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

Journal article


Publication Details

Author(s): Mavaddat N, Michailidou K, Dennis J, Lush M, Fachal L, Lee A, Tyrer JP, Chen TH, Wang Q, Bolla MK, Yang X, Adank MA, Ahearn T, Aittomaki K, Allen J, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Auer PL, Auvinen P, Barrdahl M, Freeman LEB, Beckmann M, Behrens S, Benitez J, Bermisheva M, Bernstein L, Blomqvist C, Bogdanova N, Bojesen SE, Bonanni B, Borresen-Dale AL, Brauch H, Bremer M, Brenner H, Brentnall A, Brock IW, Brooks-Wilson A, Brucker SY, Bruening T, Burwinkel B, Campa D, Carter BD, Castelao JE, Chanock SJ, Chlebowski R, Christiansen H, Clarke CL, Collee JM, Cordina-Duverger E, Cornelissen S, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Doerk T, Dos-Santos-Silva I, Dumont M, Durcan L, Dwek M, Eccles DM, Ekici AB, Eliassen AH, Ellberg C, Engel C, Eriksson M, Evans DG, Fasching P, Figueroa J, Fletcher O, Flyger H, Foersti A, Fritschi L, Gabrielson M, Gago-Dominguez M, Gapstur SM, Garcia-Saenz JA, Gaudet MM, Georgoulias V, Giles GG, Gilyazova IR, Glendon G, Goldberg MS, Goldgar DE, Gonzalez-Neira A, Alnaes GIG, Grip M, Gronwald J, Grundy A, Guenel P, Häberle L, Hahnen E, Haiman CA, Hakansson N, Hamann U, Hankinson SE, Harkness EF, Hart SN, He W, Hein A, Heyworth J, Hillemanns P, Hollestelle A, Hooning MJ, Hoover RN, Hopper JL, Howell A, Huang G, Humphreys K, Hunter DJ, Jakimovska M, Jakubowska A, Janni W, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kaczmarek K, Kataja V, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski J, Knight JA, Ko YD, Kosma VM, Koutros S, Kristensen VN, Kruger U, Kuehl T, Lambrechts D, Le Marchand L, Lee E, Lejbkowicz F, Lilyquist J, Lindblom A, Lindstrom S, Lissowska J, Lo WY, Loibl S, Long J, Lubinski J, Lux MP, Macinnis RJ, Maishman T, Makalic E, Kostovska IM, Mannermaa A, Manoukian S, Margolin S, Martens JWM, Martinez ME, Mavroudis D, Mclean C, Meindl A, Menon U, Middha P, Miller N, Moreno F, Mulligan AM, Mulot C, Munoz-Garzon VM, Neuhausen SL, Nevanlinna H, Neven P, Newman WG, Nielsen SF, Nordestgaard BG, Norman A, Offit K, Olson JE, Olsson H, Orr N, Pankratz VS, Park-Simon TW, Perez JIA, Perez-Barrios C, Peterlongo P, Peto J, Pinchev M, Plaseska-Karanfilska D, Polley EC, Prentice R, Presneau N, Prokofyeva D, Purrington K, Pylkas K, Rack B, Radice P, Rau-Murthy R, Rennert G, Rennert HS, Rhenius V, Robson M, Romero A, Ruddy KJ, Rübner M, Saloustros E, Sandler DP, Sawyer EJ, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schumacher F, Schuermann P, Schwentner L, Scott C, Scott RJ, Seynaeve C, Shah M, Sherman ME, Shrubsole MJ, Shu XO, Slager S, Smeets A, Sohn C, Soucy P, Southey MC, Spinelli JJ, Stegmaier C, Stone J, Swerdlow AJ, Tamimi RM, Tapper WJ, Taylor JA, Terry MB, Thoene K, Tollenaar RAEM, Tomlinson I, Truong T, Tzardi M, Ulmer HU, Untch M, Vachon CM, Van Veen EM, Vijai J, Weinberg CR, Wendt C, Whittemore AS, Wildiers H, Willett W, Winqvist R, Wolk A, Yang XR, Yannoukakos D, Zhang Y, Zheng W, Ziogas A, Clarke C, Balleine R, Baxter R, Braye S, Carpenter J, Dahlstrom J, Forbes J, Lee CS, Marsh D, Morey A, Pathmanathan N, Scott R, Simpson P, Spigelman A, Wilcken N, Yip D, Zeps N, Sexton A, Dobrovic A, Christian A, Trainer A, Fellows A, Shelling A, De Fazio A, Blackburn A, Crook A, Meiser B, Patterson B, Clarke C, Saunders C, Hunt C, Scott C, Amor D, Ortega DG, Marsh D, Edkins E, Salisbury E, Haan E, Macrea F, Farshid G, Lindeman G, Trench G, Mann G, Giles G, Gill G, Thorne H, Campbell I, Hickie I, Caldon L, Winship I, Cui J, Flanagan J, Kollias J, Visvader J, Taylor J, Burke J, Saunus J, Forbs J, Hopper J, Beesley J, Kirk J, French J, Tucker K, Wu K, Phillips K, Forrest L, Lipton L, Andrews L, Lobb L, Walker L, Kentwell M, Spurdle M, Cummings M, Gleeson M, Harris M, Jenkins M, Young MA, Delatycki M, Wallis M, Burgess M, Brown M, Southey M, Bogwitz M, Field M, Friedlander M, Gattas M, Saleh M, Aghmesheh M, Hayward N, Pachter N, Cohen P, Duijf P, James P, Simpson P, Fong P, Butow P, Williams R, Kefford R, Simard J, Balleine RM, Dawson SJ, Lok S, O'Connell S, Greening S, Nightingale S, Edwards S, Fox S, Mclachlan SA, Lakhani S, Dudding T, Antill Y, Sahlberg KK, Ottestad L, Karesen R, Schlichting E, Holmen MM, Sauer T, Haakensen V, Engebraten O, Naume B, Fossa A, Kiserud CE, Reinertsen K, Helland A, Riis M, Geisler J, Dunning AM, Thompson DJ, Chenevix-Trench G, Chang-Claude J, Schmidt MK, Hall P, Milne RL, Pharoah PDP, Antoniou AC, Chatterjee N, Kraft P, Garcia-Closas M, Easton DF
Journal: American Journal of Human Genetics
Publication year: 2019
Volume: 104
Journal issue: 1
Pages range: 21-34
ISSN: 0002-9297


Abstract

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.


FAU Authors / FAU Editors

Beckmann, Matthias Prof. Dr.
Lehrstuhl für Geburtshilfe und Frauenheilkunde
Ekici, Arif Bülent Dr. rer. nat.
Humangenetisches Institut
Fasching, Peter PD Dr.
Professur für Translationale Frauenheilkunde und Geburtshilfe
Hein, Alexander PD Dr.
Frauenklinik
Rübner, Matthias PD Dr.
Frauenklinik


How to cite

APA:
Mavaddat, N., Michailidou, K., Dennis, J., Lush, M., Fachal, L., Lee, A.,... Easton, D.F. (2019). Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes. American Journal of Human Genetics, 104(1), 21-34. https://dx.doi.org/10.1016/j.ajhg.2018.11.002

MLA:
Mavaddat, Nasim, et al. "Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes." American Journal of Human Genetics 104.1 (2019): 21-34.

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Last updated on 2019-18-07 at 07:32