Center for Applied Genomics, The Children's Hospital of Philadelphia Research Institute, Philadelphia, PA 19104, USA.
Clin Chem. 2010 May;56(5):723-8. doi: 10.1373/clinchem.2009.141564. Epub 2010 Mar 11.
Observational epidemiology has been instrumental in identifying modifiable causes of common diseases, and, in turn, substantially impacting public health. Spurious associations in observational epidemiologic studies are most commonly caused by confounding due to social, behavioral, or environmental factors and can therefore be difficult to control. They may also be due to reverse causation-in which the phenotypic outcome subsequently influences an environmental exposure such that it is wrongly implicated in its pathogenesis-and selection bias. Randomized controlled trials are effective in dealing with the potential sources of error; however, their use is not always leveraged, for practical or ethical reasons.
An alternative method, mendelian randomization, entails the use of genetic variants as proxies for the environmental exposures under investigation. The power of mendelian randomization lies in its ability to avoid the often substantial confounding seen in conventional observational epidemiology. Underpinning mendelian randomization is the principle of the independent assortment of alleles during meiosis, which, importantly in this context, also implies that they are independent of those behavioral and environmental factors that confound epidemiologic studies. By selecting genetic variants that influence exposure patterns or are associated with an intermediate phenotype of the disease, one can effectively re-create a randomized comparison.
In the past 4 years, genomewide association studies have yielded the first robust genetic associations with common diseases, which in turn should enable mendelian randomization to be even more informative, despite some limitations outlined in this review.
观察性流行病学在确定常见疾病的可改变病因方面发挥了重要作用，从而对公共卫生产生了重大影响。观察性流行病学研究中的虚假关联最常见于由于社会、行为或环境因素引起的混杂，因此难以控制。它们也可能是由于反向因果关系——表型结果随后影响环境暴露，使其错误地涉及发病机制——和选择偏差。随机对照试验在处理潜在的误差源方面非常有效；然而，出于实际或伦理原因，并非总是利用其优势。
一种替代方法，即孟德尔随机化，涉及使用遗传变异作为所研究环境暴露的替代物。孟德尔随机化的力量在于它能够避免常规观察性流行病学中常见的大量混杂。孟德尔随机化的基础是减数分裂过程中等位基因独立分配的原理，这在这种情况下很重要，也意味着它们与那些混杂流行病学研究的行为和环境因素无关。通过选择影响暴露模式或与疾病中间表型相关的遗传变异，人们可以有效地重新创建随机对照比较。
在过去的 4 年中，全基因组关联研究已经产生了与常见疾病的第一个可靠的遗传关联，这反过来应该使孟德尔随机化更具信息性，尽管本文综述中概述了一些局限性。
