A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer

Research output: Contribution to journalJournal articleResearchpeer-review

Lang Wu, Wei Shi, Jirong Long, Xingyi Guo, Kyriaki Michailidou, Jonathan Beesley, Manjeet K Bolla, Xiao-Ou Shu, Yingchang Lu, Qiuyin Cai, Fares Al-Ejeh, Esdy Rozali, Qin Wang, Joe Dennis, Bingshan Li, Chenjie Zeng, Helian Feng, Alexander Gusev, Richard T Barfield, Irene L Andrulis & 31 others Hoda Anton-Culver, Volker Arndt, Kristan J Aronson, Paul L Auer, Myrto Barrdahl, Caroline Baynes, Matthias W Beckmann, Javier Benitez, Marina Bermisheva, Carl Blomqvist, Natalia V Bogdanova, Stig E Bojesen, Hiltrud Brauch, Hermann Brenner, Louise Brinton, Per Broberg, Sara Y Brucker, Barbara Burwinkel, Trinidad Caldés, Federico Canzian, Brian D Carter, J Esteban Castelao, Jenny Chang-Claude, Xiaoqing Chen, Ting-Yuan David Cheng, Hans Christiansen, Christine L Clarke, Henrik Flyger, Sune F Nielsen, Børge G Nordestgaard, NBCS Collaborators

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10-6, including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Original languageEnglish
JournalNature Genetics
Volume50
Issue number7
Pages (from-to)968-978
Number of pages11
ISSN1061-4036
DOIs
Publication statusPublished - 2018

ID: 213863172