Article | Published:

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

Nature Geneticsvolume 50pages968978 (2018) | Download Citation


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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  1. 1.

    Kamangar, F., Dores, G. M. & Anderson, W. F. Patterns of cancer incidence, mortality, and prevalence across five continents: defining priorities to reduce cancer disparities in different geographic regions of the world. J. Clin. Oncol. 24, 2137–2150 (2006).

  2. 2.

    Beggs, A. D. & Hodgson, S. V. Genomics and breast cancer: the different levels of inherited susceptibility. Eur. J. Hum. Genet. 17, 855–856 (2009).

  3. 3.

    Southey, M. C. et al. PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS. J. Med. Genet. 53, 800–811 (2016).

  4. 4.

    Nathanson, K. L., Wooster, R. & Weber, B. L. Breast cancer genetics: what we know and what we need. Nat. Med. 7, 552–556 (2001).

  5. 5.

    Anglian Breast Cancer Study Group. Prevalence and penetrance of BRCA1 and BRCA2 mutations in a population-based series of breast cancer cases. Br. J. Cancer 83, 1301–1308 (2000).

  6. 6.

    Milne, R. L. et al. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer. Nat. Genet. 49, 1767–1778 (2017).

  7. 7.

    Michailidou, K. et al. Association analysis identifies 65 new breast cancer risk loci. Nature 551, 92–94 (2017).

  8. 8.

    Michailidou, K. et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat. Genet. 45, 353–361 (2013).

  9. 9.

    Michailidou, K. et al. Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer. Nat. Genet. 47, 373–380 (2015).

  10. 10.

    Cai, Q. et al. Genome-wide association analysis in East Asians identifies breast cancer susceptibility loci at 1q32.1, 5q14.3 and 15q26.1. Nat. Genet. 46, 886–890 (2014).

  11. 11.

    Zheng, W. et al. Common genetic determinants of breast-cancer risk in East Asian women: a collaborative study of 23 637 breast cancer cases and 25 579 controls. Hum. Mol. Genet. 22, 2539–2550 (2013).

  12. 12.

    Zhang, B., Beeghly-Fadiel, A., Long, J. & Zheng, W. Genetic variants associated with breast-cancer risk: comprehensive research synopsis, meta-analysis, and epidemiological evidence. Lancet Oncol. 12, 477–488 (2011).

  13. 13.

    French, J. D. et al. Functional variants at the 11q13 risk locus for breast cancer regulate cyclin D1 expression through long-range enhancers. Am. J. Hum. Genet. 92, 489–503 (2013).

  14. 14.

    Hindorff, L. A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA 106, 9362–9367 (2009).

  15. 15.

    The ENCODE Project Consortium An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

  16. 16.

    Roadmap Epigenomics, C. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

  17. 17.

    Dunning, A. M. et al. Breast cancer risk variants at 6q25 display different phenotype associations and regulate ESR1, RMND1 and CCDC170. Nat. Genet. 48, 374–386 (2016).

  18. 18.

    Ghoussaini, M. et al. Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation. Nat. Commun. 4, 4999 (2014).

  19. 19.

    Li, Q. et al. Integrative eQTL-based analyses reveal the biology of breast cancer risk loci. Cell 152, 633–641 (2013).

  20. 20.

    Darabi, H. et al. Polymorphisms in a putative enhancer at the 10q21.2 breast cancer risk locus regulate NRBF2 expression. Am. J. Hum. Genet. 97, 22–34 (2015).

  21. 21.

    Glubb, D. M. et al. Fine-scale mapping of the 5q11.2 breast cancer locus reveals at least three independent risk variants regulating MAP3K1. Am. J. Hum. Genet. 96, 5–20 (2015).

  22. 22.

    Lawrenson, K. et al. Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus. Nat. Commun. 7, 12675 (2016).

  23. 23.

    Lee, D. et al. A method to predict the impact of regulatory variants from DNA sequence. Nat. Genet. 47, 955–961 (2015).

  24. 24.

    Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).

  25. 25.

    Gusev, A. et al. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases. Am. J. Hum. Genet. 95, 535–552 (2014).

  26. 26.

    Barbeira, A.N. et al. Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics. Nat. Commun. 9, 1825 (2018).

  27. 27.

    Gamazon, E. R. et al. A gene-based association method for mapping traits using reference transcriptome data. Nat. Genet. 47, 1091–1098 (2015).

  28. 28.

    Gusev, A. et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat. Genet. 48, 245–252 (2016).

  29. 29.

    Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).

  30. 30.

    Hoffman, J. D. et al. Cis-eQTL-based trans-ethnic meta-analysis reveals novel genes associated with breast cancer risk. PLoS Genet. 13, e1006690 (2017).

  31. 31.

