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Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption
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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.
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“Additional approaches to test the exclusion restriction include weighted median56 and mode.57”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [57]
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“The MR-PRESSO method is a variation on the IVW method that first sequentially removes genetic variants from the analysis whose variant-specific causal estimate differs substantially from those of other variants 21 .”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [21]
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Density Estimation for Statistics and Data Analysis
Silverman, B. W. (2018) · Routledge eBooks · doi:10.1201/9781315140919 · Cited by 15,938
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816
Self-citationBowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922
Self-citationDensity 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
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
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983
Burgess, S., Bowden, J., Fall, T., Ingelsson, E., & Thompson, S. G. (2017) · Epidemiology · doi:10.1097/ede.0000000000000559 · Cited by 2,017
Self-citationA 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
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Causal effects of gut microbiota on sepsis: a two-sample Mendelian randomization study
Chen, J.-H., Zeng, L.-Y., Zhao, Y., Tang, H.-X., Lei, H., Wan, Y.-F., Deng, Y., & Liu, K. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1167416 · Cited by 42
Chen, J., Yu, X., Wu, X., Chai, K., & Wang, S. (2024) · Journal of Cancer · doi:10.7150/jca.92699 · Cited by 42
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Gerring, Z. F., Thorp, J. G., Treur, J. L., Verweij, K. J. H., & Derks, E. M. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02547-z · Cited by 52
Wang, Q., Wang, Y., Lehto, K., Pedersen, N. L., Williams, D. M., & Hägg, S. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.07.007 · Cited by 42
Fani, L., Georgakis, M. K., Ikram, M. A., Ikram, M. K., Malik, R., & Dichgans, M. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01400-z · Cited by 43
Review of Mendelian Randomization Studies on Ovarian Cancer
Guo, J.-Z., Xiao, Q., Gao, S., Li, X., Wu, Q., & Gong, T. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.681396 · Cited by 47
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Hirtz, R., Hars, C., Naaresh, R., Laabs, B., Antel, J., Grasemann, C., Hinney, A., Hebebrand, J., & Peters, T. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.918584 · Cited by 42
l-carnitine, a friend or foe for cardiovascular disease? A Mendelian randomization study
Zhao, J. V., Burgess, S., Fan, B., & Schooling, C. M. (2022) · BMC Medicine · doi:10.1186/s12916-022-02477-z · Cited by 41
Ren, F., Jin, Q., Liu, T., Ren, X., & Zhan, Y. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2023.1171517 · Cited by 43
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Budu‐Aggrey, A., Joyce, S., Davies, N. M., Paternoster, L., Munafo, M. R., Brown, S., Evans, J., & Sallis, H. (2021) · Clinical & Experimental Allergy · doi:10.1111/cea.14010 · Cited by 41
Porcu, E., Rüeger, S., Lepik, K., Santoni, F. A., Reymond, A., & Kutalik, Z. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/377267 · Cited by 42
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Burgess, S., Foley, C. N., & Zuber, V. (2019) · Wiley eBooks · doi:10.1002/9781119487845.ch23 · Cited by 40
Satterfield, B. A., Dikilitas, O., Safarova, M. S., Clarke, S. L., Tcheandjieu, C., Zhu, X., Bastarache, L., Larson, E. B., Justice, A. E., Shang, N., et al. (2021) · Circulation: Genomic and Precision Medicine · doi:10.1161/circgen.120.003354 · Cited by 40
