IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v14y2023i1d10.1038_s41467-023-40069-4.html
   My bibliography  Save this article

Overcoming attenuation bias in regressions using polygenic indices

Author

Listed:
  • Hans Kippersluis

    (Erasmus University Rotterdam
    Tinbergen Institute)

  • Pietro Biroli

    (University of Bologna)

  • Rita Dias Pereira

    (Erasmus University Rotterdam
    Tinbergen Institute)

  • Titus J. Galama

    (Erasmus University Rotterdam
    Tinbergen Institute
    Vrije Universiteit Amsterdam
    University of Southern California)

  • Stephanie Hinke

    (Erasmus University Rotterdam
    Tinbergen Institute
    University of Bristol)

  • S. Fleur W. Meddens

    (Erasmus University Rotterdam
    Statistics Netherlands)

  • Dilnoza Muslimova

    (Erasmus University Rotterdam
    Tinbergen Institute)

  • Eric A. W. Slob

    (Erasmus University Rotterdam
    Cambridge University
    Erasmus University Rotterdam Institute for Behavior and Biology)

  • Ronald Vlaming

    (Tinbergen Institute
    Vrije Universiteit Amsterdam)

  • Cornelius A. Rietveld

    (Erasmus University Rotterdam
    Tinbergen Institute
    Erasmus University Rotterdam Institute for Behavior and Biology)

Abstract

Measurement error in polygenic indices (PGIs) attenuates the estimation of their effects in regression models. We analyze and compare two approaches addressing this attenuation bias: Obviously Related Instrumental Variables (ORIV) and the PGI Repository Correction (PGI-RC). Through simulations, we show that the PGI-RC performs slightly better than ORIV, unless the prediction sample is very small (N

