Abstract
| Original language | English |
|---|---|
| Pages (from-to) | 21-34 |
| Number of pages | 14 |
| Journal | Hum. Mol. Genet. |
| Volume | 104 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2019 |
Keywords
- breast
- cancer
- epidemiology
- genetic
- polygenic
- prediction
- risk
- score
- screening
- stratification
- adult
- aged
- area under the curve
- Article
- biobank
- breast cancer
- breast cancer molecular subtype
- cancer incidence
- cancer prevention
- cancer risk
- controlled study
- estrogen receptor negative breast cancer
- estrogen receptor positive breast cancer
- European
- female
- genome-wide association study
- genotype
- human
- major clinical study
- middle aged
- Polygenic Risk Score
- priority journal
- prospective study
- receiver operating characteristic
- scoring system
- single nucleotide polymorphism
- United Kingdom
- validation study
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Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes : American Journal of Human Genetics. / Mavaddat, N.; Michailidou, K.; Dennis, J. et al.
In: Hum. Mol. Genet., Vol. 104, No. 1, 2019, p. 21-34.Research output: Contribution to journal › Article › peer-review
}
TY - JOUR
T1 - Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes
T2 - American Journal of Human Genetics
AU - Mavaddat, N.
AU - Michailidou, K.
AU - Dennis, J.
AU - Lush, M.
AU - Fachal, L.
AU - Lee, A.
AU - Tyrer, J.P.
AU - Chen, T.-H.
AU - Wang, Q.
AU - Bolla, M.K.
AU - Yang, X.
AU - Adank, M.A.
AU - Ahearn, T.
AU - Aittomäki, K.
AU - Allen, J.
AU - Andrulis, I.L.
AU - Anton-Culver, H.
AU - Antonenkova, N.N.
AU - Arndt, V.
AU - Aronson, K.J.
AU - Auer, P.L.
AU - Auvinen, P.
AU - Barrdahl, M.
AU - Beane Freeman, L.E.
AU - Beckmann, M.W.
AU - Behrens, S.
AU - Benitez, J.
AU - Bermisheva, M.
AU - Bernstein, L.
AU - Blomqvist, C.
AU - Bogdanova, N.V.
AU - Bojesen, S.E.
AU - Bonanni, B.
AU - Børresen-Dale, A.-L.
AU - Brauch, H.
AU - Bremer, M.
AU - Brenner, H.
AU - Brentnall, A.
AU - Brock, I.W.
AU - Brooks-Wilson, A.
AU - Brucker, S.Y.
AU - Brüning, T.
AU - Burwinkel, B.
AU - Campa, D.
AU - Carter, B.D.
AU - Castelao, J.E.
AU - Chanock, S.J.
AU - Chlebowski, R.
AU - Christiansen, H.
AU - Clarke, C.L.
AU - Collée, J.M.
AU - Cordina-Duverger, E.
AU - Cornelissen, S.
AU - Couch, F.J.
AU - Cox, A.
AU - Cross, S.S.
AU - Czene, K.
AU - Daly, M.B.
AU - Devilee, P.
AU - Dörk, T.
AU - dos-Santos-Silva, I.
AU - Dumont, M.
AU - Durcan, L.
AU - Dwek, M.
AU - Eccles, D.M.
AU - Ekici, A.B.
AU - Eliassen, A.H.
AU - Ellberg, C.
AU - Engel, C.
AU - Eriksson, M.
AU - Evans, D.G.
AU - Fasching, P.A.
AU - Figueroa, J.
AU - Fletcher, O.
AU - Flyger, H.
AU - Försti, A.
AU - Fritschi, L.
AU - Gabrielson, M.
AU - Gago-Dominguez, M.
AU - Gapstur, S.M.
AU - García-Sáenz, J.A.
AU - Gaudet, M.M.
AU - Georgoulias, V.
AU - Giles, G.G.
AU - Gilyazova, I.R.
AU - Glendon, G.
AU - Goldberg, M.S.
AU - Goldgar, D.E.
AU - González-Neira, A.
AU - Grenaker Alnæs, G.I.
AU - Grip, M.
AU - Gronwald, J.
AU - Grundy, A.
AU - Guénel, P.
AU - Haeberle, L.
AU - Hahnen, E.
AU - Haiman, C.A.
AU - Håkansson, N.
AU - Hamann, U.
AU - Hankinson, S.E.
AU - Harkness, E.F.
AU - Hart, S.N.
AU - He, W.
AU - Hein, A.
AU - Heyworth, J.
AU - Hillemanns, P.
AU - Hollestelle, A.
AU - Hooning, M.J.
AU - Hoover, R.N.
AU - Hopper, J.L.
AU - Howell, A.
AU - Huang, G.
