Cited by 3,485Genetic Associations and EpidemiologyAdvanced Causal Inference TechniquesMeta-analysis and systematic reviews

The DOI matches its Crossref record; 27 of the 28 references it cites were found in a registry or an index.

Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption

Open access

Hartwig, Fernando Pires, Davey Smith, George, Bowden, Jack·2017·International Journal of Epidemiology

DOI 10.1093/ije/dyx102PMC PMC5837715

Published version of a preprint

Open this paper in CoChat — free account Open PDF

Abstract

Background: Mendelian randomization (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions. Methods: Here, a new method - the mode-based estimate (MBE) - is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk. Results: The MBE presented less bias and lower type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared with the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia. Conclusions: The MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in sensitivity analyses.

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

Crossref · 10.1093/ije/dyx102

Cites

27 of 27 references verified0 citation errors · 0 not checkable

Statistics

Figure 1 Illustration of the ZEro Modal Pleiotropy Assumption (ZEMPA) in the simple (i.e. unweighted) mode-based estimate (MBE). βM is the simple MBE causal effect and β is the true causal effect; nldenotes the number of variants with a given horizontal pleiotropic effect (n0 denotes the number of valid instruments). Panel A: ZEMPA is satisfied. Panel B: ZEMPA is violated. SNP, single nucleotide polymorphism.CC BY · PubMed Central

Figure 2 Weighteda empirical density function of all individual-instrument ratio causal effect estimates (β^Rj) of plasma LDL-C (panel A), HDL-C (panel B), triglycerides (panel C) and urate (panel D) levels on ln(odds ratio) of coronary heart disease for different values of the tuning parameter ϕ. LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol. The dashed line indicates the zero value. aWeights were calculated without making the NOME assumption.CC BY · PubMed Central

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,938
Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816
Self-citation
Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922
Self-citation
Density Estimation for Statistics and Data Analysis
(1986) · Springer eBooks · doi:10.1007/978-1-4899-3324-9 · Cited by 8,514
Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
Burgess, S., Butterworth, A., & Thompson, S. G. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21758 · Cited by 6,050
‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*
Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882
Mendelian randomization: genetic anchors for causal inference in epidemiological studies
Davey Smith, G., & Hemani, G. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu328 · Cited by 4,677
Untitled work
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983
Sensitivity Analyses for Robust Causal Inference from Mendelian Randomization Analyses with Multiple Genetic Variants
Burgess, S., Bowden, J., Fall, T., Ingelsson, E., & Thompson, S. G. (2017) · Epidemiology · doi:10.1097/ede.0000000000000559 · Cited by 2,017
Self-citation
A framework for the investigation of pleiotropy in two‐sample summary data Mendelian randomization
Bowden, J., Del Greco M, F., Minelli, C., Davey Smith, G., Sheehan, N., & Thompson, J. (2017) · Statistics in Medicine · doi:10.1002/sim.7221 · Cited by 1,887
Self-citation

