Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

Leila Dorling; Sara Carvalho; Jamie Allen; Anna González-Neira; Craig Luccarini; Cecilia Wahlström; Karen A Pooley; Michael T Parsons; Cristina Fortuno; Qin Wang; Manjeet K Bolla; Joe Dennis; Renske Keeman; M Rosario Alonso; Nuria Álvarez; Belen Herraez; Victoria Fernandez; Rocio Núñez-Torres; Ana Osorio; Jeanette Valcich; Minerva Li; Therese Törngren; Patricia A Harrington; Caroline Baynes; Don M Conroy; Brennan Decker; Laura Fachal; Nasim Mavaddat; Thomas Ahearn; Kristiina Aittomäki; Natalia N Antonenkova; Norbert Arnold; Patrick Arveux; Margreet G E M Ausems; Päivi Auvinen; Heiko Becher; Matthias W Beckmann; Sabine Behrens; Marina Bermisheva; Katarzyna Białkowska; Carl Blomqvist; Natalia V Bogdanova; Nadja Bogdanova-Markov; Stig E Bojesen; Bernardo Bonanni; Anne-Lise Børresen-Dale; Hiltrud Brauch; Michael Bremer; Henrik Flyger; Børge G Nordestgaard; Breast Cancer Association Consortium

doi:10.1056/NEJMoa1913948

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

Leila Dorling, Sara Carvalho, Jamie Allen, Anna González-Neira, Craig Luccarini, Cecilia Wahlström, Karen A Pooley, Michael T Parsons, Cristina Fortuno, Qin Wang, Manjeet K Bolla, Joe Dennis, Renske Keeman, M Rosario Alonso, Nuria Álvarez, Belen Herraez, Victoria Fernandez, Rocio Núñez-Torres, Ana Osorio, Jeanette ValcichMinerva Li, Therese Törngren, Patricia A Harrington, Caroline Baynes, Don M Conroy, Brennan Decker, Laura Fachal, Nasim Mavaddat, Thomas Ahearn, Kristiina Aittomäki, Natalia N Antonenkova, Norbert Arnold, Patrick Arveux, Margreet G E M Ausems, Päivi Auvinen, Heiko Becher, Matthias W Beckmann, Sabine Behrens, Marina Bermisheva, Katarzyna Białkowska, Carl Blomqvist, Natalia V Bogdanova, Nadja Bogdanova-Markov, Stig E Bojesen, Bernardo Bonanni, Anne-Lise Børresen-Dale, Hiltrud Brauch, Michael Bremer, Henrik Flyger, Børge G Nordestgaard, Breast Cancer Association Consortium

558 Citations (Scopus)

Abstract

BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Original language	English
Journal	The New England journal of medicine
Volume	384
Issue number	5
Pages (from-to)	428-439
Number of pages	12
ISSN	0028-4793
DOIs	https://doi.org/10.1056/NEJMoa1913948
Publication status	Published - 4 Feb 2021

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Dorling, L., Carvalho, S., Allen, J., González-Neira, A., Luccarini, C., Wahlström, C., Pooley, K. A., Parsons, M. T., Fortuno, C., Wang, Q., Bolla, M. K., Dennis, J., Keeman, R., Alonso, M. R., Álvarez, N., Herraez, B., Fernandez, V., Núñez-Torres, R., Osorio, A., ... Breast Cancer Association Consortium (2021). Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women. The New England journal of medicine, 384(5), 428-439. https://doi.org/10.1056/NEJMoa1913948

Dorling, L, Carvalho, S, Allen, J, González-Neira, A, Luccarini, C, Wahlström, C, Pooley, KA, Parsons, MT, Fortuno, C, Wang, Q, Bolla, MK, Dennis, J, Keeman, R, Alonso, MR, Álvarez, N, Herraez, B, Fernandez, V, Núñez-Torres, R, Osorio, A, Valcich, J, Li, M, Törngren, T, Harrington, PA, Baynes, C, Conroy, DM, Decker, B, Fachal, L, Mavaddat, N, Ahearn, T, Aittomäki, K, Antonenkova, NN, Arnold, N, Arveux, P, Ausems, MGEM, Auvinen, P, Becher, H, Beckmann, MW, Behrens, S, Bermisheva, M, Białkowska, K, Blomqvist, C, Bogdanova, NV, Bogdanova-Markov, N, Bojesen, SE, Bonanni, B, Børresen-Dale, A-L, Brauch, H, Bremer, M, Flyger, H , Nordestgaard, BG & Breast Cancer Association Consortium 2021, 'Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women', The New England journal of medicine, vol. 384, no. 5, pp. 428-439. https://doi.org/10.1056/NEJMoa1913948

