Show simple item record

dc.contributor.authorNyberg, Tommyen
dc.contributor.authorDadaev, Tokhiren
dc.contributor.authorGovindasami, Koveelaen
dc.contributor.authorLee, Andrewen
dc.contributor.authorLeslie, Malgorzataen
dc.contributor.authorKote-Jarai, Zsofiaen
dc.contributor.authorEeles, Rosalinden
dc.contributor.authorAntoniou, Antonisen
dc.date.accessioned2018-09-05T11:06:15Z
dc.date.available2018-09-05T11:06:15Z
dc.date.issued2017-11en
dc.identifier.issn0741-0395
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/279133
dc.description.abstractG84E missense mutations in HOXB13 are associated with prostate cancer. However, a wide range of risk estimates has been reported. Based on case-control studies, reported OR range from 2 to 20, often with wide confidence intervals because mutations are rare in the population. To obtain more precise risk estimates, we used a kin-cohort study design and modified segregation analysis, using family data on 11,988 PCa index-cases (4509 consecutive cases, 870 and 6609 cases recruited based on family history and young age at diagnosis, respectively) enrolled in the UK Genetic Prostate Cancer Study, who had been genotyped for G84E. Among index-cases, 182 carried at least one copy of G84E. PCa incidence was assumed to follow a mixed Cox regression model of the form λ(t)=λ_0 (t)"×exp" (G+P), where G is a fixed effect which depends on G84E, P∈N(0,σ_P^2 ) a residual polygenic random effect, and λ_0 (t) is the baseline incidence for non-carriers to age t. Using maximum likelihood, after adjusting for ascertainment, we estimated the frequency and RR (i.e. penetrance) for G84E under different genetic models, and σ_P. Preliminary results suggest that under the best fitting model, the data are consistent with a multiplicative model where each copy of G84E confers RR for PCa of 2.6 (95%CI 1.7-4.2), and a significant σ_P of 1.8 (95%CI 1.7-1.9), indicating that family history increases risk above that resulting from being a mutation carrier. Ongoing work will evaluate effect-modification of RR and/or σ_P by age, birth cohort, and mutation status, and estimate absolute risks for reference family structures.
dc.titleHOXB13 G84E Mutation and Prostate Cancer Risk: Kin-Cohort Analysis Using Data From the UK Genetic Prostate Cancer Studyen
dc.typeConference Object
prism.endingPage676
prism.issueIdentifier7en
prism.publicationDate2017en
prism.publicationNameGENETIC EPIDEMIOLOGYen
prism.startingPage676
prism.volume41en
dc.identifier.doi10.17863/CAM.26513
dcterms.dateAccepted2017-06-23en
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserveden
rioxxterms.licenseref.startdate2017-11en
dc.contributor.orcidNyberg, Tommy [0000-0002-9436-0626]
dc.contributor.orcidLee, Andrew [0000-0003-0677-0252]
dc.contributor.orcidAntoniou, Antonis [0000-0001-9223-3116]
dc.identifier.eissn1098-2272
rioxxterms.typeConference Paper/Proceeding/Abstracten
pubs.funder-project-idCancer Research UK (20861)
pubs.funder-project-idCancer Research UK (C12292/A11174)
rioxxterms.freetoread.startdate2018-11-30


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record