To identify variants for multiple myeloma risk, we conducted a genome-wide association study with validation in additional series totaling 4,692 individuals with multiple myeloma (cases) and 10,990 controls. We identified four risk loci at 3q26.2 (rs10936599, P = 8.70 × 10−14), 6p21.33 (rs2285803, PSORS1C2, P = 9.67 × 10−11), 17p11.2 (rs4273077, TNFRSF13B, P = 7.67 × 10−9) and 22q13.1 (rs877529, CBX7, P = 7.63 × 10−16). These data provide further evidence for genetic susceptibility to this B-cell hematological malignancy, as well as insight into the biological basis of predisposition.

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  1. 1.

    & Multiple myeloma. N. Engl. J. Med. 351, 1860–1873 (2004).

  2. 2.

    & Multiple myeloma. N. Engl. J. Med. 364, 1046–1060 (2011).

  3. 3.

    et al. Common variation at 3p22.1 and 7p15.3 influences multiple myeloma risk. Nat. Genet. 44, 58–61 (2012).

  4. 4.

    et al. The CCND1 G870A polymorphism is a risk factor for t(11;14)(q13;q32) multiple myeloma. Nat. Genet. 45, 522–525 (2013).

  5. 5.

    et al. Assessment of clinically silent atherosclerotic disease and established and novel risk factors for predicting myocardial infarction and cardiac death in healthy middle-aged subjects: rationale and design of the Heinz Nixdorf RECALL Study. Risk factors, evaluation of coronary calcium and lifestyle. Am. Heart J. 144, 212–218 (2002).

  6. 6.

    et al. First-line treatment with zoledronic acid as compared with clodronic acid in multiple myeloma (MRC Myeloma IX): a randomised controlled trial. Lancet 376, 1989–1999 (2010).

  7. 7.

    & Cohort profile: 1958 British birth cohort (National Child Development Study). Int. J. Epidemiol. 35, 34–41 (2006).

  8. 8.

    et al. Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat. Genet. 37, 1243–1246 (2005).

  9. 9.

    et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

  10. 10.

    Meta-analysis decision analysis and cost-effectivness analysis. Oxford University Press (1994).

  11. 11.

    et al. Meta-analysis of three genome-wide association studies identifies susceptibility loci for colorectal cancer at 1q41, 3q26.2, 12q13.13 and 20q13.33. Nat. Genet. 42, 973–977 (2010).

  12. 12.

    et al. TERC polymorphisms are associated both with susceptibility to colorectal cancer and with longer telomeres. Gut 61, 248–254 (2012).

  13. 13.

    et al. Genetic variants at 6p21.33 are associated with susceptibility to follicular lymphoma. Nat. Genet. 41, 873–875 (2009).

  14. 14.

    et al. Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32. Nat. Genet. 42, 661–664 (2010).

  15. 15.

    et al. GWAS of follicular lymphoma reveals allelic heterogeneity at 6p21.32 and suggests shared genetic susceptibility with diffuse large B-cell lymphoma. PLoS Genet. 7, e1001378 (2011).

  16. 16.

    et al. A genome-wide association study of Hodgkin's lymphoma identifies new susceptibility loci at 2p16.1 (REL), 8q24.21 and 10p14 (GATA3). Nat. Genet. 42, 1126–1130 (2010).

  17. 17.

    , & A statistical method for predicting classical HLA alleles from SNP data. Am. J. Hum. Genet. 82, 48–56 (2008).

  18. 18.

    , , & HLA*IMP—an integrated framework for imputing classical HLA alleles from SNP genotypes. Bioinformatics 27, 968–972 (2011).

  19. 19.

    et al. TACI-Ig neutralizes molecules critical for B cell development and autoimmune disease. Impaired B cell maturation in mice lacking BLyS. Immunity 15, 289–302 (2001).

  20. 20.

    et al. Genome-wide association study identifies common variants at TNFRSF13B associated with IgG level in a healthy Chinese male population. Genes Immun. 13, 509–513 (2012).

  21. 21.

    et al. Loss of TACI causes fatal lymphoproliferation and autoimmunity, establishing TACI as an inhibitory BLyS receptor. Immunity 18, 279–288 (2003).

  22. 22.

    et al. The level of TACI gene expression in myeloma cells is associated with a signature of microenvironment dependence versus a plasmablastic signature. Blood 106, 1021–1030 (2005).

  23. 23.

    et al. Atacicept (TACI-Ig) inhibits growth of TACIhigh primary myeloma cells in SCID-hu mice and in coculture with osteoclasts. Leukemia 22, 406–413 (2008).

  24. 24.

    , & Role of polycomb group proteins in stem cell self-renewal and cancer. DNA Cell Biol. 24, 117–125 (2005).

  25. 25.

    , & Long noncoding RNA, polycomb, and the ghosts haunting INK4b-ARF-INK4a expression. Cancer Res. 71, 5365–5369 (2011).

  26. 26.

    et al. Role of the chromobox protein CBX7 in lymphomagenesis. Proc. Natl. Acad. Sci. USA 104, 5389–5394 (2007).

