Cited by 140Genetic Associations and EpidemiologyAdvanced Causal Inference TechniquesStatistical Methods in Epidemiology

Interpretation and Potential Biases of Mendelian Randomization Estimates With Time-Varying Exposures

Labrecque, Jeremy A, Swanson, Sonja A·2019·American Journal of Epidemiology

Abstract

Mendelian randomization (MR) is used to answer a variety of epidemiologic questions. One stated advantage of MR is that it estimates a "lifetime effect" of exposure, though this term remains vaguely defined. Instrumental variable analysis, on which MR is based, has focused on estimating the effects of point or time-fixed exposures rather than "lifetime effects." Here we use an empirical example with data from the Rotterdam Study (Rotterdam, the Netherlands, 2009-2013) to demonstrate how confusion can arise when estimating "lifetime effects." We provide one possible definition of a lifetime effect: the average change in outcome measured at time t when the entire exposure trajectory from conception to time t is shifted by 1 unit. We show that MR only estimates this type of lifetime effect under specific conditions-for example, when the effect of the genetic variants used on exposure does not change over time. Lastly, we simulate the magnitude of bias that would result in realistic scenarios that use genetic variants with effects that change over time. We recommend that investigators in future MR studies carefully consider the effect of interest and how genetic variants whose effects change with time may impact the interpretability and validity of their results.

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Crossref · 10.1093/aje/kwy204

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  • Simulations might also help understand the plausible size and direction of bias induced by assortative mating, dynastic effects, and time varying effects, if deemed relevant.

    “Simulations might also help understand the plausible size and direction of bias induced by assortative mating,62 dynastic effects,9 63 and time varying effects,77 if deemed relevant.”
  • Provided that the causal pathway from the genetic variant to the outcome is mediated entirely via the exposure, a genetic variant is a valid instrument for assessing the causal role of the exposure, even if it is associated with another variable, assuming the other instrumental variable assumptions are satisfied.

    “Provided that the causal pathway from the genetic variant to the outcome is mediated entirely via the exposure (see Figure 4), a genetic variant is a valid instrument for assessing the causal role of the exposure (assuming the other instrumental variable assumptions are satisfied), even if it is associated with another variable 31 .”
  • A scatter plot of genetic associations with the outcome against genetic associations with the exposure reveals whether different genetic variants provide similar estimates of the causal effect or if there is considerable heterogeneity, and whether the analysis is dominated by a single genetic variant.

    “For example, in a polygenic analysis, a scatter plot of the genetic associations with the outcome against the genetic associations with the exposure reveals much about the analysis – whether different genetic variants provide similar estimates of the causal effect or if there is considerable heterogeneity, and whether the analysis is dominated by a single genetic variant or not 31 .”

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Authors
Labrecque, J. A., & Swanson, S. A.
Affiliations
Erasmus MC (NL)
Corresponding author
Labrecque, Jeremy A
Venue
American Journal of Epidemiology
Published
2018-09-15
Volume
188
Issue
1
Pages
231-238
ISSN
  • 0002-9262 (ISSN-L)
  • 1476-6256
OpenAlex
W2908849404
Cited by
139
References
27
Citations by year
2026: 12 · 2025: 15 · 2024: 22 · 2023: 24 · 2022: 22 · 2021: 15 · 2020: 18 · 2019: 11
FWCI
6.74
Type
journal article
Language
en
Open access
closed
Locations
  • American Journal of Epidemiology (publishedVersion)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
Funders
  • Veni (91617066)
  • Netherlands Organisation for Scientific Research
  • Netherlands Organisation for Health Research and Development
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Keywords
Mendelian randomization, time-varying exposure, lifetime effects, exposure trajectories, genetic variants, Rotterdam Study
MeSH terms
Data Interpretation, Statistical, Humans, Mutation, Obesity, Time Factors, Bias, Causality, Mendelian Randomization Analysis

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