    Lin, W. Y. et al. Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk. Hum. Mol. Genet. 24, 285–298 (2015).

  32. 32.

    Camp, N. J. et al. Discordant haplotype sequencing identifies functional variants at the 2q33 breast cancer risk locus. Cancer Res. 76, 1916–1925 (2016).

  33. 33.

    Li, Q. et al. Expression QTL-based analyses reveal candidate causal genes and loci across five tumor types. Hum. Mol. Genet. 23, 5294–5302 (2014).

  34. 34.

    Caswell, J. L. et al. Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors. Hum. Mol. Genet. 24, 7421–7431 (2015).

  35. 35.

    Darabi, H. et al. Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs). Sci. Rep. 6, 32512 (2016).

  36. 36.

    Yang, J. et al. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits. Nat. Genet. 44, 369–375 (2012).

  37. 37.

    Kramer, A., Green, J., Pollard, J. Jr & Tugendreich, S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics 30, 523–530 (2014).

  38. 38.

    Koh, J. L. et al. COLT-Cancer: functional genetic screening resource for essential genes in human cancer cell lines. Nucleic Acids Res. 40, D957–D963 (2012).

  39. 39.

    Marcotte, R. et al. Essential gene profiles in breast, pancreatic, and ovarian cancer cells. Cancer Discov. 2, 172–189 (2012).

  40. 40.

    Walen, K. H. & Stampfer, M. R. Chromosome analyses of human mammary epithelial cells at stages of chemical-induced transformation progression to immortality. Cancer Genet. Cytogenet. 37, 249–261 (1989).

  41. 41.

    Treszezamsky, A. D. et al. BRCA1- and BRCA2-deficient cells are sensitive to etoposide-induced DNA double-strand breaks via topoisomerase II. Cancer Res. 67, 7078–7081 (2007).

  42. 42.

    Sanchez, Y. et al. Genome-wide analysis of the human p53 transcriptional network unveils a lncRNA tumour suppressor signature. Nat. Commun. 5, 5812 (2014).

  43. 43.

    Li, Y., Peart, M. J. & Prives, C. Stxbp4 regulates DeltaNp63 stability by suppression of RACK1-dependent degradation. Mol. Cell. Biol. 29, 3953–3963 (2009).

  44. 44.

    Sekine, Y. et al. The Kelch repeat protein KLHDC10 regulates oxidative stress-induced ASK1 activation by suppressing PP5. Mol. Cell 48, 692–704 (2012).

  45. 45.

    Kim, M. H. et al. Anaplastic lymphoma kinase gene copy number gain in inflammatory breast cancer (IBC): prevalence, clinicopathologic features and prognostic implication. PLoS One 10, e0120320 (2015).

  46. 46.

    Shaw, A.T. et al. Crizotinib versus chemotherapy in advanced ALK-positive lung cancer. N. Engl. J. Med. 368, 2385–2394 (2013).

  47. 47.

    Le Page, C. et al. BTN3A2 expression in epithelial ovarian cancer is associated with higher tumor infiltrating T cells and a better prognosis. PLoS One 7, e38541 (2012).

  48. 48.

    Kan, L. et al. LRRC3B is downregulated in non-small-cell lung cancer and inhibits cancer cell proliferation and invasion. Tumour Biol. 37, 1113–1120 (2016).

  49. 49.

    Cox, A. et al. A common coding variant in CASP8 is associated with breast cancer risk. Nat. Genet. 39, 352–358 (2007).

  50. 50.

    Yang, J. et al. Genomic inflation factors under polygenic inheritance. Eur. J. Hum. Genet. 19, 807–812 (2011).

  51. 51.

    Marouli, E. et al. Rare and low-frequency coding variants alter human adult height. Nature 542, 186–190 (2017).

  52. 52.

    Turcot, V. et al. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity. Nat. Genet. 50, 26–41 (2018).

  53. 53.

    Melé, M. et al. The human transcriptome across tissues and individuals. Science 348, 660–665 (2015).

  54. 54.

    The GTEx Consortium. The Genotype-Tissue Expression (GTEx) pilot analysis: multitissue gene regulation in humans. Science 348, 648–660 (2015).

  55. 55.

    McCarthy, S. et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat. Genet. 48, 1279–1283 (2016).

  56. 56.

    Delaneau, O., Marchini, J. & Zagury, J. F. A linear complexity phasing method for thousands of genomes. Nat. Methods 9, 179–181 (2012).

  57. 57.

    Howie, B. N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, e1000529 (2009).

  58. 58.

    DeLuca, D. S. et al. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics 28, 1530–1532 (2012).

  59. 59.

    Stegle, O., Parts, L., Piipari, M., Winn, J. & Durbin, R. Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses. Nat. Protoc. 7, 500–507 (2012).

  60. 60.

