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

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

© 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...

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Bibliographic Details
Main 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.
Format: Journal Article
Published: Nature Publishing Group 2018
Online Access:http://hdl.handle.net/20.500.11937/68945
Description
Summary:© 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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