Large-scale genome-wide association study of 398,238 women unveils seven novel loci associated with high-grade serous epithelial ovarian cancer risk
Author:
Barnes Daniel R.ORCID, Tyrer Jonathan P.ORCID, Dennis JoeORCID, Leslie Goska, Bolla Manjeet K., Lush Michael, Aeilts Amber M., Aittomäki Kristiina, Andrieu Nadine, Andrulis Irene L., Anton-Culver Hoda, Arason Adalgeir, Arun Banu K., Balmaña Judith, Bandera Elisa V., Barkardottir Rosa B., Berger Lieke P.V., Berrington de Gonzalez Amy, Berthet Pascaline, Białkowska Katarzyna, Bjørge Line, Blanco Amie M., Blok Marinus J., Bobolis Kristie A., Bogdanova Natalia V., Brenton James D.ORCID, Butz Henriett, Buys Saundra S., Caligo Maria A., Campbell Ian, Castillo Carmen, Claes Kathleen B.M., , , Colonna Sarah V., Cook Linda S., Daly Mary B., Dansonka-Mieszkowska Agnieszka, de la Hoya Miguel, deFazio Anna, DePersia Allison, Ding Yuan Chun, Domchek Susan M., Dörk Thilo, Einbeigi Zakaria, Engel Christoph, Evans D. Gareth, Foretova Lenka, Fortner Renée T., Fostira Florentia, Foti Maria Cristina, Friedman Eitan, Frone Megan N., Ganz Patricia A., Gentry-Maharaj Aleksandra, Glendon Gord, Godwin Andrew K., González-Neira Anna, Greene Mark H., Gronwald Jacek, Guerrieri-Gonzaga Aliana, Hamann Ute, Hansen Thomas v.O., Harris Holly R., Hauke Jan, Heitz Florian, Hogervorst Frans B.L., Hooning Maartje J., Hopper John L., Huff Chad D, Huntsman David G., Imyanitov Evgeny N., , Izatt Louise, Jakubowska Anna, James Paul A., Janavicius Ramunas, John Esther M., Kar SiddharthaORCID, Karlan Beth Y., Kennedy Catherine J., Kiemeney Lambertus A.L.M., Konstantopoulou Irene, Kupryjanczyk Jolanta, Laitman Yael, Lavie Ofer, Lawrenson Kate, Lester Jenny, Lesueur Fabienne, Lopez-Pleguezuelos Carlos, Mai Phuong L., Manoukian Siranoush, May Taymaa, McNeish Iain A.ORCID, Menon Usha, Milne Roger L., Modugno Francesmary, Mongiovi Jennifer M., Montagna Marco, Moysich Kirsten B., Neuhausen Susan L., Nielsen Finn C., Noguès Catherine, Oláh Edit, Olopade Olufunmilayo I., Osorio Ana, Papi Laura, Pathak Harsh, Pearce Celeste L., Pedersen Inge S., Peixoto Ana, Pejovic Tanja, Peng Pei-ChenORCID, Peshkin Beth N., Peterlongo Paolo, Powell C. Bethan, Prokofyeva Darya, Pujana Miquel Angel, Radice Paolo, Rashid Muhammad U., Rennert Gad, Richenberg George, Sandler Dale P., Sasamoto Naoko, Setiawan Veronica W., Sharma Priyanka, Sieh Weiva, Singer Christian F., Snape Katie, Sokolenko Anna P., Soucy Penny, Southey Melissa C., Stoppa-Lyonnet Dominique, Sutphen Rebecca, Sutter Christian, Teixeira Manuel R., Terry Kathryn L., Thomsen Liv Cecilie V., Tischkowitz Marc, Toland Amanda E., Van Gorp Toon, Vega Ana, Velez Edwards Digna R., Webb Penelope M., Weitzel Jeffrey N., Wentzensen Nicolas, Whittemore Alice S., Winham Stacey J., Wu Anna H., Yadav Siddhartha, Yu Yao, Ziogas Argyrios, Berchuck Andrew, Couch Fergus J., Goode Ellen L., Goodman Marc T., Monteiro Alvaro N., Offit Kenneth, Ramus Susan J., Risch Harvey A., Schildkraut Joellen M., Thomassen Mads, Simard Jacques, Easton Douglas F., Jones Michelle R., Chenevix-Trench Georgia, Gayther Simon A., Antoniou Antonis C., Pharoah Paul D.P.
Abstract
ABSTRACTBackgroundNineteen genomic regions have been associated with high-grade serous ovarian cancer (HGSOC). We used data from the Ovarian Cancer Association Consortium (OCAC), Consortium of Investigators of Modifiers ofBRCA1/BRCA2(CIMBA), UK Biobank (UKBB), and FinnGen to identify novel HGSOC susceptibility loci and develop polygenic scores (PGS).MethodsWe analyzed >22 million variants for 398,238 women. Associations were assessed separately by consortium and meta-analysed. OCAC and CIMBA data were used to develop PGS which were trained on FinnGen data and validated in UKBB and BioBank JapanResultsEight novel variants were associated with HGSOC risk. An interesting discovery biologically was finding thatTP533’-UTR SNP rs78378222 was associated with HGSOC (per T allele relative risk (RR)=1.44, 95%CI:1.28-1.62, P=1.76×10-9). The optimal PGS included 64,518 variants and was associated with an odds ratio of 1.46 (95%CI:1.37-1.54) per standard deviation in the UKBB validation (AUROC curve=0.61, 95%CI:0.59-0.62).ConclusionsThis study represents the largest GWAS for HGSOC to date. The results highlight that improvements in imputation reference panels and increased sample sizes can identify HGSOC associated variants that previously went undetected, resulting in improved PGS. The use of updated PGS in cancer risk prediction algorithms will then improve personalized risk prediction for HGSOC.
Publisher
Cold Spring Harbor Laboratory
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