背景:目前大量观察性研究表明估算肾小球滤过率(eGFR)下降与心血管疾病风险增加有关。但是对于估算肾小球滤过率与心血管疾病之间的潜在关系还没有统一的结论。方法:我们首先从一项全基因组关联研究(GWAS)中确定了估算肾小球滤过率的遗传工具。我们利用MR分析对不同心血管结局事件进行了双样本的分析,并采用逆方差加权、加权中位数、MR-PRESSO、MR-egger和留一法进行分析。结果:研究结果显示,经最严格的Bonferroni矫正后(Padjust = 0.01),肾小球滤过率估计值降低与心力衰竭之间的潜在因果关系有显著证据,IVW结果提示有显著统计学意义(OR = 1.009, 95%CI = 1.003~1.015, P = 0.003, P adjust)。在估算肾小球滤过率与冠状动脉综合征(CAD) (OR = 1.006, 95%CI = 0.998~1.013, P = 0.14)、估算肾小球滤过率与心血管疾病(CVD) (OR = 1.003, 95%CI = 0.995~1.011, P = 0.45)、估算肾小球滤过率与卒中(OR = 1.000, 95%CI = 0.9998~1.0001, P = 0.95)以及估算肾小球滤过率与心房颤动(AF) (OR = 1.004, 95%CI = 0.9952~1.0126, P = 0.38)的IVW试验结果均未提示eGFR与心血管结局事件之间存在潜在的因果关系。结论:我们进行的多个大型MR分析发现,估算肾小球滤过率与心衰发生的风险存在显著的因果关系,但是我们未发现估算肾小球滤过率对于其他心血管结局事件有显著因果关联。Background: A large number of observational studies have shown that a decrease in estimated glomerular filtration rate (eGFR) is associated with an increased risk of cardiovascular disease. However, there is no consensus on the potential relationship between eGFR and cardiovascular diseases. Methods: We first identified genetic instruments for eGFR from a genome-wide association study (GWAS). We conducted two-sample MR analysis for different cardiovascular outcomes using inverse-variance weighted (IVW), weighted median, MR-PRESSO, MR-Egger, and leave-one-out methods. Results: After the m