Show all 28 references

Sorted by citations

Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases
Verbanck, M., Chen, C.-Y., Neale, B., & Do, R. (2018) · Nature Genetics · doi:10.1038/s41588-018-0099-7 · Cited by 8,591
The MR-Base platform supports systematic causal inference across the human phenome
Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959
Self-citation
Reading 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
Mendelian randomization
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
Large-scale association analyses identify host factors influencing human gut microbiome composition
Kurilshikov, A., Medina-Gomez, C., Bacigalupe, R., Radjabzadeh, D., Wang, J., Demirkan, A., Le Roy, C. I., Raygoza Garay, J. A., Finnicum, C. T., Liu, X., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00763-1 · Cited by 1,786
Guidelines for performing Mendelian randomization investigations
Burgess, S., Smith, G. D., Davies, N. M., Dudbridge, F., Gill, D., Glymour, M. M., Hartwig, F. P., Holmes, M. V., Minelli, C., Relton, C. L., et al. (2019) · Wellcome Open Research · doi:10.12688/wellcomeopenres.15555.1 · Cited by 1,828
Self-citation
Meta‐analysis and Mendelian randomization: A review
Bowden, J., & Holmes, M. V. (2019) · Research Synthesis Methods · doi:10.1002/jrsm.1346 · Cited by 1,683
Self-citation
Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration.
Skrivankova, V. W., Richmond, R. C., Woolf, B. A. R., Davies, N. M., Swanson, S. A., VanderWeele, T. J., Timpson, N. J., Higgins, J. P. T., Dimou, N., Langenberg, C., et al. (2021) · BMJ · doi:10.1136/bmj.n2233 · Cited by 1,648
Evaluating the potential role of pleiotropy in Mendelian randomization studies
Hemani, G., Bowden, J., & Davey Smith, G. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy163 · Cited by 1,496
“assumption (ZEMPA) and calculate the weighted mode of the Wald ratio estimates (65).”
MethodSelf-citation
Guidelines for performing Mendelian randomization investigations
Burgess, S., Davey Smith, G., Davies, N. M., Dudbridge, F., Gill, D., Glymour, M. M., Hartwig, F. P., Holmes, M. V., Minelli, C., Relton, C. L., et al. (2020) · Wellcome Open Research · doi:10.12688/wellcomeopenres.15555.2 · Cited by 1,273
Self-citation
Recent Developments in Mendelian Randomization Studies
Zheng, J., Baird, D. A., Borges, M. C., Bowden, J., Hemani, G., Haycock, P., Evans, D. M., & Smith, G. D. (2017) · Current Epidemiology Reports · doi:10.1007/s40471-017-0128-6 · Cited by 1,147
Self-citation
Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis
Richardson, T. G., Sanderson, E., Palmer, T. M., Ala-Korpela, M., Ference, B. A., Davey Smith, G., & Holmes, M. V. (2020) · PLOS Medicine · doi:10.1371/journal.pmed.1003062 · Cited by 843
Statistical inference in two-sample summary-data Mendelian randomization using robust adjusted profile score
Zhao, Q., Wang, J., Hemani, G., Bowden, J., & Small, D. S. (2020) · The Annals of Statistics · doi:10.1214/19-aos1866 · Cited by 868
Self-citation
Mendelian Randomization: Concepts and Scope
Richmond, R. C., & Davey Smith, G. (2022) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a040501 · Cited by 841
Multivariable Mendelian Randomization and Mediation
Sanderson, E. (2021) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a038984 · Cited by 827
Guidelines for performing Mendelian randomization investigations: update for summer 2023
Burgess, S., Smith, G. D., Davies, N. M., Dudbridge, F., Gill, D., Glymour, M. M., Hartwig, F. P., Kutalik, Z., Holmes, M. V., Minelli, C., et al. (2023) · Wellcome Open Research · doi:10.12688/wellcomeopenres.15555.3 · Cited by 747
Self-citation
A robust and efficient method for Mendelian randomization with hundreds of genetic variants
Burgess, S., Foley, C. N., Allara, E., Staley, J. R., & Howson, J. M. M. (2020) · Nature Communications · doi:10.1038/s41467-019-14156-4 · Cited by 681
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
A comparison of robust Mendelian randomization methods using summary data
Slob, E. A. W., & Burgess, S. (2020) · Genetic Epidemiology · doi:10.1002/gepi.22295 · Cited by 644
Stroke genetics informs drug discovery and risk prediction across ancestries
