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dc.contributor.authorWolfson, Michael
dc.contributor.authorGribble, Steve
dc.contributor.authorPashayan, Nora
dc.contributor.authorEaston, Douglas F.
dc.contributor.authorAntoniou, Antonis C.
dc.contributor.authorLee, Andrew
dc.contributor.authorvan Katwyk, Sasha
dc.contributor.authorSimard, Jacques
dc.date.accessioned2021-10-28T15:25:59Z
dc.date.available2021-10-28T15:25:59Z
dc.date.issued2021-07-06
dc.date.submitted2021-01-24
dc.identifier.issn1098-3600
dc.identifier.others41436-021-01258-y
dc.identifier.other1258
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/330000
dc.descriptionFunder: Genome Canada; doi: https://doi.org/10.13039/http://dx.doi.org/10.13039/100008762
dc.description.abstractAbstract: Purpose: Breast cancer risk has conventionally been assessed using family history (FH) and rare high/moderate penetrance pathogenic variants (PVs), notably in BRCA1/2, and more recently PALB2, CHEK2, and ATM. In addition to these PVs, it is now possible to use increasingly predictive polygenic risk scores (PRS) as well. The comparative population-level predictive capability of these three different indicators of genetic risk for risk stratification is, however, unknown. Methods: The Canadian heritable breast cancer risk distribution was estimated using a novel genetic mixing model (GMM). A realistically representative sample of women was synthesized based on empirically observed demographic patterns for appropriately correlated family history, inheritance of rare PVs, PRS, and residual risk from an unknown polygenotype. Risk assessment was simulated using the BOADICEA risk algorithm for 10-year absolute breast cancer incidence, and compared to heritable risks as if the overall polygene, including its measured PRS component, and PV risks were fully known. Results: Generally, the PRS was most predictive for identifying women at high risk, while family history was the weakest. Only the PRS identified any women at low risk of breast cancer. Conclusion: PRS information would be the most important advance in enabling effective risk stratification for population-wide breast cancer screening.
dc.languageen
dc.publisherNature Publishing Group US
dc.subjectArticle
dc.subjectarticle
dc.titlePotential of polygenic risk scores for improving population estimates of women’s breast cancer genetic risks
dc.typeArticle
dc.date.updated2021-10-28T15:25:58Z
prism.endingPage2121
prism.issueIdentifier11
prism.publicationNameGenetics in Medicine
prism.startingPage2114
prism.volume23
dc.identifier.doi10.17863/CAM.77444
dcterms.dateAccepted2021-06-10
rioxxterms.versionofrecord10.1038/s41436-021-01258-y
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
dc.contributor.orcidWolfson, Michael [0000-0003-1941-955X]
dc.identifier.eissn1530-0366


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