Huang, JY

Kaufman, JS

Labrecque, Jeremy

English

EUR Research Repository

.......................................................Genetic instruments with too many strings:acknowledging pleiotropy and populationstructure in Mendelian randomization studiesJeremy A. Labrecque 1*, Jay S. Kaufman 2, and Jonathan Y. Huang 31Department of Epidemiology, Erasmus MC, Dr. Molewaterplein 50, 3015 GE Rotterdam, the Netherlands; 2Department of Epidemiology, Biostatistics and Occupational Health,McGill University, 1020 Avenue des Pins Ouest, H3A 1A2 Montreal, Quebec, Canada; and 3Department of Biostatistics, Singapore Institute for Clinical Sciences, Agency forScience, Technology and Research (A*STAR), 117609, SingaporeOnline publish-ahead-of-print 20 January 2020This commentary refers to ‘Genetically modulated educa-tional attainment and coronary disease risk’, by L. Zenget al., pages 2413–2420.The availability of large genetic databases has prompted renewedinterest in genetic contributions to educational attainment and theeffects of education on health. In a recent issue of the European HeartJournal, Zeng et al.1 use cohorts from across Europe and the USA toinvestigate education-associated genotypes and their role in coronaryartery disease (CAD). We would like to commend the authors forraising important questions about the relationships between genetics,education, and CAD. Nonetheless, it is our belief that the methodsemployed have important limitations not discussed by the authors.Here, we note three of these limitations.First, the authors investigate whether the genetic risk score (GRS)for education was associated with CAD independently of its effecton education by adjusting for number of years of attained educationin the regression of CAD on the GRS. The logic is to ‘block’ the effectof the GRS through attained education (Figure 1). However, beyond‘blocking’ the effect, this method will also create a new correlationbetween GRS and all other causes of education because it becomes a‘collider’2 (Figure 1, dashed arrow). Therefore, even if the effect of theeducation GRS on CAD is only mediated by years of education, theGRS will continue to be correlated with CAD after adjustment foryears of education. Any residual association after adjusting for yearsof education cannot then be interpreted as an independent or pleio-tropic effect of the GRS. To answer this question by adjustment, ap-propriate mediation methods would be required.3Second, one of the three major assumptions of Mendelian ran-domization (MR) analyses is that the effect of the single-nucleotidepolymorphisms on the outcome (CAD) only passes through the ex-posure (education).4 Therefore, if the authors’ claim to have foundpleiotropic effects of the education GRS on CAD were, in fact, true,this would also imply that the results of the MR analysis are biased.Therefore, it is difficult to know what to conclude. If the educationGRS is pleiotropic, as the authors claim, then the main MR analysismust be biased. Alternatively, if the authors claim that the MR analysisis valid, this implies that there is no pleiotropic effect of the educationGRS on CAD.Lastly, confounding by population stratification is difficult to con-trol when using a GRS, particularly, with geographically patternedphenotypes, as in the case of education and heart disease.5 Theauthors use five principal components to adjust for this but it hasbeen shown that geographic confounding may not be successfullycontrolled even with 40 principal components. This confoundingwould invalidate both the primary and MR analyses. Furthermore,such residual confounding is consistent with the finding that GRS-CAD associations become null when adjusting for body mass indexand smoking, i.e. adjusting for these factors help account for popula-tion stratification thus showing the independent association withGRS to be null.Figure 1 Adjusting for years of education blocks the effect of thegenetic risk score on coronary artery disease but creates a correl-ation between the genetic risk score and the confounders of educa-tion and coronary artery disease (dashed line).* Corresponding author. Tel: þ31 10 70 33638, Email: j.labrecque@erasmusmc.nlPublished on behalf of the European Society of Cardiology. All rights reserved. VC The Author(s) 2020. For permissions, please email: journals.permissions@oup.com.European Heart Journal (2020) 41, 892–893 DISCUSSION FORUMdoi:10.1093/eurheartj/ehz943Downloaded from https://academic.oup.com/eurheartj/article-abstract/41/7/892/5710691 by guest on 26 February 2020......................Conflict of interest: none declared.References1. Zeng L, Ntalla I, Kessler T, Kastrati A, Erdmann J; UK Biobank CardioMetabolicConsortium CHD Working Group, Danesh J, Watkins H, Samani NJ, Deloukas P,Schunkert H. Genetically modulated educational attainment and coronary diseaserisk. Eur Heart J 2019;40:2413–2420.2. Cole SR, Platt RW, Schisterman EF, Chu H, Westreich D, Richardson D, Poole C.Illustrating bias due to conditioning on a collider. Int J Epidemiol 2010;39:417–420.3. Vanderweele TJ. Explanation in Causal Inference. New York, NY: Oxford UniversityPress; 2015.4. Smith GD, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology con-tribute to understanding environmental determinants of disease? Int J Epidemiol2003;32:1–22.5. Haworth S, Mitchell R, Corbin L, Wade KH, Dudding T, Budu-Aggrey A,Carslake D, Hemani G, Paternoster L, Smith GD, Davies N, Lawson DJ,J Timpson N. Apparent latent structure within the UK Biobanksample has implications for epidemiological analysis. Nat Commun 2019;10:333.Discussion forum 893Downloaded from https://academic.oup.com/eurheartj/article-abstract/41/7/892/5710691 by guest on 26 February 2020

