Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala.
Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
Curr Opin Lipidol. 2021 Feb 1;32(1):1-8. doi: 10.1097/MOL.0000000000000721.
The current review describes the fundamentals of the Mendelian randomization framework and its current application for causal inference in human nutrition and metabolism.
In the Mendelian randomization framework, genetic variants that are strongly associated with the potential risk factor are used as instrumental variables to determine whether the risk factor is a cause of the disease. Mendelian randomization studies are less susceptible to confounding and reverse causality compared with traditional observational studies. The Mendelian randomization study design has been increasingly used in recent years to appraise the causal associations of various nutritional factors, such as milk and alcohol intake, circulating levels of micronutrients and metabolites, and obesity with risk of different health outcomes. Mendelian randomization studies have confirmed some but challenged other nutrition-disease associations recognized by traditional observational studies. Yet, the causal role of many nutritional factors and intermediate metabolic changes for health and disease remains unresolved.
Mendelian randomization can be used as a tool to improve causal inference in observational studies assessing the role of nutritional factors and metabolites in health and disease. There is a need for more large-scale genome-wide association studies to identify more genetic variants for nutritional factors that can be utilized for Mendelian randomization analyses.
本文描述了孟德尔随机化框架的基本原理及其在人类营养与代谢领域因果推断中的当前应用。
在孟德尔随机化框架中,与潜在风险因素密切相关的遗传变异可被用作工具变量,以确定该风险因素是否为疾病的病因。与传统观察性研究相比,孟德尔随机化研究较少受到混杂因素和反向因果关系的影响。近年来,孟德尔随机化研究设计已越来越多地用于评估各种营养因素(如牛奶和酒精摄入、微量营养素和代谢物的循环水平以及肥胖与不同健康结局的风险)的因果关联。孟德尔随机化研究证实了一些传统观察性研究所识别的营养-疾病关联,但也对其他一些关联提出了挑战。然而,许多营养因素和中间代谢变化对健康和疾病的因果作用仍未得到解决。
孟德尔随机化可作为一种工具,用于改善评估营养因素和代谢物在健康和疾病中的作用的观察性研究中的因果推断。需要开展更多的全基因组关联研究,以识别更多可用于孟德尔随机化分析的营养因素的遗传变异。