Estimation of time-varying causal effects with multivariable Mendelian randomization: the importance of model specification (2024)

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Volume 53 Issue 4 August 2024
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Eleanor Sanderson

MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol

, Bristol,

UK

Corresponding author. Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK. E-mail: eleanor.sanderson@bristol.ac.uk

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Kate Tilling

MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol

, Bristol,

UK

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International Journal of Epidemiology, Volume 53, Issue 4, August 2024, dyae100, https://doi.org/10.1093/ije/dyae100

Published:

27 July 2024

Article history

Received:

28 July 2023

Editorial decision:

16 April 2024

Editorial decision:

16 April 2024

Accepted:

26 July 2024

Published:

27 July 2024

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    Eleanor Sanderson, Kate Tilling, Estimation of time-varying causal effects with multivariable Mendelian randomization: the importance of model specification, International Journal of Epidemiology, Volume 53, Issue 4, August 2024, dyae100, https://doi.org/10.1093/ije/dyae100

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In their recent paper, Tian and Burgess highlight the importance of model specification when estimating effects of the same exposure at different time points with multivariable Mendelian randomization (MVMR).1 In this context, MVMR estimates the effect of a single exposure at multiple time points, with the effect estimated at each time point conditional on the exposure at the other time points included in the model.2 Tian and Burgess compare these estimates with the direct effect of each exposure time point conditional on all other possible exposure time points. They give simulation results (their Figure3) that they claim show that any misspecification of the MVMR model will give misleading estimates of the causal effect. However, their simulation design exaggerates the likely difference in real-life applications due to the parameters used in simulating the genetic variant—exposure association over time.

(Univariable) MR for an exposure that varies over time will estimate the effect of the exposure over all time points that are associated with the genetic variants used as instruments. If the genetic variants have constant effect on the exposure over time, then the interpretation of the MR effect would be the effect of a unit increase in the exposure at all time points.3 Otherwise, this interpretation needs to be adapted to allow for the exposure at other time points to change by more or less than a unit in response to the genetic variation that caused a unit change in the exposure at the time point measured. This has been described elsewhere as a unit change in the genetic liability to the exposure at the time point of interest.4

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