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‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*
Abstract
Associations between modifiable exposures and disease seen in observational epidemiology are sometimes confounded and thus misleading, despite our best efforts to improve the design and analysis of studies. Mendelian randomization—the random assortment of genes from parents to offspring that occurs during gamete formation and conception—provides one method for assessing the causal nature of some environmental exposures. The association between a disease and a polymorphism that mimics the biological link between a proposed exposure and disease is not generally susceptible to the reverse causation or confounding that may distort interpretations of conventional observational studies. Several examples where the phenotypic effects of polymorphisms are well documented provide encouraging evidence of the explanatory power of Mendelian randomization and are described. The limitations of the approach include confounding by polymorphisms in linkage disequilibrium with the polymorphism under study, that polymorphisms may have several phenotypic effects associated with disease, the lack of suitable polymorphisms for studying modifiable exposures of interest, and canalization—the buffering of the effects of genetic variation during development. Nevertheless, Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures. Genetic epidemiology—the theme of this issue of the International Journal of Epidemiology—is seen by many to be the only future for epidemiology, perhaps reflecting a growing awareness of the limitations of observational epidemiology1 (Box 1). Genetic epidemiology is concerned with understanding heritable aspects of disease risk, individual susceptibility to disease, and ultimately with contributing to a comprehensive molecular understanding of pathogenesis. The massive investment and expansion of human genetics, if it is to return value for the common good, must be integrated into public health functions. The human genome epidemiology network (HuGE Net—http://www.cdc.gov/genetics/huge.htm) has been established to promote the use of genetic knowledge—in terms of genetic tests and services—for disease prevention and health promotion.2,3 A broad taxonomy of human genome studies of public health relevance has been developed4 (Box 2). In this issue of the IJE, we publish a paper by Miguel Porta,5 who highlights the need for a more rational approach to genetic testing, given the likely low penetrance of many genes associated with cancers,6 likening the role of the genome to a jazz score that is interpreted and developed through experience and context—and is seldom predictable. Such insights may well temper enthusiasm for genetic testing in populations. However, in parallel to the approaches advocated by HuGE, genetic epidemiology can lead to a more robust understanding of environmental determinants of disease (e.g. dietary factors, occupational exposures, and health-related behaviours) relevant to whole populations (and not simply to genetically susceptible sub-populations).7–10 This approach has recently been referred to as ‘Mendelian randomization’.11–15 Here we begin by briefly reviewing reasons for current concerns about aetiological findings generated by conventional observational epidemiology and then we outline the potential contribution (and limitations) of Mendelian randomization. ‘Epidemiology set to get fast-track treatment’ ‘A consortium of leading European research centres and pharmaceutical companies will this week announce a plan to transform epidemiology by combining it with the new techniques of high-throughput biology. They plan to create a new field of study—genomic epidemiology—by using screening technologies derived from the human genome project … We think it is important to expand classical epidemiology and genetic epidemiology to take it to this high-throughput mode, says Esper Boel, vice-president of biotechnology research at Novo Nordisk. We want to use post-genomic technologies to create a new clinical science, to turn functional genomics into real clinical chemistry.’ From: Butler D. Epidemiology set to get fast-track treatment. Nature 2001;414:139. Reprinted with permission. Surveillance Population frequency of gene variants predisposing to specific diseases Population frequency of morbidity and mortality from such diseases Population frequency and effects of environmental factors known to interact with gene variants Economic costs of genetic components of diseases Coverage, access, and uptake of genetic tests and services Aetiology Magnitude of disease risk associated with gene variants in different populations Contribution of gene variants to the overall level of disease in different populations Magnitude of disease risk associated with gene–gene and gene–environment interactions in different populations Heal
