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The results from Genome-Wide Association Studies (GWAS) on thousands of phenotypes provide an unprecedented opportunity to infer the causal effect of one phenotype (exposure) on another (outcome). Mendelian randomization (MR), an…

Methodology · Statistics 2019-04-30 Jia Zhao , Jingsi Ming , Xianghong Hu , Gang Chen , Jin Liu , Can Yang

Many diseases and traits involve a complex interplay between genes and environment, generating significant interest in studying gene-environment interaction through observational data. However, for lifestyle and environmental risk factors,…

Methodology · Statistics 2023-09-22 Malka Gorfine , Conghui Qu , Ulrike Peters , Li Hsu

Mendelian randomization (MR) has become a popular approach to study causal effects by using genetic variants as instrumental variables. We propose a new MR method, GENIUS-MAWII, which simultaneously addresses the two salient phenomena that…

Methodology · Statistics 2024-02-27 Ting Ye , Zhonghua Liu , Baoluo Sun , Eric Tchetgen Tchetgen

Mendelian randomization (MR) is a popular method in genetic epidemiology to estimate the effect of an exposure on an outcome by using genetic instruments. These instruments are often selected from a combination of prior knowledge from…

Methodology · Statistics 2019-11-12 Nan Bi , Hyunseung Kang , Jonathan Taylor

Mendelian randomization is the use of genetic variants as instrumental variables to assess whether a risk factor is a cause of a disease outcome. Increasingly, Mendelian randomization investigations are conducted on the basis of summarized…

Applications · Statistics 2015-12-15 Stephen Burgess , Jack Bowden

Mendelian randomization (MR) is a popular instrumental variable (IV) approach, in which one or several genetic markers serve as IVs that can sometimes be leveraged to recover valid inferences about a given exposure-outcome causal…

Methodology · Statistics 2021-08-10 Eric J. Tchetgen Tchetgen , BaoLuo Sun , Stefan Walter

Mendelian randomization uses genetic variants to make causal inferences about the effect of a risk factor on an outcome. With fine-mapped genetic data, there may be hundreds of genetic variants in a single gene region any of which could be…

Methodology · Statistics 2017-07-10 Stephen Burgess , Verena Zuber , Elsa Valdes-Marquez , Benjamin B Sun , Jemma C Hopewell

Mendelian randomization (MR) is widely used to uncover causal relationships in the presence of unmeasured confounders. However, most existing MR methods presuppose linear causality, risking bias when the true relationships are nonlinear,…

Methodology · Statistics 2025-08-05 Xinpei Wang , Tao Huang , Jinzhu Jia

Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appropriate genetic variants as instrumental variables.…

Methodology · Statistics 2023-04-26 Ashish Patel , Francis J. DiTraglia , Verena Zuber , Stephen Burgess

Background In a study performed on multiplex Multiple Sclerosis (MS) Sardinian families to identify disease causing plasma proteins, application of Mendelian Randomization (MR) methods encounters difficulties due to relatedness of…

Mendelian randomization (MR) has become a popular approach to study the effect of a modifiable exposure on an outcome by using genetic variants as instrumental variables. A challenge in MR is that each genetic variant explains a relatively…

Methodology · Statistics 2020-10-13 Ting Ye , Jun Shao , Hyunseung Kang

Mendelian randomization uses genetic variants to make causal inferences about a modifiable exposure. Subject to a genetic variant satisfying the instrumental variable assumptions, an association between the variant and outcome implies a…

Methodology · Statistics 2018-04-17 Stephen Burgess , Jeremy A Labrecque

Mendelian Randomization (MR) is a prominent observational epidemiological research method designed to address unobserved confounding when estimating causal effects. However, core assumptions -- particularly the independence between…

Machine Learning · Computer Science 2026-02-24 Shimeng Huang , Matthew Robinson , Francesco Locatello

Mendelian randomization (MR) considers using genetic variants as instrumental variables (IVs) to infer causal effects in observational studies. However, the validity of causal inference in MR can be compromised when the IVs are potentially…

Methodology · Statistics 2024-02-06 Ziya Xu , Sai Li

Mendelian randomization (MR) uses genetic variants as instrumental variables to make causal claims. Standard MR approaches typically report a single population-averaged estimate, limiting their ability to explore effect heterogeneity or…

Methodology · Statistics 2025-07-16 Stephen Burgess , Benjamin A R Woolf , Amy M Mason

In Mendelian randomization (MR) studies, genetic variants are used as instrumental variables (IVs) to investigate causal relationships between exposures and outcomes based on observational data. However, numerous genetic studies have shown…

Methodology · Statistics 2026-04-10 Julien St-Pierre , Archer Y. Yang , Mireille E. Schnitzer , Marc-André Legault

Many Mendelian randomization (MR) papers have been conducted only in people of European ancestry, limiting transportability of results to the global population. Expanding MR to diverse ancestry groups is essential to ensure equitable…

Mendelian randomization (MR) is an epidemiological method that can be used to strengthen causal inference regarding the relationship between a modifiable environmental exposure and a medically relevant trait and to estimate the magnitude of…

Quantitative Methods · Quantitative Biology 2023-08-30 David M Evans , George Davey Smith , Gunn-Helen Moen

Mendelian Randomization (MR) is a popular method in epidemiology and genetics that uses genetic variation as instrumental variables for causal inference. Existing MR methods usually assume most genetic variants are valid instrumental…

Applications · Statistics 2022-06-15 Daniel Iong , Qingyuan Zhao , Yang Chen

Standard Mendelian randomization analysis can produce biased results if the genetic variant defining the instrumental variable (IV) is confounded and/or has a horizontal pleiotropic effect on the outcome of interest not mediated by the…

Methodology · Statistics 2021-03-31 Zhonghua Liu , Ting Ye , Baoluo Sun , Mary Schooling , Eric Tchetgen Tchetgen