Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
Population Health Sciences, Bristol Medical School, Faculty of Health Sciences, University of Bristol, Bristol, UK.
Obesity (Silver Spring). 2023 Dec;31(12):2887-2890. doi: 10.1002/oby.23927. Epub 2023 Oct 16.
Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J-shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization.
孟德尔随机化（MR）是一种广泛使用的方法，它利用种系遗传变异的独特性质来加强暴露与结果之间关系的因果推断。非线性 MR 允许估计这些关系的形状。在之前的一篇论文中，作者应用线性和非线性 MR 来估计 BMI 对英国生物库中死亡率的影响，为 BMI 与死亡率之间的 J 形关联提供了证据。然而，现在很明显，广泛使用的非线性 MR 方法存在问题，这引起了人们对几种探索关系的形状的结论可能存在错误的关注。在这里，作者使用负对照设计来探讨这些非线性 MR 方法的效用和可能存在的偏差。尽管有充分的证据表明较高的 BMI 会增加死亡风险，但不同 BMI 水平下这种关联的模式需要进一步描述。
