Assessing causal relationships using genetic proxies for exposures: an introduction to Mendelian randomization

Assessing causal relationships using genetic proxies for exposures: an introduction to Mendelian... IntroductionDetermining whether associations are causal is central to much addiction research but is challenging, with many observational associations unlikely to reflect causal relationships . Randomized controlled trials (RCTs), which support stronger causal inference, are not suited to all research questions—particularly as their external validity may be limited . Randomizing long‐term behaviours or environmental exposures in humans is unethical and impractical. Many causal questions, such as the long‐term consequences of consuming potentially harmful, addictive substances, cannot be answered with RCTs.Mendelian randomization (MR) provides a tool for assessing the causal effects of behaviours on outcomes, although only when genetic variants associated with behaviours are known . While previous reviews of MR exist , here we provide an up‐to‐date general introduction targeted specifically at addiction researchers. We note that other approaches to causal inference using observational data exist (including natural experiment approaches and statistical techniques such as propensity score‐matching, time–series analysis and structural equation modelling) . We start by revisiting challenges to causal inference in traditional observational studies, explain how MR studies potentially overcome them and outline challenges and possible solutions when applying MR. Throughout, we illustrate MR's principles with two case studies: tobacco smoking as a possible cause of mental health http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Addiction Wiley

Assessing causal relationships using genetic proxies for exposures: an introduction to Mendelian randomization

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Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
© 2018 Society for the Study of Addiction
ISSN
0965-2140
eISSN
1360-0443
D.O.I.
10.1111/add.14038
Publisher site
See Article on Publisher Site

Abstract

IntroductionDetermining whether associations are causal is central to much addiction research but is challenging, with many observational associations unlikely to reflect causal relationships . Randomized controlled trials (RCTs), which support stronger causal inference, are not suited to all research questions—particularly as their external validity may be limited . Randomizing long‐term behaviours or environmental exposures in humans is unethical and impractical. Many causal questions, such as the long‐term consequences of consuming potentially harmful, addictive substances, cannot be answered with RCTs.Mendelian randomization (MR) provides a tool for assessing the causal effects of behaviours on outcomes, although only when genetic variants associated with behaviours are known . While previous reviews of MR exist , here we provide an up‐to‐date general introduction targeted specifically at addiction researchers. We note that other approaches to causal inference using observational data exist (including natural experiment approaches and statistical techniques such as propensity score‐matching, time–series analysis and structural equation modelling) . We start by revisiting challenges to causal inference in traditional observational studies, explain how MR studies potentially overcome them and outline challenges and possible solutions when applying MR. Throughout, we illustrate MR's principles with two case studies: tobacco smoking as a possible cause of mental health

Journal

AddictionWiley

Published: Jan 1, 2018

Keywords: ; ; ; ; ;

References

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