Mishra, A., Malik, R., Hachiya, T., Jürgenson, T., Namba, S., Posner, D. C., Kamanu, F., Koido, M., Grand, Q. L., Shi, M., et al. (2022) · Nature · doi:10.1038/s41586-022-05165-3 · Cited by 623
Testing and correcting for weak and pleiotropic instruments in two‐sample multivariable Mendelian randomization
Sanderson, E. C. M., Spiller, W., & Bowden, J. (2021) · Statistics in Medicine · doi:10.1002/sim.9133 · Cited by 603
Self-citation
Mendelian randomization accounting for correlated and uncorrelated pleiotropic effects using genome-wide summary statistics
Morrison, J., Knoblauch, N., Marcus, J. H., Stephens, M., & He, X. (2020) · Nature Genetics · doi:10.1038/s41588-020-0631-4 · Cited by 587
Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort
Qin, Y., Havulinna, A. S., Liu, Y., Jousilahti, P., Ritchie, S. C., Tokolyi, A., Sanders, J. G., Valsta, L., Brożyńska, M., Zhu, Q., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00991-z · Cited by 586
Evidence for causal effects of lifetime smoking on risk for depression and schizophrenia: a Mendelian randomisation study
Wootton, R. E., Richmond, R. C., Stuijfzand, B. G., Lawn, R. B., Sallis, H. M., Taylor, G. M. J., Hemani, G., Jones, H. J., Zammit, S., Davey Smith, G., et al. (2020) · Psychological Medicine · doi:10.1017/s0033291719002678 · Cited by 587
Association between gut microbiota and preeclampsia-eclampsia: a two-sample Mendelian randomization study
Li, P., Wang, H., Guo, L., Gou, X., Chen, G., Lin, D., Fan, D., Guo, X., & Liu, Z. (2022) · BMC Medicine · doi:10.1186/s12916-022-02657-x · Cited by 581
15 years of GWAS discovery: Realizing the promise
Abdellaoui, A., Yengo, L., Verweij, K. J. H., & Visscher, P. M. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.12.011 · Cited by 570
GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability
Pasman, J. A., Verweij, K. J. H., Gerring, Z. F., Stringer, S., Sanchez‐Roige, S., Treur, J. L., Abdellaoui, A., Nivard, M. G., Baselmans, B. M. L., Ong, J., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0206-1 · Cited by 505
Bias correction for inverse variance weighting Mendelian randomization
Mounier, N., & Kutalik, Z. (2023) · Genetic Epidemiology · doi:10.1002/gepi.22522 · Cited by 451
Using genetic data to strengthen causal inference in observational research
Pingault, J.-B., O’Reilly, P. F., Schoeler, T., Ploubidis, G. B., Rijsdijk, F., & Dudbridge, F. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0020-3 · Cited by 444
Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses
Brumpton, B., Sanderson, E., Heilbron, K., Hartwig, F. P., Harrison, S., Vie, G. Å., Cho, Y., Howe, L. D., Hughes, A., Boomsma, D. I., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17117-4 · Cited by 402
Self-citation
GWAS identifies 14 loci for device-measured physical activity and sleep duration
Doherty, A., Smith-Byrne, K., Ferreira, T., Holmes, M. V., Holmes, C., Pulit, S. L., & Lindgren, C. M. (2018) · Nature Communications · doi:10.1038/s41467-018-07743-4 · Cited by 408
Mendelian randomization study of inflammatory bowel disease and bone mineral density
Wu, F., Huang, Y., Hu, J., & Shao, Z. (2020) · BMC Medicine · doi:10.1186/s12916-020-01778-5 · Cited by 404
Causal relationship between gut microbiota and cancers: a two-sample Mendelian randomisation study
Long, Y., Tang, L., Zhou, Y., Zhao, S., & Zhu, H. (2023) · BMC Medicine · doi:10.1186/s12916-023-02761-6 · Cited by 404
Distinguishing genetic correlation from causation across 52 diseases and complex traits
O’Connor, L. J., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0255-0 · Cited by 394
Mendelian randomization analyses support causal relationships between blood metabolites and the gut microbiome
Liu, X., Tong, X., Zou, Y., Lin, X., Zhao, H., Tian, L., Jie, Z., Wang, Q., Zhang, Z., Lu, H., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-00968-y · Cited by 383
The Mediterranean diet, plasma metabolome, and cardiovascular disease risk
Li, J., Guasch‐Ferré, M., Chung, W., Ruiz‐Canela, M., Toledo, E., Corella, D., Bhupathiraju, S. N., Tobias, D. K., Tabung, F. K., Hu, J., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa209 · Cited by 373
Constrained maximum likelihood-based Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects
Xue, H., Shen, X., & Pan, W. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.05.014 · Cited by 355
Implementing MR‐PRESSO and GCTA‐GSMR for pleiotropy assessment in Mendelian randomization studies from a practitioner's perspective
Ong, J., & MacGregor, S. (2019) · Genetic Epidemiology · doi:10.1002/gepi.22207 · Cited by 353
The use of two-sample methods for Mendelian randomization analyses on single large datasets
Minelli, C., Fabiola Del Greco, M., van der Plaat, D. A., Bowden, J., Sheehan, N. A., & Thompson, J. R. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab084 · Cited by 333
Self-citation
Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits.
Porcu, E., Rüeger, S., Lepik, K., eQTLGen Consortium, Agbessi, M., Ahsan, H., Alves, I., Andiappan, A., Arindrarto, W., Awadalla, P., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10936-0 · Cited by 322
Statistical methods for Mendelian randomization in genome-wide association studies: A review
Boehm, F. J., & Zhou, X. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.05.015 · Cited by 333
Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model
Lin, Z., Deng, Y., & Pan, W. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009922 · Cited by 326
Causal role of immune cells in schizophrenia: Mendelian randomization (MR) study
Wang, C., Zhu, D., Zhang, D., Zuo, X., Yao, L., Liu, T., Ge, X., He, C., Zhou, Y., & Shen, Z. (2023) · BMC Psychiatry · doi:10.1186/s12888-023-05081-4 · Cited by 322
Inferring Causal Relationships Between Risk Factors and Outcomes from Genome-Wide Association Study Data
Burgess, S., Foley, C. N., & Zuber, V. (2018) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-083117-021731 · Cited by 291
Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging
McCartney, D. L., Min, J. L., Richmond, R. C., Lu, A. T.-H., Sobczyk, M., Davies, G., Broer, L., Guo, X., Jeong, A., Jung, J., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02398-9 · Cited by 310
Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect
Tadros, R., Francis, C., Xu, X. Y., Vermeer, A. M. C., Harper, A. R., Huurman, R., Bisabu, K. K., Walsh, R., Hoorntje, E. T., Rijdt, W. P. T., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00762-2 · Cited by 288
Advancing the use of genome-wide association studies for drug repurposing
Reay, W. R., & Cairns, M. J. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-021-00387-z · Cited by 284
Invited Commentary: Detecting Individual and Global Horizontal Pleiotropy in Mendelian Randomization-A Job for the Humble Heterogeneity Statistic?
Bowden, J., Hemani, G., & Davey Smith, G. (2018) · American Journal of Epidemiology · doi:10.1093/aje/kwy185 · Cited by 251
Self-citation
Evidence of a causal relationship between body mass index and psoriasis: A mendelian randomization study
Budu‐Aggrey, A., Brumpton, B. M., Tyrrell, J., Watkins, S., Modalsli, E. H., Celis-Morales, C. A., Ferguson, L. D., Vie, G. Å., Palmer, T., Fritsche, L. G., et al. (2019) · PLoS Medicine · doi:10.1371/journal.pmed.1002739 · Cited by 268
Genome-wide associations of human gut microbiome variation and implications for causal inference analyses
Hughes, D. A., Bacigalupe, R., Wang, J., Rühlemann, M. C., Tito, R. Y., Falony, G., Joossens, M., Vieira‐Silva, S., Henckaerts, L., Rymenans, L., et al. (2020) · Nature Microbiology · doi:10.1038/s41564-020-0743-8 · Cited by 247
Selecting likely causal risk factors from high-throughput experiments using multivariable Mendelian randomization
Zuber, V., Colijn, J. M., Klaver, C. C. W., & Burgess, S. (2020) · Nature Communications · doi:10.1038/s41467-019-13870-3 · Cited by 237
An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome
Richardson, T. G., Harrison, S., Hemani, G., & Davey Smith, G. (2019) · eLife · doi:10.7554/elife.43657 · Cited by 198
“If the IVW method provides strong evidence of association but in the presence of heterogeneity, we suggest undertaking two additional MR analyses using the weighted mode (Hartwig et al., 2017) and weighed median (Bowden et al.”
Method
Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention
Wang, Z., Emmerich, A., Pillon, N. J., Moore, T. M., Hemerich, D., Cornelis, M. C., Mazzaferro, E., Broos, S., Ahluwalia, T. S., Bartz, T. M., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01165-1 · Cited by 236
