Invited Commentary: Detecting Individual and Global Horizontal Pleiotropy in Mendelian Randomization-A Job for the Humble Heterogeneity Statistic?
Open accessAbstract
Mendelian randomization (MR) is gaining in recognition and popularity as a method for strengthening causal inference in epidemiology by utilizing genetic variants as instrumental variables. Concurrently with the explosion in empirical MR studies, there has been the steady production of new approaches for MR analysis. The recently proposed "global and individual tests for direct effects" (GLIDE) approach fits into a family of methods that aim to detect horizontal pleiotropy-at the individual single nucleotide polymorphism level and at the global level-and to adjust the analysis by removing outlying single nucleotide polymorphisms. In this commentary, we explain how existing methods can (and indeed are) being used to detect pleiotropy at the individual and global levels, although not explicitly using this terminology. By doing so, we show that the true comparator for GLIDE is not MR-Egger regression (as Dai et al., the authors of the accompanying article (Am J Epidemiol. 2018;187(12):2672-2680), claim) but rather the humble heterogeneity statistic.
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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 [43]
In a one-sample setting with individual-level data, a causal effect estimate can be obtained using the two-stage least-squares (2SLS) method.
“In a one-sample setting with individual-level data, a causal effect estimate can be obtained using the two-stage least-squares (2SLS) method.”
From Guidelines for performing Mendelian randomization investigations (2020) · cites this paper as [71]
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- Authors
- Bowden, J., Hemani, G., & Davey Smith, G.
- Affiliations
- University of Bristol (GB)
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Corresponding author
- Bowden, Jack
- Venue
- American Journal of Epidemiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-09-05
- Volume
- 187
- Issue
- 12
- Pages
- 2681-2685
- ISSN
- 0002-9262 (ISSN-L)
- 1476-6256
- PMC
- PMC6269239
- OpenAlex
- W2891812515
- Cited by
- 251
- References
- 28
- Citations by year
- 2026: 8 · 2025: 36 · 2024: 84 · 2023: 35 · 2022: 27 · 2021: 21 · 2020: 26 · 2019: 14
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- American Journal of Epidemiology (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)
- Explore Bristol Research (submittedVersion, cc-by)
- Funders
- Medical Research Council (MC_UU_00011/2, MC_UU_00011/1)
- 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
- horizontal pleiotropy, Mendelian randomization, glides, instrumental variable validity, causal inference
- MeSH terms
- Polymorphism, Single Nucleotide, Mendelian Randomization Analysis
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