IDEAS home Printed from https://ideas.repec.org/a/bla/biomet/v79y2023i3p2184-2195.html
   My bibliography  Save this article

A novel penalized inverse‐variance weighted estimator for Mendelian randomization with applications to COVID‐19 outcomes

Author

Listed:
  • Siqi Xu
  • Peng Wang
  • Wing Kam Fung
  • Zhonghua Liu

Abstract

Mendelian randomization utilizes genetic variants as instrumental variables (IVs) to estimate the causal effect of an exposure variable on an outcome of interest even in the presence of unmeasured confounders. However, the popular inverse‐variance weighted (IVW) estimator could be biased in the presence of weak IVs, a common challenge in MR studies. In this article, we develop a novel penalized inverse‐variance weighted (pIVW) estimator, which adjusts the original IVW estimator to account for the weak IV issue by using a penalization approach to prevent the denominator of the pIVW estimator from being close to zero. Moreover, we adjust the variance estimation of the pIVW estimator to account for the presence of balanced horizontal pleiotropy. We show that the recently proposed debiased IVW (dIVW) estimator is a special case of our proposed pIVW estimator. We further prove that the pIVW estimator has smaller bias and variance than the dIVW estimator under some regularity conditions. We also conduct extensive simulation studies to demonstrate the performance of the proposed pIVW estimator. Furthermore, we apply the pIVW estimator to estimate the causal effects of five obesity‐related exposures on three coronavirus disease 2019 (COVID‐19) outcomes. Notably, we find that hypertensive disease is associated with an increased risk of hospitalized COVID‐19; and peripheral vascular disease and higher body mass index are associated with increased risks of COVID‐19 infection, hospitalized COVID‐19, and critically ill COVID‐19.

Suggested Citation

  • Siqi Xu & Peng Wang & Wing Kam Fung & Zhonghua Liu, 2023. "A novel penalized inverse‐variance weighted estimator for Mendelian randomization with applications to COVID‐19 outcomes," Biometrics, The International Biometric Society, vol. 79(3), pages 2184-2195, September.
  • Handle: RePEc:bla:biomet:v:79:y:2023:i:3:p:2184-2195
    DOI: 10.1111/biom.13732
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/biom.13732
    Download Restriction: no

