Application of the Instrumental Inequalities to a Mendelian Randomization Study With Multiple Proposed Instruments
Open accessAbstract
Background: Investigators often support the validity of Mendelian randomization (MR) studies, an instrumental variable approach proposing genetic variants as instruments, via. subject matter knowledge. However, the instrumental variable model implies certain inequalities, offering an empirical method of falsifying (but not verifying) the underlying assumptions. Although these inequalities are said to detect only extreme assumption violations in practice, to our knowledge they have not been used in settings with multiple proposed instruments. Methods: We applied the instrumental inequalities to an MR analysis of the effect of maternal pregnancy vitamin D on offspring psychiatric outcomes, proposing four independent maternal genetic variants as instruments. We assessed whether the proposed instruments satisfied the instrumental inequalities separately and jointly and explored the instrumental inequalities’ properties via simulations. Results: The instrumental inequalities were satisfied (i.e., we did not falsify the MR model) when considering each variant separately. However, the inequalities were violated when considering four variants jointly and for some combinations of two or three variants (two of 36 two-variant combinations and 18 of 24 three-variant combinations). In simulations, the inequalities detected structural biases more often when assessing proposed instruments jointly, although falsification in the absence of structural bias remained rare. Conclusions: The instrumental inequalities detected violations of the MR assumptions for genetic variants jointly proposed as instruments in our study, although the instrumental inequalities were satisfied when considering each proposed instrument separately. We discuss how investigators can assess instrumental inequalities to eliminate clearly invalid analyses in settings with many proposed instruments and provide appropriate code.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
One further method for identifying potential violations of the IV conditions when the exposure is binary or categorical is using IV inequality constraints.
“One further method for identifying potential violations of the IV conditions when the exposure is binary or categorical is using IV inequality constraints.29,67,68”
From Mendelian randomization (2022) · cites this paper as [67]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Holick, M. F., Binkley, N., Bischoff-Ferrari, H. A., Gordon, C. M., Hanley, D. A., Heaney, R. P., Murad, M. H., & Weaver, C. M. (2011) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2011-0385 · Cited by 10,556 · 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
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
Pierce, B. L., Ahsan, H., & VanderWeele, T. J. (2010) · International Journal of Epidemiology · doi:10.1093/ije/dyq151 · Cited by 1,837 · see citing works
Vitamin D Status: Measurement, Interpretation, and Clinical Application
Holick, M. F. (2008) · Annals of Epidemiology · doi:10.1016/j.annepidem.2007.12.001 · Cited by 1,663 · see citing works
Common genetic determinants of vitamin D insufficiency: a genome-wide association study
Wang, T. J., Zhang, F., Richards, J. B., Kestenbaum, B. R., van Meurs, J. B. J., Berry, D. J., Kiel, D. P., Streeten, E. A., Ohlsson, C., Koller, D. L., et al. (2010) · The Lancet · doi:10.1016/s0140-6736(10)60588-0 · Cited by 1,538 · see citing works
Vimaleswaran, K. S., Berry, D. J., Lu, C., Tikkanen, E., Pilz, S., Hiraki, L. T., Cooper, J. D., Dastani, Z., Li, R., Houston, D. K., et al. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001383 · Cited by 1,046 · see citing works
The Generation R Study: design and cohort update 2010
