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Mendelian randomization is a widely-used method to estimate the unconfounded effect of an exposure on an outcome by using genetic variants as instrumental variables. Mendelian randomization analyses which use variants from a single genetic…

Methodology · Statistics 2024-02-20 Ashish Patel , Dipender Gill , Paul J. Newcombe , Stephen Burgess

Mendelian randomization is the use of genetic variants to assess the existence of a causal relationship between a risk factor and an outcome of interest. Here, we focus on two-sample summary-data Mendelian randomization analyses with many…

Quantitative Methods · Quantitative Biology 2022-09-16 Apostolos Gkatzionis , Stephen Burgess , Paul J. Newcombe

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

Mendelian Randomisation (MR) uses genetic variants as instrumental variables to infer causal effects of exposures on an outcome. One key assumption of MR is that the genetic variants used as instrumental variables are independent of the…

Methodology · Statistics 2025-02-21 Maximilian M Mandl , Anne-Laure Boulesteix , Stephen Burgess , Verena Zuber

Mendelian randomization (MR) has become an essential tool for causal inference in biomedical and public health research. By using genetic variants as instrumental variables, MR helps address unmeasured confounding and reverse causation,…

Methodology · Statistics 2025-11-04 Minhao Yao , Anqi Wang , Xihao Li , Zhonghua Liu

Recent advances in genotyping technology have delivered a wealth of genetic data, which is rapidly advancing our understanding of the underlying genetic architecture of complex diseases. Mendelian Randomization (MR) leverages such genetic…

Methodology · Statistics 2023-12-19 Wenhao Cao , Saonli Basu

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

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 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 is an instrumental variable method that utilizes genetic information to investigate the causal effect of a modifiable exposure on an outcome. In most cases, the exposure changes over time. Understanding the…

Methodology · Statistics 2024-03-11 Haodong Tian , Ashish Patel , Stephen Burgess

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

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 is the use of genetic variants to make causal inferences from observational data. The field is currently undergoing a revolution fuelled by increasing numbers of genetic variants demonstrated to be associated with…

Methodology · Statistics 2018-08-31 Stephen Burgess , Jack Bowden , Frank Dudbridge , Simon G Thompson

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) is a pivotal tool in genetics, genomics, and epidemiology, leveraging genetic variants as instrumental variables to infer causal relationships between exposures and outcomes. Traditional MR methods, while…

Methodology · Statistics 2026-01-15 Bitan Sarkar , Yuchao Jiang , Tian Ge , Yang Ni

Background: Mendelian randomization (MR) is a useful approach to causal inference from observational studies when randomised controlled trials are not feasible. However, study heterogeneity of two association studies required in MR is often…

Methodology · Statistics 2021-12-16 Linyi Zou , Hui Guo , Carlo Berzuini

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 is a widely used instrumental variable method for assessing causal effects of lifelong exposures on health outcomes. Many exposures, however, have causal effects that vary across the life course and often influence…

Mendelian randomization (MR) is a powerful method that uses genetic variants as instrumental variables (IVs) to infer the causal effect of a modifiable exposure on an outcome. Although recent years have seen many extensions of basic MR…

Methodology · Statistics 2022-03-15 Sai Li , Ting Ye

Mendelian randomization (MR) is a method of exploiting genetic variation to unbiasedly estimate a causal effect in presence of unmeasured confounding. MR is being widely used in epidemiology and other related areas of population science. In…

Applications · Statistics 2019-01-03 Qingyuan Zhao , Jingshu Wang , Gibran Hemani , Jack Bowden , Dylan S. Small
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