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

Robert Szulkin; Thomas Whitington; Martin Eklund; Markus Aly; Rosalind A Eeles; Douglas Easton; Z Sofia Kote-Jarai; Ali Amin Al Olama; Sara Benlloch; Kenneth Muir; Graham G Giles; Melissa C Southey; Liesel M Fitzgerald; Brian E Henderson; Fredrick Schumacher; Christopher A Haiman; Johanna Schleutker; Tiina Wahlfors; Teuvo L J Tammela; Børge G Nordestgaard; Tim J Key; Ruth C Travis; David E Neal; Jenny L Donovan; Freddie C Hamdy; Paul Pharoah; Nora Pashayan; Kay-Tee Khaw; Janet L Stanford; Stephen N Thibodeau; Shannon K McDonnell; Daniel J Schaid; Christiane Maier; Walther Vogel; Manuel Luedeke; Kathleen Herkommer; Adam S Kibel; Cezary Cybulski; Jan Lubiński; Wojciech Kluźniak; Lisa Cannon-Albright; Hermann Brenner; Katja Butterbach; Christa Stegmaier; Jong Y Park; Thomas Sellers; Hui-Yi Lin; Hui-Yi Lim; Chavdar Slavov; Radka Kaneva; Australian Prostate Cancer BioResource

doi:10.1002/pros.23037

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

Robert Szulkin, Thomas Whitington, Martin Eklund, Markus Aly, Rosalind A Eeles, Douglas Easton, Z Sofia Kote-Jarai, Ali Amin Al Olama, Sara Benlloch, Kenneth Muir, Graham G Giles, Melissa C Southey, Liesel M Fitzgerald, Brian E Henderson, Fredrick Schumacher, Christopher A Haiman, Johanna Schleutker, Tiina Wahlfors, Teuvo L J Tammela, Børge G NordestgaardTim J Key, Ruth C Travis, David E Neal, Jenny L Donovan, Freddie C Hamdy, Paul Pharoah, Nora Pashayan, Kay-Tee Khaw, Janet L Stanford, Stephen N Thibodeau, Shannon K McDonnell, Daniel J Schaid, Christiane Maier, Walther Vogel, Manuel Luedeke, Kathleen Herkommer, Adam S Kibel, Cezary Cybulski, Jan Lubiński, Wojciech Kluźniak, Lisa Cannon-Albright, Hermann Brenner, Katja Butterbach, Christa Stegmaier, Jong Y Park, Thomas Sellers, Hui-Yi Lin, Hui-Yi Lim, Chavdar Slavov, Radka Kaneva, Australian Prostate Cancer BioResource

Department of Clinical Medicine

42 Citations (Scopus)

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
Journal	The Prostate
Volume	75
Issue number	13
Pages (from-to)	1467-74
Number of pages	8
ISSN	0270-4137
DOIs	https://doi.org/10.1002/pros.23037
Publication status	Published - 1 Sept 2015

Keywords

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

UN SDGs

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

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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. J., ... Australian Prostate Cancer BioResource (2015). Prediction of individual genetic risk to prostate cancer using a polygenic score. The Prostate, 75(13), 1467-74. https://doi.org/10.1002/pros.23037

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, TLJ, Nordestgaard, BG, Key, TJ, Travis, RC, Neal, DE, Donovan, JL, Hamdy, FC, Pharoah, P, Pashayan, N, Khaw, K-T, Stanford, JL, Thibodeau, SN, McDonnell, SK, Schaid, DJ, Maier, C, Vogel, W, Luedeke, M, Herkommer, K, Kibel, AS, Cybulski, C, Lubiński, J, Kluźniak, W, Cannon-Albright, L, Brenner, H, Butterbach, K, Stegmaier, C, Park, JY, Sellers, T, Lin, H-Y, Lim, H-Y, Slavov, C, Kaneva, R & Australian Prostate Cancer BioResource 2015, 'Prediction of individual genetic risk to prostate cancer using a polygenic score', The Prostate, vol. 75, no. 13, pp. 1467-74. https://doi.org/10.1002/pros.23037

