Sensitivity analysis for causal mediation analysis with Mendelian randomization  

基于孟德尔随机化的中介分析的敏感性分析

作　　者：Zhiya Chen Yuxi Chen Hong Zhang 陈知涯;陈禹汐;张洪(中国科学技术大学管理学院统计与金融系,安徽合肥230026)

机构地区：[1]Department of Statistics and Finance,School of Management,University of Science and Technology of China,Hefei 230026,China

出　　处：《中国科学技术大学学报》2024年第12期22-32,49,I0004,I0008,I0009,共15页JUSTC

基　　金：This work was supported by the National Natural Science Foundation of China(12171451,72091212).

摘　　要：Mendelian randomization(MR)is widely used in causal mediation analysis to control unmeasured confounding effects,which is valid under some strong assumptions.It is thus of great interest to assess the impact of violations of these MR assumptions through sensitivity analysis.Sensitivity analyses have been conducted for simple MR-based causal aver-age effect analyses,but they are not available for MR-based mediation analysis studies,and we aim to fill this gap in this paper.We propose to use two sensitivity parameters to quantify the effect due to the deviation of the IV assumptions.With these two sensitivity parameters,we derive consistent indirect causal effect estimators and establish their asymptotic prop-ersties.Our theoretical results can be used in MR-based mediation analysis to study the impact of violations of MR as-sumptions.The finite sample performance of the proposed method is illustrated through simulation studies,sensitivity ana-lysis,and application to a real genome-wide association study.孟德尔随机化(MR)被广泛用于因果中介分析,以控制未测量的混杂因素影响,这个方法要在一些强假设下才是有效的。因此,通过敏感性分析来评估违反这些MR假设的影响是非常有意义的。敏感性分析已经用于简单的基于MR的因果平均效应分析,但没有用于基于MR的中介分析。本文旨在填补这一空白,并使用两个敏感性参数来量化MR假设偏离产生的影响。利用这两个敏感性参数,本文推导出相合的间接因果效应估计量,并建立了它们的渐近性质。本文的理论结果可用于基于MR的中介分析,以研究违反MR假设的影响。通过模拟研究、敏感性分析和对真实的全基因组关联研究的应用,本文展示了所提方法的有限样本性能。

关 键 词：Mendelian randomization mediation analysis sensitivity analysis summary data 

分 类 号：O212.1[理学—概率论与数理统计]