Karina Dalsgaard Sørensen

Risk Analysis of Prostate Cancer in PRACTICAL, a Multinational Consortium, Using 25 Known Prostate Cancer Susceptibility Loci

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

  • Ali Amin Al Olama, Unknown
  • Sara Benlloch
  • ,
  • Antonis C Antoniou
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  • Graham G Giles
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  • Gianluca Severi
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  • David Neal
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  • Freddie C Hamdy
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  • Jenny L Donovan
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  • Kenneth Muir
  • ,
  • Johanna Schleutker
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  • Brian E Henderson
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  • Christopher Haiman
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  • Fredrick R Schumacher
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  • Nora Pashayan, Unknown
  • Paul D P Pharoah
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  • Elaine A Ostrander
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  • Janet L Stanford
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  • Jyotsna Batra
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  • Judith A Clements
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  • Suzanne K Chambers, Unknown
  • Maren Weischer
  • ,
  • Børge G Nordestgaard
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  • Sue Ann Ingles, Unknown
  • Karina Dalsgaard Sørensen
  • Torben F Orntoft
  • Jong Y Park
  • ,
  • Cezary Cybulski
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  • Christiane Maier
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  • Thilo Doerk
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  • Joanne L Dickinson
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  • Lisa Cannon-Albright
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  • Hermann Brenner
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  • Timothy R Rebbeck
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  • Charnita Zeigler-Johnson, Unknown
  • Tomonori Habuchi
  • ,
  • Stephen N Thibodeau
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  • Kathleen Cooney
  • ,
  • Pierre O Chappuis, Unknown
  • Pierre Hutter, Unknown
  • Radka P Kaneva, Unknown
  • William D Foulkes, Unknown
  • Maurice P Zeegers
  • ,
  • Yong-Jie Lu
  • ,
  • Hong-Wei Zhang, Unknown
  • Robert Stephenson
  • ,
  • Angela Cox
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  • Melissa C Southey
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  • Amanda B Spurdle
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  • Liesel FitzGerald
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  • The UK Genetic Prostate Cancer Study Collaborators/British Association of Urological Surgeons' Section of Oncology
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  • The UK ProtecT Study Collaborators
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  • The PRACTICAL Consortium

BACKGROUND: Genome-wide association studies have identified multiple genetic variants associated with prostate cancer (PrCa) risk which explain a substantial proportion of familial relative risk. These variants can be used to stratify individuals by their risk of PrCa.

METHODS: We genotyped 25 PrCa susceptibility loci in 40,414 individuals and derived a polygenic risk score (PRS). We estimated empirical Odds Ratios for PrCa associated with different risk strata defined by PRS and derived age-specific absolute risks of developing PrCa by PRS stratum and family history.

RESULTS: The PrCa risk for men in the top 1% of the PRS distribution was 30.6 (95% CI 16.4-57.3) fold compared with men in the bottom 1%, and 4.2 (95% CI 3.2-5.5) fold compared with the median risk. The absolute risk of PrCa by age 85 was 65.8% for a man with family history in the top 1% of the PRS distribution, compared with 3.7% for a man in the bottom 1%. The PRS was only weakly correlated with serum PSA level (correlation=0.09).

CONCLUSIONS: Risk profiling can identify men at substantially increased or reduced risk of PrCa. The effect size, measured by OR per unit PRS, was higher in men at younger ages and in men with family history of PrCa. Incorporating additional newly identified loci into a PRS should improve the predictive value of risk profiles.

IMPACT: We demonstrate that the risk profiling based on SNPs can identify men at substantially increased or reduced risk that could have useful implications for targeted prevention and screening programs.

Original languageEnglish
JournalCancer Epidemiology, Biomarkers & Prevention
Volume24
Issue7
Pages (from-to)1121-1129
ISSN1055-9965
DOIs
Publication statusPublished - 2 Apr 2015

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