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Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues

We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s...

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Autores principales: Davey Smith, George, Holmes, Michael V., Davies, Neil M., Ebrahim, Shah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125255/
https://www.ncbi.nlm.nih.gov/pubmed/32207040
http://dx.doi.org/10.1007/s10654-020-00622-7
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author Davey Smith, George
Holmes, Michael V.
Davies, Neil M.
Ebrahim, Shah
author_facet Davey Smith, George
Holmes, Michael V.
Davies, Neil M.
Ebrahim, Shah
author_sort Davey Smith, George
collection PubMed
description We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that “the hard problem of conducting high-quality, reproducible epidemiology” should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.
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spelling pubmed-71252552020-04-06 Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues Davey Smith, George Holmes, Michael V. Davies, Neil M. Ebrahim, Shah Eur J Epidemiol Commentary We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel’s laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR’s substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that “the hard problem of conducting high-quality, reproducible epidemiology” should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined. Springer Netherlands 2020-03-23 2020 /pmc/articles/PMC7125255/ /pubmed/32207040 http://dx.doi.org/10.1007/s10654-020-00622-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Commentary
Davey Smith, George
Holmes, Michael V.
Davies, Neil M.
Ebrahim, Shah
Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
title Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
title_full Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
title_fullStr Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
title_full_unstemmed Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
title_short Mendel’s laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
title_sort mendel’s laws, mendelian randomization and causal inference in observational data: substantive and nomenclatural issues
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7125255/
https://www.ncbi.nlm.nih.gov/pubmed/32207040
http://dx.doi.org/10.1007/s10654-020-00622-7
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