Self-citation
Associations between gut microbiota and Alzheimer’s disease, major depressive disorder, and schizophrenia
Zhuang, Z., Yang, R., Wang, W., Qi, L., & Huang, T. (2020) · Journal of Neuroinflammation · doi:10.1186/s12974-020-01961-8 · Cited by 220
Education and coronary heart disease: mendelian randomisation study
Tillmann, T., Vaucher, J., Okbay, A., Pikhart, H., Peasey, A., Kubinova, R., Pajak, A., Tamosiunas, A., Malyutina, S., Hartwig, F. P., et al. (2017) · BMJ · doi:10.1136/bmj.j3542 · Cited by 225
Self-citation
Mendelian randomization analysis using mixture models for robust and efficient estimation of causal effects.
Qi, G., & Chatterjee, N. (2019) · Nature Communications · doi:10.1038/s41467-019-09432-2 · Cited by 207
Genetic analysis of over half a million people characterises C-reactive protein loci
Said, S., Pazoki, R., Karhunen, V., Võsa, U., Ligthart, S., Bodinier, B., Koskeridis, F., Welsh, P. I., Alizadeh, B. Z., Chasman, D. I., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29650-5 · Cited by 213
Assessment of Causal Direction Between Gut Microbiota–Dependent Metabolites and Cardiometabolic Health: A Bidirectional Mendelian Randomization Analysis
Jia, J., Dou, P., Gao, M., Kong, X., Li, C., Liu, Z., & Huang, T. (2019) · Diabetes · doi:10.2337/db19-0153 · Cited by 194
Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?
Yarmolinsky, J., Wade, K. H., Richmond, R. C., Langdon, R., Bull, C. J., Tilling, K. M., Relton, C. L., Lewis, S. J., Smith, G. D., & Martin, R. M. (2018) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-17-1177 · Cited by 188
No Genetic Causal Association Between Periodontitis and Arthritis: A Bidirectional Two-Sample Mendelian Randomization Analysis
Yin, K.-J., Huang, J.-X., Wang, P., Yang, X., Tao, S., Li, H., Ni, J., & Pan, H. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.808832 · Cited by 187
Genetic Support for a Causal Role of Insulin Resistance on Circulating Branched-Chain Amino Acids and Inflammation
Wang, Q., Holmes, M. V., Smith, G. D., & Ala‐Korpela, M. (2017) · Diabetes Care · doi:10.2337/dc17-1642 · Cited by 182
A causal relationship between childhood obesity and risk of osteoarthritis: results from a two-sample Mendelian randomization analysis
Cao, Z., Wu, Y., Li, Q., Li, Y., & Wu, J. (2022) · Annals of Medicine · doi:10.1080/07853890.2022.2085883 · Cited by 185
Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization
Zhou, W., Liu, G., Hung, R. J., Haycock, P. C., Aldrich, M. C., Andrew, A. S., Arnold, S. M., Bickeböller, H., Bojesen, S. E., Brennan, P., et al. (2021) · International Journal of Cancer · doi:10.1002/ijc.33292 · Cited by 172
Genetic Causal Association between Iron Status and Osteoarthritis: A Two-Sample Mendelian Randomization
Xu, J., Zhang, S., Tian, Y., Si, H., Zeng, Y., Wu, Y., Liu, Y., Li, M., Sun, K., Wu, L., et al. (2022) · Nutrients · doi:10.3390/nu14183683 · Cited by 170
Midlife vascular risk factors and risk of incident dementia: Longitudinal cohort and Mendelian randomization analyses in the UK Biobank
Malik, R., Georgakis, M. K., Neitzel, J., Rannikmäe, K., Ewers, M., Seshadri, S. S., Sudlow, C. L. M., & Dichgans, M. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12320 · Cited by 170
Understanding the assumptions underlying Mendelian randomization
de Leeuw, C., Savage, J. E., Bucur, I. G., Heskes, T., & Posthuma, D. (2022) · European Journal of Human Genetics · doi:10.1038/s41431-022-01038-5 · Cited by 174
Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank
Carreras‐Torres, R., Johansson, M., Haycock, P., Relton, C. L., Smith, G. D., Brennan, P., & Martin, R. M. (2018) · BMJ · doi:10.1136/bmj.k1767 · Cited by 173
Assessing the Causal Relationships Between Insulin Resistance and Hyperuricemia and Gout Using Bidirectional Mendelian Randomization
McCormick, N., O’Connor, M. J., Yokose, C., Merriman, T. R., Mount, D. B., Leong, A., & Choi, H. K. (2021) · Arthritis & Rheumatology · doi:10.1002/art.41779 · Cited by 174
Plasma lipids and risk of aortic valve stenosis: a Mendelian randomization study
Nazarzadeh, M., Pinho-Gomes, A.-C., Bidel, Z., Dehghan, A., Canoy, D., Hassaine, A., Ayala Solares, J. R., Salimi-Khorshidi, G., Smith, G. D., Otto, C. M., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa070 · Cited by 163
