ArticleGenetic epidemiology2019
Constrained instruments and their application to Mendelian randomization with pleiotropy.
Article in Genetic epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- A flexible framework for robust and efficient Mendelian randomization with debiasing.Briefings in bioinformatics · 2026Article
- A multivariate approach to identify association between peripheral blood DNA methylation and cerebrospinal fluid biomarkers of Alzheimer disease.Scientific reports · 2025Article
- A Review of Mendelian Randomization: Assumptions, Methods, and Application to Obesity-Related Diseases.Journal of obesity & metabolic syndrome · 2025Review
- Association between cathepsins and skin cancers: A bidirectional two-sample Mendelian randomization study.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2024Article
- An efficient and robust approach to Mendelian randomization with measured pleiotropic effects in a high-dimensional setting.Biostatistics (Oxford, England) · 2022Article
- Mendelian randomization.Nature reviews. Methods primers · 2022Article
- Causal simulation experiments: Lessons from bias amplification.Statistical methods in medical research · 2022Article
- Statistical methods for Mendelian randomization in genome-wide association studies: A review.Computational and structural biotechnology journal · 2022Review
- Model checking via testing for direct effects in Mendelian Randomization and transcriptome-wide association studies.PLoS computational biology · 2021Article
- Graphical analysis for phenome-wide causal discovery in genotyped population-scale biobanks.Nature communications · 2021Article
- A comparison of robust Mendelian randomization methods using summary data.Genetic epidemiology · 2020Article
- Exploiting horizontal pleiotropy to search for causal pathways within a Mendelian randomization framework.Nature communications · 2020Article
- Epidemiology, genetic epidemiology and Mendelian randomisation: more need than ever to attend to detail.Human genetics · 2020Article
- Constrained instruments and their application to Mendelian randomization with pleiotropy.Genetic epidemiology · 2019Article
- Inferring Causal Relationships Between Risk Factors and Outcomes from Genome-Wide Association Study Data.Annual review of genomics and human genetics · 2018Review
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Authors and funding
10 authors.
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Abstract
In Mendelian randomization (MR), inference about causal relationship between a phenotype of interest and a response or disease outcome can be obtained by constructing instrumental variables from genetic variants. However, MR inference requires three assumptions, one of which is that the genetic variants only influence the outcome through phenotype of interest. Pleiotropy, that is, the situation in which some genetic variants affect more than one phenotype, can invalidate these genetic variants for use as instrumental variables; thus a naive analysis will give biased estimates of the causal relation. Here, we present new methods (constrained instrumental variable [CIV] methods) to construct valid instrumental variables and perform adjusted causal effect estimation when pleiotropy exists and when the pleiotropic phenotypes are available. We demonstrate that a smoothed version of CIV performs approximate selection of genetic variants that are valid instruments, and provides unbiased estimates of the causal effects. We provide details on a number of existing methods, together with a comparison of their performance in a large series of simulations. CIV performs robustly across different pleiotropic violations of the MR assumptions. We also analyzed the data from the Alzheimer's disease (AD) neuroimaging initiative (ADNI; Mueller et al., 2005. Alzheimer's Dementia, 11(1), 55-66) to disentangle causal relationships of several biomarkers with AD progression.
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