches is consistent with the trend of the IVW outcome. However, the reverse MR analysis suggested no evidence for the causal effect of OSA on hypothyroidism (IVW OR = 1.002, 95% CI: 0.996-1.009, = 0.454). The robustness of the results was confirmed by the sensitivity analysis. Bioinformatics analysis revealed that there were DEGs that hypothyroidism and OSA have in common.
Our findings suggested that hypothyroidism may increase the risk of OSA, while the effect of OSA on hypothyroidism was not found in this MR study. Thus, patients with hypothyroidism should be enhanced with screening for OSA for early diagnosis and appropriate treatment.
甲状腺功能减退与阻塞性睡眠呼吸暂停(OSA)之间的因果关系仍存在争议。因此,我们的研究采用双向孟德尔随机化(MR)方法,试图确定甲状腺功能减退与OSA之间的因果关系。
从公开可用的全基因组关联分析(GWAS)汇总数据库中,我们获取了与甲状腺功能减退和OSA相关的单核苷酸多态性(SNP)数据。逆方差加权(IVW)是主要使用的分析方法,同时还通过加权中位数、MR-Egger、简单模型和加权模型方法进行了验证。为了进一步评估结果的稳健性,进行了异质性检验、多效性检验和“留一法”敏感性分析。使用“limma”软件包从基因表达综合数据库(GEO)中筛选出OSA数据集(GSE135917)和甲状腺功能减退数据集(GSE176153)中的差异表达基因(DEG)。使用“clusterProfiler”和“GO plot”软件包进行进一步的富集分析,以验证MR研究的结果。利用Cytoscape软件构建DEG的蛋白质-蛋白质相互作用(PPI)网络并筛选枢纽基因。
MR分析表明,遗传预测的甲状腺功能减退与OSA风险增加相关[IVW比值比(OR)=1.734;95%置信区间(CI)=1.073-2.801;P=0.025]。其他方法的结果趋势与IVW结果的趋势一致。然而,反向MR分析表明没有证据支持OSA对甲状腺功能减退有因果效应(IVW OR=1.002,95%CI:0.996-1.009,P=0.454)。敏感性分析证实了结果的稳健性。生物信息学分析表明,甲状腺功能减退和OSA存在共同的DEG。
我们的研究结果表明,甲状腺功能减退可能会增加OSA的风险,而在本MR研究中未发现OSA对甲状腺功能减退的影响。因此,对于甲状腺功能减退患者,应加强OSA筛查,以便早期诊断和适当治疗。