English
Related papers

Related papers: Woolf et als GWAS by subtraction is not useful for…

200 papers

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

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 natural experimental design based on the random transmission of genes from parents to offspring. However, this inferential basis is typically only implicit or used as an informal justification. As…

Methodology · Statistics 2023-04-19 Matthew J Tudball , George Davey Smith , Qingyuan Zhao

Mediation analysis is a powerful tool for studying causal pathways between exposure, mediator, and outcome variables of interest. While classical mediation analysis using observational data often requires strong and sometimes unrealistic…

Methodology · Statistics 2024-05-20 Rita Qiuran Lyu , Chong Wu , Xinwei Ma , Jingshen Wang

Two-sample summary-data Mendelian randomization (MR) has become a popular research design to estimate the causal effect of risk exposures. With the sample size of GWAS continuing to increase, it is now possible to utilize genetic…

Applications · Statistics 2018-11-20 Qingyuan Zhao , Yang Chen , Jingshu Wang , Dylan S. Small

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

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

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 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 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

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 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

The use of genetic variants as instrumental variables - an approach known as Mendelian randomization - is a popular epidemiological method for estimating the causal effect of an exposure (phenotype, biomarker, risk factor) on a disease or…

Methodology · Statistics 2020-12-21 Ioan Gabriel Bucur , Tom Claassen , Tom Heskes

Mendelian randomization (MR) is an instrumental variable (IV) approach to infer causal relationships between exposures and outcomes with genome-wide association studies (GWAS) summary data. However, the multivariable inverse-variance…

Methodology · Statistics 2024-02-13 Yihe Yang , Noah Lorincz-Comi , Xiaofeng Zhu

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) is a powerful approach to examine the causal relationships between health risk factors and outcomes from observational studies. Due to the proliferation of genome-wide association studies (GWASs) and abundant…

Methodology · Statistics 2020-09-02 Qing Cheng , Baoluo Sun , Yingcun Xia , Jin Liu

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 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 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

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
‹ Prev 1 2 3 10 Next ›