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dc.contributor.authorGrant, Andrew
dc.contributor.authorKirk, Paul
dc.contributor.authorBurgess, Stephen
dc.date.accessioned2022-01-12T00:30:31Z
dc.date.available2022-01-12T00:30:31Z
dc.date.issued2022-01-27
dc.identifier.issn1553-7390
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/332633
dc.description.abstractClustering genetic variants based on their associations with different traits can provide insight into their underlying biological mechanisms. Existing clustering approaches typically group variants based on the similarity of their association estimates for various traits. We present a new procedure for clustering variants based on their proportional associations with different traits, which is more reflective of the underlying mechanisms to which they relate. The method is based on a mixture model approach for directional clustering and includes a noise cluster that provides robustness to outliers. The procedure performs well across a range of simulation scenarios. In an applied setting, clustering genetic variants associated with body mass index generates groups reflective of distinct biological pathways. Mendelian randomization analyses support that the clusters vary in their effect on coronary heart disease, including one cluster that represents elevated body mass index with a favourable metabolic profile and reduced coronary heart disease risk. Analysis of the biological pathways underlying this cluster identifies inflammation as potentially explaining differences in the effects of increased body mass index on coronary heart disease.
dc.publisherPublic Library of Science (PLoS)
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleNoise-augmented directional clustering of genetic association data identifies distinct mechanisms underlying obesity
dc.typeArticle
dc.publisher.departmentMrc Biostatistics Unit
dc.date.updated2022-01-10T13:56:35Z
prism.publicationDate2022
prism.publicationNamePLoS Genetics
dc.identifier.doi10.17863/CAM.80078
dcterms.dateAccepted2021-12-01
rioxxterms.versionAM
dc.contributor.orcidBurgess, Stephen [0000-0001-5365-8760]
rioxxterms.typeJournal Article/Review
pubs.funder-project-idWellcome Trust (204623/Z/16/Z)
cam.issuedOnline2022-01-27
cam.orpheus.success2022-01-11 - Embargo set during processing via Fast-track
cam.depositDate2022-01-10
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement
rioxxterms.freetoread.startdate2022-01-27


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