Xia L, Li Z Q, Xie Z N, Zhang Q X, Li M Y, Zhang C Y, Chen Y Z
School of clinical medicine, Dali University, Dali 671000, China.
Department of Otorhinolaryngology, Chongqing Armed Police Corps Hospital, Chongqing 400061, China.
Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi. 2023 Oct 7;58(10):974-979. doi: 10.3760/cma.j.cn115330-20230803-00032.
This study aims to explore the causal relationship between obstructive sleep apnea (OSA) and type 2 diabetes (T2D) using bidirectional Mendelian randomization (MR). The genetic data related to OSA were obtained from the FinnGen Biobank (Ncase=16, 761, Ncontrol=201, 194) in the Genome-wide association study (GWAS). Three single nucleotide polymorphism (SNP) were screened out as instrumental variable (IV) of OSA. The genetic data related to T2D were derived from a large Meta-analysis of GWAS (Ncase=62, 892, Ncontrol=596, 424), 114 SNP were selected as IV of T2D. Multiple MR methods were used for analysis and inverse variance weighted (IVW) was performed as main method. The sensitivity of MR analytic results was analyzed using MR-Egger and other methods, and the IV was evaluated using -value statistics. MR analysis showed that OSA was significantly associated with increased risk of T2D (=2.016, 95%: 1.185-3.429, <0.05). There was no significant relationship between T2D and OSA risk (=1.030, 95%: 0.980-1.082, =0.238). There was heterogeneity in both-way results (OSA➝T2D, =1.808×10; T2D➝OSA, =1.729×10), and no horizontal pleiotropy (OSA➝T2D, =0.477; T2D➝OSA, =0.349). IV of OSA and T2D-selected in the study were strong instrumental variables ( statistics of OSA=20.543; statistics of T2D=30.117). Our results supported that OSA was a risk factor for T2D, but T2D had no significant impact on the incidence of OSA. Blood glucose monitoring and diabetes screening in OSA patients might be beneficial to the early detection and intervention of T2D.
本研究旨在利用双向孟德尔随机化(MR)探索阻塞性睡眠呼吸暂停(OSA)与2型糖尿病(T2D)之间的因果关系。与OSA相关的遗传数据来自全基因组关联研究(GWAS)中的芬兰生物银行(病例数=16,761,对照数=201,194)。筛选出三个单核苷酸多态性(SNP)作为OSA的工具变量(IV)。与T2D相关的遗传数据来自一项大型GWAS荟萃分析(病例数=62,892,对照数=596,424),选择114个SNP作为T2D的IV。采用多种MR方法进行分析,并以逆方差加权(IVW)作为主要方法。使用MR-Egger等方法分析MR分析结果的敏感性,并使用F值统计评估IV。MR分析表明,OSA与T2D风险增加显著相关(比值比=2.016,95%置信区间:1.185-3.429,P<0.05)。T2D与OSA风险之间无显著关系(比值比=1.030,95%置信区间:0.980-1.082,P=0.238)。双向结果均存在异质性(OSA➝T2D,I²=1.808×10⁻²;T2D➝OSA,I²=1.729×10⁻²),且无水平多效性(OSA➝T2D,P=0.477;T2D➝OSA,P=0.349)。本研究中选择的OSA和T2D的IV是强工具变量(OSA的F统计量=20.543;T2D的F统计量=30.117)。我们的结果支持OSA是T2D的一个危险因素,但T2D对OSA的发病率无显著影响。对OSA患者进行血糖监测和糖尿病筛查可能有利于T2D的早期发现和干预。