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Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases
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Abstract
Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the 'no horizontal pleiotropy' assumption can cause severe bias in MR. We developed the Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that the MR-PRESSO test is best suited when horizontal pleiotropy occurs in <50% of instruments. Next we applied the MR-PRESSO test, along with several other MR tests, to complex traits and diseases and found that horizontal pleiotropy (i) was detectable in over 48% of significant causal relationships in MR; (ii) introduced distortions in the causal estimates in MR that ranged on average from -131% to 201%; (iii) induced false-positive causal relationships in up to 10% of relationships; and (iv) could be corrected in some but not all instances.
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“We further used the MR-PRESSO global test49 to assess for horizontal pleiotropy and found no significant P values in the four studies used in the MR meta-analysis (UKB GWAX P = 0.07, UKB GWAS P = 0.20, FinnGen P = 0.84 and GR@ACE P = 0.91, all P values unadjusted for multiple comparisons).”
From Clonal hematopoiesis is associated with protection from Alzheimer’s disease (2023) · cites this paper as [49]
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“To ensure the robustness of our findings, we employed sensitivity analyses using Cochran’s Q statistic to assess heterogeneity among instrumental variables and the MR–Egger intercept and MR pleiotropy residual sum and outlier (MR-PRESSO) to evaluate potential pleiotropy90.”
From Genetic trade-offs in fertility and longevity explain the maintenance of disease-associated alleles in humans (2026) · cites this paper as [90]
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Metadata
- Authors
- Verbanck, M., Chen, C.-Y., Neale, B., & Do, R.
- Affiliations
- Icahn School of Medicine at Mount Sinai (US)
- Broad Institute (US)
- Corresponding author
- Neale, Benjamin
- Do, Ron
- Venue
- Nature Genetics
- Published
- 2018-04-23
- Volume
- 50
- Issue
- 5
- Pages
- 693-698
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6083837
- OpenAlex
- W2803072880
- Cited by
- 8,591
- References
- 77
- Citations by year
- 2026: 837 · 2025: 1873 · 2024: 2845 · 2023: 1422 · 2022: 743 · 2021: 441 · 2020: 252 · 2019: 136 · 2018: 35
- FWCI
- 134.78
- Type
- journal article
- Language
- en
- Update notices
- correction (2018-07-02)
- Open access
- green
- doi.org
- Licence
- cc-by-nc-nd
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- American Heart Association (15CVGPSD27130014)
- National Institutes of Health
- National Heart, Lung, and Blood Institute (R01HL139865)
- National Institute of Mental Health (R01MH107649, R01MH094469)
- National Human Genome Research Institute (U01HG009088)
- National Institute of General Medical Sciences (R35GM124836)
- 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, MR-PRESSO, causal inference, complex traits, disease, summary-level data
- MeSH terms
- Disease, Humans, Genetic Variation, Genetic Predisposition to Disease, Genetic Pleiotropy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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