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In the citing paper
“The essence of an MR design is that the association between a genetic variant (G) and an outcome (Y) can be used to test whether and by how much the exposure of interest (X) influences the outcome, provided that the genetic variant is associated with the exposure of interest and has no other source of association with the outcome.1,9”
From Mendelian randomization (2022) · cites this paper as [1]
In the citing paper
“When initially presented, it was concluded that “[MR] offers a more robust approach to understanding the effect of some modifiable exposures on health outcomes than does much conventional observational epidemiology”1 and that where possible, RCTs should follow to establish the effects of interventions. This conclusion remains unchanged, although moving towards formal triangulation of all pertinent”
From Mendelian randomization (2022) · cites this paper as [1]
In the citing paper
“Canalization can occur when polymorphic phenotypes expressed during fetal development lead to the development of compensating pathways to mitigate the effects of that expression. 1,178,179”
From Mendelian randomization (2022) · cites this paper as [1]
In the citing paper
“Estimating effect sizes through the instrumental variable approach imposes a fourth assumption, usually homogeneity of effects of the exposure on the outcome.16 58 59 60”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [16]
In the citing paper
“Most MR studies rely on three core IV assumptions (relevance, independence, and exclusion restriction; fig 1, box 3) to carry out testing for causal effects of the exposure on the outcome.16”
From Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration. (2021) · cites this paper as [16]
In the citing paper
“Similarly, violation of the ‘exclusion restriction criteria’33–37 could bias causal estimates in IV analyses when used to test effects of intermediates in RCTs or when used in observational data (including MR)”
From Triangulation in aetiological epidemiology (2017) · cites this paper as [34]
In the citing paper
“but may be confounded by population stratification.33,34”
From Triangulation in aetiological epidemiology (2017) · cites this paper as [34]
In the citing paper
“Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization (MR).”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [10]
In the citing paper
“Performed well, such studies called Mendelian randomization (MR) analyses, can provide rigorous evidence of causation 9,10 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [10]
In the citing paper
“We can exploit the properties of the human genome (specifically, the random segregation of alleles and their non-modifiable nature) to make causal inferences about the relationships between risk factors and disease 10 .”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [10]
In the citing paper
“Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome.”
From Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways. (2015) · cites this paper as [1]
In the citing paper
“If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation.”
From Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways. (2015) · cites this paper as [1]
Citations
Cites
OLSSON, A. G., McMurray, J. J. V., Thorgeirsson, G., Spaulding, C. M., Slattery, J., Pyörälà, K., Færgeman, O., Wright, R. S., Berg, K. M., Wilhelmsen, L., et al. (1994) · The Lancet · Cited by 8,467
Prevention of Coronary Heart Disease with Pravastatin in Men with Hypercholesterolemia
Shepherd, J., Cobbe, S. M., Ford, I., Isles, C. G., Lorimer, A. R., Macfarlane, P. W., McKillop, J. H., & Packard, C. J. (1995) · New England Journal of Medicine · doi:10.1056/nejm199511163332001 · Cited by 7,449
Collaboration, A. T. (2002) · BMJ · doi:10.1136/bmj.324.7329.71 · Cited by 6,943
(1994) · New England Journal of Medicine · doi:10.1056/nejm199404143301501 · Cited by 4,737
Spielman, R. S., McGinnis, R. E., & Ewens, W. J. (1993) · PubMed · Cited by 3,679
Effects of a combination of beta carotene and vitamin A on lung cancer and cardiovascular disease
Omenn, G. S., Goodman, G. E., Thornquist, M. D., Balmes, J., Cullen, M. R., Glass, A., Keogh, J. P., Meyskens, F. L., Valanis, B., Williams, J. H., et al. (1996) · New England Journal of Medicine · doi:10.1056/nejm199605023341802 · Cited by 3,638
SCANDINAVIANSIMVASTATINSURVIVAL (1994) · The Lancet · doi:10.1016/s0140-6736(94)90566-5 · Cited by 3,638
Prevention of neural tube defects: Results of the Medical Research Council Vitamin Study
(1991) · The Lancet · doi:10.1016/0140-6736(91)90133-a · Cited by 3,472
CANALIZATION OF DEVELOPMENT AND THE INHERITANCE OF ACQUIRED CHARACTERS
WADDINGTON, C. H. (1942) · Nature · doi:10.1038/150563a0 · Cited by 3,255
Flagged first, then by citations
Research works printed but not linked: 3
- Skrabanek P. False Premises, False Promises. Whithorn: Tarragon Press, 2000.
- http://www.ncbi.nlm.nih.gov/Omim (accessed 12 Dec 2002).