    Guo, X., Lin, M., Rockowitz, S., Lachman, H. M. & Zheng, D. Characterization of human pseudogene-derived non-coding RNAs for functional potential. PLoS One 9, e93972 (2014).

  61. 61.

    Casbas-Hernandez, P. et al. Tumor intrinsic subtype is reflected in cancer-adjacent tissue. Cancer Epidemiol. Biomark. Prev. 24, 406–414 (2015).

  62. 62.

    Huang, X., Stern, D. F. & Zhao, H. Transcriptional profiles from paired normal samples offer complementary information on cancer patient survival – Evidence from TCGA pan-cancer data. Sci. Rep. 6, 20567 (2016).

  63. 63.

    Ghoussaini, M. et al. Genome-wide association analysis identifies three new breast cancer susceptibility loci. Nat. Genet. 44, 312–318 (2012).

  64. 64.

    Garcia-Closas, M. et al. Genome-wide association studies identify four ER negative-specific breast cancer risk loci. Nat. Genet. 45, 392–398 (2013).

  65. 65.

    Devlin, B. & Roeder, K. Genomic control for association studies. Biometrics 55, 997–1004 (1999).

  66. 66.

    Freedman, M. L. et al. Assessing the impact of population stratification on genetic association studies. Nat. Genet. 36, 388–393 (2004).

  67. 67.

    Rao, S. S. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).

  68. 68.

    He, B., Chen, C., Teng, L. & Tan, K. Global view of enhancer-promoter interactome in human cells. Proc. Natl Acad. Sci. USA 111, E2191–E2199 (2014).

  69. 69.

    Corradin, O. et al. Combinatorial effects of multiple enhancer variants in linkage disequilibrium dictate levels of gene expression to confer susceptibility to common traits. Genome Res. 24, 1–13 (2014).

  70. 70.

    Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).

  71. 71.

    The FANTOM Consortium and the RIKEN PMI and CLST (DGT). A promoter-level mammalian expression atlas. Nature 507, 462–470 (2014).

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The authors thank J. He, W. Wen, A. Giri and T. Edwards of Vanderbilt Epidemiology Center and R. Tao of the Department of Biostatistics, Vanderbilt University Medical Center for their help with the data analysis of this study. The authors would also like to thank all of the individuals for their participation in the parent studies and all of the researchers, clinicians, technicians and administrative staff for their contribution to the studies. We are also grateful to H. K. Im of University of Chicago for her help. The data analyses were conducted using the Advanced Computing Center for Research and Education (ACCRE) at Vanderbilt University. This project at Vanderbilt University Medical Center was supported in part by grants R01CA158473 and R01CA148677 from the US National Institutes of Health as well as funds from Anne Potter Wilson endowment. L.W. is supported by NCI K99 CA218892 and the Vanderbilt Molecular and Genetic Epidemiology of Cancer (MAGEC) training program (US NCI grant R25 CA160056 awarded to X.-O.S.). Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project, funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Genome Québec and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and the Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (National Institutes of Health (NIH) grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCAC is funded by Cancer Research UK (C1287/A16563), by the European Community’s Seventh Framework Programme under grant agreement 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the ‘CIHR Team in Familial Risks of Breast Cancer’ program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec—grant no. PSR-SIIRI-701. Combining of the GWAS data was supported in part by the NIH Cancer Post-Cancer GWAS initiative grant U19 CA 148065 (DRIVE, part of the GAME-ON initiative). A full description of funding and acknowledgments for BCAC studies, along with consortium membership, are included in the Supplementary Note.

Author information

Author notes

  1. A list of NBCS Collaborators and kConFab/AOCS Investigators appears in the Supplementary Note.

  2. These authors contributed equally: Lang Wu, Wei Shi.


  1. Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA

    • Lang Wu
    • , Jirong Long
    • , Xingyi Guo
    • , Xiao-Ou Shu
    • , Yingchang Lu
    • , Qiuyin Cai
    • , Chenjie Zeng
    • , Martha J. Shrubsole
    •  & Wei Zheng
  2. Cancer Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia

    • Wei Shi
    • , Jonathan Beesley
    • , Fares Al-Ejeh
    • , Esdy Rozali
    • , Xiaoqing Chen
    • , Stacey L. Edwards
    •  & Georgia Chenevix-Trench
  3. Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

    • Kyriaki Michailidou
    • , Manjeet K. Bolla
    • , Qin Wang
    • , Joe Dennis
    • , Paul D. P. Pharoah
    •  & Douglas F. Easton
  4. Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus

    • Kyriaki Michailidou
  5. Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA

    • Bingshan Li
  6. Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    • Helian Feng
    • , Richard T. Barfield
    • , Rulla M. Tamimi
    •  & Peter Kraft
  7. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    • Helian Feng
    • , A. Heather Eliassen
    • , David J. Hunter
    • , JoAnn E. Manson
    • , Rulla M. Tamimi
    • , Walter C. Willett
    •  & Peter Kraft
  8. Department of Medical Oncology, Dana Farber Cancer Institute, Boston, MA, USA

    • Alexander Gusev
  9. Department of Medicine, Harvard Medical School, Boston, MA, USA

    • Alexander Gusev
  10. Division of Genetics, Brigham and Women’s Hospital, Boston, MA, USA

    • Alexander Gusev
  11. Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada

    • Irene L. Andrulis
  12. Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada

    • Irene L. Andrulis
  13. Department of Epidemiology, University of California Irvine, Irvine, CA, USA

    • Hoda Anton-Culver
    •  & Argyrios Ziogas
  14. Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Volker Arndt
    •  & Hermann Brenner
  15. Department of Public Health Sciences, and Cancer Research Institute, Queen’s University, Kingston, Ontario, Canada

    • Kristan J. Aronson
  16. Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    • Paul L. Auer
    •  & Ross Prentice
  17. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, USA

    • Paul L. Auer
  18. Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Myrto Barrdahl
    • , Jenny Chang-Claude
    • , Ursula Eilber
    • , Audrey Jung
    • , Rudolf Kaaks
    •  & Anja Rudolph
  19. Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK

    • Caroline Baynes
    • , Laura Fachal
    • , Maya Ghoussaini
    • , Patricia Harrington
    • , Craig Luccarini
    • , Valerie Rhenius
    • , Mitul Shah
    • , Alison M. Dunning
    • , Paul D. P. Pharoah
    •  & Douglas F. Easton
  20. Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany

    • Matthias W. Beckmann
    • , Peter A. Fasching
    • , Alexander Hein
    •  & Michael P. Lux
  21. Human Cancer Genetics Program, Spanish National Cancer Research Centre, Madrid, Spain

    • Javier Benitez
    •  & Anna González-Neira
  22. Centro de Investigación en Red de Enfermedades Raras (CIBERER), Valencia, Spain

    • Javier Benitez
  23. Institute of Biochemistry and Genetics, Ufa Scientific Center of Russian Academy of Sciences, Ufa, Russia

    • Marina Bermisheva
  24. Gynaecology Research Unit, Hannover Medical School, Hannover, Germany

    • Marina Bermisheva
    • , Natalia V. Bogdanova
    • , Thilo Dörk
    • , Peter Hillemanns
    •  & Ivana Maleva Kostovska
  25. Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland

    • Carl Blomqvist
  26. Department of Oncology, University of Örebro, Örebro, Sweden

    • Carl Blomqvist
  27. Department of Radiation Oncology, Hannover Medical School, Hannover, Germany

    • Natalia V. Bogdanova
    •  & Hans Christiansen
  28. N.N. Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus

    • Natalia V. Bogdanova
  29. Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark

    • Stig E. Bojesen
    • , Sune F. Nielsen
    •  & Børge G. Nordestgaard
  30. Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark

    • Stig E. Bojesen
    • , Sune F. Nielsen
    •  & Børge G. Nordestgaard
  31. Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

    • Stig E. Bojesen
    •  & Børge G. Nordestgaard
  32. Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany

    • Hiltrud Brauch
    •  & Wing-Yee Lo
  33. University of Tübingen, Tübingen, Germany

    • Hiltrud Brauch
    •  & Wing-Yee Lo
  34. German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Hiltrud Brauch
    •  & Hermann Brenner
  35. Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany

    • Hermann Brenner
  36. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA

    • Louise Brinton
    • , Jonine Figueroa
    • , Montserrat García-Closas
    • , Robert N. Hoover
    •  & Xiaohong R. Yang
  37. Department of Cancer Epidemiology, Clinical Sciences, Lund University, Lund, Sweden

    • Per Broberg
    •  & Håkan Olsson
  38. Department of Gynecology and Obstetrics, University of Tübingen, Tübingen, Germany

    • Sara Y. Brucker
  39. Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany

    • Barbara Burwinkel
    • , Andreas Schneeweiss
    •  & Harald Surowy
  40. Molecular Epidemiology Group, C080, German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Barbara Burwinkel
    •  & Harald Surowy
  41. Medical Oncology Department, CIBERONC Hospital Clínico San Carlos, Madrid, Spain

    • Trinidad Caldés
    •  & Atocha Romero
  42. Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Federico Canzian
  43. Epidemiology Research Program, American Cancer Society, Atlanta, GA, USA

    • Brian D. Carter
    • , Susan M. Gapstur
    •  & Mia M. Gaudet
  44. Oncology and Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain

    • J. Esteban Castelao
  45. University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany

    • Jenny Chang-Claude
    •  & Kathrin Thöne
  46. Department of Epidemiology, University of Florida, Gainesville, FL, USA