  27. 27.

    et al. Integration of global SNP-based mapping and expression arrays reveals key regions, mechanisms, and genes important in the pathogenesis of multiple myeloma. Blood 108, 1733–1743 (2006).

  28. 28.

    et al. The architecture of gene regulatory variation across multiple human tissues: the MuTHER study. PLoS Genet. 7, e1002003 (2011).

  29. 29.

    et al. Patterns of cis regulatory variation in diverse human populations. PLoS Genet. 8, e1002639 (2012).

  30. 30.

    et al. Common regulatory variation impacts gene expression in a cell type–dependent manner. Science 325, 1246–1250 (2009).

  31. 31.

    & Discovery and characterization of chromatin states for systematic annotation of the human genome. Nat. Biotechnol. 28, 817–825 (2010).

  32. 32.

    , , & The clinical significance of cytogenetic studies in 100 patients with multiple myeloma, plasma cell leukemia, or amyloidosis. Blood 66, 380–390 (1985).

  33. 33.

    et al. Chromosome abnormalities clustering and its implications for pathogenesis and prognosis in myeloma. Leukemia 17, 427–436 (2003).

  34. 34.

    et al. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia 23, 2210–2221 (2009).

  35. 35.

    et al. A compendium of myeloma-associated chromosomal copy number abnormalities and their prognostic value. Blood 116, e56–e65 (2010).

  36. 36.

    , & Identification of low penetrance alleles for lung cancer: the GEnetic Lung CAncer Predisposition Study (GELCAPS). BMC Cancer 8, 244 (2008).

  37. 37.

    et al. National study of colorectal cancer genetics. Br. J. Cancer 97, 1305–1309 (2007).

  38. 38.

    et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).

  39. 39.

    & Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558 (2002).

  40. 40.

    , & 'Racial' differences in genetic effects for complex diseases. Nat. Genet. 36, 1312–1318 (2004).

  41. 41.

    , & METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).

  42. 42.

    , , , & Familial risks and temporal incidence trends of multiple myeloma. Eur. J. Cancer 42, 1661–1670 (2006).

  43. 43.

    , , , & A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39, 906–913 (2007).

  44. 44.

    , , , & A fine-scale map of recombination rates and hotspots across the human genome. Science 310, 321–324 (2005).

  45. 45.

    et al. The structure of haplotype blocks in the human genome. Science 296, 2225–2229 (2002).

  46. 46.

    et al. Deletion of chromosome 13 detected by conventional cytogenetics is a critical prognostic factor in myeloma. Leukemia 20, 1610–1617 (2006).

  47. 47.

    et al. Combining information regarding chromosomal aberrations t(4;14) and del(17p13) with the International Staging System classification allows stratification of myeloma patients undergoing autologous stem cell transplantation. Haematologica 95, 1150–1157 (2010).

  48. 48.

    et al. Genome-wide associations of gene expression variation in humans. PLoS Genet. 1, e78 (2005).

  49. 49.

    et al. Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science 315, 848–853 (2007).

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Leukaemia Lymphoma Research and Myeloma UK provided principal funding for this study in the UK. Additional funding was provided by Cancer Research UK (C1298/A8362 supported by the Bobby Moore Fund) and the NHS through the Biological Research Centre of the National Institute for Health Research at the Royal Marsden Hospital NHS Trust. This study made use of genotyping data from the 1958 Birth Cohort. Genotyping data on controls were generated by the Wellcome Trust Sanger Institute. A full list of the investigators who contributed to the generation of the data is available at http://www.wtccc.org.uk. In Germany (Heidelberg), funding was provided to Dietmar-Hopp-Stiftung Walldorf, the University Hospital Heidelberg, Deutsche Krebshilfe and the Systems Medicine funding from the German Ministry of Education and Science. We are grateful to all investigators who contributed to the National Study of Colorectal Cancer Genetics (NSCCG) and the Genetic Lung Cancer Predisposition Study (GELCAPS), from which controls in the replication were drawn. The GWAS made use of genotyping data from the population-based HNR study. The HNR study is supported by the Heinz Nixdorf Foundation (Germany). Additionally, the study is funded by the German Ministry of Education and Science and the German Research Council (DFG; projects SI 236/8-1, SI236/9-1, ER 155/6-1 and DFG CRU 216). Funding was provided to L.E. by the Medical Faculty of the University Hospital of Essen (IFORES). The genotyping of the Illumina HumanOmni-1 Quad BeadChips of the HNR subjects was financed by DZNE, Bonn. We are extremely grateful to all investigators who contributed to the generation of this data set. The German replication controls were collected by P. Bugert, Institute of Transfusion Medicine and Immunology, Medical Faculty Mannheim, Heidelberg University, German Red Cross Blood Service of Baden-Württemberg-Hessen, Mannheim, Germany. We are grateful to all the patients and investigators at the individual centers for their participation. We also thank the staff of the Clinical Trials Research Unit University of Leeds and the National Cancer Research Institute Haematology Clinical Studies Group.