Suggested Citation

  • Hans Kippersluis & Pietro Biroli & Rita Dias Pereira & Titus J. Galama & Stephanie Hinke & S. Fleur W. Meddens & Dilnoza Muslimova & Eric A. W. Slob & Ronald Vlaming & Cornelius A. Rietveld, 2023. "Overcoming attenuation bias in regressions using polygenic indices," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40069-4
    DOI: 10.1038/s41467-023-40069-4
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-023-40069-4
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-023-40069-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2003. "Instrumental variables and GMM: Estimation and testing," Stata Journal, StataCorp LP, vol. 3(1), pages 1-31, March.
    2. Matthew R. Robinson & Aaron Kleinman & Mariaelisa Graff & Anna A. E. Vinkhuyzen & David Couper & Michael B. Miller & Wouter J. Peyrot & Abdel Abdellaoui & Brendan P. Zietsch & Ilja M. Nolte & Jana V. , 2017. "Genetic evidence of assortative mating in humans," Nature Human Behaviour, Nature, vol. 1(1), pages 1-13, January.
    3. Daniel Barth & Nicholas W. Papageorge & Kevin Thom, 2020. "Genetic Endowments and Wealth Inequality," Journal of Political Economy, University of Chicago Press, vol. 128(4), pages 1474-1522.
    4. Jerry Hausman, 2001. "Mismeasured Variables in Econometric Analysis: Problems from the Right and Problems from the Left," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 57-67, Fall.
    5. Ben Gillen & Erik Snowberg & Leeat Yariv, 2019. "Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study," Journal of Political Economy, University of Chicago Press, vol. 127(4), pages 1826-1863.
    6. Frank Dudbridge, 2013. "Power and Predictive Accuracy of Polygenic Risk Scores," PLOS Genetics, Public Library of Science, vol. 9(3), pages 1-17, March.
    7. Aysu Okbay & Jonathan P. Beauchamp & Mark Alan Fontana & James J. Lee & Tune H. Pers & Cornelius A. Rietveld & Patrick Turley & Guo-Bo Chen & Valur Emilsson & S. Fleur W. Meddens & Sven Oskarsson & Jo, 2016. "Genome-wide association study identifies 74 loci associated with educational attainment," Nature, Nature, vol. 533(7604), pages 539-542, May.
    8. repec:nas:journl:v:115:y:2018:p:e4970-e4979 is not listed on IDEAS
    9. Kimball, Miles S & Sahm, Claudia R & Shapiro, Matthew D, 2008. "Imputing Risk Tolerance From Survey Responses," Journal of the American Statistical Association, American Statistical Association, vol. 103(483), pages 1028-1038.
    10. Lasse Eika & Magne Mogstad & Basit Zafar, 2019. "Educational Assortative Mating and Household Income Inequality," Journal of Political Economy, University of Chicago Press, vol. 127(6), pages 2795-2835.
    11. Richard Border & Sean O’Rourke & Teresa de Candia & Michael E. Goddard & Peter M. Visscher & Loic Yengo & Matt Jones & Matthew C. Keller, 2022. "Author Correction: Assortative mating biases marker-based heritability estimators," Nature Communications, Nature, vol. 13(1), pages 1-1, December.
    12. Christine Schwartz & Robert Mare, 2005. "Trends in educational assortative marriage from 1940 to 2003," Demography, Springer;Population Association of America (PAA), vol. 42(4), pages 621-646, November.
    13. Sanz-de-Galdeano, Anna & Terskaya, Anastasia, 2019. "Sibling Differences in Educational Polygenic Scores: How Do Parents React?," IZA Discussion Papers 12375, Institute of Labor Economics (IZA).
    14. Nicole M. Warrington & Liang-Dar Hwang & Michel G. Nivard & David M. Evans, 2021. "Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data," Nature Communications, Nature, vol. 12(1), pages 1-12, December.
    15. Richard Border & Sean O’Rourke & Teresa de Candia & Michael E. Goddard & Peter M. Visscher & Loic Yengo & Matt Jones & Matthew C. Keller, 2022. "Assortative mating biases marker-based heritability estimators," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    16. Qian Zhang & Julia Sidorenko & Baptiste Couvy-Duchesne & Riccardo E. Marioni & Margaret J. Wright & Alison M. Goate & Edoardo Marcora & Kuan-lin Huang & Tenielle Porter & Simon M. Laws & Perminder S. , 2020. "Risk prediction of late-onset Alzheimer’s disease implies an oligogenic architecture," Nature Communications, Nature, vol. 11(1), pages 1-11, December.
    17. Clare Bycroft & Colin Freeman & Desislava Petkova & Gavin Band & Lloyd T. Elliott & Kevin Sharp & Allan Motyer & Damjan Vukcevic & Olivier Delaneau & Jared O’Connell & Adrian Cortes & Samantha Welsh &, 2018. "The UK Biobank resource with deep phenotyping and genomic data," Nature, Nature, vol. 562(7726), pages 203-209, October.
    18. Chabris, C. F. & Lee, J. J. & Cesarini, D. & Benjamin, D. J. & Laibson, David I., 2015. "The Fourth Law of Behavior Genetics," Scholarly Articles 30780203, Harvard University Department of Economics.
    19. Felix C. Tropf & S. Hong Lee & Renske M. Verweij & Gert Stulp & Peter J. van der Most & Ronald de Vlaming & Andrew Bakshi & Daniel A. Briley & Charles Rahal & Robert Hellpap & Anastasia N. Iliadou & T, 2017. "Hidden heritability due to heterogeneity across seven populations," Nature Human Behaviour, Nature, vol. 1(10), pages 757-765, October.
    20. Jonathan P. Beauchamp & David Cesarini & Magnus Johannesson, 2017. "The psychometric and empirical properties of measures of risk preferences," Journal of Risk and Uncertainty, Springer, vol. 54(3), pages 203-237, June.
    21. Ronald de Vlaming & Aysu Okbay & Cornelius A Rietveld & Magnus Johannesson & Patrik K E Magnusson & André G Uitterlinden & Frank J A van Rooij & Albert Hofman & Patrick J F Groenen & A Roy Thurik & Ph, 2017. "Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies," PLOS Genetics, Public Library of Science, vol. 13(1), pages 1-23, January.
    22. Andrew D. Grotzinger & Mijke Rhemtulla & Ronald Vlaming & Stuart J. Ritchie & Travis T. Mallard & W. David Hill & Hill F. Ip & Riccardo E. Marioni & Andrew M. McIntosh & Ian J. Deary & Philipp D. Koel, 2019. "Genomic structural equation modelling provides insights into the multivariate genetic architecture of complex traits," Nature Human Behaviour, Nature, vol. 3(5), pages 513-525, May.
