Department of Epidemiology and Health Statistics, School of Public Health, Cheeloo College of Medicine, 12589Shandong University, Jinan, People's Republic of China.
Institute for Medical Dataology, Cheeloo College of Medicine, 12589Shandong University, Jinan, People's Republic of China.
Stat Methods Med Res. 2022 Jul;31(7):1263-1279. doi: 10.1177/09622802221084599. Epub 2022 Mar 29.
Causal mediation analysis investigates the mechanism linking exposure and outcome. Dealing with the impact of unobserved confounders among exposure, mediator and outcome is an issue of great concern. Moreover, when multiple mediators exist, this causal pathway intertwines with other causal pathways, rendering it difficult to estimate the path-specific effects. In this study, we propose a method (PSE-MR) to identify and estimate path-specific effects of an exposure (e.g. education) on an outcome (e.g. osteoarthritis risk) through multiple causally ordered and non-ordered mediators (e.g. body mass index and pack-years of smoking) using summarized genetic data, when the sequential ignorability assumption is violated. Specifically, PSE-MR requires a specific rank condition in which the number of instrumental variables is larger than the number of mediators. Furthermore, we illustrate the utility of PSE-MR by providing guidance for practitioners and exploring the mediation effects of body mass index and pack-years of smoking in the causal pathways from education to osteoarthritis risk. Additionally, the results of simulation reveal that the causal estimates of path-specific effects are almost unbiased with good coverage and Type I error properties. Also, we summarize the least number of instrumental variables for the specific number of mediators to achieve 80% power.
因果中介分析研究了暴露和结果之间的联系机制。处理暴露、中介和结果之间未观察到的混杂因素的影响是一个非常关注的问题。此外，当存在多个中介时，这种因果途径与其他因果途径交织在一起，使得估计特定路径的效应变得困难。在这项研究中，我们提出了一种方法（PSE-MR），该方法使用汇总的遗传数据，在违反顺序可忽略性假设的情况下，通过多个因果有序和非有序的中介（例如，体重指数和吸烟包年数）来识别和估计暴露（例如，教育）对结果（例如，骨关节炎风险）的特定路径效应，当顺序可忽略性假设被违反时。具体来说，PSE-MR 需要一个特定的秩条件，其中工具变量的数量大于中介的数量。此外，我们通过为从业者提供指导并探索体重指数和吸烟包年数在从教育到骨关节炎风险的因果途径中的中介效应，说明了 PSE-MR 的实用性。此外，模拟结果表明，特定路径效应的因果估计几乎没有偏差，具有良好的覆盖率和Ⅰ型错误属性。我们还总结了实现特定数量中介的 80%功效所需的最少工具变量数量。