Li, Y., Miao, Y., & Zhang, Q. (2022) · SLEEP · doi:10.1093/sleep/zsac298 · Cited by 40
Smith, M. L., Bull, C. J., Holmes, M. V., Smith, G. D., Sanderson, E. C. M., Anderson, E. L., & Bell, J. A. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104503 · Cited by 40
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Borges, M. C., Clayton, G., Freathy, R. M., Felix, J. F., Fernández‐Sanlés, A., Soares, A. G., Kilpi, F., Yang, Q., McEachan, R., Richmond, R. C., et al. (2024) · BMC Medicine · doi:10.1186/s12916-023-03167-0 · Cited by 43
Zeng, H., Ge, J., Xu, W., Ma, H., Chen, L., Xia, M., Pan, B., Lin, H., Wang, S., & Gao, X. (2020) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.4330 · Cited by 39
Kho, P. F., Mortlock, S., Amant, F. C., Annibali, D., Ashton, K. A., Attia, J., Auer, P. L., Beckmann, M. W., Black, A., Brinton, L. A., et al. (2021) · Human Genetics · doi:10.1007/s00439-021-02312-0 · Cited by 41
Yeung, S. L. A., Li, A. M., He, B., Kwok, K. O., & Schooling, C. M. (2022) · Addiction · doi:10.1111/add.15852 · Cited by 40
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Hwang, L., Davies, N. M., Warrington, N. M., & Evans, D. M. (2020) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a039503 · Cited by 42
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Shi, X., Pan, Z., & Miao, W. (2022) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1581 · Cited by 50
Lu, L., Wan, B., Li, L., & Sun, M. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.987401 · Cited by 41
Chen, J., Zhou, H., Jin, H., & Liu, K. (2022) · Nutrients · doi:10.3390/nu14204434 · Cited by 42
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Triozzi, J. L., Hsi, R. S., Wang, G., Akwo, E. A., Wheless, L., Chen, H., Tao, R., Ikizler, T. A., Robinson‐Cohen, C., Hung, A. M., et al. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.43290 · Cited by 38
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Hartwig, F. P., Smith, G. D., Schmidt, A. F., Sterne, J. A. C., Higgins, J. P. T., & Bowden, J. (2020) · Research Synthesis Methods · doi:10.1002/jrsm.1402 · Cited by 38
Self-citationDardani, C., Howe, L. J., Mukhopadhyay, N., Stergiakouli, E., Wren, Y. E., Humphries, K., Davies, A., Ho, K. M., Weinberg, S. M., Marazita, M. L., et al. (2020) · International Journal of Epidemiology · doi:10.1093/ije/dyaa047 · Cited by 44
Cullell, N., Cárcel‐Márquez, J., Gallego-Fábrega, C., Muiño, E., Llucià‐Carol, L., Lledós, M., Uscamaita, K. E., Krupiński, J., & Fernández‐Cadenas, I. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.05.008 · Cited by 40
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Benjamins, J. W., Yeung, M. W., van de Vegte, Y. J., Said, M. A., van der Linden, T., Ties, D., Juárez‐Orozco, L. E., Verweij, N., & van der Harst, P. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103783 · Cited by 37
Zhang, K., Li, A., Zhou, J., Zhang, C., & Chen, M. (2023) · Respiratory Research · doi:10.1186/s12931-022-02309-x · Cited by 38
Slaney, C., Sallis, H., Jones, H. J., Dardani, C., CHARGE Inflammation Working Group, Tilling, K. M., Munafo, M. R., Smith, G. D., Mahedy, L., & Khandaker, G. M. (2023) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2023.02.010 · Cited by 39
Plotnikov, D., & Guggenheim, J. A. (2019) · Ophthalmic and Physiological Optics · doi:10.1111/opo.12596 · Cited by 37
Wendt, F. R., Pathak, G. A., Deak, J. D., Angelis, F. D., Koller, D., Cabrera‐Mendoza, B., Lebovitch, D. S., Levey, D. F., Stein, M. B., Kranzler, H. R., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01469-y · Cited by 35
Cui, G., Li, S., Ye, H., Yang, Y., Huang, Q., Chu, Y., Shi, Z., & Zhang, X. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.956005 · Cited by 40
Liu, X., Zou, L., Nie, C., Qin, Y., Tong, X., Wang, J., Yang, H., Xu, X., Jin, X., Xiao, L., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-31115-8 · Cited by 44
