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

Background

Protein truncating variants inATM,BRCA1,BRCA2,CHEK2, andPALB2are 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 inATM(1146 training variants),BRCA1(644),BRCA2(1425),CHEK2(325), andPALB2(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,BRCA2andCHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains forATM(FAT and PIK domains) andBRCA1(RING and BRCT domains). ForATM,BRCA1, andBRCA2, 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. ForCHEK2, 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)) thanCHEK2protein truncating variants. There was little evidence for an association with risk for missense variants inPALB2. 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.