| 王莉娜,Zhang Zuofeng.孟德尔随机化法在因果推断中的应用[J].Chinese journal of Epidemiology,2017,38(4):547-552 |
| 孟德尔随机化法在因果推断中的应用 |
| Mendelian randomization approach, used for causal inferences |
| Received:December 14, 2016 |
| DOI：10.3760/cma.j.issn.0254-6450.2017.04.027 |
| KeyWord: 孟德尔随机化 工具变量 因果推断 全基因组关联研究 |
| English Key Word: Mendelian randomization Instrumental Variable Causal inferences GWAS |
| FundProject:国家自然科学基金（81673259）；江苏省自然科学基金（BK20161435） |
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| Abstract: |
| 孟德尔随机化（Mendelian Randomization，MR）研究设计，遵循“亲代等位基因随机分配给子代”的孟德尔遗传规律，如果基因型决定表型，基因型通过表型而与疾病发生关联，因此可以使用基因型作为工具变量来推断表型与疾病之间的关联。近年来，MR的研究设计随着统计学方法、大样本GWAS数据、表观遗传学以及各种“组学”技术的不断发展，在探讨复杂暴露因素与疾病结局因果关联中应用日益广泛。本文对近年来出现的MR研究设计策略、可靠性评价及局限性进行介绍。 |
| English Abstract: |
| Mendelian randomization (MR) approach is based on the Mendelian genetic law,which is called “Parental alleles that randomly assigned to the offspring”. MR refers to the use of genetic variants to develop causal inferences from observational data, if the variant genotype is associated with the phenotype and the variant genotype associated with the risk of disease of interest through the phenotype. Hence, the genotype can be used as Instrumental Variable (IV) to infer the causal relation between the phenotype and the risk of diseases. In recent years, MR approach is widely used in causal inference between the exposure factors and the risks of disease, along with the rapid development of statistical methods, big datasets of GWAS, epigenetics and the various “omics” techniques. This paper provides an overview of the MR strategies and addresses the related assumptions and implications, with reliability and limitations included. |
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