Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Leila Dorling; Sara Carvalho; Jamie Allen; Michael T Parsons; Cristina Fortuno; Anna González-Neira; Stephan M Heijl; Muriel A Adank; Thomas U Ahearn; Irene L Andrulis; Päivi Auvinen; Heiko Becher; Matthias W Beckmann; Sabine Behrens; Marina Bermisheva; Natalia V Bogdanova; Stig E Bojesen; Manjeet K Bolla; Michael Bremer; Ignacio Briceno; Nicola J Camp; Archie Campbell; Jose E Castelao; Jenny Chang-Claude; Stephen J Chanock; Georgia Chenevix-Trench; J Margriet Collée; Kamila Czene; Joe Dennis; Thilo Dörk; Mikael Eriksson; D Gareth Evans; Peter A Fasching; Jonine Figueroa; Henrik Flyger; Marike Gabrielson; Manuela Gago-Dominguez; Montserrat García-Closas; Graham G Giles; Gord Glendon; Pascal Guénel; Melanie Gündert; Andreas Hadjisavvas; Eric Hahnen; Per Hall; Ute Hamann; Elaine F Harkness; Mikael Hartman; Frans B L Hogervorst; Antoinette Hollestelle; NBCS Collaborators

doi:10.1186/s13073-022-01052-8

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Leila Dorling, Sara Carvalho, Jamie Allen, Michael T Parsons, Cristina Fortuno, Anna González-Neira, Stephan M Heijl, Muriel A Adank, Thomas U Ahearn, Irene L Andrulis, Päivi Auvinen, Heiko Becher, Matthias W Beckmann, Sabine Behrens, Marina Bermisheva, Natalia V Bogdanova, Stig E Bojesen, Manjeet K Bolla, Michael Bremer, Ignacio BricenoNicola J Camp, Archie Campbell, Jose E Castelao, Jenny Chang-Claude, Stephen J Chanock, Georgia Chenevix-Trench, J Margriet Collée, Kamila Czene, Joe Dennis, Thilo Dörk, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine Figueroa, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Montserrat García-Closas, Graham G Giles, Gord Glendon, Pascal Guénel, Melanie Gündert, Andreas Hadjisavvas, Eric Hahnen, Per Hall, Ute Hamann, Elaine F Harkness, Mikael Hartman, Frans B L Hogervorst, Antoinette Hollestelle, NBCS Collaborators

31 Citationer (Scopus)

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.

Originalsprog	Engelsk
Artikelnummer	51
Tidsskrift	Genome Medicine
Vol/bind	14
Udgave nummer	1
Sider (fra-til)	51
ISSN	1756-994X
DOI	https://doi.org/10.1186/s13073-022-01052-8
Status	Udgivet - 18 maj 2022

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10.1186/s13073-022-01052-8

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Dorling, L., Carvalho, S., Allen, J., Parsons, M. T., Fortuno, C., González-Neira, A., Heijl, S. M., Adank, M. A., Ahearn, T. U., Andrulis, I. L., Auvinen, P., Becher, H., Beckmann, M. W., Behrens, S., Bermisheva, M., Bogdanova, N. V., Bojesen, S. E., Bolla, M. K., Bremer, M., ... NBCS Collaborators (2022). Breast cancer risks associated with missense variants in breast cancer susceptibility genes. Genome Medicine, 14(1), 51. Artikel 51. https://doi.org/10.1186/s13073-022-01052-8

Dorling, L, Carvalho, S, Allen, J, Parsons, MT, Fortuno, C, González-Neira, A, Heijl, SM, Adank, MA, Ahearn, TU, Andrulis, IL, Auvinen, P, Becher, H, Beckmann, MW, Behrens, S, Bermisheva, M, Bogdanova, NV, Bojesen, SE, Bolla, MK, Bremer, M, Briceno, I, Camp, NJ, Campbell, A, Castelao, JE, Chang-Claude, J, Chanock, SJ, Chenevix-Trench, G, Collée, JM, Czene, K, Dennis, J, Dörk, T, Eriksson, M, Evans, DG, Fasching, PA, Figueroa, J, Flyger, H, Gabrielson, M, Gago-Dominguez, M, García-Closas, M, Giles, GG, Glendon, G, Guénel, P, Gündert, M, Hadjisavvas, A, Hahnen, E, Hall, P, Hamann, U, Harkness, EF, Hartman, M, Hogervorst, FBL, Hollestelle, A & NBCS Collaborators 2022, 'Breast cancer risks associated with missense variants in breast cancer susceptibility genes', Genome Medicine, bind 14, nr. 1, 51, s. 51. https://doi.org/10.1186/s13073-022-01052-8

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title = "Breast cancer risks associated with missense variants in breast cancer susceptibility genes",

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.",

keywords = "Breast Neoplasms/genetics, Case-Control Studies, Female, Genetic Predisposition to Disease, Humans, Mutation, Missense",

author = "Leila Dorling and Sara Carvalho and Jamie Allen and Parsons, {Michael T} and Cristina Fortuno and Anna Gonz{\'a}lez-Neira and Heijl, {Stephan M} and Adank, {Muriel A} and Ahearn, {Thomas U} and Andrulis, {Irene L} and P{\"a}ivi Auvinen and Heiko Becher and Beckmann, {Matthias W} and Sabine Behrens and Marina Bermisheva and Bogdanova, {Natalia V} and Bojesen, {Stig E} and Bolla, {Manjeet K} and Michael Bremer and Ignacio Briceno and Camp, {Nicola J} and Archie Campbell and Castelao, {Jose E} and Jenny Chang-Claude and Chanock, {Stephen J} and Georgia Chenevix-Trench and Coll{\'e}e, {J Margriet} and Kamila Czene and Joe Dennis and Thilo D{\"o}rk and Mikael Eriksson and Evans, {D Gareth} and Fasching, {Peter A} and Jonine Figueroa and Henrik Flyger and Marike Gabrielson and Manuela Gago-Dominguez and Montserrat Garc{\'i}a-Closas and Giles, {Graham G} and Gord Glendon and Pascal Gu{\'e}nel and Melanie G{\"u}ndert and Andreas Hadjisavvas and Eric Hahnen and Per Hall and Ute Hamann and Harkness, {Elaine F} and Mikael Hartman and Hogervorst, {Frans B L} and Antoinette Hollestelle and {NBCS Collaborators}",

note = "{\textcopyright} 2022. The Author(s).",

year = "2022",

month = may,

day = "18",

doi = "10.1186/s13073-022-01052-8",

language = "English",

volume = "14",

pages = "51",

journal = "Genome Medicine",

issn = "1756-994X",

publisher = "BioMed Central Ltd",

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TY - JOUR

T1 - Breast cancer risks associated with missense variants in breast cancer susceptibility genes

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 - Hollestelle, Antoinette

AU - NBCS Collaborators

PY - 2022/5/18

Y1 - 2022/5/18

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 Neoplasms/genetics

KW - Case-Control Studies

KW - Female

KW - Genetic Predisposition to Disease

KW - Humans

KW - Mutation, Missense

UR - http://www.scopus.com/inward/record.url?scp=85130251315&partnerID=8YFLogxK

U2 - 10.1186/s13073-022-01052-8

DO - 10.1186/s13073-022-01052-8

M3 - Journal article

C2 - 35585550

SN - 1756-994X

VL - 14

SP - 51

JO - Genome Medicine

JF - Genome Medicine

IS - 1

M1 - 51

ER -

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

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