    • Ting-Yuan David Cheng
  47. Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia

    • Christine L. Clarke
  48. Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands

    • Margriet Collée
  49. Division of Molecular Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands

    • Sten Cornelissen
    •  & Marjanka K. Schmidt
  50. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA

    • Fergus J. Couch
    • , Julie M. Cunningham
    •  & Jeffery Meyer
  51. Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK

    • David Cox
  52. INSERM U1052, Cancer Research Center of Lyon, Lyon, France

    • David Cox
  53. Sheffield Institute for Nucleic Acids, Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK

    • Angela Cox
  54. Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK

    • Simon S. Cross
  55. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    • Kamila Czene
    • , Mikael Eriksson
    • , Marike Gabrielson
    • , Per Hall
    •  & Keith Humphreys
  56. Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA

    • Mary B. Daly
  57. Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands

    • Peter Devilee
  58. Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands

    • Peter Devilee
  59. Center for Inherited Disease Research (CIDR), Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    • Kimberly F. Doheny
    •  & Jane Romm
  60. Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK

    • Isabel dos-Santos-Silva
    •  & Julian Peto
  61. Genomics Center, Centre Hospitalier Universitaire de Québec – Université Laval Research Center, Québec City, QC, Canada

    • Martine Dumont
    •  & Jacques Simard
  62. Department of Biomedical Sciences, Faculty of Science and Technology, University of Westminster, London, UK

    • Miriam Dwek
    •  & Nadege Presneau
  63. Cancer Sciences Academic Unit, Faculty of Medicine, University of Southampton, Southampton, UK

    • Diana M. Eccles
    •  & William Tapper
  64. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    • A. Heather Eliassen
    • , Rulla M. Tamimi
    •  & Walter C. Willett
  65. Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany

    • Christoph Engel
  66. David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California at Los Angeles, Los Angeles, CA, USA

    • Peter A. Fasching
  67. Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh, UK

    • Jonine Figueroa
  68. Institute for Medical Biometrics and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

    • Dieter Flesch-Janys
  69. Department of Cancer Epidemiology, Clinical Cancer Registry, University Medical Center Hamburg-Eppendorf, Hamburg, Germany

    • Dieter Flesch-Janys
  70. The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK

    • Olivia Fletcher
    •  & Nichola Johnson
  71. Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark

    • Henrik Flyger
  72. School of Public Health, Curtin University, Perth, Western Australia, Australia

    • Lin Fritschi
  73. Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago De Compostela, Spain

    • Manuela Gago-Dominguez
  74. Moores Cancer Center, University of California San Diego, La Jolla, CA, USA

    • Manuela Gago-Dominguez
  75. Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, Victoria, Australia

    • Graham G. Giles
    • , Robert J. MacInnis
    •  & Roger L. Milne
  76. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia

    • Graham G. Giles
    • , John L. Hopper
    • , Robert J. MacInnis
    •  & Roger L. Milne
  77. Department of Medicine, McGill University, Montréal, Quebec, Canada

    • Mark S. Goldberg
  78. Division of Clinical Epidemiology, Royal Victoria Hospital, McGill University, Montréal, Quebec, Canada

    • Mark S. Goldberg
  79. Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT, USA

    • David E. Goldgar
  80. Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif, France

    • Pascal Guénel
    •  & Thérèse Truong
  81. Center for Hereditary Breast and Ovarian Cancer, University Hospital of Cologne, Cologne, Germany

    • Eric Hahnen
    •  & Rita K. Schmutzler
  82. Center for Integrated Oncology (CIO), University Hospital of Cologne, Cologne, Germany

    • Eric Hahnen
    •  & Rita K. Schmutzler
  83. Center for Molecular Medicine Cologne (CMMC), University of Cologne, Cologne, Germany

    • Eric Hahnen
    •  & Rita K. Schmutzler
  84. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA

    • Christopher A. Haiman
    • , David Van Den Berg
    •  & Lucy Xia
  85. Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

    • Niclas Håkansson
    •  & Alicja Wolk
  86. Department of Oncology, Södersjukhuset, Stockholm, Sweden

    • Per Hall
  87. Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA

    • Emily Hallberg
    • , Janet E. Olson
    • , Christopher G. Scott
    • , Abigail Thomas
    •  & Celine Vachon
  88. Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany

    • Ute Hamann
    • , Guanmengqian Huang
    •  & Diana Torres
  89. Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA

    • Belynda Hicks
    •  & Kristine Jones
  90. Department of Medical Oncology, Family Cancer Clinic, Erasmus MC Cancer Institute, Rotterdam, The Netherlands

    • Antoinette Hollestelle
    •  & Jan Lubinski
  91. Nuffield Department of Population Health, University of Oxford, Big Data Institute, Oxford, UK

