Literature DB >> 34008876

Caution against examining the role of reverse causality in Mendelian Randomization.

Sharon M Lutz1,2, Ann Chen Wu1, John E Hokanson3, Stijn Vansteelandt4,5, Christoph Lange2.   

Abstract

Recently, Mendelian Randomization (MR) has gained in popularity as a concept to assess the causal relationship between phenotypes in genetic association studies. An extension of standard MR methodology, the MR Steiger approach, has recently been developed to infer the causal direction between two phenotypes in prospective studies. Through simulation studies, we examined and quantified the ability of the MR Steiger approach to determine the causal direction between two phenotypes (i.e., effect direction). Through simulation studies, our results show that the MR Steiger approach may fail to correctly identify the direction of causality. This is true, especially in the presence of pleiotropy. We also applied the MR Steiger method to the COPDGene study, a case-control study of chronic obstructive pulmonary disease (COPD) in current and former smokers, to examine the role of smoking on lung function. We have created an R package on Github called reverseDirection which runs simulations for user-specified scenarios to examine when the MR Steiger approach can correctly determine the causal direction between two phenotypes in any user specified scenario. In summary, our results emphasize the importance of caution when the MR Steiger approach is used in to infer the direction of causality.
© 2021 Wiley Periodicals LLC.

Entities:  

Keywords:  Mendelian Randomization; causal direction; reverse causality

Mesh:

Year:  2021        PMID: 34008876      PMCID: PMC8222166          DOI: 10.1002/gepi.22385

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.344


  23 in total

1.  'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease?

Authors:  George Davey Smith; Shah Ebrahim
Journal:  Int J Epidemiol       Date:  2003-02       Impact factor: 7.196

2.  Genetic epidemiology of COPD (COPDGene) study design.

Authors:  Elizabeth A Regan; John E Hokanson; James R Murphy; Barry Make; David A Lynch; Terri H Beaty; Douglas Curran-Everett; Edwin K Silverman; James D Crapo
Journal:  COPD       Date:  2010-02       Impact factor: 2.409

3.  Survivor bias in Mendelian randomization analysis.

Authors:  Stijn Vansteelandt; Oliver Dukes; Torben Martinussen
Journal:  Biostatistics       Date:  2018-10-01       Impact factor: 5.899

4.  Common and Rare Variants Genetic Association Analysis of Cigarettes per Day Among Ever-Smokers in Chronic Obstructive Pulmonary Disease Cases and Controls.

Authors:  Sharon M Lutz; Brittni Frederiksen; Ferdouse Begum; Merry-Lynn N McDonald; Michael H Cho; Brian D Hobbs; Margaret M Parker; Dawn L DeMeo; Craig P Hersh; Marissa A Ehringer; Kendra Young; Lai Jiang; Marilyn G Foreman; Greg L Kinney; Barry J Make; David A Lomas; Per Bakke; Amund Gulsvik; James D Crapo; Edwin K Silverman; Terri H Beaty; John E Hokanson
Journal:  Nicotine Tob Res       Date:  2019-05-21       Impact factor: 4.244

5.  Mendelian randomization: using genes as instruments for making causal inferences in epidemiology.

Authors:  Debbie A Lawlor; Roger M Harbord; Jonathan A C Sterne; Nic Timpson; George Davey Smith
Journal:  Stat Med       Date:  2008-04-15       Impact factor: 2.373

6.  Mendelian randomization analysis with multiple genetic variants using summarized data.

Authors:  Stephen Burgess; Adam Butterworth; Simon G Thompson
Journal:  Genet Epidemiol       Date:  2013-09-20       Impact factor: 2.135

7.  C-reactive protein levels and body mass index: elucidating direction of causation through reciprocal Mendelian randomization.

Authors:  N J Timpson; B G Nordestgaard; R M Harbord; J Zacho; T M Frayling; A Tybjærg-Hansen; G Davey Smith
Journal:  Int J Obes (Lond)       Date:  2010-08-17       Impact factor: 5.095

8.  Orienting the causal relationship between imprecisely measured traits using GWAS summary data.

Authors:  Gibran Hemani; Kate Tilling; George Davey Smith
Journal:  PLoS Genet       Date:  2017-11-17       Impact factor: 5.917

9.  Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator.

Authors:  Jack Bowden; George Davey Smith; Philip C Haycock; Stephen Burgess
Journal:  Genet Epidemiol       Date:  2016-04-07       Impact factor: 2.135

10.  Exploiting horizontal pleiotropy to search for causal pathways within a Mendelian randomization framework.

Authors:  Yoonsu Cho; Philip C Haycock; Eleanor Sanderson; Tom R Gaunt; Jie Zheng; Andrew P Morris; George Davey Smith; Gibran Hemani
Journal:  Nat Commun       Date:  2020-02-21       Impact factor: 14.919

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  3 in total

1.  The influence of unmeasured confounding on the MR Steiger approach.

Authors:  Sharon M Lutz; Kirsten Voorhies; Ann Chen Wu; John Hokanson; Stijn Vansteelandt; Christoph Lange
Journal:  Genet Epidemiol       Date:  2022-02-16       Impact factor: 2.135

2.  Caution against examining the role of reverse causality in Mendelian Randomization.

Authors:  Sharon M Lutz; Ann Chen Wu; John E Hokanson; Stijn Vansteelandt; Christoph Lange
Journal:  Genet Epidemiol       Date:  2021-05-19       Impact factor: 2.344

3.  Genetically predicted higher educational attainment decreases the risk of stroke: a multivariable Mendelian randomization study.

Authors:  Weihao Zhang; Yuanjin Li; Yuming Li; Kai Zheng; Shenghui Zou; Xing Jia; Hua Yang
Journal:  BMC Cardiovasc Disord       Date:  2022-06-16       Impact factor: 2.174

  3 in total

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