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Multiple regions within 8q24 independently affect risk for prostate cancer

Nature Genetics volume 39, pages 638–644 (2007)Cite this article

Abstract

After the recent discovery that common genetic variation in 8q24 influences inherited risk of prostate cancer, we genotyped 2,973 SNPs in up to 7,518 men with and without prostate cancer from five populations. We identified seven risk variants, five of them previously undescribed, spanning 430 kb and each independently predicting risk for prostate cancer (P = 7.9 × 10−19 for the strongest association, and P < 1.5 × 10−4 for five of the variants, after controlling for each of the others). The variants define common genotypes that span a more than fivefold range of susceptibility to cancer in some populations. None of the prostate cancer risk variants aligns to a known gene or alters the coding sequence of an encoded protein.

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Figure 1: Results of fine-mapping across the admixture peak, spanning the region 125.6–129.4 Mb defined in ref. 1.
Figure 2: Case-control association statistics by logistic regression for the 186 alleles for which we collected data in all five populations and are in the region 128.1–128.7 Mb.
Figure 3: The distributions of relative risks for prostate cancer in each of the populations, compared with the baseline relative risk (relative risk = 1) for individuals who do not carry any of the risk alleles at the seven markers we identified.

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Acknowledgements

We thank the men with and without prostate cancer who volunteered to participate in this study. We thank E. Lander, A. Price, J. Seidman and E. Ziv for critical comments and researchers from the NCI Cancer Genetic Markers of Susceptibility Study (CGEMS) Project, whose online data we cited to provide confirmation of the association at rs6983267. Genotyping and personnel were supported by NIH grants CA63464 to B.E.H., C.A.H., D.A., M.L.F. and D.R. and by funds from the Harvard Medical School Department of Genetics (D.R.). M.L.F. was supported by a Department of Defense Health Disparity Training-Prostate Scholar Award (17-02-1-0246) and Dana-Farber/Harvard Partners Cancer Care Prostate SPORE. N.P. was supported by NIH career transition award HG02758. S.C.G. is a Hospital for Sick Children and March of Dimes Fellow of the Pediatric Scientist Development Program, and is also supported by NICHD grant HD00850. C.A.H., D.O.S., M.C.P., L.L.M., L.N.K. and B.E.H. were supported by CA54281, E.M.J. and S.A.I. were supported by California Cancer Research Program Grants 99-00527V-10182 and 99-00524V-10258; S.A.I. was also supported by NIH grant CA84979. The Flint Men's Health Study was supported by the University of Michigan SPORE in Prostate Cancer (CA69568), the University of Michigan Department of Urology and the University of Michigan Comprehensive Cancer Center. K.A.C. was supported by grants CA69568 and CA79596, and I.O.G. and A.S.W. were supported by CA67044. D.A. is a Charles E. Culpeper Scholar of the Rockefeller Brothers Fund and a Burroughs Wellcome Fund Clinical Scholar in Translational Research. D.R. is supported by a Burroughs-Wellcome Career Development Award in the Biomedical Sciences.

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Authors and Affiliations

  1. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, 90089, California, USA

    Christopher A Haiman, Malcolm C Pike, Daniel O Stram, Melissa Frasco, David Wong, Loreall C Pooler, Sue A Ingles & Brian E Henderson

  2. Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, 02142, Massachusetts, USA

    Nick Patterson, Matthew L Freedman, Simon R Myers, Alicja Waliszewska, Julie Neubauer, Arti Tandon, Christine Schirmer, Gavin J McDonald, Kristin Ardlie, David Altshuler & David Reich

  3. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, 02115, Massachusetts, USA

    Matthew L Freedman

  4. Department of Genetics, Harvard Medical School, Boston, 02115, Massachusetts, USA

    Alicja Waliszewska, Julie Neubauer, Arti Tandon, Christine Schirmer, Gavin J McDonald, Steven C Greenway, David Altshuler & David Reich

  5. Laboratory of Molecular Immunology, Center for Neurologic Disease, Brigham and Women's Hospital, Boston, 02115, Massachusetts, USA

    Alicja Waliszewska

  6. Epidemiology Program, Cancer Research Center of Hawaii, University of Hawaii, Honolulu, 96813, Hawaii, USA

    Loic Le Marchand & Laurence N Kolonel

  7. Division of SeraCare Life Sciences Inc, Genomics Collaborative, Cambridge, 02139, Massachusetts, USA

    Kristin Ardlie

  8. Northern California Cancer Center, Fremont, 94538, California, USA

    Ingrid Oakley-Girvan & Esther M John

  9. Department of Health Research and Policy, Stanford University School of Medicine, Stanford, 94305, California, USA

    Ingrid Oakley-Girvan, Alice S Whittemore & Esther M John

  10. Departments of Medicine and Urology, University of Michigan, Ann Arbor, Michigan 48109, USA.,

    Kathleen A Cooney

  11. University of Michigan Comprehensive Cancer Center, Ann Arbor, 48109, Michigan, USA

    Kathleen A Cooney

  12. Department of Medicine, Harvard Medical School, Boston, 02115, Massachusetts, USA

    David Altshuler

  13. Center for Human Genetic Research and Department of Molecular Biology, Massachusetts General Hospital, Boston, 02114, Massachusetts, USA

    David Altshuler

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  1. Christopher A Haiman
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Corresponding author

Correspondence to David Reich.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Fig. 1

Proportion of genetic variation in HapMap samples captured by genotyping at 8q24. (PDF 56 kb)

Supplementary Fig. 2

Linkage disequilibrium scans across 8q24 for each of five populations. (PDF 477 kb)

Supplementary Fig. 3

Outlier removal and ancestry estimates. (PDF 114 kb)

Supplementary Table 1

Whole-genome admixture scan. (XLS 618 kb)

Supplementary Table 2

Linkage disequilibrium scan in five populations across the admixture peak. (XLS 2069 kb)

Supplementary Table 3

Phenotype and genotype data for each sample. (XLS 5846 kb)

Supplementary Table 4

Genotype data for 547 newly characterized polymorphisms in HapMap samples. (XLS 872 kb)

Supplementary Table 5

Linkage disequilibrium patterns among key polymorphisms in regions 1–3. (PDF 60 kb)

Supplementary Table 6

Recalculation of Table 2 for prospectively collected multiethnic cohort samples. (PDF 22 kb)

Supplementary Table 7

No evidence for epistatic interactions or nonmultiplicative effects among polymorphisms. (PDF 22 kb)

Supplementary Table 8

Association of variants to specific phenotypes of prostate cancer. (PDF 69 kb)

Supplementary Table 9

Polymorphisms used for outlier removal and ancestry estimates. (XLS 44 kb)

Supplementary Methods (PDF 78 kb)

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Haiman, C., Patterson, N., Freedman, M. et al. Multiple regions within 8q24 independently affect risk for prostate cancer. Nat Genet 39, 638–644 (2007). https://doi.org/10.1038/ng2015

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