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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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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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