Genetic instruments with too many strings: acknowledging pleiotropy and population structure in Mendelian randomization studies

EUR Research Information PortalGenetic instruments with too many strings: acknowledging pleiotropy and populationstructure in Mendelian randomization studiesPublished in:European Heart JournalPublication status and date:Published: 01/01/2020DOI (link to publisher):10.1093/eurheartj/ehz943Document VersionPublisher's PDF, also known as Version of recordCitation for the published version (APA):Labrecque, J., Kaufman, JS., & Huang, JY. (2020). Genetic instruments with too many strings: acknowledging pleiotropy andpopulation structure in Mendelian randomization studies. European Heart Journal, 41(7), 892-893.https://doi.org/10.1093/eurheartj/ehz943Link to publication on the EUR Research Information PortalTerms and Conditions of UseExcept as permitted by the applicable copyright law, you may not reproduce or make this material available to any third partywithout the prior written permission from the copyright holder(s). Copyright law allows the following uses of this materialwithout prior permission:            • you may download, save and print a copy of this material for your personal use only;            • you may share the EUR portal link to this material.In case the material is published with an open access license (e.g. a Creative Commons (CC) license), other uses may beallowed. Please check the terms and conditions of the specific license.Take-down policyIf you believe that this material infringes your copyright and/or any other intellectual property rights, you may request itsremoval by contacting us at the following email address: openaccess.library@eur.nl. Please provide us with all the relevantinformation, including the reasons why you believe any of your rights have been infringed. In case of a legitimate complaint,we will make the material inaccessible and/or remove it from the website........................................................Genetic instruments with too many strings:acknowledging pleiotropy and populationstructure in Mendelian randomization studiesJeremy A. Labrecque 1*, Jay S. Kaufman 2, and Jonathan Y. Huang 31Department of Epidemiology, Erasmus MC, Dr. Molewaterplein 50, 3015 GE Rotterdam, the Netherlands; 2Department of Epidemiology, Biostatistics and Occupational Health,McGill University, 1020 Avenue des Pins Ouest, H3A 1A2 Montreal, Quebec, Canada; and 3Department of Biostatistics, Singapore Institute for Clinical Sciences, Agency forScience, Technology and Research (A*STAR), 117609, SingaporeOnline publish-ahead-of-print 20 January 2020This commentary refers to ‘Genetically modulated educa-tional attainment and coronary disease risk’, by L. Zenget al., pages 2413–2420.The availability of large genetic databases has prompted renewedinterest in genetic contributions to educational attainment and theeffects of education on health. In a recent issue of the European HeartJournal, Zeng et al.1 use cohorts from across Europe and the USA toinvestigate education-associated genotypes and their role in coronaryartery disease (CAD). We would like to commend the authors forraising important questions about the relationships between genetics,education, and CAD. Nonetheless, it is our belief that the methodsemployed have important limitations not discussed by the authors.Here, we note three of these limitations.First, the authors investigate whether the genetic risk score (GRS)for education was associated with CAD independently of its effecton education by adjusting for number of years of attained educationin the regression of CAD on the GRS. The logic is to ‘block’ the effectof the GRS through attained education (Figure 1). However, beyond‘blocking’ the effect, this method will also create a new correlationbetween GRS and all other causes of education because it becomes a‘collider’2 (Figure 1, dashed arrow). Therefore, even if the effect of theeducation GRS