Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Eileen O Dareng, Jonathan P Tyrer, Daniel R Barnes, Michelle R Jones, Xin Yang, Katja K H Aben, Muriel A Adank, Simona Agata, Irene L Andrulis, Hoda Anton-Culver, Natalia N Antonenkova, Gerasimos Aravantinos, Banu K Arun, Annelie Augustinsson, Judith Balmaña, Elisa V Bandera, Rosa B Barkardottir, Daniel Barrowdale, Matthias W Beckmann, Alicia Beeghly-FadielJavier Benitez, Marina Bermisheva, Marcus Q Bernardini, Line Bjorge, Amanda Black, Natalia V Bogdanova, Bernardo Bonanni, Ake Borg, James D Brenton, Agnieszka Budzilowska, Ralf Butzow, Saundra S Buys, Hui Cai, Maria A Caligo, Ian Campbell, Rikki Cannioto, Hayley Cassingham, Jenny Chang-Claude, Stephen J Chanock, Kexin Chen, Yoke-Eng Chiew, Wendy K Chung, Kathleen B M Claes, Sarah Colonna, Linda S Cook, Fergus J Couch, Mary B Daly, Fanny Dao, Eleanor Davies, Miguel de la Hoya, Robin de Putter, Joe Dennis, Allison DePersia, Peter Devilee, Orland Diez, Yuan Chun Ding, Jennifer A Doherty, Susan M Domchek, Thilo Dörk, Andreas du Bois, Matthias Dürst, Diana M Eccles, Heather A Eliassen, Christoph Engel, Gareth D Evans, Peter A Fasching, James M Flanagan, Renée T Fortner, Eva Machackova, Eitan Friedman, Patricia A Ganz, Judy Garber, Francesca Gensini, Graham G Giles, Gord Glendon, Andrew K Godwin, Marc T Goodman, Mark H Greene, Jacek Gronwald, Eric Hahnen, Christopher A Haiman, Niclas Håkansson, Ute Hamann, Thomas V O Hansen, Holly R Harris, Mikael Hartman, Florian Heitz, Michelle A T Hildebrandt, Estrid Høgdall, Claus K Høgdall, John L Hopper, Ruea-Yea Huang, Chad Huff, Peter J Hulick, David G Huntsman, Evgeny N Imyanitov, Claudine Isaacs, Anna Jakubowska, Paul A James, Ramunas Janavicius, Allan Jensen, Oskar Th Johannsson, Esther M John, Michael E Jones, Daehee Kang, Beth Y Karlan, Anthony Karnezis, Linda E Kelemen, Elza Khusnutdinova, Lambertus A Kiemeney, Byoung-Gie Kim, Susanne K Kjaer, Ian Komenaka, Jolanta Kupryjanczyk, Allison W Kurian, Ava Kwong, Diether Lambrechts, Melissa C Larson, Conxi Lazaro, Nhu D Le, Goska Leslie, Jenny Lester, Fabienne Lesueur, Douglas A Levine, Lian Li, Jingmei Li, Jennifer T Loud, Karen H Lu, Jan Lubiński, Phuong L Mai, Siranoush Manoukian, Jeffrey R Marks, Rayna Kim Matsuno, Keitaro Matsuo, Taymaa May, Lesley McGuffog, John R McLaughlin, Iain A McNeish, Noura Mebirouk, Usha Menon, Austin Miller, Roger L Milne, Albina Minlikeeva, Francesmary Modugno, Marco Montagna, Kirsten B Moysich, Elizabeth Munro, Katherine L Nathanson, Susan L Neuhausen, Heli Nevanlinna, Joanne Ngeow Yuen Yie, Henriette Roed Nielsen, Finn C Nielsen, Liene Nikitina-Zake, Kunle Odunsi, Kenneth Offit, Edith Olah, Siel Olbrecht, Olufunmilayo I Olopade, Sara H Olson, Håkan Olsson, Ana Osorio, Laura Papi, Sue K Park, Michael T Parsons, Harsha Pathak, Inge Sokilde Pedersen, Ana Peixoto, Tanja Pejovic, Pedro Perez-Segura, Jennifer B Permuth, Beth Peshkin, Paolo Peterlongo, Anna Piskorz, Darya Prokofyeva, Paolo Radice, Johanna Rantala, Marjorie J Riggan, Harvey A Risch, Cristina Rodriguez-Antona, Eric Ross, Mary Anne Rossing, Ingo Runnebaum, Dale P Sandler, Marta Santamariña, Penny Soucy, Rita K Schmutzler, V Wendy Setiawan, Kang Shan, Weiva Sieh, Jacques Simard, Christian F Singer, Anna P Sokolenko, Honglin Song, Melissa C Southey, Helen Steed, Dominique Stoppa-Lyonnet, Rebecca Sutphen, Anthony J Swerdlow, Yen Yen Tan, Manuel R Teixeira, Soo Hwang Teo, Kathryn L Terry, Mary Beth Terry, Mads Thomassen, Pamela J Thompson, Liv Cecilie Vestrheim Thomsen, Darcy L Thull, Marc Tischkowitz, Linda Titus, Amanda E Toland, Diana Torres, Britton Trabert, Ruth Travis, Nadine Tung, Shelley S Tworoger, Ellen Valen, Anne M van Altena, Annemieke H van der Hout, Els Van Nieuwenhuysen, Elizabeth J van Rensburg, Ana Vega, Digna Velez Edwards, Robert A Vierkant, Frances Wang, Barbara Wappenschmidt, Penelope M Webb, Clarice R Weinberg, Jeffrey N Weitzel, Nicolas Wentzensen, Emily White, Alice S Whittemore, Stacey J Winham, Alicja Wolk, Yin-Ling Woo, Anna H Wu, Li Yan, Drakoulis Yannoukakos, Katia M Zavaglia, Wei Zheng, Argyrios Ziogas, Kristin K Zorn, Zdenek Kleibl, Douglas Easton, Kate Lawrenson, Anna DeFazio, Thomas A Sellers, Susan J Ramus, Celeste L Pearce, Alvaro N Monteiro, Julie Cunningham, Ellen L Goode, Joellen M Schildkraut, Andrew Berchuck, Georgia Chenevix-Trench, Simon A Gayther, Antonis C Antoniou, Paul D. P. Pharoah*, GEMO Study Collaborators

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Abstract

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

OriginalsprogEngelsk
TidsskriftEuropean Journal of Human Genetics
Vol/bind30
Udgave nummer3
Sider (fra-til)349-362
Antal sider14
ISSN1018-4813
DOI
StatusUdgivet - mar. 2022

Bibliografisk note

© 2021. The Author(s).

Korrektion publiceret: Dareng, E.O., Tyrer, J.P., Barnes, D.R. et al. Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk. Eur J Hum Genet (2022). https://doi-org/10.1038/s41431-022-01085-y.

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