Use of Multivariable Mendelian Randomization to Address Biases Due to Competing Risk Before Recruitment
Open accessAbstract
Background:Mendelian randomization (MR) provides unconfounded estimates. MR is open to selection bias when the underlying sample is selected on surviving to recruitment on the genetically instrumented exposure and competing risk of the outcome. Few methods to address this bias exist. Methods:We show that this selection bias can sometimes be addressed by adjusting for common causes of survival and outcome. We use multivariable MR to obtain a corrected MR estimate for statins on stroke. Statins affect survival, and stroke typically occurs later in life than ischemic heart disease (IHD), making estimates for stroke open to bias from competing risk. Results:In univariable MR in the UK Biobank, genetically instrumented statins did not protect against stroke [odds ratio (OR) 1.33, 95% confidence interval (CI) 0.80–2.20] but did in multivariable MR (OR 0.81, 95% CI 0.68–0.98) adjusted for major causes of survival and stroke [blood pressure, body mass index (BMI), and smoking initiation] with a multivariable Q-statistic indicating absence of selection bias. However, the MR estimate for statins on stroke using MEGASTROKE remained positive and the Q statistic indicated pleiotropy. Conclusion:MR studies of harmful exposures on late-onset diseases with shared etiology need to be conceptualized within a mechanistic understanding so as to identify any potential bias due to survival to recruitment on both genetically instrumented exposure and competing risk of the outcome, which may then be investigated using multivariable MR or estimated analytically and results interpreted accordingly.
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Study participation is heritable and influenced by a number of different traits, and large studies such as the UK Biobank have high levels of selection in those who participate.
“Study participation has shown to be heritable and is influenced by a number of different traits, and large studies such as the UK Biobank have been shown to have high levels of selection in those who participate.31,170–172”
From Mendelian randomization (2022) · cites this paper as [171]
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Causality: Models, Reasoning, and Inference
Pearl, J. (2009) · doi:10.1017/cbo9780511803161 · Cited by 11,653 · see citing works
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · see citing works
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · see citing works
Verbanck, M., Chen, C.-Y., Neale, B., & Do, R. (2018) · Nature Genetics · doi:10.1038/s41588-018-0099-7 · Cited by 8,591 · see citing works
Forouzanfar, M. H., Afshin, A., Alexander, L. T., Anderson, H. R., Bhutta, Z. A., Biryukov, S., Brauer, M., Burnett, R., Cercy, K., Charlson, F. J., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(16)31679-8 · Cited by 7,698 · see citing works
Self-citationGenetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Self-citationReading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians
Davies, N. M., Holmes, M. V., & Davey Smith, G. (2018) · BMJ · doi:10.1136/bmj.k601 · Cited by 4,404 · see citing works
Ettehad, D., Emdin, C. A., Kiran, A., Anderson, S. G., Callender, T., Emberson, J., Chalmers, J., Rodgers, A., & Rahimi, K. (2016) · The Lancet · doi:10.1016/s0140-6736(15)01225-8 · Cited by 3,755 · see citing works
Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption
Hartwig, F. P., Davey Smith, G., & Bowden, J. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx102 · Cited by 3,485 · see citing works
Forouzanfar, M. H., Alexander, L., Anderson, H. R., Bachman, V. F., Biryukov, S., Brauer, M., Burnett, R., Casey, D., Coates, M. M., Cohen, A., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(15)00128-2 · Cited by 2,701 · see citing works
Self-citationA comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
the CARDIoGRAMplusC4D Consortium (2015) · Nature Genetics · doi:10.1038/ng.3396 · Cited by 2,447 · see citing works