on CAD is only mediated by years of education, theGRS will continue to be correlated with CAD after adjustment foryears of education. Any residual association after adjusting for yearsof education cannot then be interpreted as an independent or pleio-tropic effect of the GRS. To answer this question by adjustment, ap-propriate mediation methods would be required.3Second, one of the three major assumptions of Mendelian ran-domization (MR) analyses is that the effect of the single-nucleotidepolymorphisms on the outcome (CAD) only passes through the ex-posure (education).4 Therefore, if the authors’ claim to have foundpleiotropic effects of the education GRS on CAD were, in fact, true,this would also imply that the results of the MR analysis are biased.Therefore, it is difficult to know what to conclude. If the educationGRS is pleiotropic, as the authors claim, then the main MR analysismust be biased. Alternatively, if the authors claim that the MR analysisis valid, this implies that there is no pleiotropic effect of the educationGRS on CAD.Lastly, confounding by population stratification is difficult to con-trol when using a GRS, particularly, with geographically patternedphenotypes, as in the case of education and heart disease.5 Theauthors use five principal components to adjust for this but it hasbeen shown that geographic confounding may not be successfullycontrolled even with 40 principal components. This confoundingwould invalidate both the primary and MR analyses. Furthermore,such residual confounding is consistent with the finding that GRS-CAD associations become null when adjusting for body mass indexand smoking, i.e. adjusting for these factors help account for popula-tion stratification thus showing the independent association withGRS to be null.Figure 1 Adjusting for years of education blocks the effect of thegenetic risk score on coronary artery disease but creates a correl-ation between the genetic risk score and the confounders of educa-tion and coronary artery disease (dashed line).* Corresponding author. Tel: þ31 10 70 33638, Email: j.labrecque@erasmusmc.nlPublished on behalf of the European Society of Cardiology. All rights reserved. VC The Author(s) 2020. For permissions, please email: journals.permissions@oup.com.European Heart Journal (2020) 41, 892–893 DISCUSSION FORUMdoi:10.1093/eurheartj/ehz943Downloaded from https://academic.oup.com/eurheartj/article-abstract/41/7/892/5710691 by guest on 26 February 2020......................Conflict of interest: none declared.References1. Zeng L, Ntalla I, Kessler T, Kastrati A, Erdmann J; UK Biobank CardioMetabolicConsortium CHD Working Group, Danesh J, Watkins H, Samani NJ, Deloukas P,Schunkert H. Genetically modulated educational attainment and coronary diseaserisk. Eur Heart J 2019;40:2413–2420.2. Cole SR, Platt RW, Schisterman EF, Chu H, Westreich D, Richardson D, Poole C.Illustrating bias due to conditioning on a collider. Int J Epidemiol 2010;39:417–420.3. Vanderweele TJ. Explanation in Causal Inference. New York, NY: Oxford UniversityPress; 2015.4. Smith GD, Ebrahim S. ‘Mendelian randomization’: can genetic epidemiology con-tribute to understanding environmental determinants of disease? Int J Epidemiol2003;32:1–22.5. Haworth S, Mitchell R, Corbin L, Wade KH, Dudding T, Budu-Aggrey A,Carslake D, Hemani G, Paternoster L, Smith GD, Davies N, Lawson DJ,J Timpson N. Apparent latent structure within the UK Biobanksample has implications for epidemiological analysis. Nat Commun 2019;10:333.Discussion forum 893Downloaded from https://academic.oup.com/eurheartj/article-abstract/41/7/892/5710691 by guest on 26 February 2020

Undetermined

https://pure.eur.nl/ws/files/48291123/Repub_124840.pdf

Genetic instruments with too many strings: acknowledging pleiotropy and population structure in Mendelian randomization studies

Abstract

Similar works

Full text

Available Versions

EUR Research Repository

EUR Research Repository

EUR Research Repository