ArticleGenetic epidemiology2021
Mendelian randomisation with coarsened exposures.
Article in Genetic epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
17 citing papers in PubMed.
- Protein mediators of chronic kidney disease in Type 2 diabetes: A mendelian randomization study.PLoS medicine · 2026Article
- Causal Associations Between Pre-Pregnancy Diabetes Mellitus and Pre-Eclampsia Risk: Insights from a Mendelian Randomization Study.Healthcare (Basel, Switzerland) · 2025Article
- Article
- Depicting deterministic variables within directed acyclic graphs: an aid for identifying and interpreting causal effects involving derived variables and compositional data.American journal of epidemiology · 2025Article
- Exploring the Link Between Genetic Predictors of Cardiovascular Disease and Psoriasis.JAMA cardiology · 2024Article
- Exercise may delay cognitive decline in Chinese older adults: a causal inference for ordered multi-categorical exposures with a Mendelian randomization approach.Scientific reports · 2024Article
- Mendelian randomisation and mediation analysis of self-reported walking pace and coronary artery disease.Scientific reports · 2024Article
- Investigating the causal interplay between sleep traits and risk of acute myocardial infarction: a Mendelian randomization study.BMC medicine · 2023Article
- Relaxing parametric assumptions for non-linear Mendelian randomization using a doubly-ranked stratification method.PLoS genetics · 2023Article
- Assessing the causal relationships between gout and hypertension: a bidirectional Mendelian randomisation study with coarsened exposures.Arthritis research & therapy · 2022Article
- Phenotypic Causal Inference Using Genome-Wide Association Study Data: Mendelian Randomization and Beyond.Annual review of biomedical data science · 2022Review
- A phenome-wide bidirectional Mendelian randomization analysis of atrial fibrillation.International journal of epidemiology · 2022Article
- Estimation of causal effects of a time-varying exposure at multiple time points through multivariable mendelian randomization.PLoS genetics · 2022Article
- Interpreting Mendelian-randomization estimates of the effects of categorical exposures such as disease status and educational attainment.International journal of epidemiology · 2022Article
- Is genetic liability to ADHD and ASD causally linked to educational attainment?International journal of epidemiology · 2022Article
- The Risk of Atrial Fibrillation Increases with Earlier Onset of Obesity: A Mendelian Randomization Study.International journal of medical sciences · 2022Article
- Mendelian randomisation with coarsened exposures.Genetic epidemiology · 2021Article
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
A key assumption in Mendelian randomisation is that the relationship between the genetic instruments and the outcome is fully mediated by the exposure, known as the exclusion restriction assumption. However, in epidemiological studies, the exposure is often a coarsened approximation to some latent continuous trait. For example, latent liability to schizophrenia can be thought of as underlying the binary diagnosis measure. Genetically driven variation in the outcome can exist within categories of the exposure measurement, thus violating this assumption. We propose a framework to clarify this violation, deriving a simple expression for the resulting bias and showing that it may inflate or deflate effect estimates but will not reverse their sign. We then characterise a set of assumptions and a straight-forward method for estimating the effect of SD increases in the latent exposure. Our method relies on a sensitivity parameter which can be interpreted as the genetic variance of the latent exposure. We show that this method can be applied in both the one-sample and two-sample settings. We conclude by demonstrating our method in an applied example and reanalysing two papers which are likely to suffer from this type of bias, allowing meaningful interpretation of their effect sizes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.