ArticleInternational journal of epidemiology2019
Detecting and correcting for bias in Mendelian randomization analyses using Gene-by-Environment interactions.
Article in International journal of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
60 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Unraveling the connection and pathogenesis of systemic lupus erythematosus and thyroid cancer: integrative meta-analysis, Mendelian randomization, and transcriptomic insights.Clinical rheumatology · 2026Pooled it
- No association between interleukin-18 levels and risk of cardiovascular disease: A Mendelian randomization study.Hereditas · 2020Pooled it
- Can increasing years of schooling reduce type 2 diabetes (T2D)?: Evidence from a Mendelian randomization of T2D and 10 of its risk factors.Scientific reports · 2020Trial
- Context-Stratified Mendelian Randomization: Exploiting Regional Exposure Variation to Explore Causal Effect Heterogeneity and Nonlinearity.Statistics in medicine · 2026Article
- Integrating genetic data with biological insight: A practical guide to cis-Mendelian randomization.American journal of human genetics · 2026Review
- Challenges and future directions for Mendelian randomization.Nature genetics · 2026Review
- Utilizing offspring genotype-by-proxy Mendelian randomization to investigate the causal effect of offspring perinatal traits on maternal health.International journal of epidemiology · 2026Article
- Mendelian Randomization With Longitudinal Exposure Data: Simulation Study and Real Data Application.Statistics in medicine · 2026Article
- Investigating the Relationship Between Maternal Smoking During Pregnancy and Offspring Handedness: Extending the Proxy Gene-by-Environment Mendelian Randomization Study Design to Include Polygenic Risk Scores.Behavior genetics · 2025Article
- Non-linear Mendelian randomization: evaluation of effect modification in the residual and doubly-ranked methods with simulated and empirical examples.European journal of epidemiology · 2025Article
- Common sleep characteristics and the risk of common perinatal complications and adverse outcomes: a multi-sample, bidirectional Mendelian randomization study.BMC pregnancy and childbirth · 2025Article
- No Bidirectional Causal Relationship Between Traumatic Brain Injury and Parkinson's Disease: A Two-Sample Mendelian Randomization Study.Health science reports · 2025Article
- Latent Association Between Diets and Glioma Risk: A Mendelian Randomization Analysis.Nutrients · 2025Article
- A Review of Mendelian Randomization: Assumptions, Methods, and Application to Obesity-Related Diseases.Journal of obesity & metabolic syndrome · 2025Review
- Cohort profile update: the Korean Cancer Prevention Study-II (KCPS-II) biobank.Epidemiology and health · 2025Article
- Triangulating Instrumental Variable, confounder adjustment and difference-in-difference methods for comparative effectiveness research in observational data.Wellcome open research · 2025Article
- Mendelian Randomization Studies: Opening a New Window in the Study of Metabolic Diseases and Chronic Kidney Disease.Endocrine, metabolic & immune disorders drug targets · 2025Review
- Gene-environment interactions in human health.Nature reviews. Genetics · 2024Review
- Letter to the editor Regarding 'Causal relationship between basal metabolic rate and intervertebral disc degeneration: a Mendelian randomization study' by Liu Z, et al. (Eur Spine J. 2024 Jun 24. Doi: 10.1007/s00586-024-08367-7).European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024Article
- Exploring potential therapeutic targets for asthma: a proteome-wide Mendelian randomization analysis.Journal of translational medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundMendelian randomization (MR) has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial, as horizontal pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene-environment interactions in detecting and correcting for pleiotropic bias in MR analyses.
methodsWe introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias. If an instrument-covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary MR approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument.
resultsWe investigate the effect of adiposity, measured using body mass index (BMI), upon systolic blood pressure (SBP) using data from the UK Biobank and a single weighted allelic score informed by data from the GIANT consortium. We find MRGxE produces findings in agreement with two-sample summary MR approaches. Further, we perform simulations highlighting the utility of the approach even when the MRGxE assumptions are violated.
conclusionsBy utilizing instrument-covariate interactions in MR analyses implemented within a linear-regression framework, it is possible to identify and correct for horizontal pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction-covariate subgroups.
Indexed as
Identifiers
What OpenQuestion holds
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.