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Nature as a Trialist?

Deconstructing the Analogy Between Mendelian Randomization and Randomized Trials

Swanson, Sonja A.a,b; Tiemeier, Henninga,c,d; Ikram, M. Arfana; Hernán, Miguel A.b,e,f

doi: 10.1097/EDE.0000000000000699

Mendelian randomization (MR) studies are often described as naturally occurring randomized trials in which genetic factors are randomly assigned by nature. Conceptualizing MR studies as randomized trials has profound implications for their design, conduct, reporting, and interpretation. For example, analytic practices that are discouraged in randomized trials should also be discouraged in MR studies. Here, we deconstruct the oft-made analogy between MR and randomized trials. We describe four key threats to the analogy between MR studies and randomized trials: (1) exchangeability is not guaranteed; (2) time zero (and therefore the time for setting eligibility criteria) is unclear; (3) the treatment assignment is often measured with error; and (4) adherence is poorly defined. By precisely defining the causal effects being estimated, we underscore that MR estimates are often vaguely analogous to per-protocol effects in randomized trials, and that current MR methods for estimating analogues of per-protocol effects could be biased in practice. We conclude that the analogy between randomized trials and MR studies provides further perspective on both the strengths and the limitations of MR studies as currently implemented, as well as future directions for MR methodology development and application. In particular, the analogy highlights potential future directions for some MR studies to produce more interpretable and informative numerical estimates.

From the aDepartment of Epidemiology, Erasmus MC, Rotterdam, The Netherlands; bDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; cDepartment of Child and Adult Psychiatry, Erasmus MC, Rotterdam, The Netherlands; dDepartment of Psychiatry, Erasmus MC, Rotterdam, The Netherlands; eDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts; and fHarvard-MIT Division of Health Sciences and Technology, Harvard University and Massachusetts Institute of Technology, Boston, Massachusetts.

Submitted 25 September 2016; accepted 25 May 2017.

Supported by the National Institutes of Health (R01 AI102634) and by a DynaHEALTH Grant (European Union H2020-PHC-2014; 633595). S.A.S. is supported by a NWO/ZonMW Veni Grant (91617066).

The authors report no conflicts of interest.

Correspondence: Sonja A. Swanson, Department of Epidemiology, Erasmus MC, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands. E-mail:

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