Abstract

Abstract Observational epidemiological studies suffer from many potential biases, from confounding and from reverse causation, and this limits their ability to robustly identify causal associations. Several high‐profile situations exist in which randomized controlled trials of precisely the same intervention that has been examined in observational studies have produced markedly different findings. In other observational sciences, the use of instrumental variable (IV) approaches has been one approach to strengthening causal inferences in non‐experimental situations. The use of germline genetic variants that proxy for environmentally modifiable exposures as instruments for these exposures is one form of IV analysis that can be implemented within observational epidemiological studies. The method has been referred to as ‘Mendelian randomization’, and can be considered as analogous to randomized controlled trials. This paper outlines Mendelian randomization, draws parallels with IV methods, provides examples of implementation of the approach and discusses limitations of the approach and some methods for dealing with these. Copyright © 2007 John Wiley & Sons, Ltd.

Keywords

Mendelian randomizationObservational studyCausal inferenceConfoundingInstrumental variableCausationRandomized controlled trialCausality (physics)EpidemiologyProxy (statistics)MedicineComputer scienceEconometricsBiologyGeneticsMachine learningMathematicsPathologyEpistemology

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Publication Info

Year
2007
Type
article
Volume
27
Issue
8
Pages
1133-1163
Citations
4718
Access
Closed

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Debbie A. Lawlor, Roger Harbord, Jonathan A C Sterne et al. (2007). Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology. Statistics in Medicine , 27 (8) , 1133-1163. https://doi.org/10.1002/sim.3034

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DOI
10.1002/sim.3034