Jaddoe, V. W. V., van Duijn, C. M., van der Heijden, A. J., Mackenbach, J. P., Moll, H. A., Steegers, E. A. P., Tiemeier, H., Uitterlinden, A. G., Verhulst, F. C., & Hofman, A. (2010) · European Journal of Epidemiology · doi:10.1007/s10654-010-9516-7 · Cited by 1,027 · see citing works
Self-citationCausal associations between risk factors and common diseases inferred from GWAS summary data
Zhu, Z., Zheng, Z., Zhang, F., Wu, Y., Trzaskowski, M., Maier, R., Robinson, M. R., McGrath, J. J., Visscher, P. M., Wray, N. R., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02317-2 · Cited by 951 · see citing works
NONPARAMETRIC BOUNDS ON TREATMENT EFFECTS
Manski, C. F. (1989) · American Economic Review · Cited by 801 · see citing works
Bounds on Treatment Effects from Studies with Imperfect Compliance
Balke, A., & Pearl, J. (1997) · Journal of the American Statistical Association · doi:10.1080/01621459.1997.10474074 · Cited by 564 · see citing works
Methodological Challenges in Mendelian Randomization
VanderWeele, T. J., Tchetgen Tchetgen, E. J., Cornelis, M., & Kraft, P. (2014) · Epidemiology · doi:10.1097/ede.0000000000000081 · Cited by 555 · see citing works
Use of allele scores as instrumental variables for Mendelian randomization
Burgess, S., & Thompson, S. G. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dyt093 · Cited by 452 · see citing works
Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study
Mokry, L. E., Ross, S., Ahmad, O. S., Forgetta, V., Smith, G. D., Leong, A., Greenwood, C. M. T., Thanassoulis, G., & Richards, J. B. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001866 · Cited by 445 · see citing works
Glymour, M. M., Tchetgen Tchetgen, E. J., & Robins, J. M. (2012) · American Journal of Epidemiology · doi:10.1093/aje/kwr323 · Cited by 292 · see citing works
Kang, H., Zhang, A., Cai, T. T., & Small, D. S. (2016) · Journal of the American Statistical Association · doi:10.1080/01621459.2014.994705 · Cited by 265 · see citing works
Hudziak, J., Copeland, W., Stanger, C., & Wadsworth, M. (2004) · Journal of Child Psychology and Psychiatry and Allied Disciplines · doi:10.1111/j.1469-7610.2004.00314.x · Cited by 259 · see citing works
(2015) · Apple Academic Press eBooks · doi:10.1201/b18536-15 · Cited by 256 · see citing works
Mental health in Dutch children: (I) a cross‐cultural comparison
Verhulst, F. C., Akkerhuis, G. W., & Althaus, M. (1985) · Acta Psychiatrica Scandinavica · doi:10.1111/j.1600-0447.1985.tb10512.x · Cited by 227 · see citing works
The Generation R Study: Biobank update 2015
Kruithof, C. J., Kooijman, M. N., van Duijn, C. M., Franco, O. H., de Jongste, J. C., Klaver, C. C. W., Mackenbach, J. P., Moll, H. A., Raat, H., Rings, E. H. H. M., et al. (2014) · European Journal of Epidemiology · doi:10.1007/s10654-014-9980-6 · Cited by 225 · see citing works
Self-citationCommentary: How to Report Instrumental Variable Analyses (Suggestions Welcome)
Swanson, S. A., & Hernán, M. A. (2013) · Epidemiology · doi:10.1097/ede.0b013e31828d0590 · Cited by 197 · see citing works
Self-citationGestational vitamin D deficiency and autism-related traits: the Generation R Study
Vinkhuyzen, A. A. E., Eyles, D. W., Burne, T. H. J., Blanken, L. M. E., Kruithof, C. J., Verhulst, F. C., Jaddoe, V. W. V., Tiemeier, H. W., & McGrath, J. J. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.213 · Cited by 197 · see citing works
Self-citationWhy the minimum desirable serum 25-hydroxyvitamin D level should be 75 nmol/L (30 ng/ml)
Vieth, R. (2011) · Best Practice & Research Clinical Endocrinology & Metabolism · doi:10.1016/j.beem.2011.06.009 · Cited by 192 · see citing works
Labrecque, J., & Swanson, S. A. (2018) · Current Epidemiology Reports · doi:10.1007/s40471-018-0152-1 · Cited by 190 · see citing works
