'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?
'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?
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DOI：
10.1093/ije/dyg070
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发表时间：
2003-02-01
影响因子：
7.7
通讯作者：
Ebrahim, S
中科院分区：
文献类型：
--
作者：
Smith, GD;Ebrahim, S
尽管我们尽最大努力改进研究的设计和分析，但在观察性流行病学中发现的可变暴露与疾病之间的关联有时会混淆，从而产生误导。孟德尔随机化在配子形成和受孕过程中发生的基因从父母到后代的随机分配为评估某些环境暴露的因果性质提供了一种方法。疾病与多态性之间的关联（其模拟了拟定暴露与疾病之间的生物学联系）通常不容易受到可能扭曲传统观察性研究解释的反向因果关系或混杂因素的影响。几个例子，多态性的表型效应有据可查，孟德尔随机化的解释力提供了令人鼓舞的证据，并进行了描述。该方法的局限性包括与研究中的多态性连锁不平衡的多态性的混杂，多态性可能具有与疾病相关的几种表型效应，缺乏合适的多态性用于研究感兴趣的可改变的暴露，以及渠道化-发育过程中遗传变异影响的缓冲。尽管如此，孟德尔随机化为检验因果关系提供了新的机会，并表明对人类基因组项目的投资如何有助于理解和预防可改变的接触对人类健康的不利影响。
Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization-the random assortment of genes from parents to offspring that occurs during gamete formation and conception-provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization-the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.