@article{4c0546fab4934d1c8047cab2285bcf2d,

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, Risk Factors",

author = "Robert Szulkin and Thomas Whitington and Martin Eklund and Markus Aly and Eeles, {Rosalind A} and Douglas Easton and Kote-Jarai, {Z Sofia} and {Amin Al Olama}, Ali and Sara Benlloch and Kenneth Muir and Giles, {Graham G} and Southey, {Melissa C} and Fitzgerald, {Liesel M} and Henderson, {Brian E} and Fredrick Schumacher and Haiman, {Christopher A} and Johanna Schleutker and Tiina Wahlfors and Tammela, {Teuvo L J} and Nordestgaard, {B{\o}rge G} and Key, {Tim J} and Travis, {Ruth C} and Neal, {David E} and Donovan, {Jenny L} and Hamdy, {Freddie C} and Paul Pharoah and Nora Pashayan and Kay-Tee Khaw and Stanford, {Janet L} and Thibodeau, {Stephen N} and McDonnell, {Shannon K} and Schaid, {Daniel J} and Christiane Maier and Walther Vogel and Manuel Luedeke and Kathleen Herkommer and Kibel, {Adam S} and Cezary Cybulski and Jan Lubi{\'n}ski and Wojciech Klu{\'z}niak and Lisa Cannon-Albright and Hermann Brenner and Katja Butterbach and Christa Stegmaier and Park, {Jong Y} and Thomas Sellers and Hui-Yi Lin and Hui-Yi Lim and Chavdar Slavov and Radka Kaneva and {Australian Prostate Cancer BioResource}",

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

AU - Szulkin, Robert

AU - Whitington, Thomas

AU - Eklund, Martin

AU - Aly, Markus

AU - Eeles, Rosalind A

AU - Easton, Douglas

AU - Kote-Jarai, Z Sofia

AU - Amin Al Olama, Ali

AU - Benlloch, Sara

AU - Muir, Kenneth

AU - Giles, Graham G

AU - Southey, Melissa C

AU - Fitzgerald, Liesel M

AU - Henderson, Brian E

AU - Schumacher, Fredrick

AU - Haiman, Christopher A

AU - Schleutker, Johanna

AU - Wahlfors, Tiina

AU - Tammela, Teuvo L J

AU - Nordestgaard, Børge G

AU - Key, Tim J

AU - Travis, Ruth C

AU - Neal, David E

AU - Donovan, Jenny L

AU - Hamdy, Freddie C

AU - Pharoah, Paul

AU - Pashayan, Nora

AU - Khaw, Kay-Tee

AU - Stanford, Janet L

AU - Thibodeau, Stephen N

AU - McDonnell, Shannon K

AU - Schaid, Daniel J

AU - Maier, Christiane

AU - Vogel, Walther

AU - Luedeke, Manuel

AU - Herkommer, Kathleen

AU - Kibel, Adam S

AU - Cybulski, Cezary

AU - Lubiński, Jan

AU - Kluźniak, Wojciech

AU - Cannon-Albright, Lisa

AU - Brenner, Hermann

AU - Butterbach, Katja

AU - Stegmaier, Christa

AU - Park, Jong Y

AU - Sellers, Thomas

AU - Lin, Hui-Yi

AU - Lim, Hui-Yi

AU - Slavov, Chavdar

AU - Kaneva, Radka

AU - Australian Prostate Cancer BioResource

PY - 2015/9/1

Y1 - 2015/9/1

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

KW - Risk Factors

U2 - 10.1002/pros.23037

DO - 10.1002/pros.23037

M3 - Journal article

C2 - 26177737

SN - 0270-4137

VL - 75

SP - 1467

EP - 1474

JO - The Prostate. Supplement

JF - The Prostate. Supplement

IS - 13

ER -

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

Abstract

Keywords

UN SDGs

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