Self-citationAssociation of vitamin D levels and risk of ovarian cancer: a Mendelian randomization study
Ong, J., Cuéllar-Partida, G., Lu, Y., Study, A. O. C., Fasching, P. A., Hein, A., Burghaus, S., Beckmann, M. W., Lambrechts, D., Nieuwenhuysen, E. V., et al. (2016) · International Journal of Epidemiology · doi:10.1093/ije/dyw207 · Cited by 136 · see citing works
Sikora, D. M., Hall, T. A., Hartley, S. L., Gerrard-Morris, A. E., & Cagle, S. E. (2007) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-007-0407-z · Cited by 135 · see citing works
Lawlor, D. A., Richmond, R. C., Warrington, N. M., McMahon, G., Smith, G. D., Bowden, J., & Evans, D. M. (2017) · Wellcome Open Research · doi:10.12688/wellcomeopenres.10567.1 · Cited by 129 · see citing works
Groot, A. D., Koot, H. M., & Verhulst, F. C. (1996) · Research on Child and Adolescent Psychopathology · doi:10.1007/bf01670105 · Cited by 116 · see citing works
14-Year Changes in Emotional and Behavioral Problems of Very Young Dutch Children
Tick, N. T., van der Ende, J., Koot, H. M., & Verhulst, F. C. (2007) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/chi.0b013e3181337532 · Cited by 96 · see citing works
Greenland, S., & Mansournia, M. A. (2015) · European Journal of Epidemiology · doi:10.1007/s10654-015-9995-7 · Cited by 84 · 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
Swanson, S. A., Labrecque, J. A., & Hernán, M. Á. (2018) · European Journal of Epidemiology · doi:10.1007/s10654-018-0396-6 · Cited by 40 · see citing works
Self-citationA 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
Self-citationSoma, Y., Nakamura, K., Oyama, M., Tsuchiya, Y., & Yamamoto, M. (2009) · Environmental Health and Preventive Medicine · doi:10.1007/s12199-008-0075-4 · Cited by 33 · see citing works
Erratum: On falsification of the binary instrumental variable model
Wang, L., Robins, J. M., & Richardson, T. S. (2017) · Biometrika · doi:10.1093/biomet/asx011 · Cited by 21 · see citing works
Likelihood analysis of the binary instrumental variable model
Ramsahai, R. R., & Lauritzen, S. L. (2011) · Biometrika · doi:10.1093/biomet/asr040 · Cited by 19 · see citing works
On falsification of the binary instrumental variable model
Wang, L., Robins, J. M., & Richardson, T. S. (2016) · Biometrika · doi:10.1093/biomet/asw064 · Cited by 19 · see citing works
Flagged first, then by citations
1 of the 40 references couldn’t be matched to a known paper.
Research works printed but not linked: 4
- [10]Tchetgen EJT Sun B Walter S The GENIUS approach to robust Mendelian randomization inference. 2017 arXiv preprint arXiv:1709.07779. · arXiv
- [14]Pearl J On the testability of causal models with latent and instrumental variables. In: Proceedings of the Eleventh Conference on Uncertainty in Artificial Intelligence August 18–20, 1995 San Francisco, CA: Morgan Kaufmann Publishers Inc.
- [15]Bonet B Instrumentality tests revisited. In: Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence August 2–5, 2001 San Francisco, CA: Morgan Kaufmann Publishers Inc.
- [31]Ross AC Taylor CL Yaktine AL; Institute of Medicine (US) Committee to Review Dietary Reference Intakes for Vitamin D and Calcium. Dietary Reference Intakes for Calcium and Vitamin D. 2011 Washington, DC: The National Academies Press. 21796828
Cited by
Sorted by citations
Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., Palmer, T., Schooling, C. M., Wallace, C., Zhao, Q., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00092-5 · Cited by 2,229 · see citing works
Yang, Q., Sanderson, E., Tilling, K., Borges, M. C., & Lawlor, D. A. (2019) · doi:10.1101/19009605 · Cited by 85 · see citing works
Power, G. M., Sanderson, E. C. M., Pagoni, P., Fraser, A., Morris, T., Prince, C., Frayling, T. M., Heron, J., Richardson, T. G., Richmond, R. C., et al. (2023) · European Journal of Epidemiology · doi:10.1007/s10654-023-01032-1 · Cited by 61 · see citing works
