The DOI matches its Crossref record; 120 of the 120 references it cites were found in a registry or an index.
Evaluating the potential role of pleiotropy in Mendelian randomization studies
Open accessAbstract
Pleiotropy, the phenomenon of a single genetic variant influencing multiple traits, is likely widespread in the human genome. If pleiotropy arises because the single nucleotide polymorphism (SNP) influences one trait, which in turn influences another ('vertical pleiotropy'), then Mendelian randomization (MR) can be used to estimate the causal influence between the traits. Of prime focus among the many limitations to MR is the unprovable assumption that apparent pleiotropic associations are mediated by the exposure (i.e. reflect vertical pleiotropy), and do not arise due to SNPs influencing the two traits through independent pathways ('horizontal pleiotropy'). The burgeoning treasure trove of genetic associations yielded through genome wide association studies makes for a tantalizing prospect of phenome-wide causal inference. Recent years have seen substantial attention devoted to the problem of horizontal pleiotropy, and in this review we outline how newly developed methods can be used together to improve the reliability of MR.
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“This pattern is consistent with a directional influence of disease liability on longevity27,64 and is also compatible with vertical pleiotropy65.”
From Genetic trade-offs in fertility and longevity explain the maintenance of disease-associated alleles in humans (2026) · cites this paper as [65]
In the citing paper
“However, confounding of the genetic variants with the outcome in a sample can be induced by population stratification, dynastic effects and assortative mating,60 violating the second IV condition.”
From Mendelian randomization (2022) · cites this paper as [60]
In the citing paper
“If there are many correlated candidate variants in a gene region, then including all variants in a single analysis will typically result in numerical instability, as the analysis can be highly sensitive to small changes in the variant correlation matrix 62 .”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [62]
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Cites
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · cited 1×
“Independence is often ensured using LDbased clumping and pruning (45).”
MethodBowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · cited 3×
“Here, it is assumed that on an average the random effects have zero mean and are uncorrelated with the SNP-exposure effect (55) (Appendix 1).”
BackgroundMethodSelf-citationBowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · cited 2×
“This can be extended to a more efficient weighted analysis, which then requires that the set of instruments accounting for 50% or more of the total weight is valid (64).”
BackgroundSelf-citationVerbanck, M., Chen, C.-Y., Neale, B., & Do, R. (2018) · Nature Genetics · doi:10.1038/s41588-018-0099-7 · Cited by 8,591 · cited 3×
“based heterogeneity and outlier test is proposed within MR-PRESSO (61), which performs similarly to modified second-order”
BackgroundMethodThe 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 · cited 8×
“It is also common to see leaveone-out analyses where the causal effect is re-estimated but sequentially omitting a particular instrument each time, to evaluate if any one variant is driving the analysis (8).”
BackgroundMethodResultInfluentialSelf-citationDavey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · cited 3×
“In these cases, extending the analogy to RCTs, each instrumenting SNP is considered an independent experiment (in the sense that they independently modify the exposure), and as such the results from each experiment can be meta-analysed to give an overall estimate (7,46,47).”
MethodCommon polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
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 · cited 5×
“In these cases, extending the analogy to RCTs, each instrumenting SNP is considered an independent experiment (in the sense that they independently modify the exposure), and as such the results from each experiment can be meta-analysed to give an overall estimate (7,46,47).”
MethodInfluentialSelf-citationGiambartolomei, C., Vukcevic, D., Schadt, E. E., Franke, L., Hingorani, A. D., Wallace, C., & Plagnol, V. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004383 · Cited by 4,261 · cited 4×
“The R/coloc (25) package uses summary data for the SNPs in a region and estimates the posterior probability of shared genetic factors by evaluating the similarity of effect size patterns across the region.”
BackgroundMethodInfluentialIdentification and estimation of local average treatment effects
Imbens, G. W., & Angrist, J. D. (1994) · Econometrica · doi:10.2307/2951620 · Cited by 4,101
Research works printed but not linked: 1
- Purcell, 2009, International Schizophrenia Consortium, Nature, 460, 748
Cited by
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Morley, A. P., Ardissino, M., Carter, P., Raman, B., Mead, A. J., Quirós, P. M., Vassiliou, G. S., & Raisi‐Estabragh, Z. (2025) · Open Heart · doi:10.1136/openhrt-2025-003602 · Cited by 3
“35 Limitations While helpful in removing systematic biases, MR cannot completely exclude the potential for horizontal and/ or vertical pleiotropy, 60 although appreciation of relevant potential biological mechanisms can aid in understanding these limitations.”
Metadata
- Authors
- Hemani, G., Bowden, J., & Davey Smith, G.
- Affiliations
- University of Bristol (GB)
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol
- Corresponding author
- Hemani, Gibran
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-05-16
- Volume
- 27
- Issue
- R2
- Pages
- R195-R208
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- PMC
- PMC6061876
- OpenAlex
- W2810852503
- Cited by
- 1,496
- References
- 113
- Citations by year
- 2026: 129 · 2025: 266 · 2024: 422 · 2023: 209 · 2022: 169 · 2021: 131 · 2020: 101 · 2019: 62 · 2018: 7
- FWCI
- 10.71
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Human Molecular Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (208806/Z/17/Z)
- Medical Research Council (MC_UU_12013/1)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetics and Physical Performance
- Keywords
- pleiotropy, Mendelian randomization, horizontal pleiotropy, single nucleotide polymorphisms, causal inference, phenome-wide association study, genetic variants
- MeSH terms
- Animals, Humans, Phenotype, Genetic Variation, Reproducibility of Results, Genome, Human, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Mendelian Randomization Analysis, Genetic Pleiotropy
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