Adiposity, metabolites, and colorectal cancer risk: Mendelian randomization study
Bull, C. J., Bell, J. A., Murphy, N., Sanderson, E. C. M., Smith, G. D., Timpson, N. J., Banbury, B. L., Albanes, D., Berndt, S. I., Bezieau, S., et al. (2020) · BMC Medicine · doi:10.1186/s12916-020-01855-9 · Cited by 174
Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis
Leong, A., Cole, J. B., Brenner, L. N., Meigs, J. B., Florez, J. C., & Mercader, J. M. (2021) · PLoS Medicine · doi:10.1371/journal.pmed.1003553 · Cited by 166
Within family Mendelian randomization studies
Davies, N. M., Howe, L. J., Brumpton, B., Havdahl, A., Evans, D. M., & Davey Smith, G. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddz204 · Cited by 158
Investigating causal relations between sleep traits and risk of breast cancer in women: mendelian randomisation study
Richmond, R. C., Anderson, E. L., Dashti, H. S., Jones, S. E., Lane, J. M., Strand, L. B., Brumpton, B. M., Rutter, M. K., Wood, A. R., Straíf, K., et al. (2019) · BMJ · doi:10.1136/bmj.l2327 · Cited by 156
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 150
MendelianRandomization v0.5.0: updates to an R package for performing Mendelian randomization analyses using summarized data
Broadbent, J. R., Foley, C. N., Grant, A. J., Mason, A. M., Staley, J. R., & Burgess, S. (2020) · Wellcome Open Research · doi:10.12688/wellcomeopenres.16374.2 · Cited by 148
Bidirectional Mendelian Randomization and Multiphenotype GWAS Show Causality and Shared Pathophysiology Between Depression and Type 2 Diabetes
Maina, J. G., Balkhiyarova, Z., Nouwen, A., Pupko, I., Ulrich, A., Boissel, M., Bonnefond, A., Froguel, P., Khamis, A., Prokopenko, I., et al. (2023) · Diabetes Care · doi:10.2337/dc22-2373 · Cited by 154
Genome-wide association studies and Mendelian randomization analyses for leisure sedentary behaviours
van de Vegte, Y. J., Said, M. A., Rienstra, M., van der Harst, P., & Verweij, N. (2020) · Nature Communications · doi:10.1038/s41467-020-15553-w · Cited by 145
Genetic and functional insights into the fractal structure of the heart
Meyer, H. V., Dawes, T. J. W., Serrani, M., Bai, W., Tokarczuk, P. F., Cai, J., de Marvao, A., Henry, A., Lumbers, R. T., Gierten, J., et al. (2020) · Nature · doi:10.1038/s41586-020-2635-8 · Cited by 139
Large-scale association analyses identify host factors influencing human gut microbiome compositionPreprint
Kurilshikov, A., Medina‐Gómez, C., Bacigalupe, R., Radjabzadeh, D., Wang, J., Demirkan, A., Roy, C. I. L., Garay, J. A. R., Finnicum, C. T., Liu, X., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.06.26.173724 · Cited by 143
Modifiable Risk Factors for Intracranial Aneurysm and Aneurysmal Subarachnoid Hemorrhage: A Mendelian Randomization Study
Karhunen, V., Bakker, M. K., Ruigrok, Y. M., Gill, D., & Larsson, S. C. (2021) · Journal of the American Heart Association · doi:10.1161/jaha.121.022277 · Cited by 143
Bidirectional two-sample Mendelian randomization analysis identifies causal associations between relative carbohydrate intake and depression
Yao, S., Zhang, M., Dong, S., Wang, J.-H., Zhang, K., Guo, J., Guo, Y., & Yang, T. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01412-9 · Cited by 144
A bidirectional Mendelian randomization study supports causal effects of kidney function on blood pressure
Yu, Z., Coresh, J., Qi, G., Grams, M., Boerwinkle, E., Snieder, H., Teumer, A., Pattaro, C., Köttgen, A., Chatterjee, N., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.04.044 · Cited by 135
Diabetes Mellitus, Glycemic Traits, and Cerebrovascular Disease
Georgakis, M. K., Harshfield, E. L., Malik, R., Franceschini, N., Langenberg, C., Wareham, N. J., Markus, H. S., & Dichgans, M. (2021) · Neurology · doi:10.1212/wnl.0000000000011555 · Cited by 145
Mendelian randomization analyses support causal relationships between brain imaging-derived phenotypes and risk of psychiatric disorders
Guo, J., Yu, K., Dong, S., Yao, S., Rong, Y., Wu, H., Zhang, K., Jiang, F., Chen, Y.-X., Guo, Y., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01174-7 · Cited by 143