    File URL: https://libkey.io/10.1111/biom.13732?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. Zhihong Zhu & Zhili Zheng & Futao Zhang & Yang Wu & Maciej Trzaskowski & Robert Maier & Matthew R. Robinson & John J. McGrath & Peter M. Visscher & Naomi R. Wray & Jian Yang, 2018. "Causal associations between risk factors and common diseases inferred from GWAS summary data," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    2. Nuala A Sheehan & Vanessa Didelez & Paul R Burton & Martin D Tobin, 2008. "Mendelian Randomisation and Causal Inference in Observational Epidemiology," PLOS Medicine, Public Library of Science, vol. 5(8), pages 1-6, 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. Noémi Kreif & Richard Grieve & M. Zia Sadique, 2013. "Statistical Methods For Cost‐Effectiveness Analyses That Use Observational Data: A Critical Appraisal Tool And Review Of Current Practice," Health Economics, John Wiley & Sons, Ltd., vol. 22(4), pages 486-500, April.
    2. Zhen Qiao & Julia Sidorenko & Joana A. Revez & Angli Xue & Xueling Lu & Katri Pärna & Harold Snieder & Peter M. Visscher & Naomi R. Wray & Loic Yengo, 2023. "Estimation and implications of the genetic architecture of fasting and non-fasting blood glucose," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    3. Wenhan Chen & Yang Wu & Zhili Zheng & Ting Qi & Peter M. Visscher & Zhihong Zhu & Jian Yang, 2021. "Improved analyses of GWAS summary statistics by reducing data heterogeneity and errors," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    4. 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).
    5. Kathryn E. Kemper & Julia Sidorenko & Huanwei Wang & Ben J. Hayes & Naomi R. Wray & Loic Yengo & Matthew C. Keller & Michael Goddard & Peter M. Visscher, 2024. "Genetic influence on within-person longitudinal change in anthropometric traits in the UK Biobank," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    6. Ciarrah Barry & Junxi Liu & Rebecca Richmond & Martin K Rutter & Deborah A Lawlor & Frank Dudbridge & Jack Bowden, 2021. "Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data," PLOS Genetics, Public Library of Science, vol. 17(8), pages 1-26, August.
    7. Gemma Cadby & Corey Giles & Phillip E. Melton & Kevin Huynh & Natalie A. Mellett & Thy Duong & Anh Nguyen & Michelle Cinel & Alex Smith & Gavriel Olshansky & Tingting Wang & Marta Brozynska & Mike Ino, 2022. "Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    8. Nicola Barban & Elisabetta De Cao & Sonia Oreffice & Climent Quintana-Domeque, 2016. "Assortative Mating on Education: A Genetic Assessment," Working Papers 2016-034, Human Capital and Economic Opportunity Working Group.
    9. Black, Nicole & Hughes, Robert & Jones, Andrew M., 2018. "The health care costs of childhood obesity in Australia: An instrumental variables approach," Economics & Human Biology, Elsevier, vol. 31(C), pages 1-13.
    10. Yi-Qian Sun & Rebecca C Richmond & Yue Chen & Xiao-Mei Mai, 2020. "Mixed evidence for the relationship between periodontitis and Alzheimer’s disease: A bidirectional Mendelian randomization study," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-9, January.
    11. Lilah M. Besser & Willa D. Brenowitz & Oanh L. Meyer & Serena Hoermann & John Renne, 2021. "Methods to Address Self-Selection and Reverse Causation in Studies of Neighborhood Environments and Brain Health," IJERPH, MDPI, vol. 18(12), pages 1-19, June.
    12. Matthew T. Patrick & Qinmengge Li & Rachael Wasikowski & Nehal Mehta & Johann E. Gudjonsson & James T. Elder & Xiang Zhou & Lam C. Tsoi, 2022. "Shared genetic risk factors and causal association between psoriasis and coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    13. Charley Xia & Sarah J. Pickett & David C. M. Liewald & Alexander Weiss & Gavin Hudson & W. David Hill, 2023. "The contributions of mitochondrial and nuclear mitochondrial genetic variation to neuroticism," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    14. Zipeng Liu & Yiming Qin & Tian Wu & Justin D. Tubbs & Larry Baum & Timothy Shin Heng Mak & Miaoxin Li & Yan Dora Zhang & Pak Chung Sham, 2023. "Reciprocal causation mixture model for robust Mendelian randomization analysis using genome-scale summary data," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    15. Xiaobo Li & Yuqiong Li & Bei Song & Shujie Guo & Shaoli Chu & Nan Jia & Wenquan Niu, 2012. "Hematopoietically-Expressed Homeobox Gene Three Widely-Evaluated Polymorphisms and Risk for Diabetes: A Meta-Analysis," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-10, November.
    16. Lina Zgaga & Felix Agakov & Evropi Theodoratou & Susan M Farrington & Albert Tenesa & Malcolm G Dunlop & Paul McKeigue & Harry Campbell, 2013. "Model Selection Approach Suggests Causal Association between 25-Hydroxyvitamin D and Colorectal Cancer," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-11, May.
    17. Yanjun Guo & Quanhong Liu & Zhilin Zheng & Mengxia Qing & Tianci Yao & Bin Wang & Min Zhou & Dongming Wang & Qinmei Ke & Jixuan Ma & Zhilei Shan & Weihong Chen, 2024. "Genetic association of inflammatory marker GlycA with lung function and respiratory diseases," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    18. William R. Reay & Michael P. Geaghan & Murray J. Cairns, 2022. "The genetic architecture of pneumonia susceptibility implicates mucin biology and a relationship with psychiatric illness," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    19. M d Mesbah Uddin & Ngoc Quynh H. Nguyen & Bing Yu & Jennifer A. Brody & Akhil Pampana & Tetsushi Nakao & Myriam Fornage & Jan Bressler & Nona Sotoodehnia & Joshua S. Weinstock & Michael C. Honigberg &, 2022. "Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease," Nature Communications, Nature, vol. 13(1), pages 1-16, December.
    20. Jessica M B Rees & Angela M Wood & Frank Dudbridge & Stephen Burgess, 2019. "Robust methods in Mendelian randomization via penalization of heterogeneous causal estimates," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-24, September.

    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:bla:biomet:v:79:y:2023:i:3:p:2184-2195. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .

    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.