Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction
Yiangou, Kristia; Mavaddat, Nasim; Dennis, Joe; Zanti, Maria; Wang, Qin; Bolla, Manjeet K; Abubakar, Mustapha; Ahearn, Thomas U; Andrulis, Irene L; Anton-Culver, Hoda; Antonenkova, Natalia N; Arndt, Volker; Aronson, Kristan J; Augustinsson, Annelie; Baten, Adinda; Behrens, Sabine; Bermisheva, Marina; de Gonzalez, Amy Berrington; Białkowska, Katarzyna; Boddicker, Nicholas; Bodelon, Clara; Bogdanova, Natalia V; Bojesen, Stig E; Brantley, Kristen D; Brauch, Hiltrud; Brenner, Hermann; Camp, Nicola J; Canzian, Federico; Castelao, Jose E; Cessna, Melissa H; Chang-Claude, Jenny; Chenevix-Trench, Georgia; Chung, Wendy K; NBCS Collaborators; Colonna, Sarah V; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Daly, Mary B; Devilee, Peter; Dörk, Thilo; Dunning, Alison M; Eccles, Diana M; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Evans, D Gareth; Fasching, Peter A; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gago-Dominguez, Manuela; Gentry-Maharaj, Aleksandra; González-Neira, Anna; Guénel, Pascal; Hahnen, Eric; Haiman, Christopher A; Hamann, Ute; Hartikainen, Jaana M; Ho, Vikki; Hodge, James; Hollestelle, Antoinette; Honisch, Ellen; Hooning, Maartje J; Hoppe, Reiner; Hopper, John L; Howell, Sacha; Howell, Anthony; ABCTB Investigators; kConFab Investigators,; Jakovchevska, Simona; Jakubowska, Anna; Jernström, Helena; Johnson, Nichola; Kaaks, Rudolf; Khusnutdinova, Elza K; Kitahara, Cari M; Koutros, Stella; Kristensen, Vessela N; Lacey, James V; Lambrechts, Diether; Lejbkowicz, Flavio; Lindblom, Annika; Lush, Michael; Mannermaa, Arto; Mavroudis, Dimitrios; Menon, Usha; Murphy, Rachel A; Nevanlinna, Heli; Obi, Nadia; Offit, Kenneth; Park-Simon, Tjoung-Won; Patel, Alpa V; Peng, Cheng; Peterlongo, Paolo; Pita, Guillermo; Plaseska-Karanfilska, Dijana; Pylkäs, Katri; Radice, Paolo; Rashid, Muhammad U; Rennert, Gad; Roberts, Eleanor; Rodriguez, Juan; Romero, Atocha; Rosenberg, Efraim H; Saloustros, Emmanouil; Sandler, Dale P; Sawyer, Elinor J; Schmutzler, Rita K; Scott, Christopher G; Shu, Xiao-Ou; Southey, Melissa C; Stone, Jennifer; Taylor, Jack A; Teras, Lauren R; van de Beek, Irma; Willett, Walter; Winqvist, Robert; Zheng, Wei; Vachon, Celine M; Schmidt, Marjanka K; Hall, Per; MacInnis, Robert J; Milne, Roger L; Pharoah, Paul D P; Simard, Jacques; Antoniou, Antonis C; Easton, Douglas F; Michailidou, Kyriaki (2024-12-29)
Biomed central
29.12.2024
Yiangou, K., Mavaddat, N., Dennis, J. et al. Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction. Breast Cancer Res 26, 189 (2024). https://doi.org/10.1186/s13058-024-01947-x
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© The Author(s) 2024. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
https://creativecommons.org/licenses/by-nc-nd/4.0/
© The Author(s) 2024. This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:oulu-202501101118
https://urn.fi/URN:NBN:fi:oulu-202501101118
Tiivistelmä
Abstract
Background:
The 313-variant polygenic risk score (PRS313) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed.
Methods:
We explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank. The mean PRS was calculated by country in the BCAC dataset and by country of birth in the UK Biobank. We explored different approaches to reduce the observed heterogeneity in the mean PRS across the countries, and investigated the implications of the distribution variability in risk prediction.
Results:
The mean PRS313 differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS313 distribution to define risk categories, leads to overestimation and underestimation of risk in some individuals from these countries. Adjustment for principal components explained most of the observed heterogeneity in the mean PRS. The mean estimates derived when using an empirical Bayes approach were similar to the predicted means after principal component adjustment.
Conclusions:
Our results demonstrate that PRS distribution differs even within European ancestry populations leading to underestimation or overestimation of risk in specific European countries, which could potentially influence clinical management of some individuals if is not appropriately accounted for. Population-specific PRS distributions may be used in breast cancer risk estimation to ensure predicted risks are correctly calibrated across risk categories.
Background:
The 313-variant polygenic risk score (PRS313) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed.
Methods:
We explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer diagnosis, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 223,316 females without breast cancer diagnosis from the UK Biobank. The mean PRS was calculated by country in the BCAC dataset and by country of birth in the UK Biobank. We explored different approaches to reduce the observed heterogeneity in the mean PRS across the countries, and investigated the implications of the distribution variability in risk prediction.
Results:
The mean PRS313 differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS313 distribution to define risk categories, leads to overestimation and underestimation of risk in some individuals from these countries. Adjustment for principal components explained most of the observed heterogeneity in the mean PRS. The mean estimates derived when using an empirical Bayes approach were similar to the predicted means after principal component adjustment.
Conclusions:
Our results demonstrate that PRS distribution differs even within European ancestry populations leading to underestimation or overestimation of risk in specific European countries, which could potentially influence clinical management of some individuals if is not appropriately accounted for. Population-specific PRS distributions may be used in breast cancer risk estimation to ensure predicted risks are correctly calibrated across risk categories.
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