Rare germline copy number variants (CNVs) and breast cancer risk

Joe Dennis, Jonathan P Tyrer, Logan C Walker, Kyriaki Michailidou, Leila Dorling, Manjeet K Bolla, Qin Wang, Thomas U Ahearn, Irene L Andrulis, Hoda Anton-Culver, Natalia N Antonenkova, Volker Arndt, Kristan J Aronson, Laura E Beane Freeman, Matthias W Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Natalia V Bogdanova, Stig E BojesenHermann Brenner, Jose E Castelao, Jenny Chang-Claude, Georgia Chenevix-Trench, Christine L Clarke, J Margriet Collée, Fergus J Couch, Angela Cox, Simon S Cross, Kamila Czene, Peter Devilee, Thilo Dörk, Laure Dossus, A Heather Eliassen, Mikael Eriksson, D Gareth Evans, Peter A Fasching, Jonine Figueroa, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Marike Gabrielson, Manuela Gago-Dominguez, Montserrat García-Closas, Graham G Giles, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A Haiman, Per Hall, NBCS Collaborators

Abstract

Germline copy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data. Gene burden tests detected the strongest association for deletions in BRCA1 (P = 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P = 0.0008), ATM (P = 0.002) and BRCA2 (P = 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci. To the best of our knowledge, this is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

Original languageEnglish
Article number65
JournalCommunications biology
Volume5
Issue number1
Pages (from-to)65
ISSN2399-3642
DOIs
Publication statusPublished - 18 Jan 2022

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