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Recent Developments in Mendelian Randomization Studies
PURPOSE OF REVIEW: Mendelian randomization (MR) is a strategy for evaluating causality in observational epidemiological studies. MR exploits the fact that genotypes are not generally susceptible to reverse causation and confounding, due to their fixed nature and Mendel’s First and Second Laws of Inh...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711966/ https://www.ncbi.nlm.nih.gov/pubmed/29226067 http://dx.doi.org/10.1007/s40471-017-0128-6 |
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author | Zheng, Jie Baird, Denis Borges, Maria-Carolina Bowden, Jack Hemani, Gibran Haycock, Philip Evans, David M. Smith, George Davey |
author_facet | Zheng, Jie Baird, Denis Borges, Maria-Carolina Bowden, Jack Hemani, Gibran Haycock, Philip Evans, David M. Smith, George Davey |
author_sort | Zheng, Jie |
collection | PubMed |
description | PURPOSE OF REVIEW: Mendelian randomization (MR) is a strategy for evaluating causality in observational epidemiological studies. MR exploits the fact that genotypes are not generally susceptible to reverse causation and confounding, due to their fixed nature and Mendel’s First and Second Laws of Inheritance. MR has the potential to provide information on causality in many situations where randomized controlled trials are not possible, but the results of MR studies must be interpreted carefully to avoid drawing erroneous conclusions. RECENT FINDINGS: In this review, we outline the principles behind MR, as well as assumptions and limitations of the method. Extensions to the basic approach are discussed, including two-sample MR, bidirectional MR, two-step MR, multivariable MR, and factorial MR. We also consider some new applications and recent developments in the methodology, including its ability to inform drug development, automation of the method using tools such as MR-Base, and phenome-wide and hypothesis-free MR. SUMMARY: In conjunction with the growing availability of large-scale genomic databases, higher level of automation and increased robustness of the methods, MR promises to be a valuable strategy to examine causality in complex biological/omics networks, inform drug development and prioritize intervention targets for disease prevention in the future. |
format | Online Article Text |
id | pubmed-5711966 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-57119662017-12-07 Recent Developments in Mendelian Randomization Studies Zheng, Jie Baird, Denis Borges, Maria-Carolina Bowden, Jack Hemani, Gibran Haycock, Philip Evans, David M. Smith, George Davey Curr Epidemiol Rep Genetic Epidemiology (C Amos, Section Editor) PURPOSE OF REVIEW: Mendelian randomization (MR) is a strategy for evaluating causality in observational epidemiological studies. MR exploits the fact that genotypes are not generally susceptible to reverse causation and confounding, due to their fixed nature and Mendel’s First and Second Laws of Inheritance. MR has the potential to provide information on causality in many situations where randomized controlled trials are not possible, but the results of MR studies must be interpreted carefully to avoid drawing erroneous conclusions. RECENT FINDINGS: In this review, we outline the principles behind MR, as well as assumptions and limitations of the method. Extensions to the basic approach are discussed, including two-sample MR, bidirectional MR, two-step MR, multivariable MR, and factorial MR. We also consider some new applications and recent developments in the methodology, including its ability to inform drug development, automation of the method using tools such as MR-Base, and phenome-wide and hypothesis-free MR. SUMMARY: In conjunction with the growing availability of large-scale genomic databases, higher level of automation and increased robustness of the methods, MR promises to be a valuable strategy to examine causality in complex biological/omics networks, inform drug development and prioritize intervention targets for disease prevention in the future. Springer International Publishing 2017-11-22 2017 /pmc/articles/PMC5711966/ /pubmed/29226067 http://dx.doi.org/10.1007/s40471-017-0128-6 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Genetic Epidemiology (C Amos, Section Editor) Zheng, Jie Baird, Denis Borges, Maria-Carolina Bowden, Jack Hemani, Gibran Haycock, Philip Evans, David M. Smith, George Davey Recent Developments in Mendelian Randomization Studies |
title | Recent Developments in Mendelian Randomization Studies |
title_full | Recent Developments in Mendelian Randomization Studies |
title_fullStr | Recent Developments in Mendelian Randomization Studies |
title_full_unstemmed | Recent Developments in Mendelian Randomization Studies |
title_short | Recent Developments in Mendelian Randomization Studies |
title_sort | recent developments in mendelian randomization studies |
topic | Genetic Epidemiology (C Amos, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5711966/ https://www.ncbi.nlm.nih.gov/pubmed/29226067 http://dx.doi.org/10.1007/s40471-017-0128-6 |
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