- Heart Protection Study Collaborative Group. MRC/BHF heart protection Study of cholesterol lowering with simvastatin in 20 536 high-risk individuals. Lancet2002;360:7–22. · DOI · Paper page
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Sorted by citations
Items 801–900 of 1,037
Serum magnesium and calcium levels in relation to ischemic stroke
Larsson, S. C., Traylor, M., Burgess, S., Boncoraglio, G. B., Jern, C., Michaëlsson, K., Markus, H. S., Malik, R., Chauhan, G., Traylor, M., et al. (2019) · Neurology · doi:10.1212/wnl.0000000000007001 · Cited by 72
Aung, N., Khanji, M. Y., Munroe, P. B., & Petersen, S. E. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.586308 · Cited by 69
Brandkvist, M., Bjørngaard, J. H., Ødegård, R. A., Åsvold, B. O., Smith, G. D., Brumpton, B. M., Hveem, K., Richardson, T. G., & Vie, G. Å. (2020) · Human Molecular Genetics · doi:10.1093/hmg/ddaa256 · Cited by 72
Estimation of Parental Effects Using Polygenic Scores
Balbona, J. V., Kim, Y., & Keller, M. C. (2021) · Behavior Genetics · doi:10.1007/s10519-020-10032-w · Cited by 68
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Bochud, M., Marquant, F., Marques-Vidal, P. M., Vollenweider, P., Beckmann, J. S., Mooser, V., Paccaud, F. M., & Rousson, V. (2009) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-2428 · Cited by 72
Lattka, E., Koletzko, B. V., Kunze, S., Hibbeln, J. R., Klopp, N., Ring, S. M., & Steer, C. D. (2012) · British Journal Of Nutrition · doi:10.1017/s0007114512003108 · Cited by 71
Obesity and peripheral arterial disease: A Mendelian Randomization analysis
Huang, Y. F., Xu, M., Xie, L., Wang, T., Huang, X., Lv, X., Chen, Y., Ding, L., Lin, L., Wang, W., et al. (2015) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2015.12.034 · Cited by 71
Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference
Corbin, L. J., Tan, V. Y., Hughes, D. A., Wade, K. H., Paul, D. S., Tansey, K. E., Butcher, F. C., Dudbridge, F., Howson, J. M. M., Jallow, M. W., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-03109-y · Cited by 72
Shi, F., Sun, L., & Kaptoge, S. (2021) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2021.01.018 · Cited by 70
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Wang, J., Rao, Y., & Houser, D. E. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1610902114 · Cited by 70
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Fu, Y., Xu, F., Jiang, L., Miao, Z., Liang, X., Yang, J., Larsson, S. C., & Zheng, J. (2021) · BMC Medicine · doi:10.1186/s12916-021-02041-1 · Cited by 73
Yarmolinsky, J., Díez‐Obrero, V., Richardson, T. G., Pigeyre, M., Sjaarda, J., Paré, G., Walker, V. M., Vincent, E. E., Tan, V. Y., Obón‐Santacana, M., et al. (2022) · PLoS Medicine · doi:10.1371/journal.pmed.1003897 · Cited by 71
Sbarra, D. A., Ramadan, F. A., Choi, K. W., Treur, J. L., Levey, D. F., Wootton, R. E., Stein, M. B., Gelernter, J. E., & Klimentidis, Y. C. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02259-w · Cited by 74
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Schatzkin, A. G., Abnet, C. C., Cross, A. J., Gunter, M. J., Pfeiffer, R., Gail, M., Lim, U., & Smith, G. D. (2009) · Cancer Prevention Research · doi:10.1158/1940-6207.capr-08-0070 · Cited by 72
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Howe, L. J., Nivard, M. G., Morris, T., Hansen, A. F., Rasheed, H., Cho, Y., Chittoor, G., Lind, P. A., Palviainen, T., van der Zee, M. D., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.05.433935 · Cited by 70
Wu, B.-S., Zhang, Y.-R., Li, H.-Q., Kuo, K., Chen, S.-D., Dong, Q., Liu, Y., & Yu, J.-T. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01599-x · Cited by 69
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Vineis, P. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh277 · Cited by 68
Tobin, M. D. (2004) · International Journal of Epidemiology · doi:10.1093/ije/dyh016 · Cited by 68
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Yuan, S., Mason, A. M., Burgess, S., & Larsson, S. C. (2021) · European Journal of Epidemiology · doi:10.1007/s10654-021-00737-5 · Cited by 66
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Shungin, D., Cornelis, M. C., Divaris, K., Holtfreter, B., Shaffer, J. R., Yu, Y., Barros, S. P., Beck, J. D., Biffar, R., Boerwinkle, E., et al. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv075 · Cited by 68
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Testa, A., Mallamaci, F., Spoto, B., Pisano, A., Sanguedolce, M. C., Tripepi, G. L., Leonardis, D., & Zoccali, C. (2014) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.11041013 · Cited by 66
Husemoen, L. L. N., Toft, U., Fenger, M., Jørgensen, T., Johansen, N., & Linneberg, A. R. (2006) · International Journal of Epidemiology · doi:10.1093/ije/dyl094 · Cited by 66
Morris, R. W., Taylor, A. E., Fluharty, M., Bjørngaard, J. H., Åsvold, B. O., Gabrielsen, M. E., Campbell, A., Marioni, R. E., Meena Kumari, B., Korhonen, T., et al. (2015) · BMJ Open · doi:10.1136/bmjopen-2015-008808 · Cited by 73
Causal associations between body mass index and mental health: a Mendelian randomisation study
van den Broek, N., Treur, J. L., Larsen, J. K., Verhagen, M., Verweij, K. J. H., & Vink, J. M. (2018) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2017-210000 · Cited by 68
Behaviour Genetic Frameworks of Causal Reasoning for Personality Psychology
Briley, D. A., Livengood, J., & Derringer, J. L. (2018) · European Journal of Personality · doi:10.1002/per.2153 · Cited by 69
Mendelian Randomization: Applications and Limitations in Epigenetic Studies
Relton, C. L., & Smith, G. D. (2015) · Epigenomics · doi:10.2217/epi.15.88 · Cited by 67
Sadreev, I. I., Elsworth, B., Mitchell, R. E., Paternoster, L., Sanderson, E. C. M., Davies, N. M., Millard, L. A. C., Smith, G. D., Haycock, P., Bowden, J., et al. (2021) · medRxiv · doi:10.1101/2021.06.28.21259622 · Cited by 62
Washburn, J. D., Burch, M. B., & Franco, J. A. V. (2020) · Crop Science · doi:10.1002/csc2.20052 · Cited by 65
Gill, D., Karhunen, V., Malik, R., Dichgans, M., & Sofat, N. (2021) · Osteoarthritis and Cartilage · doi:10.1016/j.joca.2020.12.015 · Cited by 64
Xue, A., Jiang, L., Zhu, Z., Wray, N. R., Visscher, P. M., Zeng, J., & Yang, J. (2021) · Nature Communications · doi:10.1038/s41467-020-20237-6 · Cited by 62
Zhang, M., Wang, Y., Wang, Y., Bai, Y., & Gu, D. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.860794 · Cited by 65
Systemic Lupus Erythematosus and Cardiovascular Disease: A Mendelian Randomization Study
Gao, N., Kong, M., Li, X., Wei, D., Zhu, X., Hong, Z., Ni, M., Wang, Y., & Dong, A. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.908831 · Cited by 66
Husemoen, L. L. N., Fenger, M., Friedrich, N., Tolstrup, J. S., Fredriksen, S. B., & Linneberg, A. R. (2008) · Alcoholism Clinical and Experimental Research · doi:10.1111/j.1530-0277.2008.00780.x · Cited by 65
Galeone, C., Edefonti, V. C., Parpinel, M. T., Leoncini, E., Matsuo, K., Talamini, R., Olshan, A. F., Zevallos, J. P., Winn, D. M., Jayaprakash, V., et al. (2014) · International Journal of Cancer · doi:10.1002/ijc.29044 · Cited by 65
Jiang, X., Kiel, D. P., & Kraft, P. L. (2018) · Bone · doi:10.1016/j.bone.2018.10.006 · Cited by 66
Gibson, M., Munafo, M. R., Taylor, A. E., & Treur, J. L. (2018) · Nicotine & Tobacco Research · doi:10.1093/ntr/nty230 · Cited by 62
Peres, L. C., Mallen, A. R., Townsend, M. K., Poole, E. M., Trabert, B. L., Allen, N. E., Arslan, A. A., Dossus, L., Fortner, R. T., Gram, I. T., et al. (2019) · Cancer Research · doi:10.1158/0008-5472.can-19-1554 · Cited by 65
Body mass index and breast cancer survival: a Mendelian randomization analysis
Guo, Q., Burgess, S., Turman, C., Bolla, M. K., Wang, Q., Lush, M., Abraham, J., Aittomäki, K., Andrulis, I. L., Apicella, C., et al. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx131 · Cited by 64
Jiang, X., Dimou, N. L., Al-Dabhani, K. M., Lewis, S. J., Martin, R. M., Haycock, P., Gunter, M. J., Key, T. J., Eeles, R. A., Muir, K. R., et al. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyy284 · Cited by 66
Cheng, Q., Yang, Y., Shi, X., Yeung, K.-F., Yang, C., Peng, H., & Liu, J. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa028 · Cited by 63
Chu, X., Jaeger, M., Beumer, J., Bakker, O. B., Aguirre‐Gamboa, R., Oosting, M., Smeekens, S. P., Moorlag, S. J. C. F. M., Mourits, V. P., Koeken, V. A. C. M., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02413-z · Cited by 64
Modern Methods for Epidemiology
Gilthorpe, M. S., Frydenberg, M., Ya-ping, C., & Bælum, V. (2012) · Springer eBooks · doi:10.1007/978-94-007-3024-3 · Cited by 66
Associations between an Obesity Related Genetic Variant (FTO rs9939609) and Prostate Cancer Risk
Lewis, S. J., Murad, A. A. A., Chen, L., Smith, G. D., Donovan, J., Palmer, T., Hamdy, F. C., Neal, D. E., Lane, J. A., Davis, M., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013485 · Cited by 65
Shin, C. M., Han, K., Lee, D. H., Choi, Y. J., Kim, N., Park, Y. S., & Yoon, H. (2017) · Diseases of the Colon & Rectum · doi:10.1097/dcr.0000000000000876 · Cited by 63
Exercise genomics—a paradigm shift is needed: a commentary
Bouchard, C. (2015) · British Journal of Sports Medicine · doi:10.1136/bjsports-2015-095294 · Cited by 63
Mendelian randomization: the challenge of unobserved environmental confounds
Koellinger, P., & de Vlaming, R. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz138 · Cited by 61
Carreras‐Torres, R., Ibáñez‐Sanz, G., Obón‐Santacana, M., Duell, E. J., & Moreno, V. R. (2020) · Scientific Reports · doi:10.1038/s41598-020-76361-2 · Cited by 66
Accelerated MRI-predicted brain ageing and its associations with cardiometabolic and brain disorders
Kolbeinsson, A., Filippi, S., Panagakis, Y., Matthews, P. M., Elliott, P., Dehghan, A., & Tzoulaki, I. (2020) · Scientific Reports · doi:10.1038/s41598-020-76518-z · Cited by 65
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Yuan, S., Wan, Z., Cheng, S., Michaëlsson, K., & Larsson, S. C. (2021) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaa963 · Cited by 63
Khouja, J. N., Wootton, R. E., Taylor, A. E., Smith, G. D., & Munafo, M. R. (2021) · PLoS Medicine · doi:10.1371/journal.pmed.1003555 · Cited by 63
Childhood obesity and multiple sclerosis: A Mendelian randomization study
Harroud, A., Mitchell, R. E., Richardson, T. G., Morris, J. A., Forgetta, V., Smith, G. D., Baranzini, S. E., & Richards, J. B. (2021) · Multiple Sclerosis Journal · doi:10.1177/13524585211001781 · Cited by 66
Metadata
- Authors
- Davey Smith, G., & Ebrahim, S.
- ORCID
- Ebrahim, Shah
- Venue
- International Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2003-02
- Volume
- 32
- Issue
- 1
- Pages
- 1-22
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- OpenAlex
- W2106036991
- Cited by
- 5,882
- References
- 179
- Citations by year
- 2026: 333 · 2025: 673 · 2024: 1162 · 2023: 681 · 2022: 453 · 2021: 442 · 2020: 353 · 2019: 235 · 2018: 201 · 2017: 157 · 2016: 163 · 2015: 118 · 2014: 115 · 2013: 94 · 2012: 101
- FWCI
- 31.89
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Epidemiology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- Mendelian randomization, genetic epidemiology, environmental factors in disease, causal inference, confounding, reverse causality, linkage disequilibrium, canalization, genetic polymorphism, genetic testing, public health genetics, disease prevention, Human Genome Project, pathogenesis, cancer genetics
- MeSH terms
- Animals, Disease, Environmental Exposure, Genotype, Humans, Polymorphism, Genetic, Molecular Epidemiology, Risk Assessment
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