Prediction of Individual Genetic Risk to Prostate Cancer Using a Polygenic Score

被引：46

作者：

Szulkin, Robert ^{[1
]}

Whitington, Thomas ^{[1
]}

Eklund, Martin ^{[1
]}

Aly, Markus ^{[1
,2
]}

Eeles, Rosalind A. ^{[3
,4
,5
]}

Easton, Douglas ^{[6
]}

Kote-Jarai, ZSofia ^{[3
]}

Al Olama, Ali Amin ^{[6
]}

Benlloch, Sara ^{[6
]}

Muir, Kenneth ^{[7
,8
]}

Giles, Graham G. ^{[9
,10
]}

Southey, Melissa C. ^{[11
]}

Fitzgerald, Liesel M. ^{[9
]}

Henderson, Brian E. ^{[12
]}

Schumacher, Fredrick ^{[12
]}

Haiman, Christopher A. ^{[12
]}

Schleutker, Johanna ^{[13
,14
,15
]}

Wahlfors, Tiina ^{[14
,15
]}

Tammela, Teuvo L. J. ^{[16
,17
]}

Nordestgaard, Borge G. ^{[18
,19
]}

Key, Tim J. ^{[20
]}

Travis, Ruth C. ^{[20
]}

Neal, David E. ^{[21
,22
]}

Donovan, Jenny L. ^{[23
]}

Hamdy, Freddie C. ^{[24
]}

Pharoah, Paul ^{[25
]}

Pashayan, Nora ^{[25
,26
]}

Khaw, Kay-Tee ^{[27
]}

Stanford, Janet L. ^{[28
,29
]}

Thibodeau, Stephen N. ^{[30
]}

McDonnell, Shannon K. ^{[30
]}

Schaid, Daniel J. ^{[30
]}

Maier, Christiane ^{[31
]}

Vogel, Walther ^{[32
]}

Luedeke, Manuel ^{[31
]}

Herkommer, Kathleen ^{[33
]}

Kibel, Adam S. ^{[34
]}

Cybulski, Cezary ^{[35
]}

Lubinski, Jan ^{[35
]}

Kluzniak, Wojciech ^{[35
]}

Cannon-Albright, Lisa ^{[36
,37
]}

Brenner, Hermann ^{[38
,39
,40
]}

Butterbach, Katja ^{[38
]}

Stegmaier, Christa ^{[41
]}

Park, Jong Y. ^{[42
]}

Sellers, Thomas ^{[42
]}

Lim, Hui-Yi ^{[43
]}

Slavov, Chavdar ^{[44
,45
]}

Kaneva, Radka ^{[46
]}

Mitev, Vanio ^{[46
]}

机构：

[1] Karolinska Inst, Dept Med Epidemiol & Biostat, Box 281, SE-17177 Stockholm, Sweden

[2] Danderyd Hosp, Dept Clin Sci, Stockholm, Sweden

[3] Inst Canc Res, London SW3 6JB, England

[4] Royal Marsden Natl Hlth Serv NHS Fdn Trust, London, England

[5] Royal Marsden Natl Hlth Serv NHS Fdn Trust, Sutton, Surrey, England

[6] Univ Cambridge, Strangeways Lab, Dept Publ Hlth & Primary Care, Ctr Canc Genet Epidemiol, Cambridge, England

[7] Univ Manchester, Inst Populat Hlth, Manchester, Lancs, England

[8] Univ Warwick, Warwick Med Sch, Coventry CV4 7AL, W Midlands, England

[9] Canc Council Victoria, Canc Epidemiol Ctr, Melbourne, Vic, Australia

[10] Univ Melbourne, Melbourne Sch Populat & Global Hlth, Ctr Epidemiol & Biostat, Melbourne, Vic 3010, Australia

[11] Univ Melbourne, Dept Pathol, Genet Epidemiol Lab, Melbourne, Vic 3010, Australia

[12] Univ So Calif, Keck Sch Med, Dept Prevent Med, Norris Comprehens Canc Ctr, Los Angeles, CA 90033 USA

[13] Univ Turku, Inst Biomed Kiinamyllynkatu 10, Dept Med Biochem & Genet, SF-20500 Turku, Finland

[14] Univ Tampere, BioMediTech, FIN-33101 Tampere, Finland

[15] FimLab Labs, Tampere, Finland

[16] Univ Tampere, Dept Urol, Tampere Univ Hosp, FIN-33101 Tampere, Finland

[17] Univ Tampere, Sch Med, FIN-33101 Tampere, Finland

[18] Copenhagen Univ Hosp, Herlev Hosp, Dept Clin Biochem, Herlev, Denmark

[19] Univ Copenhagen, Fac Hlth & Med Sci, DK-1168 Copenhagen, Denmark

[20] Univ Oxford, Nuffield Dept Populat Hlth, Canc Epidemiol, Oxford, England

[21] Univ Cambridge, Dept Oncol, Addenbrookes Hosp, Cambridge CB2 1TN, England

[22] Li Ka Shing Ctr, Canc Res UK Cambridge Res Inst, Cambridge, England

[23] Univ Bristol, Sch Social & Community Med, Bristol, Avon, England

[24] Univ Oxford, John Radcliffe Hosp, Fac Med Sci, Nuffield Dept Surg Sci, Oxford OX3 9DU, England

