IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v7y2010i3p711-728d7227.html
   My bibliography  Save this article

Usefulness of Mendelian Randomization in Observational Epidemiology

Author

Listed:
  • Murielle Bochud

    (University Institute of Social and Preventive Medicine, Rue du Bugnon 17, 1005 Lausanne, Switzerland)

  • Valentin Rousson

    (University Institute of Social and Preventive Medicine, Rue du Bugnon 17, 1005 Lausanne, Switzerland)

Abstract

Mendelian randomization refers to the random allocation of alleles at the time of gamete formation. In observational epidemiology, this refers to the use of genetic variants to estimate a causal effect between a modifiable risk factor and an outcome of interest. In this review, we recall the principles of a “Mendelian randomization” approach in observational epidemiology, which is based on the technique of instrumental variables; we provide simulations and an example based on real data to demonstrate its implications; we present the results of a systematic search on original articles having used this approach; and we discuss some limitations of this approach in view of what has been found so far.

Suggested Citation

  • Murielle Bochud & Valentin Rousson, 2010. "Usefulness of Mendelian Randomization in Observational Epidemiology," IJERPH, MDPI, vol. 7(3), pages 1-18, February.
    • Handle: RePEc:gam:jijerp:v:7:y:2010:i:3:p:711-728:d:7227
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/7/3/711/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/7/3/711/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eric J Brunner & Mika Kivimäki & Daniel R Witte & Debbie A Lawlor & George Davey Smith & Jackie A Cooper & Michelle Miller & Gordon D O Lowe & Ann Rumley & Juan P Casas & Tina Shah & Steve E Humphries, 2008. "Inflammation, Insulin Resistance, and Diabetes—Mendelian Randomization Using CRP Haplotypes Points Upstream," PLOS Medicine, Public Library of Science, vol. 5(8), pages 1-9, August.
    2. James Robins & Andrea Rotnitzky, 2004. "Estimation of treatment effects in randomised trials with non-compliance and a dichotomous outcome using structural mean models," Biometrika, Biometrika Trust, vol. 91(4), pages 763-783, December.
    3. Debbie A Lawlor & Roger M Harbord & Nic J Timpson & Gordon D O Lowe & Ann Rumley & Tom R Gaunt & Ian Baker & John W G Yarnell & Mika Kivimäki & Meena Kumari & Paul E Norman & Konrad Jamrozik & Graeme , 2008. "The Association of C-Reactive Protein and CRP Genotype with Coronary Heart Disease: Findings from Five Studies with 4,610 Cases amongst 18,637 Participants," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-14, August.
    4. Nelson, Charles R & Startz, Richard, 1990. "The Distribution of the Instrumental Variables Estimator and Its t-Ratio When the Instrument Is a Poor One," The Journal of Business, University of Chicago Press, vol. 63(1), pages 125-140, January.
    5. Stock, James H & Wright, Jonathan H & Yogo, Motohiro, 2002. "A Survey of Weak Instruments and Weak Identification in Generalized Method of Moments," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 518-529, October.
    6. S. Vansteelandt & E. Goetghebeur, 2003. "Causal inference with generalized structural mean models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(4), pages 817-835, November.
    7. Mika Kivimäki & Debbie A Lawlor & George Davey Smith & Meena Kumari & Ann Donald & Annie Britton & Juan P Casas & Tina Shah & Eric Brunner & Nicholas J Timpson & Julian P J Halcox & Michelle A Miller , 2008. "Does High C-reactive Protein Concentration Increase Atherosclerosis? The Whitehall II Study," PLOS ONE, Public Library of Science, vol. 3(8), pages 1-8, August.
    Full references (including those not matched with items on IDEAS)