AU - Humphreys, K.
AU - Hunter, D.J.
AU - Jakimovska, M.
AU - Jakubowska, A.
AU - Janni, W.
AU - John, E.M.
AU - Johnson, N.
AU - Jones, M.E.
AU - Jukkola-Vuorinen, A.
AU - Jung, A.
AU - Kaaks, R.
AU - Kaczmarek, K.
AU - Kataja, V.
AU - Keeman, R.
AU - Kerin, M.J.
AU - Khusnutdinova, E.
AU - Kiiski, J.I.
AU - Knight, J.A.
AU - Ko, Y.-D.
AU - Kosma, V.-M.
AU - Koutros, S.
AU - Kristensen, V.N.
AU - Krüger, U.
AU - Kühl, T.
AU - Lambrechts, D.
AU - Le Marchand, L.
AU - Lee, E.
AU - Lejbkowicz, F.
AU - Lilyquist, J.
AU - Lindblom, A.
AU - Lindström, S.
AU - Lissowska, J.
AU - Lo, W.-Y.
AU - Loibl, S.
AU - Long, J.
AU - Lubiński, J.
AU - Lux, M.P.
AU - MacInnis, R.J.
AU - Maishman, T.
AU - Makalic, E.
AU - Maleva Kostovska, I.
AU - Mannermaa, A.
AU - Manoukian, S.
AU - Margolin, S.
AU - Martens, J.W.M.
AU - Martinez, M.E.
AU - Mavroudis, D.
AU - McLean, C.
AU - Meindl, A.
AU - Menon, U.
AU - Middha, P.
AU - Miller, N.
AU - Moreno, F.
AU - Mulligan, A.M.
AU - Mulot, C.
AU - Muñoz-Garzon, V.M.
AU - Neuhausen, S.L.
AU - Nevanlinna, H.
AU - Neven, P.
AU - Newman, W.G.
AU - Nielsen, S.F.
AU - Nordestgaard, B.G.
AU - Norman, A.
AU - Offit, K.
AU - Olson, J.E.
AU - Olsson, H.
AU - Orr, N.
AU - Pankratz, V.S.
AU - Park-Simon, T.-W.
AU - Perez, J.I.A.
AU - Pérez-Barrios, C.
AU - Peterlongo, P.
AU - Peto, J.
AU - Pinchev, M.
AU - Plaseska-Karanfilska, D.
AU - Polley, E.C.
AU - Prentice, R.
AU - Presneau, N.
AU - Prokofyeva, D.
AU - Purrington, K.
AU - Pylkäs, K.
AU - Rack, B.
AU - Radice, P.
AU - Rau-Murthy, R.
AU - Rennert, G.
AU - Rennert, H.S.
AU - Rhenius, V.
AU - Robson, M.
AU - Romero, A.
AU - Ruddy, K.J.
AU - Ruebner, M.
AU - Saloustros, E.
AU - Sandler, D.P.
AU - Sawyer, E.J.
AU - Schmidt, D.F.
AU - Schmutzler, R.K.
AU - Schneeweiss, A.
AU - Schoemaker, M.J.
AU - Schumacher, F.
AU - Schürmann, P.
AU - Schwentner, L.
AU - Scott, C.
AU - Scott, R.J.
AU - Seynaeve, C.
AU - Shah, M.
AU - Sherman, M.E.
AU - Shrubsole, M.J.
AU - Shu, X.-O.
AU - Slager, S.
AU - Smeets, A.
AU - Sohn, C.
AU - Soucy, P.
AU - Southey, M.C.
AU - Spinelli, J.J.
AU - Stegmaier, C.
AU - Stone, J.
AU - Swerdlow, A.J.
AU - Tamimi, R.M.
AU - Tapper, W.J.
AU - Taylor, J.A.
AU - Terry, M.B.
AU - Thöne, K.
AU - Tollenaar, R.A.E.M.
AU - Tomlinson, I.
AU - Truong, T.
AU - Tzardi, M.
AU - Ulmer, H.-U.
AU - Untch, M.
AU - Vachon, C.M.
AU - van Veen, E.M.
AU - Vijai, J.
AU - Weinberg, C.R.
AU - Wendt, C.
AU - Whittemore, A.S.
AU - Wildiers, H.
AU - Willett, W.
AU - Winqvist, R.
AU - Wolk, A.
AU - Yang, X.R.
AU - Yannoukakos, D.
AU - Zhang, Y.
AU - Zheng, W.
AU - Ziogas, A.
AU - Dunning, A.M.
AU - Thompson, D.J.
AU - Chenevix-Trench, G.
AU - Chang-Claude, J.
AU - Schmidt, M.K.
AU - Hall, P.
AU - Milne, R.L.
AU - Pharoah, P.D.P.
