Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Authors:
Dr. Jonine Figueroa, PhD
Dr. Jonine Figueroa, PhD
Usher Institute of Population Health Sciences and Informatics
Chancellor's Fellow
Molecular epidemiology
Edinburgh, Scotland | United Kingdom
Nasim Mavaddat Kyriaki Michailidou Joe Dennis Michael Lush Laura Fachal Andrew Lee Jonathan P Tyrer Ting-Huei Chen Qin Wang Manjeet K Bolla Xin Yang Muriel A Adank Thomas Ahearn Kristiina Aittomäki Jamie Allen Irene L Andrulis Hoda Anton-Culver Natalia N Antonenkova Volker Arndt Kristan J Aronson Paul L Auer Päivi Auvinen Myrto Barrdahl Laura E Beane Freeman Matthias W Beckmann Sabine Behrens Javier Benitez Marina Bermisheva Leslie Bernstein Carl Blomqvist Natalia V Bogdanova Stig E Bojesen Bernardo Bonanni Anne-Lise Børresen-Dale Hiltrud Brauch Michael Bremer Hermann Brenner Adam Brentnall Ian W Brock Angela Brooks-Wilson Sara Y Brucker Thomas Brüning Barbara Burwinkel Daniele Campa Brian D Carter Jose E Castelao Stephen J Chanock Rowan Chlebowski Hans Christiansen Christine L Clarke J Margriet Collée Emilie Cordina-Duverger Sten Cornelissen Fergus J Couch Angela Cox Simon S Cross Kamila Czene Mary B Daly Peter Devilee Thilo Dörk Isabel Dos-Santos-Silva Martine Dumont Lorraine Durcan Miriam Dwek Diana M Eccles Arif B Ekici A Heather Eliassen Carolina Ellberg Christoph Engel Mikael Eriksson D Gareth Evans Peter A Fasching Olivia Fletcher Henrik Flyger Asta Försti Lin Fritschi Marike Gabrielson Manuela Gago-Dominguez Susan M Gapstur José A García-Sáenz Mia M Gaudet Vassilios Georgoulias Graham G Giles Irina R Gilyazova Gord Glendon Mark S Goldberg David E Goldgar Anna González-Neira Grethe I Grenaker Alnæs Mervi Grip Jacek Gronwald Anne Grundy Pascal Guénel Lothar Haeberle Eric Hahnen Christopher A Haiman Niclas Håkansson Ute Hamann Susan E Hankinson Elaine F Harkness Steven N Hart Wei He Alexander Hein Jane Heyworth Peter Hillemanns Antoinette Hollestelle Maartje J Hooning Robert N Hoover John L Hopper Anthony Howell Guanmengqian Huang Keith Humphreys David J Hunter Milena Jakimovska Anna Jakubowska Wolfgang Janni Esther M John Nichola Johnson Michael E Jones Arja Jukkola-Vuorinen Audrey Jung Rudolf Kaaks Katarzyna Kaczmarek Vesa Kataja Renske Keeman Michael J Kerin Elza Khusnutdinova Johanna I Kiiski Julia A Knight Yon-Dschun Ko Veli-Matti Kosma Stella Koutros Vessela N Kristensen Ute Krüger Tabea Kühl Diether Lambrechts Loic Le Marchand Eunjung Lee Flavio Lejbkowicz Jenna Lilyquist Annika Lindblom Sara Lindström Jolanta Lissowska Wing-Yee Lo Sibylle Loibl Jirong Long Jan Lubiński Michael P Lux Robert J MacInnis Tom Maishman Enes Makalic Ivana Maleva Kostovska Arto Mannermaa Siranoush Manoukian Sara Margolin John W M Martens Maria Elena Martinez Dimitrios Mavroudis Catriona McLean Alfons Meindl Usha Menon Pooja Middha Nicola Miller Fernando Moreno Anna Marie Mulligan Claire Mulot Victor M Muñoz-Garzon Susan L Neuhausen Heli Nevanlinna Patrick Neven William G Newman Sune F Nielsen Børge G Nordestgaard Aaron Norman Kenneth Offit Janet E Olson Håkan Olsson Nick Orr V Shane Pankratz Tjoung-Won Park-Simon Jose I A Perez Clara Pérez-Barrios Paolo Peterlongo Julian Peto Mila Pinchev Dijana Plaseska-Karanfilska Eric C Polley Ross Prentice Nadege Presneau Darya Prokofyeva Kristen Purrington Katri Pylkäs Brigitte Rack Paolo Radice Rohini Rau-Murthy Gad Rennert Hedy S Rennert Valerie Rhenius Mark Robson Atocha Romero Kathryn J Ruddy Matthias Ruebner Emmanouil Saloustros Dale P Sandler Elinor J Sawyer Daniel F Schmidt Rita K Schmutzler Andreas Schneeweiss Minouk J Schoemaker Fredrick Schumacher Peter Schürmann Lukas Schwentner Christopher Scott Rodney J Scott Caroline Seynaeve Mitul Shah Mark E Sherman Martha J Shrubsole Xiao-Ou Shu Susan Slager Ann Smeets Christof Sohn Penny Soucy Melissa C Southey John J Spinelli Christa Stegmaier Jennifer Stone Anthony J Swerdlow Rulla M Tamimi William J Tapper Jack A Taylor Mary Beth Terry Kathrin Thöne Rob A E M Tollenaar Ian Tomlinson Thérèse Truong Maria Tzardi Hans-Ulrich Ulmer Michael Untch Celine M Vachon Elke M van Veen Joseph Vijai Clarice R Weinberg Camilla Wendt Alice S Whittemore Hans Wildiers Walter Willett Robert Winqvist Alicja Wolk Xiaohong R Yang Drakoulis Yannoukakos Yan Zhang Wei Zheng Argyrios Ziogas Alison M Dunning Deborah J Thompson Georgia Chenevix-Trench Jenny Chang-Claude Marjanka K Schmidt Per Hall Roger L Milne Paul D P Pharoah Antonis C Antoniou Nilanjan Chatterjee Peter Kraft Montserrat García-Closas Jacques Simard Douglas F Easton

Am J Hum Genet 2019 Jan 13;104(1):21-34. Epub 2018 Dec 13.

Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

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Source
https://linkinghub.elsevier.com/retrieve/pii/S00029297183040
Publisher Site
http://dx.doi.org/10.1016/j.ajhg.2018.11.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323553PMC
January 2019
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