Non-linear Mendelian randomization: evaluation of effect modification in the residual and doubly-ranked methods with simulated and empirical examples.

IF 5.9 1区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
European Journal of Epidemiology Pub Date : 2025-06-01 Epub Date: 2025-06-02 DOI:10.1007/s10654-025-01208-x
Fergus W Hamilton, David A Hughes, Tianyuan Lu, Zoltán Kutalik, Apostolos Gkatzionis, Kate Tilling, Fernando P Hartwig, George Davey Smith
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引用次数: 0

Abstract

Non-linear Mendelian randomisation (NLMR) is a relatively recently developed approach to estimate the causal effect of an exposure on an outcome where this is expected to be non-linear. Two commonly used techniques-based on stratifying the exposure and performing Mendelian randomisation (MR) within each strata-are the residual and doubly-ranked methods. The residual method is known to be biased in the presence of genetic effect heterogeneity-where the effect of the genotype on the exposure varies between individuals. The doubly-ranked method is considered to be less sensitive to genetic effect heterogeneity. In this paper, we simulate genetic effect heterogeneity and confounding of the exposure and outcome and identify that both methods are susceptible to likely unpredictable bias in this setting. Using UK Biobank, we identify empirical evidence of genetic effect heterogeneity and show via simulated outcomes that this leads to biased MR estimates within strata, whilst conventional MR across the full sample remains unbiased. We suggest that these biases are highly likely to be present in other empirical NLMR analyses using these methods and urge caution in current usage. Simulated outcome analyses may represent a useful test to identify if genetic effect heterogeneity is likely to bias NLMR estimates in future analyses.

非线性孟德尔随机化:用模拟和经验实例评价残差法和双秩法的效果修正。
非线性孟德尔随机化(NLMR)是一种相对较新的方法,用于估计暴露对预期结果的因果效应,其中该结果是非线性的。两种常用的技术是残差法和双秩法,这两种技术是基于分层暴露和在每一层中执行孟德尔随机化(MR)。已知残差法在存在遗传效应异质性时是有偏差的——基因型对暴露的影响在个体之间是不同的。双排序法被认为对遗传效应异质性不太敏感。在本文中,我们模拟了遗传效应的异质性和暴露和结果的混淆,并确定这两种方法在这种情况下都容易受到不可预测的偏差的影响。使用UK Biobank,我们确定了遗传效应异质性的经验证据,并通过模拟结果显示,这导致地层内的MR估计有偏差,而整个样本的常规MR保持无偏倚。我们认为,这些偏差极有可能出现在使用这些方法的其他经验NLMR分析中,并敦促当前使用谨慎。模拟结果分析可能是一个有用的测试,以确定遗传效应异质性是否可能在未来的分析中偏差NLMR估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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