Mendelian Randomization for Strengthening Causal Inference in Observational Studies

Abstract

Identification of environmentally modifiable factors causally influencing disease risk is fundamental to public-health improvement strategies. Unfortunately, observational epidemiological studies are limited in their ability to reliably identify such causal associations, reflected in the many cases in which conventional epidemiological studies have apparently identified such associations that randomized controlled trials have failed to verify. The use of genetic variants as proxy measures of exposure —an application of the Mendelian randomization principle—can contribute to strengthening causal inference. Genetic variants are not subject to bias due to reverse causation (disease processes influencing exposure, rather than vice versa) or recall bias, and if simple precautions are applied, they are not influenced by confounding or attenuation by errors. The principles of Mendelian randomization are illustrated with specific reference to studies of the effects of alcohol intake on various health-related outcomes through the utilization of genetic variants related to alcohol metabolism (in ALDH2 and ADH1B). Ways of incorporating Gene × Environment interactions into the Mendelian randomization framework are developed, and the strengths and limitations of the approach discussed.