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dc.contributor.authorZuber, Verena
dc.contributor.authorGrinberg, Nastasiya F
dc.contributor.authorGill, Dipender
dc.contributor.authorManipur, Ichcha
dc.contributor.authorSlob, Eric AW
dc.contributor.authorPatel, Ashish
dc.contributor.authorWallace, Chris
dc.contributor.authorBurgess, Stephen
dc.date.accessioned2022-05-25T01:04:35Z
dc.date.available2022-05-25T01:04:35Z
dc.date.issued2022-05-05
dc.identifier.issn0002-9297
dc.identifier.other35452592
dc.identifier.otherPMC7612737
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337446
dc.description.abstractMendelian 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.
dc.languageeng
dc.publisherElsevier BV
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.sourcenlmid: 0370475
dc.sourceessn: 1537-6605
dc.subjectGenetic epidemiology
dc.subjectCausal Inference
dc.subjectPhenome-wide Association Study
dc.subjectPost-gwas Investigations
dc.subjectShared Heritability
dc.subjectHumans
dc.subjectCausality
dc.subjectPhenotype
dc.subjectGenome-Wide Association Study
dc.subjectMendelian Randomization Analysis
dc.titleCombining evidence from Mendelian randomization and colocalization: Review and comparison of approaches.
dc.typeArticle
dc.date.updated2022-05-25T01:04:35Z
prism.endingPage782
prism.issueIdentifier5
prism.publicationNameAm J Hum Genet
prism.startingPage767
prism.volume109
dc.identifier.doi10.17863/CAM.84859
dcterms.dateAccepted2022-03-31
rioxxterms.versionofrecord10.1016/j.ajhg.2022.04.001
rioxxterms.versionVoR
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidBurgess, Stephen [0000-0001-5365-8760]
dc.identifier.eissn1537-6605
pubs.funder-project-idWellcome Trust (204623/Z/16/Z)
pubs.funder-project-idMedical Research Council (MC_UU_00002/4)
pubs.funder-project-idMedical Research Council (MC_UU_00002/7)
pubs.funder-project-idNational Institute for Health Research (IS-BRC-1215-20014)
pubs.funder-project-idWellcome Trust (220788/Z/20/Z)
cam.issuedOnline2022-04-21


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International