Prediction of individual genetic risk to prostate cancer using a polygenic score

R Szulkin; T Whitington; M Eklund; M Aly; R A Eeles; D Easton; Z S Kote-Jarai; A Amin Al Olama; S Benlloch; K Muir; G G Giles; M C Southey; L M Fitzgerald; B E Henderson; F Schumacher; C A Haiman; J Schleutker; T Wahlfors; T L Tammela; B G Nordestgaard; T J Key; R C Travis; D E Neal; J L Donovan; F C Hamdy; P Pharoah; N Pashayan; K T Khaw; J L Stanford; S N Thibodeau; S K McDonnell; D J Schaid; C Maier; W Vogel; M Luedeke; K Herkommer; A S Kibel; C Cybulski; J Lubinski; W Kluzniak; L Cannon-Albright; H Brenner; K Butterbach; C Stegmaier; J Y Park; T Sellers; H Y Lim; C Slavov; R Kaneva; V Mitev; J Batra; J A Clements; A Spurdle; M R Teixeira; P Paulo; S Maia; H Pandha; A Michael; A Kierzek; H Gronberg; F Wiklund

doi:10.1002/pros.23037

Prediction of individual genetic risk to prostate cancer using a polygenic score

R Szulkin, T Whitington, M Eklund, M Aly, R A Eeles, D Easton, Z S Kote-Jarai, A Amin Al Olama, S Benlloch, K Muir, G G Giles, M C Southey, L M Fitzgerald, B E Henderson, F Schumacher, C A Haiman, J Schleutker, T Wahlfors, T L Tammela, B G NordestgaardT J Key, R C Travis, D E Neal, J L Donovan, F C Hamdy, P Pharoah, N Pashayan, K T Khaw, J L Stanford, S N Thibodeau, S K McDonnell, D J Schaid, C Maier, W Vogel, M Luedeke, K Herkommer, A S Kibel, C Cybulski, J Lubinski, W Kluzniak, L Cannon-Albright, H Brenner, K Butterbach, C Stegmaier, J Y Park, T Sellers, H Y Lim, C Slavov, R Kaneva, V Mitev, J Batra, J A Clements, A Spurdle, M R Teixeira, P Paulo, S Maia, H Pandha, A Michael, A Kierzek, H Gronberg, F Wiklund

Research output: Contribution to journal › Article › peer-review

Abstract

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 = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-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.

Original language	English
Pages (from-to)	1467-74
Number of pages	1392
Journal	Prostate
Volume	75
Issue number	13
DOIs	https://doi.org/10.1002/pros.23037
Publication status	Published - 2015

Keywords

Genetic Markers
Genetic Predisposition to Disease
Genetic Variation
Humans
Linkage Disequilibrium
Male
Prostatic Neoplasms/ genetics
Risk Factors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1002/pros.23037

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Szulkin, R., Whitington, T., Eklund, M., Aly, M., Eeles, R. A., Easton, D., Kote-Jarai, Z. S., Amin Al Olama, A., Benlloch, S., Muir, K., Giles, G. G., Southey, M. C., Fitzgerald, L. M., Henderson, B. E., Schumacher, F., Haiman, C. A., Schleutker, J., Wahlfors, T., Tammela, T. L., ... Wiklund, F. (2015). Prediction of individual genetic risk to prostate cancer using a polygenic score. Prostate, 75(13), 1467-74. https://doi.org/10.1002/pros.23037

@article{e22b7dee4d484c3f9d1661baa0d2ebbe,

title = "Prediction of individual genetic risk to prostate cancer using a polygenic score",

abstract = "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 = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-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.",

keywords = "Genetic Markers, Genetic Predisposition to Disease, Genetic Variation, Humans, Linkage Disequilibrium, Male, Prostatic Neoplasms/ genetics, Risk Factors",

