孟德尔随机化在糖尿病肾病中的研究进展

Research progress of Mendelian randomization in diabetic kidney disease

摘要:

孟德尔随机化是一种基于遗传变异作为工具变量的因果推理方法，其巧妙利用遗传变异的随机分布和时间优先性，能够有效避免传统观察性研究中的混杂偏差和反向因果问题。近年来，这一方法已成为研究领域的热点。糖尿病肾病是糖尿病引发的微血管并发症之一，也是导致终末期肾脏病的重要原因。糖尿病肾病的致病机制复杂，涉及多种因素，然而现有的认知多基于传统的观察性研究，缺乏强有力的证据来确认因果关系。该文综述了孟德尔随机化方法在糖尿病肾病的研究进展，为糖尿病肾病的治疗提供新的依据。

Abstract:

Mendelian randomization (MR), a causal inference method using genetic variants as instrumental variables, leverages the random allocation of alleles at conception to minimize confounding and reverse causation inherent in observational studies. Recently, MR has gained prominence. Diabetic kidney disease (DKD), a major microvascular complication of diabetes and leading cause of end-stage renal disease, has a complex pathogenesis involving multiple factors. Current understanding largely stems from observational studies lacking robust causal evidence. This review summarizes the application and progress of MR in DKD research, aiming to provide new insights for DKD treatment.