학술논문

Breast cancer risks associated with missense variants in breast cancer susceptibility genes
Document Type
article
Author
Leila DorlingSara CarvalhoJamie AllenMichael T. ParsonsCristina FortunoAnna González-NeiraStephan M. HeijlMuriel A. AdankThomas U. AhearnIrene L. AndrulisPäivi AuvinenHeiko BecherMatthias W. BeckmannSabine BehrensMarina BermishevaNatalia V. BogdanovaStig E. BojesenManjeet K. BollaMichael BremerIgnacio BricenoNicola J. CampArchie CampbellJose E. CastelaoJenny Chang-ClaudeStephen J. ChanockGeorgia Chenevix-TrenchNBCS CollaboratorsJ. Margriet ColléeKamila CzeneJoe DennisThilo DörkMikael ErikssonD. Gareth EvansPeter A. FaschingJonine FigueroaHenrik FlygerMarike GabrielsonManuela Gago-DominguezMontserrat García-ClosasGraham G. GilesGord GlendonPascal GuénelMelanie GündertAndreas HadjisavvasEric HahnenPer HallUte HamannElaine F. HarknessMikael HartmanFrans B. L. HogervorstAntoinette HollestelleReiner HoppeAnthony HowellkConFab InvestigatorsSGBCC InvestigatorsAnna JakubowskaAudrey JungElza KhusnutdinovaSung-Won KimYon-Dschun KoVessela N. KristensenInge M. M. LakemanJingmei LiAnnika LindblomMaria A. LoizidouArtitaya LophatananonJan LubińskiCraig LuccariniMichael J. MadsenArto MannermaaMehdi ManoochehriSara MargolinDimitrios MavroudisRoger L. MilneNur Aishah Mohd TaibKenneth MuirHeli NevanlinnaWilliam G. NewmanJan C. OosterwijkSue K. ParkPaolo PeterlongoPaolo RadiceEmmanouil SaloustrosElinor J. SawyerRita K. SchmutzlerMitul ShahXueling SimMelissa C. SoutheyHarald SurowyMaija SuvantoIan TomlinsonDiana TorresThérèse TruongChristi J. van AsperenRegina WaltesQin WangXiaohong R. YangPaul D. P. PharoahMarjanka K. SchmidtJavier BenitezBas VrolingAlison M. DunningSoo Hwang TeoAnders KvistMiguel de la HoyaPeter DevileeAmanda B. SpurdleMaaike P. G. VreeswijkDouglas F. Easton
Source
Genome Medicine, Vol 14, Iss 1, Pp 1-17 (2022)
Subject
Breast cancer
Genetic epidemiology
Risk prediction
Missense variants
Medicine
Genetics
QH426-470
Language
English
ISSN
1756-994X
Abstract
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.