Differentially expressed genes reflect disease-induced rather than disease-causing changes in the transcriptome
Porcu, E., Sadler, M. C., Lepik, K., Auwerx, C., Wood, A. R., Weihs, A., Sleiman, M. S. B., Ribeiro, D. M., Bandinelli, S., Tanaka, T., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-25805-y · Cited by 141
Evaluation of the causal effects between subjective wellbeing and cardiometabolic health: mendelian randomisation study
Wootton, R. E., Lawn, R. B., Millard, L. A. C., Davies, N. M., Taylor, A. E., Munafò, M. R., Timpson, N. J., Davis, O. S. P., Davey Smith, G., & Haworth, C. M. A. (2018) · BMJ · doi:10.1136/bmj.k3788 · Cited by 132
Multivariable two-sample Mendelian randomization estimates of the effects of intelligence and education on health
Davies, N. M., Hill, W. D., Anderson, E. L., Sanderson, E., Deary, I. J., & Davey Smith, G. (2019) · eLife · doi:10.7554/elife.43990 · Cited by 135
Exploiting horizontal pleiotropy to search for causal pathways within a Mendelian randomization framework
Cho, Y., Haycock, P., Sanderson, E. C. M., Gaunt, T. R., Zheng, J., Morris, A. P., Smith, G. D., & Hemani, G. (2020) · Nature Communications · doi:10.1038/s41467-020-14452-4 · Cited by 139
A multivariable Mendelian randomization analysis investigating smoking and alcohol consumption in oral and oropharyngeal cancer
Gormley, M., Dudding, T., Sanderson, E. C. M., Martin, R. M., Thomas, S. J., Tyrrell, J., Ness, A., Brennan, P., Munafo, M. R., Pring, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19822-6 · Cited by 133
Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization
Ye, T., Shao, J., & Kang, H. (2021) · The Annals of Statistics · doi:10.1214/20-aos2027 · Cited by 133
Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants
Rosoff, D. B., Clarke, T., Adams, M. J., McIntosh, A. M., Smith, G. D., Jung, J., & Lohoff, F. W. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0535-9 · Cited by 133
The relationship between circulating lipids and breast cancer risk: A Mendelian randomization study
Johnson, K. E., Siewert, K. M., Klarin, D. M., Damrauer, S. M., Program, T. V. M. V., Chang, K., Tsao, P. S., Assimes, T. L., Maxwell, K. N., & Voight, B. F. (2020) · PLoS Medicine · doi:10.1371/journal.pmed.1003302 · Cited by 125
Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics
Hu, X., Zhao, J., Lin, Z., Wang, Y., Peng, H., Zhao, H., Wan, X., & Yang, C. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2106858119 · Cited by 132
Causal effects of blood lipids on amyotrophic lateral sclerosis: a Mendelian randomization study
Zeng, P., & Zhou, X. (2019) · Human Molecular Genetics · doi:10.1093/hmg/ddy384 · Cited by 130
Modifiable pathways for colorectal cancer: a mendelian randomisation analysis
Cornish, A. J., Law, P., Timofeeva, M. N., Palin, K., Farrington, S. M., Palles, C., Jenkins, M. A., Casey, G., Brenner, H., Chang-Claude, J. C., et al. (2019) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(19)30294-8 · Cited by 126
Association of inflammatory markers with cerebral small vessel disease in community-based population
Jiang, L., Cai, X., Yao, D., Jing, J., Mei, L., Yang, Y., Li, S., Jin, A., Meng, X., Li, H., et al. (2022) · Journal of Neuroinflammation · doi:10.1186/s12974-022-02468-0 · Cited by 130
Association Between Genetically Proxied Inhibition of HMG-CoA Reductase and Epithelial Ovarian Cancer
Yarmolinsky, J., Bull, C. J., Vincent, E. E., Robinson, J., Walther, A., Smith, G. D., Lewis, S. J., Relton, C. L., & Martin, R. M. (2020) · JAMA · doi:10.1001/jama.2020.0150 · Cited by 124
Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease
Zheng, J., Zhang, Y., Rasheed, H., Walker, V. M., Sugawara, Y., Li, J., Leng, Y., Elsworth, B., Wootton, R. E., Fang, S., et al. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab203 · Cited by 124
Cardiometabolic Traits, Sepsis, and Severe COVID-19
Ponsford, M., Gkatzionis, A., Walker, V. M., Grant, A. J., Wootton, R. E., Moore, L. S. P., Fatumo, S., Mason, A. M., Zuber, V., Willer, C. J., et al. (2020) · Circulation · doi:10.1161/circulationaha.120.050753 · Cited by 124
No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study
Yang, M., Wan, X., Zheng, H., Xu, K., Xie, J., Yu, H., Wang, J., & Xu, P. (2023) · Nutrients · doi:10.3390/nu15041057 · Cited by 125

