TY - JOUR
T1 - Breast cancer risks associated with missense variants in breast cancer susceptibility genes
AU - NBCS Collaborators
AU - kConFab Investigators
AU - SGBCC Investigators
AU - Dorling, Leila
AU - Carvalho, Sara
AU - Allen, Jamie
AU - Parsons, Michael T.
AU - Fortuno, Cristina
AU - González-Neira, Anna
AU - Heijl, Stephan M.
AU - Adank, Muriel A.
AU - Ahearn, Thomas U.
AU - Andrulis, Irene L.
AU - Auvinen, Päivi
AU - Becher, Heiko
AU - Beckmann, Matthias W.
AU - Behrens, Sabine
AU - Bermisheva, Marina
AU - Bogdanova, Natalia V.
AU - Bojesen, Stig E.
AU - Bolla, Manjeet K.
AU - Bremer, Michael
AU - Briceno, Ignacio
AU - Camp, Nicola J.
AU - Campbell, Archie
AU - Castelao, Jose E.
AU - Chang-Claude, Jenny
AU - Chanock, Stephen J.
AU - Chenevix-Trench, Georgia
AU - Collée, J. Margriet
AU - Czene, Kamila
AU - Dennis, Joe
AU - Dörk, Thilo
AU - Eriksson, Mikael
AU - Evans, D. Gareth
AU - Fasching, Peter A.
AU - Figueroa, Jonine
AU - Flyger, Henrik
AU - Gabrielson, Marike
AU - Gago-Dominguez, Manuela
AU - García-Closas, Montserrat
AU - Giles, Graham G.
AU - Glendon, Gord
AU - Guénel, Pascal
AU - Gündert, Melanie
AU - Hadjisavvas, Andreas
AU - Hahnen, Eric
AU - Hall, Per
AU - Hamann, Ute
AU - Harkness, Elaine F.
AU - Hartman, Mikael
AU - Hogervorst, Frans B.L.
AU - Torres, Diana
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - 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.
AB - 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.
KW - Breast cancer
KW - Genetic epidemiology
KW - Missense variants
KW - Risk prediction
UR - https://www.scopus.com/pages/publications/85130251315
U2 - 10.1186/s13073-022-01052-8
DO - 10.1186/s13073-022-01052-8
M3 - Article
C2 - 35585550
AN - SCOPUS:85130251315
SN - 1756-994X
VL - 14
JO - Genome Medicine
JF - Genome Medicine
IS - 1
M1 - 51
ER -
SDG 3 Good Health and Well-being