Malik, R., Chauhan, G., Traylor, M., Sargurupremraj, M., Okada, Y., Mishra, A., Rutten‐Jacobs, L. C. A., Giese, A., van der Laan, S. W., Grétarsdóttir, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0058-3 · Cited by 1,566 · see citing works
Zhou, W., Nielsen, J. B., Fritsche, L. G., Dey, R., Gabrielsen, M. E., Wolford, B. N., LeFaive, J., VandeHaar, P., Taliun, S. A. G., Gifford, A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0184-y · Cited by 1,406 · see citing works
Program, T. M. V., Evangelou, E., Warren, H. R., Mosen-Ansorena, D., Mifsud, B., Pazoki, R., Gao, H., Ntritsos, G., Dimou, N., Cabrera, C. P., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0205-x · Cited by 1,381 · see citing works
Self-citationMendelian randomization: prospects, potentials, and limitations
Smith, G. D. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh132 · Cited by 1,222 · see citing works
An introduction to instrumental variables for epidemiologists
Greenland, S. (2000) · International Journal of Epidemiology · doi:10.1093/ije/29.4.722 · Cited by 1,156 · see citing works
Sanderson, E., Davey Smith, G., Windmeijer, F., & Bowden, J. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyy262 · Cited by 1,085 · see citing works
Biobank-driven genomic discovery yields new insight into atrial fibrillation biology
Nielsen, J. B., Thorolfsdottir, R. B., Fritsche, L. G., Zhou, W., Skov, M. W., Graham, S. E., Herron, T. J., McCarthy, S., Schmidt, E. M., Sveinbjornsson, G., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0171-3 · Cited by 876 · see citing works
Collider scope: when selection bias can substantially influence observed associations
Munafò, M. R., Tilling, K., Taylor, A. E., Evans, D. M., & Davey Smith, G. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyx206 · Cited by 813 · see citing works
Mendelian randomization in cardiometabolic disease: challenges in evaluating causality
Holmes, M. V., Ala-Korpela, M., & Smith, G. D. (2017) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2017.78 · Cited by 679 · see citing works
Causal inference and the data-fusion problem
Bareinboim, E., & Pearl, J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1510507113 · Cited by 621 · see citing works
Statins for Prevention of Cardiovascular Disease in Adults
Chou, R., Dana, T., Blazina, I., Daeges, M., & Jeanne, T. L. (2016) · JAMA · doi:10.1001/jama.2015.15629 · Cited by 570 · see citing works
What can mendelian randomisation tell us about modifiable behavioural and environmental exposures?
Smith, G. D., & Ebrahim, S. (2005) · BMJ · doi:10.1136/bmj.330.7499.1076 · Cited by 545 · see citing works
Rees, J. M. B., Wood, A., & Burgess, S. (2017) · Statistics in Medicine · doi:10.1002/sim.7492 · Cited by 403 · see citing works
A meta-analysis of genome-wide association studies identifies multiple longevity genes
Deelen, J., Evans, D. S., Arking, D. E., Tesi, N., Nygaard, M., Liu, X., Wojczynski, M. K., Biggs, M. L., van der Spek, A., Atzmon, G., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11558-2 · Cited by 370 · see citing works
The Birth Weight "Paradox" Uncovered?
Hernández–Dı́az, S., Schisterman, E. F., & Hernán, M. Á. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj275 · Cited by 357 · see citing works
Verbanck, M., Chen, C., Neale, B. M., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0164-2 · Cited by 341 · see citing works
Mendelian Randomization Study of ACLY and Cardiovascular Disease
Ference, B. A., Ray, K. K., Catapano, A. L., Ference, T. B., Burgess, S., Neff, D., Oliver‐Williams, C., Wood, A., Butterworth, A. S., Angelantonio, E. D., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1806747 · Cited by 340 · see citing works
Mills, E. J., WU, P., Chong, G., Ghement, I., Singh, S., Akl, E. A., Eyawo, O., Guyatt, G., Berwanger, O., & Briel, M. (2011) · QJM · doi:10.1093/qjmed/hcq165 · Cited by 338 · see citing works
Use of Mendelian randomisation to assess potential benefit of clinical intervention.
