Kristia Yiangou, Nasim Mavaddat, Joe Dennis, Maria Zanti, Qin Wang, Manjeet K Bolla, Mustapha Abubakar, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Natalia N Antonenkova, Volker Arndt, Kristan J Aronson, Annelie Augustinsson, Adinda Baten, Sabine Behrens, Marina Bermisheva, Amy Berrington de Gonzalez, Katarzyna Białkowska, Nicholas Boddicker, Clara Bodelon, Natalia V Bogdanova, Stig E Bojesen, Kristen D Brantley, Hiltrud Brauch, Hermann Brenner, Nicola J Camp, Federico Canzian, Jose E Castelao, Melissa H Cessna, Jenny Chang-Claude, Georgia Chenevix-Trench, Wendy K Chung, Sarah V Colonna, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Mary B Daly, Peter Devilee, Thilo Dörk, Alison M Dunning, Diana M Eccles, A Heather Eliassen, Christoph Engel, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Manuela Gago-Dominguez, Aleksandra Gentry-Maharaj, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A Haiman, Ute Hamann, Jaana M Hartikainen, Vikki Ho, James Hodge, Antoinette Hollestelle, Ellen Honisch, Maartje J Hooning, Reiner Hoppe, John L Hopper, Sacha Howell, Anthony Howell, Simona Jakovchevska, Anna Jakubowska, Helena Jernström, Nichola Johnson, Rudolf Kaaks, Elza K Khusnutdinova, Cari M Kitahara, Stella Koutros, Vessela N Kristensen, James V Lacey, Diether Lambrechts, Flavio Lejbkowicz, Annika Lindblom, Michael Lush, Arto Mannermaa, Dimitrios Mavroudis, Usha Menon, Rachel A Murphy, Heli Nevanlinna, Nadia Obi, Kenneth Offit, Tjoung-Won Park-Simon, Alpa V Patel, Cheng Peng, Paolo Peterlongo, Guillermo Pita, Dijana Plaseska-Karanfilska, Katri Pylkäs, Paolo Radice, Muhammad U Rashid, Gad Rennert, Eleanor Roberts, Juan Rodriguez, Atocha Romero, Efraim H Rosenberg, Emmanouil Saloustros, Dale P Sandler, Elinor J Sawyer, Rita K Schmutzler, Christopher G Scott, Xiao-Ou Shu, Melissa C Southey, Jennifer Stone, Jack A Taylor, Lauren R Teras, Irma van de Beek, Walter Willett, Robert Winqvist, Wei Zheng, Celine M Vachon, Marjanka K Schmidt, Per Hall, Robert J MacInnis, Roger L Milne, Paul D P Pharoah, Jacques Simard, Antonis C Antoniou, Douglas F Easton, Kyriaki Michailidou
{"title":"欧洲血统人群的多基因评分分布差异：对乳腺癌风险预测的影响。","authors":"Kristia Yiangou, Nasim Mavaddat, Joe Dennis, Maria Zanti, Qin Wang, Manjeet K Bolla, Mustapha Abubakar, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Natalia N Antonenkova, Volker Arndt, Kristan J Aronson, Annelie Augustinsson, Adinda Baten, Sabine Behrens, Marina Bermisheva, Amy Berrington de Gonzalez, Katarzyna Białkowska, Nicholas Boddicker, Clara Bodelon, Natalia V Bogdanova, Stig E Bojesen, Kristen D Brantley, Hiltrud Brauch, Hermann Brenner, Nicola J Camp, Federico Canzian, Jose E Castelao, Melissa H Cessna, Jenny Chang-Claude, Georgia Chenevix-Trench, Wendy K Chung, Sarah V Colonna, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Mary B Daly, Peter Devilee, Thilo Dörk, Alison M Dunning, Diana M Eccles, A Heather Eliassen, Christoph Engel, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Manuela Gago-Dominguez, Aleksandra Gentry-Maharaj, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A Haiman, Ute Hamann, Jaana M Hartikainen, Vikki Ho, James Hodge, Antoinette Hollestelle, Ellen Honisch, Maartje J Hooning, Reiner Hoppe, John L Hopper, Sacha Howell, Anthony Howell, Simona Jakovchevska, Anna Jakubowska, Helena Jernström, Nichola Johnson, Rudolf Kaaks, Elza K Khusnutdinova, Cari M Kitahara, Stella Koutros, Vessela N Kristensen, James V Lacey, Diether Lambrechts, Flavio Lejbkowicz, Annika Lindblom, Michael Lush, Arto Mannermaa, Dimitrios Mavroudis, Usha Menon, Rachel A Murphy, Heli Nevanlinna, Nadia Obi, Kenneth Offit, Tjoung-Won Park-Simon, Alpa V Patel, Cheng Peng, Paolo Peterlongo, Guillermo Pita, Dijana Plaseska-Karanfilska, Katri Pylkäs, Paolo Radice, Muhammad U Rashid, Gad Rennert, Eleanor Roberts, Juan Rodriguez, Atocha Romero, Efraim H Rosenberg, Emmanouil Saloustros, Dale P Sandler, Elinor J Sawyer, Rita K Schmutzler, Christopher G Scott, Xiao-Ou Shu, Melissa C Southey, Jennifer Stone, Jack A Taylor, Lauren R Teras, Irma van de Beek, Walter Willett, Robert Winqvist, Wei Zheng, Celine M Vachon, Marjanka K Schmidt, Per Hall, Robert J MacInnis, Roger L Milne, Paul D P Pharoah, Jacques Simard, Antonis C Antoniou, Douglas F Easton, Kyriaki Michailidou","doi":"10.1186/s13058-024-01947-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The 313-variant polygenic risk score (PRS<sub>313</sub>) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS<sub>313</sub> across different European populations which could influence risk estimation has not been performed.</p><p><strong>Methods: </strong>We explored the distribution of PRS<sub>313</sub> 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.