Breast cancer risks associated with missense variants in breast cancer susceptibility genes.
Breast cancer
Genetic epidemiology
Missense variants
Risk prediction
Journal
Genome medicine
ISSN: 1756-994X
Titre abrégé: Genome Med
Pays: England
ID NLM: 101475844
Informations de publication
Date de publication:
18 05 2022
18 05 2022
Historique:
received:
20
08
2021
accepted:
04
05
2022
entrez:
18
5
2022
pubmed:
19
5
2022
medline:
21
5
2022
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 35585550
doi: 10.1186/s13073-022-01052-8
pii: 10.1186/s13073-022-01052-8
pmc: PMC9116026
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
51Subventions
Organisme : Wellcome Trust
ID : 203477/Z/16/Z
Pays : United Kingdom
Organisme : Cancer Research UK
ID : C1287/A16563
Pays : United Kingdom
Organisme : Wellcome Trust
ID : v203477/Z/16/Z
Pays : United Kingdom
Informations de copyright
© 2022. The Author(s).
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