    • David J. Hunter
  92. Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland

    • Anna Jakubowska
  93. Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland

    • Anna Jakubowska
  94. Department of Gynecology and Obstetrics, University Hospital Ulm, Ulm, Germany

    • Wolfgang Janni
    •  & Brigitte Rack
  95. Department of Epidemiology, Cancer Prevention Institute of California, Fremont, CA, USA

    • Esther M. John
  96. Department of Health Research and Policy - Epidemiology, Stanford University School of Medicine, Stanford, CA, USA

    • Esther M. John
    •  & Alice S. Whittemore
  97. Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA

    • Esther M. John
    • , Elza Khusnutdinova
    •  & Alice S. Whittemore
  98. Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK

    • Michael E. Jones
    •  & Anthony J. Swerdlow
  99. School of Medicine, National University of Ireland, Galway, Ireland

    • Michael J. Kerin
  100. Department of Genetics and Fundamental Medicine, Bashkir State University, Ufa, Russia

    • Elza Khusnutdinova
  101. Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland

    • Veli-Matti Kosma
    •  & Arto Mannermaa
  102. Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland

    • Veli-Matti Kosma
    •  & Arto Mannermaa
  103. Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland

    • Veli-Matti Kosma
    •  & Arto Mannermaa
  104. Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway

    • Vessela N. Kristensen
  105. Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway

    • Vessela N. Kristensen
  106. Department of Clinical Molecular Biology, Oslo University Hospital, University of Oslo, Oslo, Norway

    • Vessela N. Kristensen
  107. VIB KULeuven Center for Cancer Biology, VIB, Leuven, Belgium

    • Diether Lambrechts
  108. Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium

    • Diether Lambrechts
  109. Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA

    • Loic Le Marchand
  110. Human Genetics, Genome Institute of Singapore, Singapore, Singapore

    • Jingmei Li
  111. Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA

    • Sara Lindström
  112. Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    • Sara Lindström
  113. Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Institute - Oncology Center, Warsaw, Poland

    • Jolanta Lissowska
  114. German Breast Group, GmbH, Neu Isenburg, Germany

    • Sibylle Loibl
  115. Southampton Clinical Trials Unit, University of Southampton, Southampton, UK

    • Tom Maishman
  116. Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov”, Macedonian Academy of Sciences and Arts, Skopje, Macedonia

    • Ivana Maleva Kostovska
    •  & Dijana Plaseska-Karanfilska
  117. Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    • JoAnn E. Manson
  118. Department of Oncology - Pathology, Karolinska Institutet, Stockholm, Sweden

    • Sara Margolin
    •  & Camilla Wendt
  119. Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece

    • Dimitrios Mavroudis
  120. Department of Clinical Genetics, VU University Medical Center, Amsterdam, The Netherlands

    • Hanne Meijers-Heijboer
  121. Division of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany

    • Alfons Meindl
  122. Gynaecological Cancer Research Centre, Women’s Cancer, Institute for Women’s Health, University College London, London, UK

    • Usha Menon
  123. Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada

    • Anna Marie Mulligan
  124. Laboratory Medicine Program, University Health Network, Toronto, Ontario, Canada

    • Anna Marie Mulligan
  125. Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA

    • Susan L. Neuhausen
  126. Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland

    • Heli Nevanlinna
  127. Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium

    • Patrick Neven
    • , Ann Smeets
    •  & Hans Wildiers
  128. Center for Clinical Cancer Genetics and Global Health, The University of Chicago, Chicago, IL, USA

    • Olufunmilayo I. Olopade
  129. IFOM, The FIRC (Italian Foundation for Cancer Research) Institute of Molecular Oncology, Milan, Italy

    • Paolo Peterlongo
  130. Laboratory of Cancer Genetics and Tumor Biology, Cancer and Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland

    • Katri Pylkäs
    •  & Robert Winqvist
  131. Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland

    • Katri Pylkäs
    • , Quinten Waisfisz
    •  & Robert Winqvist
  132. Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Istituto Nazionale dei Tumori (INT), Milan, Italy

    • Paolo Radice
  133. Section of Cancer Genetics, The Institute of Cancer Research, London, UK

    • Nazneen Rahman
    •  & Sheila Seal
  134. Department of Community Medicine and Epidemiology, Carmel Medical Center, Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology and Clalit National Cancer Control Center, Haifa, Israel

    • Gad Rennert
    •  & Hedy S. Rennert
  135. Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid, Spain

    • Atocha Romero
  136. Hereditary Cancer Clinic, University Hospital of Heraklion, Heraklion, Greece

    • Emmanouil Saloustros
  137. Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA

    • Dale P. Sandler
    •  & Jack A. Taylor
  138. Research Oncology, Guy’s Hospital, King’s College London, London, UK

