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dc.contributor.authorBurren, Oliver S
dc.contributor.authorReales, Guillermo
dc.contributor.authorWong, Limy
dc.contributor.authorBowes, John
dc.contributor.authorLee, James C
dc.contributor.authorBarton, Anne
dc.contributor.authorLyons, Paul A
dc.contributor.authorSmith, Kenneth GC
dc.contributor.authorThomson, Wendy
dc.contributor.authorKirk, Paul DW
dc.contributor.authorWallace, Chris
dc.date.accessioned2020-11-11T00:30:36Z
dc.date.available2020-11-11T00:30:36Z
dc.date.issued2020-11-25
dc.identifier.issn1756-994X
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/312751
dc.description.abstractBACKGROUND: Genome-wide association studies (GWAS) have identified pervasive sharing of genetic architectures across multiple immune-mediated diseases (IMD). By learning the genetic basis of IMD risk from common diseases, this sharing can be exploited to enable analysis of less frequent IMD where, due to limited sample size, traditional GWAS techniques are challenging. METHODS: Exploiting ideas from Bayesian genetic fine-mapping, we developed a disease-focused shrinkage approach to allow us to distill genetic risk components from GWAS summary statistics for a set of related diseases. We applied this technique to 13 larger GWAS of common IMD, deriving a reduced dimension "basis" that summarised the multidimensional components of genetic risk. We used independent datasets including the UK Biobank to assess the performance of the basis and characterise individual axes. Finally, we projected summary GWAS data for smaller IMD studies, with less than 1000 cases, to assess whether the approach was able to provide additional insights into genetic architecture of less common IMD or IMD subtypes, where cohort collection is challenging. RESULTS: We identified 13 IMD genetic risk components. The projection of independent UK Biobank data demonstrated the IMD specificity and accuracy of the basis even for traits with very limited case-size (e.g. vitiligo, 150 cases). Projection of additional IMD-relevant studies allowed us to add biological interpretation to specific components, e.g. related to raised eosinophil counts in blood and serum concentration of the chemokine CXCL10 (IP-10). On application to 22 rare IMD and IMD subtypes, we were able to not only highlight subtype-discriminating axes (e.g. for juvenile idiopathic arthritis) but also suggest eight novel genetic associations. CONCLUSIONS: Requiring only summary-level data, our unsupervised approach allows the genetic architectures across any range of clinically related traits to be characterised in fewer dimensions. This facilitates the analysis of studies with modest sample size by matching shared axes of both genetic and biological risk across a wider disease domain, and provides an evidence base for possible therapeutic repurposing opportunities.
dc.format.mediumElectronic
dc.languageeng
dc.publisherSpringer Science and Business Media LLC
dc.rightsAll rights reserved
dc.titleGenetic feature engineering enables characterisation of shared risk factors in immune-mediated diseases.
dc.typeArticle
prism.issueIdentifier1
prism.publicationDate2020
prism.publicationNameGenome Med
prism.startingPage106
prism.volume12
dc.identifier.doi10.17863/CAM.59852
dcterms.dateAccepted2020-11-02
rioxxterms.versionofrecord10.1186/s13073-020-00797-4
rioxxterms.versionAM
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2020-11-25
dc.contributor.orcidWallace, Chris [0000-0001-9755-1703]
dc.identifier.eissn1756-994X
rioxxterms.typeJournal Article/Review
pubs.funder-project-idWellcome Trust (107881/Z/15/Z)
pubs.funder-project-idMedical Research Council (MC_UU_00002/4)
pubs.funder-project-idWellcome Trust (083650/Z/07/Z)
pubs.funder-project-idWellcome Trust (110303/Z/15/Z)
pubs.funder-project-idWellcome Trust (105920/Z/14/Z)
cam.issuedOnline2020-11-25
cam.orpheus.successTue Feb 01 19:00:22 GMT 2022 - Embargo updated
cam.orpheus.counter6
rioxxterms.freetoread.startdate2020-11-25


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