author = "R Szulkin and T Whitington and M Eklund and M Aly and Eeles, \{R A\} and D Easton and Kote-Jarai, \{Z S\} and \{Amin Al Olama\}, A and S Benlloch and K Muir and Giles, \{G G\} and Southey, \{M C\} and Fitzgerald, \{L M\} and Henderson, \{B E\} and F Schumacher and Haiman, \{C A\} and J Schleutker and T Wahlfors and Tammela, \{T L\} and Nordestgaard, \{B G\} and Key, \{T J\} and Travis, \{R C\} and Neal, \{D E\} and Donovan, \{J L\} and Hamdy, \{F C\} and P Pharoah and N Pashayan and Khaw, \{K T\} and Stanford, \{J L\} and Thibodeau, \{S N\} and McDonnell, \{S K\} and Schaid, \{D J\} and C Maier and W Vogel and M Luedeke and K Herkommer and Kibel, \{A S\} and C Cybulski and J Lubinski and W Kluzniak and L Cannon-Albright and H Brenner and K Butterbach and C Stegmaier and Park, \{J Y\} and T Sellers and Lim, \{H Y\} and C Slavov and R Kaneva and V Mitev and J Batra and Clements, \{J A\} and A Spurdle and Teixeira, \{M R\} and P Paulo and S Maia and H Pandha and A Michael and A Kierzek and H Gronberg and F Wiklund",

note = "Szulkin, Robert Whitington, Thomas Eklund, Martin Aly, Markus Eeles, Rosalind A Easton, Douglas Kote-Jarai, Z Sofia Amin Al Olama, Ali Benlloch, Sara Muir, Kenneth Giles, Graham G Southey, Melissa C Fitzgerald, Liesel M Henderson, Brian E Schumacher, Fredrick Haiman, Christopher A Schleutker, Johanna Wahlfors, Tiina Tammela, Teuvo L J Nordestgaard, Borge G Key, Tim J Travis, Ruth C Neal, David E Donovan, Jenny L Hamdy, Freddie C Pharoah, Paul Pashayan, Nora Khaw, Kay-Tee Stanford, Janet L Thibodeau, Stephen N McDonnell, Shannon K Schaid, Daniel J Maier, Christiane Vogel, Walther Luedeke, Manuel Herkommer, Kathleen Kibel, Adam S Cybulski, Cezary Lubinski, Jan Kluzniak, Wojciech Cannon-Albright, Lisa Brenner, Hermann Butterbach, Katja Stegmaier, Christa Park, Jong Y Sellers, Thomas Lim, Hui-Yi Slavov, Chavdar Kaneva, Radka Mitev, Vanio Batra, Jyotsna Clements, Judith A Australian Prostate Cancer BioResource Spurdle, Amanda Teixeira, Manuel R Paulo, Paula Maia, Sofia Pandha, Hardev Michael, Agnieszka Kierzek, Andrzej Practical Consortium Gronberg, Henrik Wiklund, Fredrik 14136/Cancer Research UK/United Kingdom United States The Prostate Prostate. 2015 Sep;75(13):1467-74. doi: 10.1002/pros.23037. Epub 2015 Jul 14.",

year = "2015",

doi = "10.1002/pros.23037",

language = "English",

volume = "75",

pages = "1467--74",

journal = "Prostate",

issn = "0270-4137",

publisher = "John Wiley \& Sons Ltd",

number = "13",

}

Szulkin, R, Whitington, T, Eklund, M, Aly, M, Eeles, RA, Easton, D, Kote-Jarai, ZS, Amin Al Olama, A, Benlloch, S, Muir, K, Giles, GG, Southey, MC, Fitzgerald, LM, Henderson, BE, Schumacher, F, Haiman, CA, Schleutker, J, Wahlfors, T, Tammela, TL, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, KT, Stanford, JL, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Lubinski, J, Kluzniak, W, Cannon-Albright, L, Brenner, H, Butterbach, K, Stegmaier, C, Park, JY, Sellers, T, Lim, HY, Slavov, C, Kaneva, R, Mitev, V, Batra, J, Clements, JA, Spurdle, A, Teixeira, MR, Paulo, P, Maia, S, Pandha, H, Michael, A, Kierzek, A, Gronberg, H & Wiklund, F 2015, 'Prediction of individual genetic risk to prostate cancer using a polygenic score', Prostate, vol. 75, no. 13, pp. 1467-74. https://doi.org/10.1002/pros.23037

TY - JOUR

T1 - Prediction of individual genetic risk to prostate cancer using a polygenic score

