Breast cancer risks associated with missense variants in breast cancer susceptibility genes
Creators: name: Dorling, Leila
name: Carvalho, Sara
name: Allen, Jamie
name: Parsons, Michael T
name: Fortuno, Cristina
name: González-Neira, Anna
name: Heijl, Stephan M
name: Adank, Muriel A
name: Ahearn, Thomas U
name: Andrulis, Irene L
name: Auvinen, Päivi
name: Becher, Heiko
name: Beckmann, Matthias W
name: Behrens, Sabine
name: Bermisheva, Marina
name: Bogdanova, Natalia V
name: Bojesen, Stig E
name: Bolla, Manjeet K
name: Bremer, Michael
name: Briceno, Ignacio
name: Camp, Nicola J
name: Campbell, Archie
name: Castelao, Jose E
name: Chang-Claude, Jenny
name: Chanock, Stephen J
name: Chenevix-Trench, Georgia
name: Collée, J Margriet
name: Czene, Kamila
name: Dennis, Joe
name: Dörk, Thilo
name: Eriksson, Mikael
name: Evans, D Gareth
name: Fasching, Peter A
name: Figueroa, Jonine
name: Flyger, Henrik
name: Gabrielson, Marike
name: Gago-Dominguez, Manuela
name: García-Closas, Montserrat
name: Giles, Graham G
name: Glendon, Gord
name: Guénel, Pascal
name: Gündert, Melanie
name: Hadjisavvas, Andreas
name: Hahnen, Eric
name: Hall, Per
name: Hamann, Ute
name: Harkness, Elaine F
name: Hartman, Mikael
name: Hogervorst, Frans BL
name: Hollestelle, Antoinette
name: Hoppe, Reiner
name: Howell, Anthony
name: Jakubowska, Anna
name: Jung, Audrey
name: Khusnutdinova, Elza
name: Kim, Sung-Won
name: Ko, Yon-Dschun
name: Kristensen, Vessela N
name: Lakeman, Inge MM
name: Li, Jingmei
name: Lindblom, Annika
name: Loizidou, Maria A
name: Lophatananon, Artitaya
name: Lubiński, Jan
name: Luccarini, Craig
name: Madsen, Michael J
name: Mannermaa, Arto
name: Manoochehri, Mehdi
name: Margolin, Sara
name: Mavroudis, Dimitrios
name: Milne, Roger L
name: Mohd Taib, Nur Aishah
name: Muir, Kenneth
name: Nevanlinna, Heli
name: Newman, William G
name: Oosterwijk, Jan C
name: Park, Sue K
name: Peterlongo, Paolo
name: Radice, Paolo
name: Saloustros, Emmanouil
name: Sawyer, Elinor J
name: Schmutzler, Rita K
name: Shah, Mitul
name: Sim, Xueling
name: Southey, Melissa C
name: Surowy, Harald
name: Suvanto, Maija
name: Tomlinson, Ian
name: Torres, Diana
name: Truong, Thérèse
name: Van Asperen, Christi J
name: Waltes, Regina
name: Wang, Qin
name: Yang, Xiaohong R
name: Pharoah, Paul DP
name: Schmidt, Marjanka K
name: Benitez, Javier
name: Vroling, Bas
name: Dunning, Alison M
name: Teo, Soo Hwang
name: Kvist, Anders
name: De La Hoya, Miguel
name: Devilee, Peter
name: Spurdle, Amanda B
name: Vreeswijk, Maaike PG
name: Easton, Douglas F
Publisher: name: Apollo - University of Cambridge Repository
Year: 2022
Subjects: Research
Breast cancer
Genetic epidemiology
Risk prediction
Missense variants

description: Abstract: Background: Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. Methods: We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. Results: The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47–2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. Conclusions: These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.