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Common variants in ZNF365 are associated with both mammographic density and breast cancer risk

Nature Genetics volume 43, pages 185–187 (2011)Cite this article

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Abstract

High-percent mammographic density adjusted for age and body mass index is one of the strongest risk factors for breast cancer. We conducted a meta analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P = 9.6 × 10−10). Common variants in ZNF365 have also recently been associated with susceptibility to breast cancer.

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Figure 1: Regional association plot for ZNF365 across a 300-kb window.

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Acknowledgements

This study was supported by Public Health Service Grants CA131332, CA087969, CA049449, CA128931, CA116201, CA075016, CA122340 and CA089393 from the National Cancer Institute, National Institutes of Health, Department of Health and Human Services and Breast Cancer Research Fund. The Nurses' Health Study (NHS) breast cancer cases and controls were genotyped with support from the National Cancer Institute's Cancer Markers of Susceptibility (CGEMS) initiative. Data evaluation of mammograms and analysis of the EPIC-Norfolk and SIBS studies was supported by Cancer Research UK. The SASBAC study was supported by Märit and Hans Rausing's Initiative against Breast Cancer, National Institutes of Health, Susan Komen Foundation and Agency for Science, Technology and Research of Singapore (A*STAR). Genotyping in the TORONTO/MELBOURNE subjects was supported by the Campbell Family Institute for Breast Cancer Research. Support was also provided by the Ontario Ministry of Health and Long Term Care.

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Authors and Affiliations

  1. Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA

    Sara Lindström, Aditi Hazra, David J Hunter & Peter Kraft

  2. Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA

    Sara Lindström, Susan E Hankinson, Aditi Hazra, David J Hunter, Peter Kraft & Rulla M Tamimi

  3. Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA

    Celine M Vachon, Christopher G Scott & V Shane Pankratz

  4. Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden

    Jingmei Li, Louise Eriksson, Kamila Czene & Per Hall

  5. Human Genetics, Genome Institute of Singapore, Singapore

    Jingmei Li & JianJun Liu

  6. Department of Public Health and Primary Care, Centre for Genetic Epidemiology, University of Cambridge, Cambridge, UK

    Jajini Varghese, Deborah Thompson, Judith Brown, Jean Leyland, Tina Audley & Douglas F Easton

  7. Department of Radiology, Addenbrookes Hospital, Cambridge, UK

    Ruth Warren

  8. Medical Research Council (MRC) Epidemiology Unit, Cambridge, UK

    Nicholas J Wareham & Ruth J F Loos

  9. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

    Andrew D Paterson

  10. Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada

    Andrew D Paterson & Johanna Rommens

  11. Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada

    Darryl Waggott

  12. Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada

    Lisa J Martin & Norman F Boyd

  13. Department of Medicine, Channing Laboratory, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA

    Susan E Hankinson, Aditi Hazra, David J Hunter & Rulla M Tamimi

  14. Centre for Molecular, Environmental, Genetic and Analytic Epidemiology School of Population Health, The University of Melbourne, Melbourne, Australia

    John L Hopper, Jennifer Stone & Carmel Apicella

  15. Department of Pathology, Genetic Epidemiology Laboratory, The University of Melbourne, Melbourne, Australia

    Melissa C Southey

  16. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA

    Stephen J Chanock

  17. Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK

    Isabel dos Santos Silva

  18. Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA

    Fergus J Couch

  19. Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA

    Peter Kraft

Authors
  1. Sara Lindström
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  2. Celine M Vachon
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  3. Jingmei Li
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  4. Jajini Varghese
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  5. Deborah Thompson
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  6. Ruth Warren
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  7. Judith Brown
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  8. Jean Leyland
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  9. Tina Audley
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  10. Nicholas J Wareham
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  11. Ruth J F Loos
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  12. Andrew D Paterson
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  13. Johanna Rommens
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  14. Darryl Waggott
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  15. Lisa J Martin
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  16. Christopher G Scott
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  17. V Shane Pankratz
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  18. Susan E Hankinson
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  19. Aditi Hazra
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  20. David J Hunter
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  21. John L Hopper
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  22. Melissa C Southey
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  23. Stephen J Chanock
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  24. Isabel dos Santos Silva
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  25. JianJun Liu
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  26. Louise Eriksson
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  27. Fergus J Couch
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  28. Jennifer Stone
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  29. Carmel Apicella
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  30. Kamila Czene
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  31. Peter Kraft
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  32. Per Hall
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  33. Douglas F Easton
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  34. Norman F Boyd
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  35. Rulla M Tamimi
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Contributions

S.L., C.M.V., J.L.H., P.K., P.H., D.F.E., N.F.B. and R.M.T. designed and executed the study. S.L., J. Li, J.V., A.D.P., D.W., C.G.S., V.S.P., J.S., K.C. and P.K. led the statistical analysis. C.M.V., D.T., R.W., J.B., J. Leyland, T.A., N.J.W., R.J.F.L., A.D.P., L.J.M., S.E.H., A.H., D.J.H., J.L.H., M.C.S., S.J.C., I.d.S.S., J. Liu, L.E., F.J.C., C.A., K.C., P.H., D.F.E., N.F.B. and R.M.T. collected and provided data to the initial GWAS analysis and replication studies. S.L., C.M.V., J. Li, D.T., R.J.F.L., J.L.H., J.S., D.F.E. and R.M.T. wrote the manuscript with contributions from all the authors.

Corresponding author

Correspondence to Rulla M Tamimi.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

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Supplementary Figures 1 and 2, Supplementary Tables 1–6 and Supplementary Methods (PDF 369 kb)

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Lindström, S., Vachon, C., Li, J. et al. Common variants in ZNF365 are associated with both mammographic density and breast cancer risk. Nat Genet 43, 185–187 (2011). https://doi.org/10.1038/ng.760

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