Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk

Abstract

We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totaling 21,096 cases and 19,555 controls. We identified three new CRC risk loci at 6p21 (rs1321311, near CDKN1A; P = 1.14 × 10−10), 11q13.4 (rs3824999, intronic to POLD3; P = 3.65 × 10−10) and Xp22.2 (rs5934683, near SHROOM2; P = 7.30 × 10−10) This brings the number of independent loci associated with CRC risk to 20 and provides further insight into the genetic architecture of inherited susceptibility to CRC.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Regional plots of association results and recombination rates for the 6p21, 11q13.4 and Xp22.2 susceptibility loci.

Similar content being viewed by others

References

  1. Lichtenstein, P. et al. Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark, and Finland. N. Engl. J. Med. 343, 78–85 (2000).

    Article  CAS  Google Scholar 

  2. Aaltonen, L., Johns, L., Jarvinen, H., Mecklin, J.P. & Houlston, R. Explaining the familial colorectal cancer risk associated with mismatch repair (MMR)-deficient and MMR-stable tumors. Clin. Cancer Res. 13, 356–361 (2007).

    Article  CAS  Google Scholar 

  3. Lubbe, S.J., Webb, E.L., Chandler, I.P. & Houlston, R.S. Implications of familial colorectal cancer risk profiles and microsatellite instability status. J. Clin. Oncol. 27, 2238–2244 (2009).

    Article  Google Scholar 

  4. Tomlinson, I.P. et al. A genome-wide association study identifies colorectal cancer susceptibility loci on chromosomes 10p14 and 8q23.3. Nat. Genet. 40, 623–630 (2008).

    Article  CAS  Google Scholar 

  5. Tomlinson, I.P. et al. Multiple common susceptibility variants near BMP pathway loci GREM1, BMP4, and BMP2 explain part of the missing heritability of colorectal cancer. PLoS Genet. 7, e1002105 (2011).

    Article  CAS  Google Scholar 

  6. Tenesa, A. et al. Genome-wide association scan identifies a colorectal cancer susceptibility locus on 11q23 and replicates risk loci at 8q24 and 18q21. Nat. Genet. 40, 631–637 (2008).

    Article  CAS  Google Scholar 

  7. Houlston, R.S. et al. Meta-analysis of genome-wide association data identifies four new susceptibility loci for colorectal cancer. Nat. Genet. 40, 1426–1435 (2008).

    Article  CAS  Google Scholar 

  8. Houlston, R.S. 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).

    Article  CAS  Google Scholar 

  9. Broderick, P. et al. A genome-wide association study shows that common alleles of SMAD7 influence colorectal cancer risk. Nat. Genet. 39, 1315–1317 (2007).

    Article  CAS  Google Scholar 

  10. Jaeger, E. et al. Common genetic variants at the CRAC1 (HMPS) locus on chromosome 15q13.3 influence colorectal cancer risk. Nat. Genet. 40, 26–28 (2008).

    Article  CAS  Google Scholar 

  11. Tenesa, A. & Dunlop, M.G. New insights into the aetiology of colorectal cancer from genome-wide association studies. Nat. Rev. Genet. 10, 353–358 (2009).

    Article  CAS  Google Scholar 

  12. Miquel, C. et al. Frequent alteration of DNA damage signalling and repair pathways in human colorectal cancers with microsatellite instability. Oncogene 26, 5919–5926 (2007).

    Article  CAS  Google Scholar 

  13. Holm, H. et al. Several common variants modulate heart rate, PR interval and QRS duration. Nat. Genet. 42, 117–122 (2010).

    Article  CAS  Google Scholar 

  14. Abbas, T. & Dutta, A. p21 in cancer: intricate networks and multiple activities. Nat. Rev. Cancer 9, 400–414 (2009).

    Article  CAS  Google Scholar 

  15. Dunlop, M.G. et al. Cancer risk associated with germline DNA mismatch repair gene mutations. Hum. Mol. Genet. 6, 105–110 (1997).

    Article  CAS  Google Scholar 

  16. Quehenberger, F., Vasen, H.F. & van Houwelingen, H.C. Risk of colorectal and endometrial cancer for carriers of mutations of the hMLH1 and hMSH2 gene: correction for ascertainment. J. Med. Genet. 42, 491–496 (2005).

    Article  CAS  Google Scholar 

  17. Baglietto, L. et al. Risks of Lynch syndrome cancers for MSH6 mutation carriers. J. Natl. Cancer Inst. 102, 193–201 (2010).

    Article  CAS  Google Scholar 

  18. Clayton, D. Testing for association on the X chromosome. Biostatistics 9, 593–600 (2008).

    Article  Google Scholar 

  19. Farber, M.J., Rizaldy, R. & Hildebrand, J.D. Shroom2 regulates contractility to control endothelial morphogenesis. Mol. Biol. Cell 22, 795–805 (2011).

    Article  CAS  Google Scholar 

  20. Forbes, S.A. et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res. 39, D945–D950 (2011).

    Article  CAS  Google Scholar 

  21. Fairbank, P.D. et al. Shroom2 (APXL) regulates melanosome biogenesis and localization in the retinal pigment epithelium. Development 133, 4109–4118 (2006).