    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. Milo Bianchi & Paolo Buonanno & Paolo Pinotti, 2012. "Do Immigrants Cause Crime?," Journal of the European Economic Association, European Economic Association, vol. 10(6), pages 1318-1347, December.
    2. Russell Davidson & James G. MacKinnon, 2006. "The case against JIVE," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 827-833, September.
    3. Cai, Zongwu & Fang, Ying & Su, Jia, 2012. "Reducing asymptotic bias of weak instrumental estimation using independently repeated cross-sectional information," Statistics & Probability Letters, Elsevier, vol. 82(1), pages 180-185.
    4. Keane, Michael & Neal, Timothy, 2023. "Instrument strength in IV estimation and inference: A guide to theory and practice," Journal of Econometrics, Elsevier, vol. 235(2), pages 1625-1653.
    5. D.S. Poskitt & C.L. Skeels, 2005. "Small Concentration Asymptotics and Instrumental Variables Inference," Department of Economics - Working Papers Series 948, The University of Melbourne.
    6. Becker, Bo & Cronqvist, Henrik & Fahlenbrach, Rüdiger, 2011. "Estimating the Effects of Large Shareholders Using a Geographic Instrument," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(4), pages 907-942, August.
    7. Dufour, Jean-Marie & Khalaf, Lynda & Kichian, Maral, 2006. "Inflation dynamics and the New Keynesian Phillips Curve: An identification robust econometric analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1707-1727.
    8. Richard Startz & Charles Nelson & Eric Zivot, 1999. "Improved Inference for the Instrumental Variable Estimator," Working Papers 0039, University of Washington, Department of Economics.
    9. Dufour, Jean-Marie & Taamouti, Mohamed, 2007. "Further results on projection-based inference in IV regressions with weak, collinear or missing instruments," Journal of Econometrics, Elsevier, vol. 139(1), pages 133-153, July.
    10. Brian P. Poi, 2006. "Jackknife instrumental variables estimation in Stata," Stata Journal, StataCorp LLC, vol. 6(3), pages 364-376, September.
    11. Emma M. Iglesias & Garry D. A. Phillips, 2012. "Almost Unbiased Estimation in Simultaneous Equation Models With Strong and/or Weak Instruments," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(4), pages 505-520, June.
    12. Alastair R. Hall, 2015. "Econometricians Have Their Moments: GMM at 32," The Economic Record, The Economic Society of Australia, vol. 91(S1), pages 1-24, June.
    13. Paul S. Clarke & Frank Windmeijer, 2012. "Instrumental Variable Estimators for Binary Outcomes," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(500), pages 1638-1652, December.
    14. Paul S. Clarke & Tom M. Palmer & Frank Windmeijer, 2011. "Estimating Structural Mean Models with Multiple Instrumental Variables using the Generalised Method of Moments," The Centre for Market and Public Organisation 11/266, The Centre for Market and Public Organisation, University of Bristol, UK.
    15. repec:dau:papers:123456789/5382 is not listed on IDEAS
    16. Fuhrer, Jeffrey C. & Rudebusch, Glenn D., 2004. "Estimating the Euler equation for output," Journal of Monetary Economics, Elsevier, vol. 51(6), pages 1133-1153, September.
    17. Gonzalez-Hermosillo Gonzalez, B.M., 2008. "Transmission of shocks across global financial markets : The role of contagion and investors' risk appetite," Other publications TiSEM d684f3c7-7ad8-4e93-88cf-a, Tilburg University, School of Economics and Management.
    18. Han Zhang & Jing Qin & Sonja I. Berndt & Demetrius Albanes & Lu Deng & Mitchell H. Gail & Kai Yu, 2020. "On Mendelian randomization analysis of case‐control study," Biometrics, The International Biometric Society, vol. 76(2), pages 380-391, June.
    19. D. S. Poskitt & C. L. Skeels, 2004. "Approximating the Distribution of the Instrumental Variables Estimator when the Concentration Parameter is Small," Monash Econometrics and Business Statistics Working Papers 19/04, Monash University, Department of Econometrics and Business Statistics.
    20. He Jiwei & Stephens-Shields Alisa & Joffe Marshall, 2015. "Structural Nested Mean Models to Estimate the Effects of Time-Varying Treatments on Clustered Outcomes," The International Journal of Biostatistics, De Gruyter, vol. 11(2), pages 203-222, November.
    21. Pallab Ghosh & Kevin Grier & Jaeho Kim, 2021. "Heterogeneous endogeneity," Statistical Papers, Springer, vol. 62(2), pages 847-886, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:gam:jijerp:v:7:y:2010:i:3:p:711-728:d:7227. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.