Lukas Eva, van de Weijer Margot, Bergstedt Jacob, Bezzina Connie R, Treur Jorien L
Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, The Netherlands.
Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
Heart Rhythm. 2025 Jan;22(1):203-216. doi: 10.1016/j.hrthm.2024.07.015. Epub 2024 Jul 15.
Mendelian randomization (MR) uses genetic variants associated with an exposure (eg, high blood pressure) as instrumental variables to test causal effects on an outcome (eg, atrial fibrillation [AF]). By leveraging the random assortment of genetic variants during gamete formation, MR reduces biases like confounding and reverse causation. We screened 391 papers, examining 277 that applied MR to investigate arrhythmia and, in others, cardiovascular traits, lifestyle, behavioral traits, and body composition. Our analysis focused on MR studies of arrhythmia and cardiovascular traits. Key findings highlight high systolic blood pressure, low resting heart rate, elevated cardiac troponin I levels, coronary artery disease, and heart failure as risk factors for AF, whereas AF itself increases heart failure risk. As genetic data become more accessible, MR's relevance grows. Sensitivity analyses and integrating MR with other methodologies in a triangulation framework enhance the robustness of causal inferences by navigating different biases.
孟德尔随机化(MR)使用与暴露因素(如高血压)相关的基因变异作为工具变量,来检验其对结局(如心房颤动[AF])的因果效应。通过利用配子形成过程中基因变异的随机分配,MR减少了混杂和反向因果关系等偏倚。我们筛选了391篇论文,审查了其中277篇应用MR来研究心律失常以及其他心血管特征、生活方式、行为特征和身体成分的论文。我们的分析集中在心律失常和心血管特征的MR研究上。主要发现突出了收缩压升高、静息心率降低、心肌肌钙蛋白I水平升高、冠状动脉疾病和心力衰竭作为AF的危险因素,而AF本身会增加心力衰竭风险。随着基因数据越来越容易获取,MR的相关性也在增加。敏感性分析以及在三角测量框架中将MR与其他方法相结合,通过应对不同的偏倚来增强因果推断的稳健性。