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Estimation of time-varying causal effects with multivariable Mendelian randomization: some cautionary notes
Haodong Tian1, Stephen Burgess1,2
1MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK.
International Journal of Epidemiology
|January 20, 2023
Summary
Multivariable Mendelian randomization (MVMR) can provide misleading results for time-varying exposures. Causal effect estimates vary significantly depending on the time periods analyzed, urging caution in interpretation.
Area of Science:
- Epidemiology
- Statistical Genetics
Background:
- Life course exposures can have time-varying effects.
- Multivariable Mendelian randomization (MVMR) uses genetic variants to assess related risk factors.
- MVMR has been recently applied to estimate exposure effects during specific time periods.
Purpose of the Study:
- To investigate the behavior of MVMR estimates in time-varying causal scenarios through simulation.
- To conduct an applied analysis on body mass index and systolic blood pressure, examining time-period variations in MVMR estimates.
Main Methods:
- Simulation study of MVMR under different time-varying causal scenarios.
- Applied analysis using MVMR to assess body mass index's effect on systolic blood pressure across different time periods.
Main Results:
- MVMR estimates closely matched true values in simulations with correctly specified models.
- In realistic scenarios, MVMR estimates were misleading, showing incorrect directions of causal effects (e.g., negative for a positive true effect).
- Applied analysis revealed highly variable MVMR estimates depending on the time periods considered.
Conclusions:
- MVMR's poor performance in studying time-varying causal effects stems from model misspecification and violated assumptions.
- Caution is advised regarding quantitative and qualitative interpretations of MVMR analyses for time-varying exposures.
Keywords:
Instrumental variablescausal inferenceexclusion restrictionlife-course epidemiologymisspecificationMore Related Videos
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