Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zheng, Jie, Baird, Denis, Borges, Maria-Carolina, Bowden, Jack, Hemani, Gibran, Haycock, Philip, Evans, David M., Smith, George Davey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
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
_version_ 1783283130106380288
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
work_keys_str_mv AT zhengjie recentdevelopmentsinmendelianrandomizationstudies
AT bairddenis recentdevelopmentsinmendelianrandomizationstudies
AT borgesmariacarolina recentdevelopmentsinmendelianrandomizationstudies
AT bowdenjack recentdevelopmentsinmendelianrandomizationstudies
AT hemanigibran recentdevelopmentsinmendelianrandomizationstudies
AT haycockphilip recentdevelopmentsinmendelianrandomizationstudies
AT evansdavidm recentdevelopmentsinmendelianrandomizationstudies
AT smithgeorgedavey recentdevelopmentsinmendelianrandomizationstudies