EPAS1和2型糖尿病：一项双样本孟德尔随机化研究

EPAS1 and Type 2 Diabetes Mellitus: A Two-Sample Mendelian Randomization Study

摘要: 目的：采用两样本孟德尔随机化分析法，探讨EPAS1与2型糖尿病(T2DM)的因果关联，以期为T2DM的防治提供新思路。方法：利用全基因组关联研究(GWAS)的数据，将EPAS1作为暴露因素，以T2DM为结局变量，进行孟德尔随机化分析。本研究以逆方差加权(IVW)法作为主要的MR分析手段，将单核苷酸多态性(SNP)的因果效应估计进行汇总合并，同时结合MR-Egger回归、加权中位数、加权模式作为补充方法分析二者之间的潜在因果关联。利用Cochran’s Q检验、MR-Egger回归截距、留一法进行敏感性分析。结果：IVW分析结果显示，EPAS1与T2DM之间存在显著的正向因果关联(OR: 1.055, 95% CI: 1.044~1.067, P = 6.96e−22)。敏感性分析显示不存在多效性，但异质性显著，结果相对可靠。结论：EPAS1与T2DM之间存在显著的正向因果关联，但需进行进一步验证。

Abstract: Aim: To explore the cause-and-effect relationship between EPAS1 and Type 2 Diabetes Mellitus (T2DM), a two-sample Mendelian randomization analysis was used to provide new ideas for the prevention and treatment of T2DM. Method: Using data from the Genome-Wide Association Study (GWAS), mendelian randomization analysis was performed with EPAS1 as an exposure factor and T2DM as an outcome variable. In this paper, Inverse Variance Weighting (IVW) was used as the primary analysis method to pool and combine the causal effect estimates of Single Nucleotide Polymorphisms (SNPs), and MR-Egger regression, weighted median, and weighted model were used as supplementary methods to analyze the potential causal association between the two. Cochran’s Q test, MR-Egger regression intercept, and leave-one-out method were used for sensitivity analysis. Results: IVW analysis showed that EPAS1 and T2DM had a significant positive causal relationship (OR: 1.055, 95% CI: 1.044~1.067, P = 6.96e–22). Sensitivity analysis showed no pleiotropy but significant heterogeneity, and the results were relatively reliable. Conclusion: EPAS1 and T2DM have a significant positive causal relationship, but further verification is needed.