Yuan, Z., Liu, L., Guo, P., Yan, R., Xue, F., & Zhou, X. (2022) · Science Advances · doi:10.1126/sciadv.abl5744 · Cited by 37
Guo, W., Zhao, L., Huang, W., Chen, J., Zhong, T., Yan, S., Hu, W., Zeng, F., Peng, C., & Yan, H. (2024) · Cardiovascular Diabetology · doi:10.1186/s12933-024-02210-5 · Cited by 40
Multivariable MR Can Mitigate Bias in Two‐Sample MR Using Covariable‐Adjusted Summary Associations
Gilbody, J., Borges, M. C., Smith, G. D., & Sanderson, E. C. M. (2025) · Genetic Epidemiology · doi:10.1002/gepi.22606 · Cited by 34
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Zheng, J., Frysz, M., Kemp, J. P., Evans, D. M., Smith, G. D., & Tobias, J. H. (2019) · Frontiers in Endocrinology · doi:10.3389/fendo.2019.00807 · Cited by 36
Ye, Y., Yang, H., Wang, Y., & Zhao, H. (2020) · Genetic Epidemiology · doi:10.1002/gepi.22357 · Cited by 36
Xue, H., & Pan, W. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009105 · Cited by 37
Said, M. A., Yeung, M. W., van de Vegte, Y. J., Benjamins, J. W., Dullaart, R. P. F., Ruotsalainen, S., Ripatti, S., Natarajan, P., Juarez-Orozco, L. E., Verweij, N., et al. (2021) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.120.315300 · Cited by 39
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Li, S., Fu, Y., Liu, Y., Zhang, X., Li, H., Tian, L., Zhuo, L., Liu, M. R., & Cui, J. (2022) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgac190 · Cited by 37
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Sethi, A., Ruby, J. G., Veras, M. A., Telis, N., & Melamud, E. (2023) · Nature Communications · doi:10.1038/s41467-023-38279-x · Cited by 36
Mak, J. K. L., Kananen, L., Qin, C., Kuja‐Halkola, R., Tang, B., Lin, J., Wang, Y., Jääskeläinen, T., Koskinen, S. V. P., Lu, Y., et al. (2023) · Aging Cell · doi:10.1111/acel.13868 · Cited by 36
Wu, J., Zhang, B., Zhou, S., Huang, Z., Xu, Y., Lu, X., Zheng, X., & Ouyang, D. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1236847 · Cited by 37
Chen, H., Peng, L., Wang, Z., He, Y., & Zhang, X. (2023) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.13906 · Cited by 39
Tang, C. K., Lei, X., Ding, Y., Yang, S., Ma, Y., & He, D. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1339649 · Cited by 37
Yang, S., Pudasaini, R., Zhi, H., & Wang, L. (2021) · Nutrients · doi:10.3390/nu14010181 · Cited by 39
Li, Y., Li, Q., Cao, Z., & Wu, J. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.962787 · Cited by 37
Zeng, Y., Cao, S., & Yang, H. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2023.1135923 · Cited by 39
Gormley, M., Dudding, T., Thomas, S. J., Tyrrell, J., Ness, A., Pring, M., Legge, D., Smith, G. D., Richmond, R. C., Vincent, E. E., et al. (2023) · eLife · doi:10.7554/elife.82674 · Cited by 36
Georgakis, M. K., Malik, R., Gill, D., Franceschini, N., Sudlow, C. L. M., & Dichgans, M. (2019) · medRxiv · doi:10.1101/19007682 · Cited by 36
Liu, S., Feng, S., Du, F., Zhang, K., & Shen, Y. (2023) · BMC Cancer · doi:10.1186/s12885-023-10737-1 · Cited by 35
Li, H., Pan, X., Zhang, S., Shen, X., Wan, L., Shang, W., Wen, Z., Huang, S., Chen, L., Zhang, X., et al. (2023) · Critical Care · doi:10.1186/s13054-023-04763-5 · Cited by 36
Wu, Y., Feng, X., Li, M., Hu, Z., Zheng, Y., Chen, S., & Luo, H. (2023) · EBioMedicine · doi:10.1016/j.ebiom.2023.104918 · Cited by 38
Vela, S. O., Beyeler, M. J., Trofimova, O., Iuliani, I., Quiros, J. V., de Vries, V. A., Meloni, I., Elwakil, A., Hoogewoud, F., Liefers, B. J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-52334-1 · Cited by 36
Mendelian Randomization in Cardiovascular Research
Bell, K., Loy, C. T., Cust, A. E., & Teixeira-Pinto, A. M. (2021) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.119.005623 · Cited by 35