    • Elinor J. Sawyer
  139. Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam, The Netherlands

    • Marjanka K. Schmidt
  140. National Center for Tumor Diseases, University of Heidelberg, Heidelberg, Germany

    • Andreas Schneeweiss
  141. Division of Molecular Medicine, Pathology North, John Hunter Hospital, Newcastle, New South Wales, Australia

    • Rodney J. Scott
  142. Discipline of Medical Genetics, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, New South Wales, Australia

    • Rodney J. Scott
  143. Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia

    • Melissa C. Southey
  144. Cancer Control Research, BC Cancer Agency, Vancouver, British Columbia, Canada

    • John J. Spinelli
  145. School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada

    • John J. Spinelli
  146. The Curtin UWA Centre for Genetic Origins of Health and Disease, Curtin University and University of Western Australia, Perth, Western Australia, Australia

    • Jennifer Stone
  147. Department of Obstetrics and Gynaecology, University of Melbourne and the Royal Women’s Hospital, Melbourne, Victoria, Australia

    • Jennifer Stone
  148. Division of Breast Cancer Research, The Institute of Cancer Research, London, UK

    • Anthony J. Swerdlow
  149. Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA

    • Jack A. Taylor
  150. Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA

    • Mary Beth Terry
  151. McGill University and Génome Québec Innovation Centre, Montréal, Quebec, Canada

    • Daniel C. Tessier
    •  & Daniel Vincent
  152. Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands

    • Rob A. E. M. Tollenaar
  153. Institute of Human Genetics, Pontificia Universidad Javeriana, Bogota, Colombia

    • Diana Torres
  154. Department of Gynecology and Obstetrics, Helios Clinics Berlin-Buch, Berlin, Germany

    • Michael Untch
  155. Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA

    • Clarice R. Weinberg
  156. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    • Walter C. Willett
  157. Department of Medicine, Institute for Human Genetics, UCSF Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, CA, USA

    • Elad Ziv


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  1. NBCS Collaborators

    1. kConFab/AOCS Investigators


      W.Z. and J. Long conceived the study. L.W. contributed to the study design and performed statistical analyses. L.W., W.Z. and G.C.-T. wrote the manuscript with significant contributions from W.S., J. Long, X.G. and S.L.E. W.S. performed the in vitro experiments. G.C.-T. directed the in vitro experiments. X.G. contributed to the model building and pathway analyses. J.B. contributed to the bioinformatics analyses. F.A.-E., E.R. and S.L.E. contributed to the in vitro experiments. Y.L. and C.Z. contributed to the model building. K.M., M.K.B., X.-O.S., Q.W., J.D., B.L., C.Z., H.F., A.G., R.T.B., A.M.D., P.D.P.P., J.S., R.L.M., P.K. and D.F.E. contributed to manuscript revision, statistical analyses and/or BCAC data management. I.L.A., H.A.-C., V.A., K.J.A., P.L.A., M. Barrdahl, C.B., M.W.B., J.B., M. Bermisheva, C.B., N.V.B., S.E.B., H. Brauch, H. Brenner, L.B., P.B., S.Y.B., B.B., Q.C., T.C., F.C., B.D.C., J.E.C., J.C.-C., X.C., T.-Y.D.C., H.C., C.L.C., NBCS Collaborators, M.C., S.C., F.J.C., D.C., A.C., S.S.C., J.M.C., K.C., M.B.D., P.D., K.F.D., T.D., I.d.S.S., M. Dumont, M. Dwek, D.M.E., U.E., H.E., C.E., M.E., L.F., P.A.F., J.F., D.F.-J., O.F., H.F., L.F., M. Gabrielson, M.G.-D., S.M.G., M.G.-C., M.M.G., M. Ghoussaini, G.G.G., M.S.G., D.E.G., A.G.-N., P.G., E. Hahnen, C.A.H., N.H., P. Hall, E. Hallberg, U.H., P. Harrington, A. Hein, B.H., P. Hillemanns, A. Hollestelle, R.N.H., J.L.H., G.H., K.H., D.J.H., A.J., W.J., E.M.J., N.J., K.J., M.E.J., A. Jung, R.K., M.J.K., E.K., V.-M.K., V.N.K., D.L., L.L.M., J. Li, S.L., J. Lissowska, W.-Y.L., S. Loibl, J. Lubinski, C.L., M.P.L., R.J.M., T.M., I.M.K., A. Mannermaa, J.E.M., S.M., D.M., H.M.-H., A. Meindl, U.M., J.M., A.M.M., S.L.N., H.N., P.N., S.F.N., B.G.N., O.I.O., J.E.O., H.O., P.P., J.P., D.P.-K., R.P., N.P., K.P., B.R., P.R., N.R., G.R., H.S.R., V.R., A. Romero, J.R., A. Rudolph, E.S., D.P.S., E.J.S., M.K.S., R.K.S., A.S., R.J.S., C.G.S., S.S., M.S., M.J.S., A.S., M.C.S., J.J.S., J.S., H.S., A.J.S., R.T., W.T., J.A.T., M.B.T., D.C.T., A.T., K.T., R.A.E.M.T., D.T., T.T., M.U., C.V., D.V.D.B., D.V., Q.W., C.R.W., C.W., A.S.W., H.W., W.C.W., R.W., A.W., L.X., X.R.Y., A.Z., E.Z. and kConFab/AOCS Investigators contributed to the collection of the data and biological samples for the original BCAC studies. All authors have reviewed and approved the final manuscript.

