Non-linear Mendelian randomization: detection of biases using negative controls with a focus on BMI, Vitamin D and LDL cholesterol.

IF 7.7 1区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH European Journal of Epidemiology Pub Date : 2024-05-01 Epub Date: 2024-05-25 DOI:10.1007/s10654-024-01113-9
Fergus W Hamilton, David A Hughes, Wes Spiller, Kate Tilling, George Davey Smith
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Abstract

Mendelian randomisation (MR) is an established technique in epidemiological investigation, using the principle of random allocation of genetic variants at conception to estimate the causal linear effect of an exposure on an outcome. Extensions to this technique include non-linear approaches that allow for differential effects of the exposure on the outcome depending on the level of the exposure. A widely used non-linear method is the residual approach, which estimates the causal effect within different strata of the non-genetically predicted exposure (i.e. the "residual" exposure). These "local" causal estimates are then used to make inferences about non-linear effects. Recent work has identified that this method can lead to estimates that are seriously biased, and a new method-the doubly-ranked method-has been introduced as a possibly more robust approach. In this paper, we perform negative control outcome analyses in the MR context. These are analyses with outcomes onto which the exposure should have no predicted causal effect. Using both methods we find clearly biased estimates in certain situations. We additionally examined a situation for which there are robust randomised controlled trial estimates of effects-that of low-density lipoprotein cholesterol (LDL-C) reduction onto myocardial infarction, where randomised trials have provided strong evidence of the shape of the relationship. The doubly-ranked method did not identify the same shape as the trial data, and for LDL-C and other lipids they generated some highly implausible findings. Therefore, we suggest there should be extensive simulation and empirical methodological examination of performance of both methods for NLMR under different conditions before further use of these methods. In the interim, use of NLMR methods needs justification, and a number of sanity checks (such as analysis of negative and positive control outcomes, sensitivity analyses excluding removal of strata at the extremes of the distribution, examination of biological plausibility and triangulation of results) should be performed.

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非线性孟德尔随机化:利用负对照检测偏差,重点关注体重指数、维生素 D 和低密度脂蛋白胆固醇。
孟德尔随机化(Mendelian randomisation,MR)是流行病学调查中的一项成熟技术,它利用受孕时随机分配遗传变异的原理来估计暴露对结果的因果线性效应。该技术的扩展包括非线性方法,允许暴露对结果的不同影响取决于暴露水平。一种广泛使用的非线性方法是残差法,它可以估计非遗传预测暴露(即 "残差 "暴露)的不同层内的因果效应。然后利用这些 "局部 "因果效应估计值来推断非线性效应。最近的研究发现,这种方法可能会导致估计值严重偏差,因此引入了一种新方法--双重排序法--作为一种可能更稳健的方法。在本文中,我们在 MR 背景下进行了负控制结果分析。这些分析涉及的结果是,暴露对其不产生预测的因果效应。使用这两种方法,我们发现在某些情况下,估计值存在明显偏差。此外,我们还研究了一种有可靠随机对照试验估计效应的情况,即降低低密度脂蛋白胆固醇(LDL-C)对心肌梗死的影响,随机对照试验为这种关系的形状提供了有力的证据。双重排序法并不能确定与试验数据相同的形状,对于低密度脂蛋白胆固醇和其他血脂,它们产生了一些非常难以置信的结果。因此,我们建议在进一步使用这两种方法之前,应对这两种方法在不同条件下的 NLMR 性能进行广泛的模拟和实证方法学检查。在此期间,使用 NLMR 方法需要有正当理由,并应进行一系列合理性检查(如分析阴性和阳性对照结果、敏感性分析(不包括去除分布极端的分层)、生物合理性检查和结果三角测量)。
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来源期刊
European Journal of Epidemiology
European Journal of Epidemiology 医学-公共卫生、环境卫生与职业卫生
CiteScore
21.40
自引率
1.50%
发文量
109
审稿时长
6-12 weeks
期刊介绍: The European Journal of Epidemiology, established in 1985, is a peer-reviewed publication that provides a platform for discussions on epidemiology in its broadest sense. It covers various aspects of epidemiologic research and statistical methods. The journal facilitates communication between researchers, educators, and practitioners in epidemiology, including those in clinical and community medicine. Contributions from diverse fields such as public health, preventive medicine, clinical medicine, health economics, and computational biology and data science, in relation to health and disease, are encouraged. While accepting submissions from all over the world, the journal particularly emphasizes European topics relevant to epidemiology. The published articles consist of empirical research findings, developments in methodology, and opinion pieces.
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