Zhang, X., Τheodoratou, E., Li, X., Farrington, S. M., Law, P., Broderick, P., Walker, M., Klimentidis, Y. C., Rees, J. M. B., Houlston, R. S., et al. (2021) · British Journal of Cancer · doi:10.1038/s41416-020-01236-2 · Cited by 36
Sun, L., Zhu, J., Ling, Y., Mi, S., Li, Y., Wang, T., & Li, Y. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab052 · Cited by 35
The Causal Relationship Between Body Mass Index and the Risk of Osteoarthritis
He, Y., Zheng, C., He, M., & Huang, J. (2021) · International Journal of General Medicine · doi:10.2147/ijgm.s314180 · Cited by 36
Abdominal obesity is a more important causal risk factor for pancreatic cancer than overall obesity
Maina, J. G., Pascat, V., Zudina, L., Ulrich, A., Pupko, I., Bonnefond, A., Balkhiyarova, Z., Kaakinen, M., Froguel, P., & Prokopenko, I. (2023) · European Journal of Human Genetics · doi:10.1038/s41431-023-01301-3 · Cited by 34
Liu, X., Sun, X., Zhang, Y., Jiang, W., Lai, M. M., Wiggins, K. L., Raffield, L. M., Bielak, L. F., Zhao, W., Pitsillides, A., et al. (2023) · Journal of the American Heart Association · doi:10.1161/jaha.122.029090 · Cited by 36
Xue, M., Xie, Y., Zang, X., Zhong, Y., Ma, X., Sun, H., & Liu, J. (2024) · iMeta · doi:10.1002/imt2.225 · Cited by 37
Groot, H. E., van de Vegte, Y. J., Verweij, N., Lipšic, E., Karper, J. C., & van der Harst, P. (2020) · Scientific Reports · doi:10.1038/s41598-020-70724-5 · Cited by 35
Nazarzadeh, M., Bidel, Z., Mohseni, H., Canoy, D., Pinho‐Gomes, A., Hassaïne, A., Dehghan, A., Trégouët, D., Smith, N. L., & Rahimi, K. (2022) · Cardiovascular Research · doi:10.1093/cvr/cvac135 · Cited by 34
Rodríguez‐Fernández, B., Vilor‐Tejedor, N., Arenaza‐Urquijo, E. M., Sánchez‐Benavides, G., Suárez‐Calvet, M., Operto, G., Minguillón, C., Fauria, K., Kollmorgen, G., Suridjan, I., et al. (2022) · Alzheimer s Research & Therapy · doi:10.1186/s13195-022-01101-9 · Cited by 31
Luo, G., Yao, Y., Tao, J., Wang, T., & Yan, M. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.1074605 · Cited by 38
Min, Q., Geng, H., Gao, Q., & Xu, M. (2023) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1203902 · Cited by 36
Zhan, Y., & Hägg, S. (2020) · GeroScience · doi:10.1007/s11357-020-00283-0 · Cited by 35
Gao, Y., Wei, Y., Zhou, X., Huang, S., Zhao, H., & Zeng, P. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.583106 · Cited by 33
Habitual coffee intake and plasma lipid profile: Evidence from UK Biobank
Zhou, A., & Hyppönen, E. (2021) · Clinical Nutrition · doi:10.1016/j.clnu.2020.12.042 · Cited by 35
Shapland, C. Y., Zhao, Q., & Bowden, J. (2022) · Statistics in Medicine · doi:10.1002/sim.9320 · Cited by 32
Self-citationZhao, S. S., Bellou, E., Verstappen, S. M. M., Cook, M. J., Sergeant, J. C., Warren, R. B., Barton, A. C., & Bowes, J. (2022) · Rheumatology · doi:10.1093/rheumatology/keac403 · Cited by 36
Hartwig, F. P., Wang, L., Smith, G. D., & Davies, N. M. (2023) · Epidemiology · doi:10.1097/ede.0000000000001596 · Cited by 33
Self-citationKim, M. S., Song, M., Kim, S., Kim, B., Kang, W., Kim, J. Y., Myung, W., Lee, I., Do, R., Khera, A. V., et al. (2023) · Obesity · doi:10.1002/oby.23722 · Cited by 33
Elevated plasma complement factor H related 5 protein is associated with venous thromboembolism
Iglesias, M. J., Sánchez‐Rivera, L., Ibrahim‐Kosta, M., Naudin, C., Munsch, G., Goumidi, L., Farm, M., Smith, P. M., Thibord, F., Kral-Pointner, J. B., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38383-y · Cited by 38
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Xue, A., Zhu, Z., Wang, H., Jiang, L., Visscher, P. M., Zeng, J., & Yang, J. (2024) · Communications Medicine · doi:10.1038/s43856-024-00473-3 · Cited by 32
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Metadata
- 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
- 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
- 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
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