Background: 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.
Content: 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.
Summary: 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.