References
Burgess S, Davies NM, Thompson SG. Instrumental variable analysis with a nonlinear exposure-outcome relationship. Epidemiology. 2014;25(6):877–85. https://doi.org/10.1097/ede.0000000000000161.
Staley JR, Burgess S. Semiparametric methods for estimation of a nonlinear exposure-outcome relationship using instrumental variables with application to mendelian randomization. Genet Epidemiol. 2017;41(4):341–52.
Yusuf S, Wittes J, Probstfield J, Tyroler HA. Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials. JAMA. 1991;266(1):93–8.
Cole SR, Platt RW, Schisterman EF, et al. Illustrating bias due to conditioning on a collider. Int J Epidemiol. 2010;39(2):417–20.
Burgess S, Davies NM, Thompson SG. Instrumental variable analysis with a nonlinear exposure–outcome relationship. Epidemiology. 2014;25(6):877.
Burgess S. Violation of the constant genetic effect assumption can result in biased estimates for non-linear mendelian randomization. Human Hered. 2023;88(1):79–90.
Tian H, Mason AM, Liu C, Burgess S. Relaxing parametric assumptions for non-linear mendelian randomization using a doubly-ranked stratification method. PLoS Genet. 2023;19(6):e1010823. https://doi.org/10.1101/2022.06.28.497930.
Sofianopoulou E, Kaptoge SK, Afzal S, et al. Estimating dose-response relationships for vitamin D with coronary heart disease, stroke, and all-cause mortality: observational and mendelian randomisation analyses. Lancet Diabetes Endocrinol. 2024;12(1):e2–11.
Hamilton FW, Hughes DA, Spiller W, Tilling K, Davey Smith G. Non-linear mendelian randomization: detection of biases using negative controls with a focus on BMI, vitamin D and LDL-cholesterol. Eur J Epidemiol. 2024.
Burgess S, Sun Y-Q, Zhou A, Buck C, Mason AM, Mai X-M. Body mass index and all-cause mortality in HUNT and UK Biobank studies: revised non-linear Mendelian randomization analyses. medRxiv. 2023. https://doi.org/10.1101/2023.10.31.23297612.
Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol. 2017;186(9):1026–34.
Schoeler T, Speed D, Porcu E, Pirastu N, Pingault J-B, Kutalik Z. Participation bias in the UK Biobank distorts genetic associations and downstream analyses. Nat Hum Behav. 2023;7:1216–27. https://doi.org/10.1101/2022.09.28.509845.
Yang G, Mason AM, Wood AM, Schooling CM, Burgess S. Dose-response associations of lipid traits with coronary artery Disease and Mortality. JAMA Netw Open. 2024;7(1):e2352572.
Mason AM, Burgess S. Software Application Profile: SUMnlmr, an R package that facilitates flexible and reproducible non-linear mendelian randomization analyses. Int J Epidemiol. 2022;51(6):2014–9. https://doi.org/10.1093/ije/dyac150.
Manson JE, Cook NR, Lee I-M, et al. Vitamin D supplements and Prevention of Cancer and Cardiovascular Disease. N Engl J Med. 2019;380(1):33–44. https://doi.org/10.1056/NEJMoa1809944.
Burgess S, Thompson SG. Avoiding bias from weak instruments in mendelian randomization studies. Int J Epidemiol. 2011;40(3):755–64.
Burgess S, Davey Smith G, Davies NM, et al. Guidelines for performing mendelian randomization investigations. Wellcome Open Res. 2020;4:186. https://doi.org/10.12688/wellcomeopenres.15555.3.
Lawlor DA, Tilling K, Davey Smith G. Triangulation in aetiological epidemiology. Int J Epidemiol. 2016;45(6):1866–86.
Acknowledgements
The author would like to thank Benjamin Woolf, Dipender Gill, and Guoyi Yang for useful discussions in the development of this work.
Funding
This work was supported by the Wellcome Trust (225790/Z/22/Z) and the United Kingdom Research and Innovation Medical Research Council (MC_UU_00002/7).
Author information
Authors and Affiliations
Contributions
SB is the sole author of this work.
Corresponding author
Ethics declarations
Ethical approval
Not relevant – this paper does not contain data.
Conflict of interest
The author has no relevant financial or non-financial interests to disclose.
Consent to participate
Not relevant – this paper does not contain data.
Consent to publish
Not relevant – this paper does not contain data.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Burgess, S. Towards more reliable non-linear mendelian randomization investigations. Eur J Epidemiol (2024). https://doi.org/10.1007/s10654-024-01121-9
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s10654-024-01121-9