Burgess, S., Butterworth, A., Malarstig, A., & Thompson, S. G. (2012) · BMJ · doi:10.1136/bmj.e7325 · Cited by 292 · see citing works
Nitsch, D., Molokhia, M., Smeeth, L. L., Stavola, B. L. D., Whittaker, J. C., & Leon, D. A. (2006) · American Journal of Epidemiology · doi:10.1093/aje/kwj062 · Cited by 228 · see citing works
PCSK9 monoclonal antibodies for the primary and secondary prevention of cardiovascular disease
Schmidt, A. F., Pearce, L. S., Wilkins, J. T., Overington, J. P., Hingorani, A. D., & Casas, J. P. (2017) · Cochrane Database of Systematic Reviews · doi:10.1002/14651858.cd011748.pub2 · Cited by 202 · see citing works
Swanson, S. A., Tiemeier, H., Ikram, M. A., & Hernán, M. A. (2017) · Epidemiology · doi:10.1097/ede.0000000000000699 · Cited by 202 · see citing works
Contextualizing selection bias in Mendelian randomization: how bad is it likely to be?
Gkatzionis, A., & Burgess, S. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyy202 · Cited by 182 · see citing works
Mendelian Randomization Study of Obesity and Cerebrovascular Disease
Marini, S., Merino, J., Montgomery, B. E., Malik, R., Sudlow, C. L. M., Dichgans, M., Florez, J. C., Rosand, J. M., Gill, D., & Anderson, C. D. (2020) · Annals of Neurology · doi:10.1002/ana.25686 · Cited by 147 · see citing works
Genetic predisposition to smoking in relation to 14 cardiovascular diseases
Larsson, S. C., Mason, A. M., Bäck, M., Klarin, D. M., Damrauer, S. M., Program, M. V., Michaëlsson, K., & Burgess, S. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa193 · Cited by 147 · see citing works
FinnGen, Sakaue, S., Kanai, M., Karjalainen, J. M., Akiyama, M., Kurki, M., Matoba, N., Takahashi, A., Hirata, M., Kubo, M., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-0785-8 · Cited by 119 · see citing works
Hartwig, F. P., Tilling, K. M., Smith, G. D., Lawlor, D. A., & Borges, M. C. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyaa266 · Cited by 116 · see citing works
Adjustment for index event bias in genome-wide association studies of subsequent events.
Dudbridge, F., Allen, R. J., Sheehan, N. A., Schmidt, A. F., Lee, J. C., Jenkins, R. G., Wain, L. V., Hingorani, A. D., & Patel, R. S. (2019) · Nature Communications · doi:10.1038/s41467-019-09381-w · Cited by 115 · see citing works
Hughes, R. A., Davies, N. M., Davey Smith, G., & Tilling, K. (2019) · Epidemiology · doi:10.1097/ede.0000000000000972 · Cited by 89 · see citing works
Survival Bias in Mendelian Randomization Studies: A Threat to Causal Inference
Smit, R. A. J., Trompet, S., Dekkers, O. M., Jukema, J. W., & le Cessie, S. (2019) · Epidemiology · doi:10.1097/ede.0000000000001072 · Cited by 83 · see citing works
Differential effects of PCSK9 variants on risk of coronary disease and ischaemic stroke
Hopewell, J. C., Malik, R., Valdés‐Márquez, E., Worrall, B. B., & Collins, R. (2017) · European Heart Journal · doi:10.1093/eurheartj/ehx373 · Cited by 75 · see citing works
Relative effects of LDL-C on ischemic stroke and coronary disease
Valdés‐Márquez, E., Parish, S., Clarke, R., Stari, T., Worrall, B. B., & Hopewell, J. C. (2019) · Neurology · doi:10.1212/wnl.0000000000007091 · Cited by 72 · see citing works
Instrumental Variable Analyses and Selection Bias
Canan, C. E., Lesko, C. R., & Lau, B. M. (2017) · Epidemiology · doi:10.1097/ede.0000000000000639 · Cited by 65 · see citing works
Using Instrumental Variables to Address Bias From Unobserved Confounders
Maciejewski, M. L., & Brookhart, M. A. (2019) · JAMA · doi:10.1001/jama.2019.5646 · Cited by 64 · see citing works
Emdin, C. A., Callender, T., Cao, J., & Rahimi, K. (2015) · EP Europace · doi:10.1093/europace/euv021 · Cited by 55 · see citing works
Nelson, C. P., Lai, F. Y., Nath, M., Ye, S., Webb, T. R., Schunkert, H., & Samani, N. J. (2019) · Circulation: Genomic and Precision Medicine · doi:10.1161/circgen.118.002196 · Cited by 55 · see citing works
Glymour, M. M., & Vittinghoff, E. (2013) · Epidemiology · doi:10.1097/ede.0000000000000013 · Cited by 48 · see citing works
Survivor bias in Mendelian randomization analysis
Vansteelandt, S., Dukes, O., & Martinussen, T. (2018) · Biostatistics · doi:10.1093/biostatistics/kxx050 · Cited by 46 · see citing works
Mendelian randomization studies in the elderly
Boef, A. G. C., le Cessie, S., & Dekkers, O. M. (2015) · Epidemiology · doi:10.1097/ede.0000000000000243 · Cited by 39 · see citing works
A Practical Guide to Selection Bias in Instrumental Variable Analyses
Swanson, S. A. (2019) · Epidemiology · doi:10.1097/ede.0000000000000973 · Cited by 36 · see citing works
Menotti, A., Puddu, P. E., Tolonen, H. K., Adachi, H., Kafatos, A., & Kromhout, D. (2018) · Acta cardiologica. Supplementum · doi:10.1080/00015385.2018.1453960 · Cited by 28 · see citing works
Peng, H., Yang, Y., Zhao, Y., & Xiao, H. (2018) · Pacing and Clinical Electrophysiology · doi:10.1111/pace.13485 · Cited by 23 · see citing works
AGE AT DEATH FROM DIFFERENT DISEASES: THE FLEMISH EXPERIENCE DURING THE PERIOD 2000-2004
Kesteloot, H., & Decramer, M. L. A. (2008) · Acta Clinica Belgica · doi:10.1179/acb.2008.047 · Cited by 18 · see citing works
Schooling, C. M., LOPEZ, P. M., Yang, Z., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/716621 · Cited by 17 · see citing works
Self-citationBiased Estimates in Mendelian Randomization Studies Conducted in Unrepresentative Samples
Munafo, M. R., & Smith, G. D. (2017) · JAMA Cardiology · doi:10.1001/jamacardio.2017.4279 · Cited by 15 · see citing works
Hartwig, F. P., Tilling, K., Smith, G. D., Lawlor, D. A., & Borges, M. C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/816363 · Cited by 14 · see citing works
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Self-citationYang, Q., Sanderson, E., Tilling, K., Borges, M. C., & Lawlor, D. A. (2019) · doi:10.1101/19009605 · Cited by 85 · see citing works
Schooling, C., Zhao, J., Au Yeung, S., & Leung, G. (2020) · eLife · doi:10.7554/elife.58567 · Cited by 39 · see citing works
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- Authors
- Schooling, C. M., Lopez, P. M., Yang, Z., Zhao, J. V., Au Yeung, S. L., & Huang, J. V.
- Affiliations
- City University of New York (US)
- University of Hong Kong (HK)
- Agency for Science, Technology and Research (SG)
- Corresponding author
- Schooling, C. M.
- Venue
- Frontiers in Genetics
- Publisher
- Frontiers Media SA
- Published
- 2021-01-15
- Volume
- 11
- Pages
- 610852-610852
- ISSN
- 1664-8021 (ISSN-L)
- PMC
- PMC7845663
- OpenAlex
- W3122256196
- Cited by
- 102
- References
- 57
- Citations by year
- 2026: 2 · 2025: 7 · 2024: 13 · 2023: 19 · 2022: 23 · 2021: 30 · 2020: 6 · 2019: 1
- FWCI
- 12.58
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Frontiers in Genetics (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Keywords
- multivariable Mendelian randomization, selection bias, competing risks, statins, stroke, ischemic heart disease, pleiotropy, q-statistics, blood pressure, body mass index, smoking initiation, late-onset disease, shared etiology
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