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Combining evidence from Mendelian randomization and colocalization: Review and comparison of approaches

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Zuber, Verena, Grinberg, Nastasiya F., Gill, Dipender, Manipur, Ichcha, Slob, Eric A.W., Patel, Ashish, Wallace, Chris, Burgess, Stephen·2022·The American Journal of Human Genetics
DOI 10.1016/j.ajhg.2022.04.001PMC PMC7612737
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Abstract

Mendelian randomization and colocalization are two statistical approaches that can be applied to summarized data from genome-wide association studies (GWASs) to understand relationships between traits and diseases. However, despite similarities in scope, they are different in their objectives, implementation, and interpretation, in part because they were developed to serve different scientific communities. Mendelian randomization assesses whether genetic predictors of an exposure are associated with the outcome and interprets an association as evidence that the exposure has a causal effect on the outcome, whereas colocalization assesses whether two traits are affected by the same or distinct causal variants. When considering genetic variants in a single genetic region, both approaches can be performed. While a positive colocalization finding typically implies a non-zero Mendelian randomization estimate, the reverse is not generally true: there are several scenarios which would lead to a non-zero Mendelian randomization estimate but lack evidence for colocalization. These include the existence of distinct but correlated causal variants for the exposure and outcome, which would violate the Mendelian randomization assumptions, and a lack of strong associations with the outcome. As colocalization was developed in the GWAS tradition, typically evidence for colocalization is concluded only when there is strong evidence for associations with both traits. In contrast, a non-zero estimate from Mendelian randomization can be obtained despite only nominally significant genetic associations with the outcome at the locus. In this review, we discuss how the two approaches can provide complementary information on potential therapeutic targets.

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  • The study applied MR to significant colocalisation events to assess causality, a strategy recommended by Zuber et al.

    “We then applied MR to significant colocalisation events to assess causality, a strategy recommended by Zuber et al.17.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [17]

    The Discussion recommends that positive cis-MR analyses be accompanied by colocalization, supporting the use of the two methods together. It does not recommend the specific strategy attributed here—selecting significant colocalization events and then applying MR to them. Page numbers are unavailable in our copy. (LLM, conf=0.86)

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  • A positive colocalisation finding typically implies a non-zero MR estimate, but the reverse is not generally true.

    “As they have highlighted, a positive colocalisation finding typically implies a non-zero MR estimate, the reverse is not generally true17.”

    From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [17]

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Sorted by citations

Authors
Zuber, V., Grinberg, N. F., Gill, D., Manipur, I., Slob, E. A. W., Patel, A., Wallace, C., & Burgess, S.
Affiliations
  • UK Dementia Research Institute (GB)
  • National Institute of Agricultural Botany (GB)
  • St George's, University of London (GB)
  • University of Cambridge (GB)
Corresponding author
Burgess, Stephen
ORCID
Venue
The American Journal of Human Genetics
Publisher
Elsevier BV
Published
2022-05
Volume
109
Issue
5
Pages
767-782
ISSN
0002-9297 (ISSN-L)
DOI
10.1016/j.ajhg.2022.04.001
PMC
PMC7612737
OpenAlex
W4224299153
Cited by
532
References
22
Citations by year
2026: 107 · 2025: 157 · 2024: 186 · 2023: 67 · 2022: 15
FWCI
16.63
Type
journal article
Language
en
Open access
Licence
Locations
  • The American Journal of Human Genetics (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • Apollo (University of Cambridge) (submittedVersion)
  • Apollo (University of Cambridge) (submittedVersion, cc-by)
  • Apollo
  • Apollo (cc-by)
Funders
  • Wellcome Trust (204623/Z/16/Z, WT220788, 107881/Z/15/Z, 204623, 220788/Z/20/Z, BRC-1215-20014, 220788)
  • National Institute for Health and Care Research ([IS-BRC-1215-20014, NIHRDH-IS-BRC-1215-20014, BRC1215-20014)
  • Department of Health and Social Care
  • Royal Society (204623/Z/16/Z, BRC-1215-20014)
  • Medical Research Council (MR/S019669/1, MC_UU_00002/4, MC_PC_17228, BRC-1215-20014, MR/W029790/1, MC UU 00002/7)
  • NIHR Cambridge Biomedical Research Centre ((BRC-1215-20014))
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and phenotypic traits in livestock
Keywords
Mendelian randomization, colocalization, causal inference, genetic variants, genome-wide association study, causal variants, therapeutic target
MeSH terms
Humans, Phenotype, Causality, Genome-Wide Association Study, Mendelian Randomization Analysis

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