Authors: Hartwig, F. P., Davey Smith, G., & Bowden, J.
Affiliations: Universidade Federal de Pelotas (BR)
MRC Integrative Epidemiology Unit and
University of Bristol (GB)
Corresponding author: Hartwig, Fernando Pires
ORCID: Hartwig, Fernando Pires
Bowden, Jack
Venue: International Journal of Epidemiology
Publisher: Oxford University Press (OUP)
Published: 2017-07-12
Volume: 46
Issue: 6
Pages: 1985-1998
ISSN: 0300-5771 (ISSN-L)
1464-3685
DOI: 10.1093/ije/dyx102
PMC: PMC5837715
OpenAlex: W2613603864
Cited by: 3,485
References: 28
Citations by year: 2026: 387 · 2025: 798 · 2024: 1094 · 2023: 475 · 2022: 231 · 2021: 226 · 2020: 119 · 2019: 88 · 2018: 53 · 2017: 12
FWCI: 49.57
Type: journal article
Language: en
Open access: hybrid
doi.org
Licence: cc-by
Locations: International Journal of Epidemiology (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
Bristol Research (University of Bristol) (submittedVersion, cc-by)
Explore Bristol Research (submittedVersion, cc-by)
Funders: University of Bristol (MC_UU_12013/9)
Medical Research Council (MC_UU_12013, MR/N501906/1, MC_UU_12013/9)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Keywords: Mendelian randomization, summary data, invalid instruments, causal effect estimation, MR-Egger, weighted median, inverse variance weighting, plasma lipids, uric acid, coronary artery disease, sensitivity analysis
MeSH terms: Humans, Models, Statistical, Causality, Sample Size, Genome-Wide Association Study, Mendelian Randomization Analysis, Genetic Pleiotropy

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

Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption

Abstract

Overview

Integrity signals

Figures

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks