Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome
Open accessAbstract
Mendelian randomisation (MR) estimates causal effects of modifiable phenotypes on an outcome by using genetic variants as instrumental variables, but its validity relies on the assumption of no pleiotropy, that is, genes influence the outcome only through the given phenotype. Excluding pleiotropy is difficult, but the use of multiple instruments can indirectly address the issue: if all genes represent valid instruments, their MR estimates should vary only by chance. The Sargan test detects pleiotropy when individual phenotype, outcome and genotype data are measured in the same subjects. We propose an alternative approach to be used when only summary genetic data are available or data on gene-phenotype and gene-outcome come from different subjects. The presence of pleiotropy is investigated using the between-instrument heterogeneity Q test (together with the I(2) index) in a meta-analysis of MR Wald estimates, derived separately from each instrument. For a continuous outcome, we evaluate the approach through simulations and illustrate it using published data. For the scenario where all data come from the same subjects, we compare it with the Sargan test. The Q test tends to be conservative in small samples. Its power increases with the degree of pleiotropy and the sample size, as does the precision of the I(2) index, in which case results are similar to those of the Sargan test. In MR studies with large sample sizes based on summary data, the between-instrument Q test represents a useful tool to explore the presence of heterogeneity due to pleiotropy or other causes.
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The study addressed bias from pleiotropic variants by considering heterogeneity in MR estimates from different instrument SNPs and by using weighted median MR sensitivity analysis.
“which we addressed by considering the heterogeneity in the MR estimates produced by our different instrument SNPs [27,43] and in statistical sensitivity analysis using the weighted median MR approach, which is more robust to the inclusion of pleiotropic variants [29].”
From Associations of genetically determined iron status across the phenome: A mendelian randomization study (2019) · cites this paper as [27]
When genetic variants are all valid instruments, power depends on the proportion of variance in the exposure explained by the variants, so a polygenic Mendelian randomization investigation will typically have greater power than one including variants only from a single gene region.
“When genetic variants are all valid instruments, power depends on the proportion of variance in the exposure explained by the variants 56 – hence a polygenic Mendelian randomization investigation will typically have greater power than one including variants only from a single gene region.”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [56]
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- Authors
- Greco M, F. D., Minelli, C., Sheehan, N. A., & Thompson, J. R.
- Affiliations
- Center for Biomedicine, EURAC research Bolzano Italy
- Imperial College London (GB)
- University of Leicester (GB)
- Venue
- Statistics in Medicine
- Publisher
- Wiley
- Published
- 2015-05-07
- Volume
- 34
- Issue
- 21
- Pages
- 2926-2940
- ISSN
- 0277-6715 (ISSN-L)
- 1097-0258
- OpenAlex
- W1902575419
- Cited by
- 1,700
- References
- 43
- Citations by year
- 2026: 154 · 2025: 371 · 2024: 606 · 2023: 244 · 2022: 113 · 2021: 70 · 2020: 45 · 2019: 35 · 2018: 26 · 2017: 22 · 2016: 11 · 2015: 3
- FWCI
- 14.14
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Statistics in Medicine (publishedVersion)
- PubMed (publishedVersion)
- Figshare (submittedVersion, cc-by)
- Leicester Research Archive (University of Leicester) (submittedVersion, other-oa)
- Spiral (Imperial College London) (submittedVersion)
- Open Research (University of Surrey) (submittedVersion)
- Funders
- Royal Society (Travel grant)
- 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
- pleiotropy, Mendelian randomization, continuous outcomes, multiple instruments, causal inference, meta-analysis heterogeneity
- MeSH terms
- Computer Simulation, Diabetes Mellitus, Humans, Models, Genetic, Phenotype, Regression Analysis, Sensitivity and Specificity, Genetic Variation, Meta-Analysis as Topic, Causality, Sample Size, Mendelian Randomization Analysis, Genetic Pleiotropy
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