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title = "Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women",

abstract = "BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).",

author = "Leila Dorling and Sara Carvalho and Jamie Allen and Anna Gonz{\'a}lez-Neira and Craig Luccarini and Cecilia Wahlstr{\"o}m and Pooley, {Karen A} and Parsons, {Michael T} and Cristina Fortuno and Qin Wang and Bolla, {Manjeet K} and Joe Dennis and Renske Keeman and Alonso, {M Rosario} and Nuria {\'A}lvarez and Belen Herraez and Victoria Fernandez and Rocio N{\'u}{\~n}ez-Torres and Ana Osorio and Jeanette Valcich and Minerva Li and Therese T{\"o}rngren and Harrington, {Patricia A} and Caroline Baynes and Conroy, {Don M} and Brennan Decker and Laura Fachal and Nasim Mavaddat and Thomas Ahearn and Kristiina Aittom{\"a}ki and Antonenkova, {Natalia N} and Norbert Arnold and Patrick Arveux and Ausems, {Margreet G E M} and P{\"a}ivi Auvinen and Heiko Becher and Beckmann, {Matthias W} and Sabine Behrens and Marina Bermisheva and Katarzyna Bia{\l}kowska and Carl Blomqvist and Bogdanova, {Natalia V} and Nadja Bogdanova-Markov and Bojesen, {Stig E} and Bernardo Bonanni and Anne-Lise B{\o}rresen-Dale and Hiltrud Brauch and Michael Bremer and Henrik Flyger and Nordestgaard, {B{\o}rge G} and {Breast Cancer Association Consortium}",

note = "Copyright {\textcopyright} 2021 Massachusetts Medical Society.",

year = "2021",

month = feb,

day = "4",

doi = "10.1056/NEJMoa1913948",

language = "English",

volume = "384",

pages = "428--439",

journal = "The New England journal of medicine",

issn = "0028-4793",

publisher = "Massachusetts Medical Society",

number = "5",

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TY - JOUR

T1 - Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

AU - Dorling, Leila

AU - Carvalho, Sara

AU - Allen, Jamie

AU - González-Neira, Anna

AU - Luccarini, Craig

AU - Wahlström, Cecilia

AU - Pooley, Karen A

AU - Parsons, Michael T

AU - Fortuno, Cristina

AU - Wang, Qin

AU - Bolla, Manjeet K

AU - Dennis, Joe

AU - Keeman, Renske

AU - Alonso, M Rosario

AU - Álvarez, Nuria

AU - Herraez, Belen

AU - Fernandez, Victoria

AU - Núñez-Torres, Rocio

AU - Osorio, Ana

AU - Valcich, Jeanette

AU - Li, Minerva

AU - Törngren, Therese

AU - Harrington, Patricia A

AU - Baynes, Caroline

AU - Conroy, Don M

AU - Decker, Brennan

AU - Fachal, Laura

AU - Mavaddat, Nasim

AU - Ahearn, Thomas

AU - Aittomäki, Kristiina

AU - Antonenkova, Natalia N

AU - Arnold, Norbert

AU - Arveux, Patrick

AU - Ausems, Margreet G E M

AU - Auvinen, Päivi

AU - Becher, Heiko

AU - Beckmann, Matthias W

AU - Behrens, Sabine

AU - Bermisheva, Marina

AU - Białkowska, Katarzyna

AU - Blomqvist, Carl

AU - Bogdanova, Natalia V

AU - Bogdanova-Markov, Nadja

AU - Bojesen, Stig E

AU - Bonanni, Bernardo

AU - Børresen-Dale, Anne-Lise

AU - Brauch, Hiltrud

AU - Bremer, Michael

AU - Flyger, Henrik

AU - Nordestgaard, Børge G

AU - Breast Cancer Association Consortium

PY - 2021/2/4

Y1 - 2021/2/4

N2 - BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

AB - BACKGROUND: Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.METHODS: We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.RESULTS: Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.CONCLUSIONS: The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

UR - http://www.scopus.com/inward/record.url?scp=85100590625&partnerID=8YFLogxK

U2 - 10.1056/NEJMoa1913948

DO - 10.1056/NEJMoa1913948

M3 - Journal article

C2 - 33471991

SN - 0028-4793

VL - 384

SP - 428

EP - 439

JO - The New England journal of medicine

JF - The New England journal of medicine

IS - 5

ER -

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

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