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,
Ignacio Briceno,
Thomas Brüning,
Barbara Burwinkel,
David A Cameron,
Nicola J Camp,
Archie Campbell,
Angel Carracedo,
Jose E Castelao,
Melissa H Cessna,
Stephen J Chanock,
Hans Christiansen,
J Margriet Collée,
Emilie Cordina-Duverger,
Sten Cornelissen,
Kamila Czene,
Thilo Dörk,
Arif B Ekici,
Christoph Engel,
Mikael Eriksson,
Peter A Fasching,
Jonine Figueroa,
Henrik Flyger,
Asta Försti,
Marike Gabrielson,
Manuela Gago-Dominguez,
Vassilios Georgoulias,
Fabian Gil,
Graham G Giles,
Gord Glendon,
Encarna B Gómez Garcia,
Grethe I Grenaker Alnæs,
Pascal Guénel,
Andreas Hadjisavvas,
Lothar Haeberle,
Eric Hahnen,
Per Hall,
Ute Hamann,
Elaine F Harkness,
Jaana M Hartikainen,
Mikael Hartman,
Wei He,
Bernadette A M Heemskerk-Gerritsen,
Peter Hillemanns,
Frans B L Hogervorst,
Antoinette Hollestelle,
Weang Kee Ho,
Maartje J Hooning,
Anthony Howell,
Keith Humphreys,
Faiza Idris,
Anna Jakubowska,
Audrey Jung,
Pooja Middha Kapoor,
Michael J Kerin,
Elza Khusnutdinova,
Sung-Won Kim,
Yon-Dschun Ko,
Veli-Matti Kosma,
Vessela N Kristensen,
Kyriacos Kyriacou,
Inge M M Lakeman,
Jong Won Lee,
Min Hyuk Lee,
Jingmei Li,
Annika Lindblom,
Wing-Yee Lo,
Maria A Loizidou,
Artitaya Lophatananon,
Jan Lubiński,
Robert J MacInnis,
Michael J Madsen,
Arto Mannermaa,
Mehdi Manoochehri,
Siranoush Manoukian,
Sara Margolin,
Maria Elena Martinez,
Tabea Maurer,
Dimitrios Mavroudis,
Catriona McLean,
Alfons Meindl,
Arjen R Mensenkamp,
Kyriaki Michailidou,
Nicola Miller,
Nur Aishah Mohd Taib,
Kenneth Muir,
Anna Marie Mulligan,
Heli Nevanlinna,
William G Newman,
Børge G Nordestgaard,
Pei-Sze Ng,
Jan C Oosterwijk,
Sue K Park,
Tjoung-Won Park-Simon,
Jose I A Perez,
Paolo Peterlongo,
David J Porteous,
Karolina Prajzendanc,
Darya Prokofyeva,
Paolo Radice,
Muhammad U Rashid,
Valerie Rhenius,
Matti A Rookus,
Thomas Rüdiger,
Emmanouil Saloustros,
Elinor J Sawyer,
Rita K Schmutzler,
Andreas Schneeweiss,
Peter Schürmann,
Mitul Shah,
Christof Sohn,
Melissa C Southey,
Harald Surowy,
Maija Suvanto,
Somchai Thanasitthichai,
Ian Tomlinson,
Diana Torres,
Thérèse Truong,
Maria Tzardi,
Yana Valova,
Christi J van Asperen,
Rob M Van Dam,
Ans M W van den Ouweland,
Lizet E van der Kolk,
Elke M van Veen,
Camilla Wendt,
Justin A Williams,
Xiaohong R Yang,
Sook-Yee Yoon,
M Pilar Zamora,
D Gareth Evans,
Miguel de la Hoya,
Jacques Simard,
Antonis C Antoniou,
Åke Borg,
Irene L Andrulis,
Jenny Chang-Claude,
Montserrat García-Closas,
Georgia Chenevix-Trench,
Roger L Milne,
Paul D P Pharoah,
Marjanka K Schmidt,
Amanda B Spurdle,
Maaike P G Vreeswijk,
Javier Benitez,
Alison M Dunning,
Anders Kvist,
Soo H Teo,
Peter Devilee,
Douglas F Easton
Abstract
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.
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.).
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.
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.