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

    Access Status
    Fulltext not available
    Authors
    Wu, L.
    Shi, W.
    Long, J.
    Guo, X.
    Michailidou, K.
    Beesley, J.
    Bolla, M.
    Shu, X.
    Lu, Y.
    Cai, Q.
    Al-Ejeh, F.
    Rozali, E.
    Wang, Q.
    Dennis, J.
    Li, B.
    Zeng, C.
    Feng, H.
    Gusev, A.
    Barfield, R.
    Andrulis, I.
    Anton-Culver, H.
    Arndt, V.
    Aronson, K.
    Auer, P.
    Barrdahl, M.
    Baynes, C.
    Beckmann, M.
    Benitez, J.
    Bermisheva, M.
    Blomqvist, C.
    Bogdanova, N.
    Bojesen, S.
    Brauch, H.
    Brenner, H.
    Brinton, L.
    Broberg, P.
    Brucker, S.
    Burwinkel, B.
    Caldés, T.
    Canzian, F.
    Carter, B.
    Castelao, J.
    Chang-Claude, J.
    Chen, X.
    Cheng, T.
    Christiansen, H.
    Clarke, C.
    Collée, M.
    Cornelissen, S.
    Couch, F.
    Cox, D.
    Cox, A.
    Cross, S.
    Cunningham, J.
    Czene, K.
    Daly, M.
    Devilee, P.
    Doheny, K.
    Dörk, T.
    Dos-Santos-Silva, I.
    Dumont, M.
    Dwek, M.
    Eccles, D.
    Eilber, U.
    Eliassen, A.
    Engel, C.
    Eriksson, M.
    Fachal, L.
    Fasching, P.
    Figueroa, J.
    Flesch-Janys, D.
    Fletcher, O.
    Flyger, H.
    Fritschi, Lin
    Gabrielson, M.
    Date
    2018
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Wu, L. and Shi, W. and Long, J. and Guo, X. and Michailidou, K. and Beesley, J. and Bolla, M. et al. 2018. A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer. Nature Genetics: pp. 1-11.
    Source Title
    Nature Genetics
    DOI
    10.1038/s41588-018-0132-x
    ISSN
    1061-4036
    School
    School of Public Health
    URI
    http://hdl.handle.net/20.500.11937/68945
    Collection
    • Curtin Research Publications
    Abstract

    © 2018 The Author(s) 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.

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