Prostate cancer risk prediction using a polygenic risk score

dc.contributor.authorCsilla Sipeky
dc.contributor.authorKirsi M. Talala
dc.contributor.authorTeuvo L. J. Tammela
dc.contributor.authorKimmo Taari
dc.contributor.authorAnssi Auvinen & Johanna Schleutker
dc.contributor.organizationfi=biolääketieteen laitos|en=Institute of Biomedicine|
dc.contributor.organizationfi=tyks, vsshp|en=tyks, varha|
dc.contributor.organization-code1.2.246.10.2458963.20.77952289591
dc.converis.publication-id50706910
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/50706910
dc.date.accessioned2022-10-28T13:26:38Z
dc.date.available2022-10-28T13:26:38Z
dc.description.abstractHereditary factors have a strong influence on prostate cancer (PC) risk and poorer outcomes, thus stratification by genetic factors addresses a critical need for targeted PC screening and risk-adapted follow-up. In this Finnish population-based retrospective study 2283 clinically diagnosed and 455 screen-detected patients from the Finnish Randomised Study of Screening for Prostate Cancer (FinRSPC), 2400 healthy individuals have been involved. Individual genetic risk through establishment of a polygenic risk score based on 55 PC risk SNPs identified through the Finnish subset of the Collaborative Oncological Gene-Environment Study was assessed. Men with PC had significantly higher median polygenic risk score compared to the controls (6.59 vs. 3.83, P<0.0001). The polygenic risk score above the control median was a significant predictor of PC (OR 2.13, 95% CI 1.90-2.39). The polygenic risk score predicted the risk of PC with an AUC of 0.618 (95% CI 0.60-0.63). Men in the highest polygenic risk score quartile were 2.8-fold (95% CI 2.4-3.30) more likely to develop PC compared with men in the lowest quartile. In the FinRSPC cohort, a significantly higher percentage of men had a PSA level of4 ng/mL in polygenic risk score quartile four compared to quartile one (18.7% vs 8.3%, P<0.00001). Adding the PRS to a PSA-only model contributed additional information in predicting PC in the FinRSPC model. Results strongly suggest that use of the polygenic risk score would facilitate the identification of men at increased risk for PC.
dc.identifier.eissn2045-2322
dc.identifier.jour-issn2045-2322
dc.identifier.olddbid182118
dc.identifier.oldhandle10024/165212
dc.identifier.urihttps://www.utupub.fi/handle/11111/39304
dc.identifier.urnURN:NBN:fi-fe2021042827064
dc.language.isoen
dc.okm.affiliatedauthorSipeky, Csilla
dc.okm.affiliatedauthorSchleutker, Johanna
dc.okm.affiliatedauthorDataimport, tyks, vsshp
dc.okm.discipline3122 Cancersen_GB
dc.okm.discipline3122 Syöpätauditfi_FI
dc.okm.internationalcopublicationnot an international co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherNATURE RESEARCH
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.articlenumberARTN 17075
dc.relation.doi10.1038/s41598-020-74172-z
dc.relation.ispartofjournalScientific Reports
dc.relation.issue1
dc.relation.volume10
dc.source.identifierhttps://www.utupub.fi/handle/10024/165212
dc.titleProstate cancer risk prediction using a polygenic risk score
dc.year.issued2020

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