In Mendelian randomization (MR) studies, genetic variants are used as instrumental variables (IVs) to investigate causal relationships between exposures and outcomes based on observational data. However, numerous genetic studies have shown the pervasive pleiotropy of genetic variants, meaning that many, if not most, variants are associated with multiple traits, potentially violating the core assumptions of IV estimation. Uncorrelated pleiotropy occurs when genetic variants have a direct effect on the outcome that is not mediated by the exposure, while correlated pleiotropy occurs when genetic variants affect the exposure and outcome via shared heritable confounders. In this work, we propose a novel MR method, called MR-Quantile, based on weighted quantile regression (WQR) that is robust to both correlated and uncorrelated pleiotropy. We propose a procedure for selecting the optimal quantile of the ratio estimates through a likelihood-based formulation of WQR using the asymmetric Laplace distribution. Monte Carlo simulations demonstrate the empirical performance of the proposed method, especially in settings with many invalid IVs with weak pleiotropic effects. Finally, we apply our method to study the causal effect of resting heart rate on atrial fibrillation. Genetic variants associated with heart rate were identified in a genome-wide association study of 425,748 individuals from the VA Million Veteran Program, and used as instruments in a two-sample MR analysis with summary statistics from a genetic meta-analysis of 228,926 AF cases across eight studies.

翻译：在孟德尔随机化（MR）研究中，遗传变异被用作工具变量（IVs），以基于观察性数据探究暴露与结局之间的因果关系。然而，大量遗传研究表明遗传变异存在普遍的多效性，即许多（若非大多数）变异与多种性状相关，这可能导致IV估计的核心假设被违反。不相关多效性是指遗传变异对结局产生并非通过暴露介导的直接效应，而相关多效性则是指遗传变异通过共享的可遗传混杂因素影响暴露和结局。在本研究中，我们提出一种名为MR-Quantile的新型MR方法，该方法基于对相关和不相关多效性均具有稳健性的加权分位数回归（WQR）。我们提出了一种通过使用非对称拉普拉斯分布的基于似然的WQR公式来选择比率估计最优分位数的程序。蒙特卡洛模拟展示了所提方法的实证性能，尤其是在存在大量具有弱多效性效应的无效IV的设置中。最后，我们将该方法应用于研究静息心率对房颤的因果效应。从VA百万退伍军人计划的425,748名个体全基因组关联研究中识别出与心率相关的遗传变异，并将其作为工具变量应用于一项两样本MR分析，该分析使用了来自八项研究中228,926例房颤病例的遗传元分析汇总统计量。