Author information

Author notes

    • Daniel Chubb
    •  & Niels Weinhold

    These authors contributed equally to this work.

    • Gareth J Morgan
    • , Kari Hemminki
    • , Richard S Houlston
    •  & Hartmut Goldschmidt

    These authors jointly directed this work.


  1. Division of Genetics and Epidemiology, Institute of Cancer Research, Surrey, UK.

    • Daniel Chubb
    • , Peter Broderick
    • , Jayaram Vijayakrishnan
    • , Gabriele Migliorini
    • , Sara E Dobbins
    • , Amy Holroyd
    •  & Richard S Houlston
  2. Department of Internal Medicine V, University of Heidelberg, Heidelberg, Germany.

    • Niels Weinhold
    • , Dirk Hose
    • , Kai Neben
    • , Elisabeth Dörner
    •  & Hartmut Goldschmidt
  3. German Cancer Research Center, Heidelberg, Germany.

    • Bowang Chen
    • , Asta Försti
    •  & Kari Hemminki
  4. Department of Haemato-Oncology, Division of Pathology, Institute of Cancer Research, Surrey, UK.

    • David C Johnson
    • , Brian A Walker
    • , Faith E Davies
    •  & Gareth J Morgan
  5. Center for Primary Health Care Research, Lund University, Malmo, Sweden.

    • Asta Försti
    •  & Kari Hemminki
  6. National Centre of Tumour Diseases, Heidelberg, Germany.

    • Dirk Hose
    •  & Hartmut Goldschmidt
  7. Leeds Institute of Molecular Medicine, Section of Clinical Trials Research, University of Leeds, Leeds, UK.

    • Walter A Gregory
  8. Royal Victoria Infirmary, Newcastle upon Tyne, UK.

    • Graham H Jackson
  9. Newcastle Cancer Centre, Northern Institute for Cancer Research, Medical School, Newcastle University, Newcastle upon Tyne, UK.

    • Julie A Irving
    •  & James M Allan
  10. Department of Haematology, Birmingham Heartlands Hospital, Birmingham, UK.

    • Guy Pratt
  11. Department of Haematology, School of Medicine, Cardiff University, Cardiff, UK.

    • Chris Fegan
  12. Leeds Teaching Hospitals National Health Service (NHS) Trust, Leeds, UK.

    • James A L Fenton
  13. Institute of Human Genetics, University of Bonn, Bonn, Germany.

    • Per Hoffmann
    • , Markus M Nöthen
    •  & Thomas W Mühleisen
  14. Department of Genomics, University of Bonn, Bonn, Germany.

    • Per Hoffmann
    • , Markus M Nöthen
    •  & Thomas W Mühleisen
  15. German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.

    • Markus M Nöthen
  16. Institute for Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University Duisburg-Essen, Essen, Germany.

    • Lewin Eisele
  17. Cytogenetics Group, Wessex Regional Cytogenetic Laboratory, Salisbury, UK.

    • Fiona M Ross
  18. Schön Klinik Starnberger See, Berg, Germany.

    • Christian Straka
  19. Department of Internal Medicine II, University of Würzburg, Würzburg, Germany.

    • Hermann Einsele
  20. Department of Internal Medicine III, University of Ulm, Ulm, Germany.

    • Christian Langer
  21. Institute of Human Genetics, University of Heidelberg, Heidelberg, Germany.

    • Anna Jauch


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R.S.H. and K.H. designed the study. R.S.H. and G.M. obtained financial support in the UK, and K.H. and H.G. obtained support in Germany. R.S.H. drafted the manuscript. D.C., B.C. and N.W. performed the principal statistical and bioinformatic analyses. S.E.D. and G.M. performed additional statistical and bioinformatic analyses. P.B. coordinated the UK laboratory analyses. J.V. and A.H. performed genotyping in the UK. D.C.J. managed and prepared Myeloma IX and Myeloma XI case study DNA samples. J.M.A. conceived of the Newcastle-based myeloma study (NMS). J.M.A. established the study and supervised data collation and sample management of the NMS. J.A.I., G.H.J., G.P., J.A.L.F. and C.F. developed protocols for the recruitment of individuals with myeloma and performed sample collection of cases within the NMS. H.G., D.H., K.N. and N.W. coordinated and managed the German DNA samples, and K.H. and A.F. coordinated the German genotyping. H.E., C.L. and C.S. ascertained and collected DSMM and Ulm case study samples, and C.L. prepared DNA samples. E.D. and N.W. performed genotyping of German replication cases and controls. B.A.W. performed UK expression analyses. F.M.R. performed UK and A.J. performed German FISH analyses. G.J.M., F.E.D., W.A.G., G.H.J. and J.A.I. performed ascertainment and collection of case study samples. P.H., T.W.M. and M.M.N. performed and coordinated the GWAS of German cases and controls. L.E. ascertained and managed the HNR sample. All authors contributed to the final paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Richard S Houlston.

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