[25] Univ Cambridge, Dept Oncol, Strangeways Res Lab, Ctr Canc Genet Epidemiol, Cambridge, England

[26] UCL, London, England

[27] Univ Cambridge, Clin Gerontol Unit, Cambridge, England

[28] Fred Hutchinson Canc Res Ctr, Div Publ Hlth Sci, Seattle, WA 98104 USA

[29] Univ Washington, Sch Publ Hlth, Dept Epidemiol, Seattle, WA 98195 USA

[30] Mayo Clin, Rochester, MN USA

[31] Univ Hosp Ulm, Dept Urol, Ulm, Germany

[32] Univ Hosp Ulm, Inst Human Genet, Ulm, Germany

[33] Techn Univ Muenchen, Klinikum Rechts Isar, Dept Urol, Munich, Germany

[34] Brigham & Womens Hosp, Dana Farber Canc Inst, Div Urol Surg, Boston, MA 02115 USA

[35] Pomeranian Med Univ, Dept Genet & Pathol, Int Hereditary Canc Ctr, Szczecin, Poland

[36] Univ Utah, Sch Med, Dept Med, Div Genet Epidemiol, Salt Lake City, UT USA

[37] George E Wahlen Dept Vet Affairs Med Ctr, Salt Lake City, UT USA

[38] German Canc Res Ctr, Div Clin Epidemiol & Aging Res, Heidelberg, Germany

[39] German Canc Res Ctr, Div Prevent Oncol, Heidelberg, Germany

[40] German Canc Res Ctr, German Canc Consortium DKTK, Heidelberg, Germany

[41] Saarland Canc Registry, Saarbrucken, Germany

[42] H Lee Moffitt Canc Ctr & Res Inst, Dept Canc Epidemiol, Tampa, FL USA

[43] H Lee Moffitt Canc Ctr & Res Inst, Biostat Program, Tampa, FL USA

[44] Med Univ Sofia, Dept Urol, Sofia, Bulgaria

[45] Med Univ Sofia, Alexandrovska Univ Hosp, Sofia, Bulgaria

[46] Med Univ Sofia, Mol Med Ctr, Dept Med Chem & Biochem, Sofia, Bulgaria

[47] Queensland Univ Technol, Australian Prostate Canc Res Centre Qld, Inst Hlth & Biomed Innovat, Brisbane, Qld 4001, Australia

[48] Queensland Univ Technol, Sch Biomed Sci, Brisbane, Qld 4001, Australia

[49] Australian Prostate Canc BioResource, Brisbane, Qld, Australia

[50] Queensland Inst Med Res, Mol Canc Epidemiol Lab, Brisbane, Qld 4006, Australia

来源：

PROSTATE | 2015年 / 75卷 / 13期

基金：

英国医学研究理事会;

关键词：

prostate cancer; polygenic risk score; risk prediction; SUSCEPTIBILITY LOCI; BREAST; BRCA2; CONSORTIUM; VARIANTS;

D O I：

10.1002/pros.23037

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

BACKGROUND. Polygenic risk scores comprising established susceptibility variants have shown to be informative classifiers for several complex diseases including prostate cancer. For prostate cancer it is unknown if inclusion of genetic markers that have so far not been associated with prostate cancer risk at a genome-wide significant level will improve disease prediction. METHODS. We built polygenic risk scores in a large training set comprising over 25,000 individuals. Initially 65 established prostate cancer susceptibility variants were selected. After LD pruning additional variants were prioritized based on their association with prostate cancer. Six-fold cross validation was performed to assess genetic risk scores and optimize the number of additional variants to be included. The final model was evaluated in an independent study population including 1,370 cases and 1,239 controls. RESULTS. The polygenic risk score with 65 established susceptibility variants provided an area under the curve (AUC) of 0.67. Adding an additional 68 novel variants significantly increased the AUC to 0.68 (P-0012) and the net reclassification index with 0.21 (P-8.5 E-08). All novel variants were located in genomic regions established as associated with prostate cancer risk. CONCLUSIONS. Inclusion of additional genetic variants from established prostate cancer susceptibility regions improves disease prediction. (C) 2015 Wiley Periodicals, Inc.

引用

页码：1467 / 1474

页数：8

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