Mendelian Randomization With Repeated Measures of a Time-varying Exposure
Shi, J., Swanson, S. A., Kraft, P., ROSNER, B. A., Vivo, I. D., & Hernán, M. Á. (2021) · Epidemiology · doi:10.1097/ede.0000000000001417 · Cited by 28 · see citing works
Self-citationMendelian randomisation approaches to the study of prenatal exposures: A systematic review
Diemer, E. W., Labrecque, J. A., Neumann, A., Tiemeier, H., & Swanson, S. A. (2021) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12691 · Cited by 21 · see citing works
Self-citationSwanson, S. A., & Miller, M. (2024) · American Journal of Epidemiology · doi:10.1093/aje/kwae036 · Cited by 12 · see citing works
Self-citationHomayra, F., Enns, B., Min, J. E., Kurz, M., Bach, P., Bruneau, J., Greenland, S., Gustafson, P., Karim, M. E., Korthuis, P. T., et al. (2023) · Epidemiology · doi:10.1097/ede.0000000000001697 · Cited by 9 · see citing works
Guo, K., Diemer, E. W., Labrecque, J. A., & Swanson, S. A. (2023) · European Journal of Epidemiology · doi:10.1007/s10654-023-01003-6 · Cited by 9 · see citing works
Self-citationDiemer, E. W., Havdahl, A., Andreassen, O. A., Munafo, M. R., Njølstad, P. R., Tiemeier, H. W., Zuccolo, L., & Swanson, S. A. (2023) · Paediatric and Perinatal Epidemiology · doi:10.1111/ppe.12951 · Cited by 6 · see citing works
Self-citationSanderson, E. C. M., & Smith, G. D. (2023) · European Journal of Epidemiology · doi:10.1007/s10654-023-01035-y · Cited by 5 · see citing works
Trane, R. M., & Kang, H. (2022) · Statistics in Medicine · doi:10.1002/sim.9368 · Cited by 4 · see citing works
Diemer, E. W., Zuccolo, L., & Swanson, S. A. (2022) · Epidemiology · doi:10.1097/ede.0000000000001526 · Cited by 4 · see citing works
Self-citationRejoinder: Handgun Divestment and Risk of Suicide
Swanson, S. A., Studdert, D. M., Zhang, Y., & Miller, M. (2023) · Epidemiology · doi:10.1097/ede.0000000000001585 · Cited by 4 · see citing works
Self-citationThe Causal Effects of Causal Inference Pedagogy
Swanson, S. A. (2023) · Epidemiology · doi:10.1097/ede.0000000000001639 · Cited by 4 · see citing works
Self-citationDiemer and Swanson Reply to “Considerations Before Using Pandemic as Instrument”
Diemer, E. W., & Swanson, S. A. (2021) · American Journal of Epidemiology · doi:10.1093/aje/kwab175 · Cited by 3 · see citing works
Self-citationDiemer, E. W., Havdahl, A., Andreassen, O. A., Munafo, M. R., Njølstad, P. R., Tiemeier, H. W., Zuccolo, L., & Swanson, S. A. (2022) · medRxiv · doi:10.1101/2022.05.10.22274902 · Cited by 2 · see citing works
Self-citationDimitris, M. C., & Platt, R. W. (2021) · American Journal of Epidemiology · doi:10.1093/aje/kwab230
Diemer, E. W. (2024) · Epidemiology · doi:10.1097/ede.0000000000001751
Self-citationDiemer, E. W., Shi, J., Hernán, M. Á., & Swanson, S. A. (2024) · European Journal of Epidemiology · doi:10.1007/s10654-024-01130-8
Self-citation
- Authors
- Diemer, E. W., Labrecque, J., Tiemeier, H., & Swanson, S. A.
- Affiliations
- Erasmus MC (NL)
- Harvard University (US)
- Corresponding author
- Diemer, Elizabeth W.
- Venue
- Epidemiology
- Published
- 2020-01
- Volume
- 31
- Issue
- 1
- Pages
- 65-74
- ISSN
- 1044-3983 (ISSN-L)
- PMC
- PMC6889903
- OpenAlex
- W2980988155
- Cited by
- 19
- References
- 40
- Citations by year
- 2024: 3 · 2023: 7 · 2022: 5 · 2021: 3 · 2020: 1
- FWCI
- 1.76
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Epidemiology (publishedVersion, cc-by-nc-nd)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
- Funders
- ZonMw (91617066)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- Mendelian randomization, multiple instruments, assessment validity, structural bias, maternal vitamin D, genetic variants, simulation study
- MeSH terms
- Humans, Bias, Mendelian Randomization Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
