Karageorgiou Vasilios, Tyrrell Jess, Mckinley Trevelyan J, Bowden Jack
Exeter Diabetes Group (ExCEED), College of Medicine and Health, University of Exeter, Exeter, UK.
Genet Epidemiol. 2023 Mar;47(2):135-151. doi: 10.1002/gepi.22512. Epub 2023 Jan 22.
Mendelian randomization (MR) leverages genetic data as an instrumental variable to provide estimates for the causal effect of an exposure X on a health outcome Y that is robust to confounding. Unfortunately, horizontal pleiotropy-the direct association of a genetic variant with multiple phenotypes-is highly prevalent and can easily render a genetic variant an invalid instrument.
Building on existing work, we propose a simple method for leveraging sex-specific genetic associations to perform weak and pleiotropy-robust MR analysis. This is achieved by constructing an MR estimator in which pleiotropy is perfectly removed by cancellation, while placing it within the powerful machinery of the robust adjusted profile score (MR-RAPS) method. Pleiotropy cancellation has the attractive property that it removes heterogeneity and therefore justifies a statistically efficient fixed effects model. We extend the method from the typical two-sample summary-data MR setting to the one-sample setting by adapting the technique of Collider-Correction. Simulation studies and applied examples are used to assess how the sex-stratified MR-RAPS estimator performs against other common approaches.
The sex-stratified MR-RAPS method is shown to be robust to pleiotropy even in cases where all genetic variants violated the standard Instrument Strength Independent of Direct Effect assumption. In some cases where the strength of the pleiotropic effect additionally varied by sex (and so perfect cancellation was not achieved), over-dispersed MR-RAPS implementations can still consistently estimate the true causal effect. In applied analyses, we investigate the causal effect of waist-hip ratio (WHR), an important marker of central obesity, on a range of downstream traits. While the conventional approaches suggested paradoxical links between WHR and height and body mass index, the sex-stratified approach obtained a more realistic null effect. Nonzero effects were also detected for systolic and diastolic blood pressure as well as high-density and low-density lipoprotein cholesterol.
We provide a simple but attractive method for weak and pleiotropy robust causal estimation of sexually dimorphic traits on downstream outcomes, by combining several existing approaches in a novel fashion.
孟德尔随机化（MR）利用遗传数据作为工具变量，为暴露因素X对健康结局Y的因果效应提供稳健的混杂因素估计。不幸的是，水平多效性——即一个基因变异与多种表型的直接关联——非常普遍，很容易使基因变异成为无效工具。
基于现有研究，我们提出了一种利用性别特异性遗传关联进行弱且多效性稳健的MR分析的简单方法。这是通过构建一个MR估计量来实现的，其中多效性通过抵消被完全消除，同时将其置于稳健调整轮廓评分（MR-RAPS）方法的强大框架内。多效性抵消具有消除异质性的吸引人的特性，因此证明了统计效率高的固定效应模型的合理性。我们通过采用对撞机校正技术，将该方法从典型的两样本汇总数据MR设置扩展到单样本设置。模拟研究和应用实例用于评估性别分层的MR-RAPS估计量与其他常用方法相比的性能。
即使在所有基因变异都违反标准的独立于直接效应的工具强度假设的情况下，性别分层的MR-RAPS方法也被证明对多效性具有稳健性。在某些多效性效应强度因性别而异（因此未实现完全抵消）的情况下，过度分散的MR-RAPS实现仍然可以一致地估计真实的因果效应。在应用分析中，我们研究了中心性肥胖的重要标志物腰臀比（WHR）对一系列下游性状的因果效应。虽然传统方法表明WHR与身高和体重指数之间存在矛盾的联系，但性别分层方法获得了更现实的零效应。还检测到收缩压和舒张压以及高密度和低密度脂蛋白胆固醇的非零效应。
我们通过以新颖的方式结合几种现有方法，为对下游结局的性别二态性状进行弱且多效性稳健的因果估计提供了一种简单但有吸引力的方法。