      Competing interests

      The authors declare no competing interests.

      Corresponding authors

      Correspondence to Georgia Chenevix-Trench or Wei Zheng.

      Integrated Supplementary Information

      1. Supplementary Figure 1

        Study design flow chart

      2. Supplementary Figure 2 Performance of expression prediction models in GTEx and TCGA datasets for genes with at least 10% correlation in GTEx data.

        The x axis represents the prediction performance (R2) in the GTEx dataset (n = 67). The y axis represents the prediction performance in the TCGA dataset (n = 86). Each dot represents the expression prediction model for one gene. There is a trend that genes with high internal prediction performance in GTEx data also have high external prediction performance in TCGA data (Pearson's correlation coefficient: 0.55).

      3. Supplementary Figure 3 Quantile–quantile plots.

        a, Quantile–quantile plot of P values in –log scale of associations between the genetically predicted expression levels of 8,597 genes and breast cancer risk. b, Quantile–quantile plot of P values in –log scale of associations between all 11.8 million SNPs and breast cancer risk in BCAC. c, Quantile–quantile plot of P values in –log scale of associations between the over 250,000 SNPs predicting expression levels of the 8,597 genes and breast cancer risk in BCAC.

      4. Supplementary Figure 4 Heatmap of log fold change (FC) of selected genes normalized to expression levels in 184A1 breast cells.

        Two or three primer sets were designed for each gene (y axis), and mRNA levels were quantified by qPCR in the indicated cells lines (x axis), including 184A1. The FC of genes normalized to that in 184A1 equals the mRNA level in the indicated cells divided by the mRNA level in 184A1. The log2 (FC) over 184A1 is depicted as a heatmap. An X represents ‘not detectable’ with all primer sets. The experiment was repeated independently twice with similar results.

      5. Supplementary Figure 5 Validation of knockdown.

        184A1, MCF7 and T47D cells, transfected with the indicated siRNAs, were harvested after 36 h for qPCR analysis to assess knockdown efficiency. The fold changes over NTCsi-transfected parental cells are plotted. The experiment was repeated three times independently with similar results.

      6. Supplementary Figure 6 Proliferation in breast cells using two independent siRNAs.

        ac, 184A1 (a), MCF7 (b) and T47D (c) cells were transfected with the indicated siRNAs over 7 d, and phase-contrast images were collected using an IncuCyte ZOOM. Each cell proliferation time course was normalized to the baseline confluency and analyzed in GraphPad Prism. Corrected proliferation % = 100 ± (relative proliferation in indicated siRNA – proliferation in control siRNA (consi))/knockdown efficiency. Related to Fig. 2a.

      7. Supplementary Figure 7 Colony formation efficiency in MCF7 cells using two independent siRNAs.

        MCF7 cells were transfected with the indicated siRNAs and then reseeded after 16 h for colony formation (CF) assays. At day 14, colonies were fixed with methanol, stained with crystal violet, scanned and batch analyzed by ImageJ. Corrected CF efficiency (CFE) % = 100 ± (relative CFE in indicated siRNA – CFE in control siRNA (consi))/knockdown efficiency. Error bars, s.d. (n = 4). P values were determined by one-way ANOVA followed by Dunnett’s multiple-comparisons test: *P < 0.05. Related to Fig. 2b.

      8. Supplementary Figure 8 Power calculation of the TWAS analysis.

        The simulation analysis is based on 122,977 cases and 105,974 controls. Gene expression was generated from the empirical distribution of predicted gene expression levels in the BCAC. Statistical power was calculated at P < 5.82 × 10–6 (the significance level used in the main TWAS analyses) according for cis-heritability (h2), which we aim to capture using gene expression prediction models (R2). The figure shows results per 1 s.d. increase (or decrease) in the gene expression based on 1,000 replicates.

      Supplementary information

      1. Supplementary Text and Figures

        Supplementary Figures 1–8, Supplementary Tables 1, 5, 6, 8–11 and 13, and Supplementary Note

      2. Reporting Summary

      3. Supplementary Tables

        Supplementary Tables 2–4, 7 and 12

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