Mendelian randomization

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An important focus of observational epidemiology is the identification of modifiable causes of common diseases that are of public health interest. In order to have firm evidence that a recommended public health intervention will have the desired beneficial effect, the observed association between the particular risk factor and disease must mean that the risk factor is causal for the disease.

Well-known successes include the identified causal links between smoking and lung cancer and between blood pressure and stroke. However, there have also been notable failures when identified exposures were later shown by randomised controlled trials (RCTs) to be non-causal. For instance, it has now been shown that hormone replacement therapy will not prevent cardiovascular disease, as was previously implied, and may have other adverse health effects. The reason for such spurious findings in observational epidemiology is most likely to be confounding by social, behavioural or physiological factors which are difficult to control for and particularly difficult to measure accurately. Moreover, many findings cannot be replicated by RCTs for ethical reasons.

Mendelian randomization is a method that allows one to test for, or in certain cases to estimate, a causal effect from observational data in the presence of confounding. It uses common genetic polymorphisms with well-understood effects on exposure patterns (e.g. propensity to drink alcohol) or effects that mimic those produced by modifiable exposures (e.g. raised blood cholesterol). Importantly, the genotype must only affect the disease status indirectly via its effect on the exposure of interest. Because genotypes are assigned randomly when passed from parents to offspring during meiosis, the population genotype distribution should be unrelated to the usual confounders that typically plague observational epidemiology studies. In this regard, Mendelian randomization can be thought of as a “natural” RCT. The method relies on getting good estimates from genetic association studies. Misleading conclusions can also be drawn in the presence of linkage disequilibrium, genetic heterogeneity, pleiotropy or population stratification.

[edit] References:

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3. G. Davey Smith and S. Ebrahim (2003) Mendelian randomization: can genetic epidemiology contribute to understanding environmental determinants of disease? International Journal of Epidemiology 32: 1-22.

4. D.C. Thomas and D.V. Conti (2004) Commentary: The concept of Mendelian randomization. International Journal of Epidemiology 32: 21-25

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