    23. Joel Becker & Casper A. P. Burik & Grant Goldman & Nancy Wang & Hariharan Jayashankar & Michael Bennett & Daniel W. Belsky & Richard Karlsson Linnér & Rafael Ahlskog & Aaron Kleinman & David A. Hinds , 2021. "Resource profile and user guide of the Polygenic Index Repository," Nature Human Behaviour, Nature, vol. 5(12), pages 1744-1758, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stephanie von Hinke & Nicolai Vitt, 2024. "An analysis of the accuracy of retrospective birth location recall using sibling data," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Daniel J. Benjamin & David Cesarini & Patrick Turley & Alexander Strudwick Young, 2024. "Social-Science Genomics: Progress, Challenges, and Future Directions," NBER Working Papers 32404, National Bureau of Economic Research, Inc.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pietro Biroli & Titus Galama & Stephanie von Hinke & Hans van Kippersluis & Kevin Thom, 2022. "Economics and Econometrics of Gene-Environment Interplay," Bristol Economics Discussion Papers 22/759, School of Economics, University of Bristol, UK.
    2. Pereira, Rita & Biroli, Pietro & von hinke, stephanie & Van Kippersluis, Hans & Galama, Titus & Rietveld, Niels & Thom, Kevin, 2022. "Gene-Environment Interplay in the Social Sciences," OSF Preprints d96z3, Center for Open Science.
    3. Barban, Nicola & De Cao, Elisabetta & Oreffice, Sonia & Quintana-Domeque, Climent, 2021. "The effect of education on spousal education: A genetic approach," Labour Economics, Elsevier, vol. 71(C).
    4. von Hinke, Stephanie & Sørensen, Emil N., 2023. "The long-term effects of early-life pollution exposure: Evidence from the London smog," Journal of Health Economics, Elsevier, vol. 92(C).
    5. Cornelius A. Rietveld & Eric A.W. Slob & A. Roy Thurik, 2021. "A decade of research on the genetics of entrepreneurship: a review and view ahead," Small Business Economics, Springer, vol. 57(3), pages 1303-1317, October.
    6. Hans Fredrik Sunde & Nikolai Haahjem Eftedal & Rosa Cheesman & Elizabeth C. Corfield & Thomas H. Kleppesto & Anne Caroline Seierstad & Eivind Ystrom & Espen Moen Eilertsen & Fartein Ask Torvik, 2024. "Genetic similarity between relatives provides evidence on the presence and history of assortative mating," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    7. Nicola Barban & Elisabetta De Cao & Marco Francesconi, 2021. "Gene-Environment Effects on Female Fertility," CESifo Working Paper Series 9337, CESifo.
    8. Gianmarco Mignogna & Caitlin E. Carey & Robbee Wedow & Nikolas Baya & Mattia Cordioli & Nicola Pirastu & Rino Bellocco & Kathryn Fiuza Malerbi & Michel G. Nivard & Benjamin M. Neale & Raymond K. Walte, 2023. "Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci," Nature Human Behaviour, Nature, vol. 7(8), pages 1371-1387, August.
    9. Jonsdottir, Gudrun A. & Einarsson, Gudmundur & Thorleifsson, Gudmar & Magnusson, Sigurdur H. & Gunnarsson, Arni F. & Frigge, Michael L. & Gisladottir, Rosa S. & Unnsteinsdottir, Unnur & Gunnarsson, Bj, 2021. "Genetic propensities for verbal and spatial ability have opposite effects on body mass index and risk of schizophrenia," Intelligence, Elsevier, vol. 88(C).
    10. Quentin Lippmann & Khushboo Surana, 2022. "The Hierarchy of Partner Preferences," Discussion Papers 22/08, Department of Economics, University of York.
    11. Tabea Schoeler & Doug Speed & Eleonora Porcu & Nicola Pirastu & Jean-Baptiste Pingault & Zoltán Kutalik, 2023. "Participation bias in the UK Biobank distorts genetic associations and downstream analyses," Nature Human Behaviour, Nature, vol. 7(7), pages 1216-1227, July.
    12. Hyeokmoon Kweon & Casper A.P. Burik & Richard Karlsson Linner & Ronald de Vlaming & Aysu Okbay & Daphne Martschenko & Kathryn Paige Harden & Thomas A. DiPrete & Philipp D. Koellinger, 2020. "Genetic Fortune: Winning or Losing Education, Income, and Health," Tinbergen Institute Discussion Papers 20-053/V, Tinbergen Institute, revised 01 Dec 2020.
    13. Daniel J. Benjamin & David Cesarini & Patrick Turley & Alexander Strudwick Young, 2024. "Social-Science Genomics: Progress, Challenges, and Future Directions," NBER Working Papers 32404, National Bureau of Economic Research, Inc.
    14. Holden, Stein T. & Tilahun, Mesfin, 2022. "Can the risky investment game predict real world investments?," CLTS Working Papers 5/22, Norwegian University of Life Sciences, Centre for Land Tenure Studies.
    15. Thomas Buser & Rafael Ahlskog & Magnus Johannesson & Philipp Koellinger & Sven Oskarsson, 2021. "Using Genes to Explore the Effects of Cognitive and Non-cognitive Skills on Education and Labor Market Outcomes," Tinbergen Institute Discussion Papers 21-088/I, Tinbergen Institute, revised 29 Mar 2023.
    16. Jennifer Sjaarda & Zoltán Kutalik, 2023. "Partner choice, confounding and trait convergence all contribute to phenotypic partner similarity," Nature Human Behaviour, Nature, vol. 7(5), pages 776-789, May.
    17. Insoo Cho & Peter F. Orazem, 2021. "How endogenous risk preferences and sample selection affect analysis of firm survival," Small Business Economics, Springer, vol. 56(4), pages 1309-1332, April.
    18. Lee, Boram & Rosenthal, Leonard & Veld, Chris & Veld-Merkoulova, Yulia, 2015. "Stock market expectations and risk aversion of individual investors," International Review of Financial Analysis, Elsevier, vol. 40(C), pages 122-131.
    19. Mitchell, Brittany L. & Hansell, Narelle K. & McAloney, Kerrie & Martin, Nicholas G. & Wright, Margaret J. & Renteria, Miguel E. & Grasby, Katrina L., 2022. "Polygenic influences associated with adolescent cognitive skills," Intelligence, Elsevier, vol. 94(C).
    20. Mathias Seviiri & Matthew H. Law & Jue-Sheng Ong & Puya Gharahkhani & Pierre Fontanillas & Catherine M. Olsen & David C. Whiteman & Stuart MacGregor, 2022. "A multi-phenotype analysis reveals 19 susceptibility loci for basal cell carcinoma and 15 for squamous cell carcinoma," Nature Communications, Nature, vol. 13(1), pages 1-14, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-40069-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.