Cargando…
Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors
OBJECTIVE: Mendelian randomization is a popular technique for assessing and estimating the causal effects of risk factors. If genetic variants which are instrumental variables for a risk factor are shown to be additionally associated with a disease outcome, then the risk factor is a cause of the dis...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687951/ https://www.ncbi.nlm.nih.gov/pubmed/26291580 http://dx.doi.org/10.1016/j.jclinepi.2015.08.001 |
_version_ | 1782406695699349504 |
---|---|
author | Burgess, Stephen Butterworth, Adam S. Thompson, John R. |
author_facet | Burgess, Stephen Butterworth, Adam S. Thompson, John R. |
author_sort | Burgess, Stephen |
collection | PubMed |
description | OBJECTIVE: Mendelian randomization is a popular technique for assessing and estimating the causal effects of risk factors. If genetic variants which are instrumental variables for a risk factor are shown to be additionally associated with a disease outcome, then the risk factor is a cause of the disease. However, in many cases, the instrumental variable assumptions are not plausible, or are in doubt. In this paper, we provide a theoretical classification of scenarios in which a causal conclusion is justified or not justified, and discuss the interpretation of causal effect estimates. RESULTS: A list of guidelines based on the ‘Bradford Hill criteria’ for judging the plausibility of a causal finding from an applied Mendelian randomization study is provided. We also give a framework for performing and interpreting investigations performed in the style of Mendelian randomization, but where the choice of genetic variants is statistically, rather than biologically motivated. Such analyses should not be assigned the same evidential weight as a Mendelian randomization investigation. CONCLUSION: We discuss the role of such investigations (in the style of Mendelian randomization), and what they add to our understanding of potential causal mechanisms. If the genetic variants are selected solely according to statistical criteria, and the biological roles of genetic variants are not investigated, this may be little more than what can be learned from a well-designed classical observational study. |
format | Online Article Text |
id | pubmed-4687951 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-46879512016-01-15 Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors Burgess, Stephen Butterworth, Adam S. Thompson, John R. J Clin Epidemiol Original Article OBJECTIVE: Mendelian randomization is a popular technique for assessing and estimating the causal effects of risk factors. If genetic variants which are instrumental variables for a risk factor are shown to be additionally associated with a disease outcome, then the risk factor is a cause of the disease. However, in many cases, the instrumental variable assumptions are not plausible, or are in doubt. In this paper, we provide a theoretical classification of scenarios in which a causal conclusion is justified or not justified, and discuss the interpretation of causal effect estimates. RESULTS: A list of guidelines based on the ‘Bradford Hill criteria’ for judging the plausibility of a causal finding from an applied Mendelian randomization study is provided. We also give a framework for performing and interpreting investigations performed in the style of Mendelian randomization, but where the choice of genetic variants is statistically, rather than biologically motivated. Such analyses should not be assigned the same evidential weight as a Mendelian randomization investigation. CONCLUSION: We discuss the role of such investigations (in the style of Mendelian randomization), and what they add to our understanding of potential causal mechanisms. If the genetic variants are selected solely according to statistical criteria, and the biological roles of genetic variants are not investigated, this may be little more than what can be learned from a well-designed classical observational study. Elsevier 2016-01 /pmc/articles/PMC4687951/ /pubmed/26291580 http://dx.doi.org/10.1016/j.jclinepi.2015.08.001 Text en © 2016 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Original Article Burgess, Stephen Butterworth, Adam S. Thompson, John R. Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors |
title | Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors |
title_full | Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors |
title_fullStr | Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors |
title_full_unstemmed | Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors |
title_short | Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors |
title_sort | beyond mendelian randomization: how to interpret evidence of shared genetic predictors |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4687951/ https://www.ncbi.nlm.nih.gov/pubmed/26291580 http://dx.doi.org/10.1016/j.jclinepi.2015.08.001 |
work_keys_str_mv | AT burgessstephen beyondmendelianrandomizationhowtointerpretevidenceofsharedgeneticpredictors AT butterworthadams beyondmendelianrandomizationhowtointerpretevidenceofsharedgeneticpredictors AT thompsonjohnr beyondmendelianrandomizationhowtointerpretevidenceofsharedgeneticpredictors |