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Interpretation and Potential Biases of Mendelian Randomization Estimates With Time-Varying Exposures
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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In the citing paper
“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.”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [77]
In the citing paper
“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 .”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [31]
In the citing paper
“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 .”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [31]
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Metadata
- Authors
- Labrecque, J. A., & Swanson, S. A.
- Affiliations
- Erasmus MC (NL)
- Corresponding author
- Labrecque, Jeremy A
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- 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
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- 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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