AU - Szulkin, R

AU - Whitington, T

AU - Eklund, M

AU - Aly, M

AU - Eeles, R A

AU - Easton, D

AU - Kote-Jarai, Z S

AU - Amin Al Olama, A

AU - Benlloch, S

AU - Muir, K

AU - Giles, G G

AU - Southey, M C

AU - Fitzgerald, L M

AU - Henderson, B E

AU - Schumacher, F

AU - Haiman, C A

AU - Schleutker, J

AU - Wahlfors, T

AU - Tammela, T L

AU - Nordestgaard, B G

AU - Key, T J

AU - Travis, R C

AU - Neal, D E

AU - Donovan, J L

AU - Hamdy, F C

AU - Pharoah, P

AU - Pashayan, N

AU - Khaw, K T

AU - Stanford, J L

AU - Thibodeau, S N

AU - McDonnell, S K

AU - Schaid, D J

AU - Maier, C

AU - Vogel, W

AU - Luedeke, M

AU - Herkommer, K

AU - Kibel, A S

AU - Cybulski, C

AU - Lubinski, J

AU - Kluzniak, W

AU - Cannon-Albright, L

AU - Brenner, H

AU - Butterbach, K

AU - Stegmaier, C

AU - Park, J Y

AU - Sellers, T

AU - Lim, H Y

AU - Slavov, C

AU - Kaneva, R

AU - Mitev, V

AU - Batra, J

AU - Clements, J A

AU - Spurdle, A

AU - Teixeira, M R

AU - Paulo, P

AU - Maia, S

AU - Pandha, H

AU - Michael, A

AU - Kierzek, A

AU - Gronberg, H

AU - Wiklund, F

N1 - Szulkin, Robert Whitington, Thomas Eklund, Martin Aly, Markus Eeles, Rosalind A Easton, Douglas Kote-Jarai, Z Sofia Amin Al Olama, Ali Benlloch, Sara Muir, Kenneth Giles, Graham G Southey, Melissa C Fitzgerald, Liesel M Henderson, Brian E Schumacher, Fredrick Haiman, Christopher A Schleutker, Johanna Wahlfors, Tiina Tammela, Teuvo L J Nordestgaard, Borge G Key, Tim J Travis, Ruth C Neal, David E Donovan, Jenny L Hamdy, Freddie C Pharoah, Paul Pashayan, Nora Khaw, Kay-Tee Stanford, Janet L Thibodeau, Stephen N McDonnell, Shannon K Schaid, Daniel J Maier, Christiane Vogel, Walther Luedeke, Manuel Herkommer, Kathleen Kibel, Adam S Cybulski, Cezary Lubinski, Jan Kluzniak, Wojciech Cannon-Albright, Lisa Brenner, Hermann Butterbach, Katja Stegmaier, Christa Park, Jong Y Sellers, Thomas Lim, Hui-Yi Slavov, Chavdar Kaneva, Radka Mitev, Vanio Batra, Jyotsna Clements, Judith A Australian Prostate Cancer BioResource Spurdle, Amanda Teixeira, Manuel R Paulo, Paula Maia, Sofia Pandha, Hardev Michael, Agnieszka Kierzek, Andrzej Practical Consortium Gronberg, Henrik Wiklund, Fredrik 14136/Cancer Research UK/United Kingdom United States The Prostate Prostate. 2015 Sep;75(13):1467-74. doi: 10.1002/pros.23037. Epub 2015 Jul 14.

PY - 2015

Y1 - 2015

N2 - 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 = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-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.

AB - 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 = 0.0012) and the net reclassification index with 0.21 (P = 8.5E-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.

KW - Genetic Markers

KW - Genetic Predisposition to Disease

KW - Genetic Variation

KW - Humans

KW - Linkage Disequilibrium

KW - Male

KW - Prostatic Neoplasms/ genetics

KW - Risk Factors

UR - https://www.scopus.com/pages/publications/84939154897

U2 - 10.1002/pros.23037

DO - 10.1002/pros.23037

M3 - Article

SN - 0270-4137

VL - 75

SP - 1467

EP - 1474

JO - Prostate

JF - Prostate

IS - 13

ER -

Prediction of individual genetic risk to prostate cancer using a polygenic score

Abstract

Keywords

UN SDGs

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