</p><p><strong>Results: </strong>The mean PRS<sub>313</sub> differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS<sub>313</sub> 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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":49227,"journal":{"name":"Breast Cancer Research","volume":"26 1","pages":"189"},"PeriodicalIF":7.4000,"publicationDate":"2024-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11682615/pdf/","citationCount":"0","resultStr":"{\"title\":\"Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.\",\"authors\":\"Kristia Yiangou, Nasim Mavaddat, Joe Dennis, Maria Zanti, Qin Wang, Manjeet K Bolla, Mustapha Abubakar, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Natalia N Antonenkova, Volker Arndt, Kristan J Aronson, Annelie Augustinsson, Adinda Baten, Sabine Behrens, Marina Bermisheva, Amy Berrington de Gonzalez, Katarzyna Białkowska, Nicholas Boddicker, Clara Bodelon, Natalia V Bogdanova, Stig E Bojesen, Kristen D Brantley, Hiltrud Brauch, Hermann Brenner, Nicola J Camp, Federico Canzian, Jose E Castelao, Melissa H Cessna, Jenny Chang-Claude, Georgia Chenevix-Trench, Wendy K Chung, Sarah V Colonna, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Mary B Daly, Peter Devilee, Thilo Dörk, Alison M Dunning, Diana M Eccles, A Heather Eliassen, Christoph Engel, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Manuela Gago-Dominguez, Aleksandra Gentry-Maharaj, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A Haiman, Ute Hamann, Jaana M Hartikainen, Vikki Ho, James Hodge, Antoinette Hollestelle, Ellen Honisch, Maartje J Hooning, Reiner Hoppe, John L Hopper, Sacha Howell, Anthony Howell, Simona Jakovchevska, Anna Jakubowska, Helena Jernström, Nichola Johnson, Rudolf Kaaks, Elza K Khusnutdinova, Cari M Kitahara, Stella Koutros, Vessela N Kristensen, James V Lacey, Diether Lambrechts, Flavio Lejbkowicz, Annika Lindblom, Michael Lush, Arto Mannermaa, Dimitrios Mavroudis, Usha Menon, Rachel A Murphy, Heli Nevanlinna, Nadia Obi, Kenneth Offit, Tjoung-Won Park-Simon, Alpa V Patel, Cheng Peng, Paolo Peterlongo, Guillermo Pita, Dijana Plaseska-Karanfilska, Katri Pylkäs, Paolo Radice, Muhammad U Rashid, Gad Rennert, Eleanor Roberts, Juan Rodriguez, Atocha Romero, Efraim H Rosenberg, Emmanouil Saloustros, Dale P Sandler, Elinor J Sawyer, Rita K Schmutzler, Christopher G Scott, Xiao-Ou Shu, Melissa C Southey, Jennifer Stone, Jack A Taylor, Lauren R Teras, Irma van de Beek, Walter Willett, Robert Winqvist, Wei Zheng, Celine M Vachon, Marjanka K Schmidt, Per Hall, Robert J MacInnis, Roger L Milne, Paul D P Pharoah, Jacques Simard, Antonis C Antoniou, Douglas F Easton, Kyriaki Michailidou\",\"doi\":\"10.1186/s13058-024-01947-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The 313-variant polygenic risk score (PRS<sub>313</sub>) provides a promising tool for clinical breast cancer risk prediction. However, evaluation of the PRS<sub>313</sub> across different European populations which could influence risk estimation has not been performed.</p><p><strong>Methods: </strong>We explored the distribution of PRS<sub>313</sub> 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.</p><p><strong>Results: </strong>The mean PRS<sub>313</sub> differed markedly across European countries, being highest in individuals from Greece and Italy and lowest in individuals from Ireland. Using the overall European PRS<sub>313</sub> 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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":49227,\"journal\":{\"name\":\"Breast Cancer Research\",\"volume\":\"26 1\",\"pages\":\"189\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-12-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11682615/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Breast Cancer Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s13058-024-01947-x\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Breast Cancer Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s13058-024-01947-x","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Polygenic score distribution differences across European ancestry populations: implications for breast cancer risk prediction.
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.
期刊介绍：
Breast Cancer Research, an international, peer-reviewed online journal, publishes original research, reviews, editorials, and reports. It features open-access research articles of exceptional interest across all areas of biology and medicine relevant to breast cancer. This includes normal mammary gland biology, with a special emphasis on the genetic, biochemical, and cellular basis of breast cancer. In addition to basic research, the journal covers preclinical, translational, and clinical studies with a biological basis, including Phase I and Phase II trials.
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