Mendelian Randomization in the Era of Genomewide Association Studies

Abstract

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.

Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

“…As the subject moves forward, ever more ambitious analyses are being attempted. In particular, due to the proliferation of genome-wide association studies, the number of Mendelian randomization analyses using a large number of genetic variants is rapidly increasing 4 , 5 . If the variants in total explain a larger proportion of the variance in the exposure, this will lead to more precise estimates of causal effects, thus increasing the power for testing causal hypotheses 6 , 7 .…”

Body mass index and depressive symptoms: instrumental‐variables regression with genetic risk score

“…). This score was then used as an instrument for adult and adolescent BMI in predicting adult depressive symptoms, providing a stronger instrument for BMI than single genetic variants (Sleiman & Grant ).…”

SERPINE1rs1799768 polymorphism contributes to sepsis risk and mortality

“…First, this meta-analysis is based on the summaries of case-control and cohort studies, which rarely establish causal relationship, and it is encouraging to incorporate the concept of Mendelian randomization into observational association studies. 25 Second, only one polymorphism in the SERPINE1 gene was evaluated in this study, which might not be sufficient to address the complex genetic architecture of sepsis. Third, only published articles written in the English language were retrieved for inclusion and some unpublished small and/or negative articles might be missing, leading to the potential existence of publication bias.…”