AU - Antoniou, A.C.
AU - Chatterjee, N.
AU - Kraft, P.
AU - García-Closas, M.
AU - Simard, J.
AU - Easton, D.F.
AU - Investigators, ABCTB
AU - Investigators, kConFab/AOCS
AU - Collaborators, NBCS
N1 - Cited By :64 Export Date: 28 February 2020 CODEN: AJHGA Correspondence Address: Mavaddat, N.; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of CambridgeUnited Kingdom; email: nm274@medschl.cam.ac.uk Funding details: Novartis Funding details: Eli Lilly and Company Funding details: AstraZeneca Funding details: AbbVie Funding details: Pfizer UK Funding details: Celgene Funding details: Eisai Funding details: Genentech Funding details: Merck Sharp and Dohme Funding details: Roche Funding details: Cancer Research UK, C1287/A16563 Funding details: Government of Canada Funding details: Array BioPharma Funding details: Genome Canada Funding details: PSR-SIIRI-701 Funding details: National Institutes of Health, 1 U19 CA 148065 Funding details: European Commission, C1287/A10710 Funding details: Ministère de l'Économie, de l’Innovation et des Exportations du Québec Funding details: 633784, 634935 Funding details: X01HG007492, C1287/A10118, U19 CA148065 Funding details: Seventh Framework Programme, HEALTH-F2-2009-223175, 223175 Funding details: Canadian Institutes of Health Research, GPH-129344 Funding text 1: D.G.E. reports grants from AstraZeneca and AmGen, outside the submitted work; U.M. has stock ownership and has received research funding from Abcodia Pvt Ltd.; A. Smeets reports other from MSD, outside of the submitted work; P.A.F. reports grants and personal fees from Novartis and personal fees from Pfizer, Roche, Teva, and Celgene, outside the submitted work; R.C. declares personal fees from Novartis, AstraZeneca, and Genentech, outside the submitted work. B.R. reports funding for the conduct of the clinical Success trial paid to her institution from AstraZeneca, Chugai, Lilly, Novartis, Veridex (now Janssen Diagnostics), and Sanofi Aventis. M. Robson reports grants, personal fees, and non-financial support from AstraZeneca, personal fees from McKesson, grants and personal fees from Pfizer, non-financial support from Myriad, non-financial support from Invitae, and grants from AbbVie, Tesaro, and Medivation, outside the submitted work; and M.P.L. reports personal fees from Novartis, Pfizer, Roche, Teva, AstraZeneca, Lilly, and Eisai, outside the submitted work. Funding text 2: BCAC was funded by Cancer Research UK ( C1287/A16563 ) and by the European Community’s Seventh Framework Programme under grant agreement no. 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the OncoArray was principally funded by Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344 ), the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Genome Québec, the Quebec Breast Cancer Foundation; NIH grants U19 CA148065 and X01HG007492 ; and Cancer Research UK ( C1287/A10118 and C1287/A16563 ). Genotyping of the iCOGS array was funded by the European Union ( HEALTH-F2-2009-223175 ), Cancer Research UK ( C1287/A10710 ), the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec (grant # PSR-SIIRI-701 ). Combining the GWAS data was supported in part by the National Institutes of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA 148065 (DRIVE, part of the GAME-ON initiative). We thank all the individuals who took part in these studies and all researchers, clinicians, technicians, and administrative staff who enabled this work to be carried out. For other acknowledgments and sources of funding, see Supplemental Acknowledgments . 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PY - 2019
Y1 - 2019
N2 - 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. © 2018 The Authors
AB - 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. © 2018 The Authors
KW - breast
KW - cancer
KW - epidemiology
KW - genetic
KW - polygenic
KW - prediction
KW - risk
KW - score
KW - screening
KW - stratification
KW - adult
KW - aged
KW - area under the curve
KW - Article
KW - biobank
KW - breast cancer
KW - breast cancer molecular subtype
KW - cancer incidence
KW - cancer prevention
KW - cancer risk
KW - controlled study
KW - estrogen receptor negative breast cancer
KW - estrogen receptor positive breast cancer
KW - European
KW - female
KW - genome-wide association study
KW - genotype
KW - human
KW - major clinical study
KW - middle aged
KW - Polygenic Risk Score
KW - priority journal
KW - prospective study
KW - receiver operating characteristic
KW - scoring system
KW - single nucleotide polymorphism
KW - United Kingdom
KW - validation study
U2 - 10.1016/j.ajhg.2018.11.002
DO - 10.1016/j.ajhg.2018.11.002
M3 - Article
VL - 104
SP - 21
EP - 34
JO - Hum. Mol. Genet.
JF - Hum. Mol. Genet.
SN - 1460-2083
IS - 1
ER -