    Article  CAS  Google Scholar 

  22. Houlston, R.S. et al. Congenital hypertrophy of retinal pigment epithelium in patients with colonic polyps associated with cancer family syndrome. Clin. Genet. 42, 16–18 (1992).

    Article  CAS  Google Scholar 

  23. Dunlop, M.G. et al. Extracolonic features of familial adenomatous polyposis in patients with sporadic colorectal cancer. Br. J. Cancer 74, 1789–1795 (1996).

    Article  CAS  Google Scholar 

  24. Matys, V. et al. TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes. Nucleic Acids Res. 34, D108–D110 (2006).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  27. Levin, J.H. & Kaler, S.G. Non-random maternal X-chromosome inactivation associated with PHACES. Clin. Genet. 72, 345–350 (2007).

    Article  CAS  Google Scholar 

  28. Kristiansen, M. et al. High incidence of skewed X chromosome inactivation in young patients with familial non-BRCA1/BRCA2 breast cancer. J. Med. Genet. 42, 877–880 (2005).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  30. Pettiti, D. Meta-analysis Decision Analysis and Cost-effectiveness Analysis (Oxford University Press, 1994).

  31. Higgins, J.P. & Thompson, S.G. Quantifying heterogeneity in a meta-analysis. Stat. Med. 21, 1539–1558 (2002).

    Article  Google Scholar 

  32. Ioannidis, J.P., Ntzani, E.E. & Trikalinos, T.A. 'Racial' differences in genetic effects for complex diseases. Nat. Genet. 36, 1312–1318 (2004).

    Article  CAS  Google Scholar 

  33. Chow, J.C., Yen, Z., Ziesche, S.M. & Brown, C.J. Silencing of the mammalian X chromosome. Annu. Rev. Genomics Hum. Genet. 6, 69–92 (2005).

    Article  CAS  Google Scholar 

  34. Myers, S., Bottolo, L., Freeman, C., McVean, G. & Donnelly, P. A fine-scale map of recombination rates and hotspots across the human genome. Science 310, 321–324 (2005).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  36. Ferretti, V. et al. PReMod: a database of genome-wide mammalian cis-regulatory module predictions. Nucleic Acids Res. 35, D122–D126 (2007).

    Article  CAS  Google Scholar 

  37. Dunning, M.J., Smith, M.L., Ritchie, M.E. & Tavare, S. beadarray: R classes and methods for Illumina bead-based data. Bioinformatics 23, 2183–2184 (2007).

    Article  CAS  Google Scholar 

  38. Smyth, G.K. Limma: linear models for microarray data. in Bioinformatics and Computational Biology Solutions using R and Bioconductor (eds. Gentleman, R., Carey, V., Dudoit, S., Irizarry, R. & Huber, W.) 397–420 (Springer, New York, 2005).

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

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  41. Boland, C.R. et al. A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer. Cancer Res. 58, 5248–5257 (1998).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

Cancer Research UK provided principal funding for this study individually to R.S.H. (C1298/A8362–Bobby Moore Fund for Cancer Research UK), I.P.T. and M.G.D. At the Institute of Cancer Research, additional funding was provided by a Centre Grant from Core as part of the Digestive Cancer Campaign, the National Cancer Research Network and the NHS via the Biological Research Centre of the NIHR at the Royal Marsden Hospital NHS Trust. S.L. received a PhD studentship from Cancer Research UK, I.C. received a Clinical Research Training Fellowship from St. George's Hospital Medical School, and N.W. received a PhD Studentship from the Institute of Cancer Research. M.H. was in receipt of a Post-Doctoral Training post from the Leukaemia Lymphoma Research Fund.

In Oxford, additional funding was provided by the Oxford Comprehensive Biomedical Research Centre (E.D., C.P. and I.P.T.) and the European Union Framework Programme 7 (FP7) CHIBCHA grant (A.M.J., L.G.C.-C. and I.P.T.). Core infrastructure support to the Wellcome Trust Centre for Human Genetics, Oxford, was provided by grant (090532/Z/09/Z).

We are grateful to many colleagues within the UK Clinical Genetics Departments (for CORGI) and to many collaborators who participated in the VICTOR and QUASAR2 trials. We also thank colleagues from the UK National Cancer Research Network (for NSCCG).

In Edinburgh, funding was provided by a Cancer Research UK Programme Grant (C348/A12076) and a Centre Grant from the CORE Charity. E.T. was funded by a Cancer Research UK Fellowship (C31250/A10107). L.-Y.O. is supported by a Cancer Research UK Research Training Fellowship (C10195/A12996). C. Smillie is supported by an MRC Research Studentship to the MRC Human Genetics Unit (HGU). We gratefully acknowledge the work of M. Walker and S. Reid in technical support, R. Wilson (SOCCS3 and COGS study coordinator), G. Barr for data entry in SOCCS studies, the research nurse recruitment teams, the Wellcome Trust Clinical Research Facility for sample preparation and all surgeons, oncologists and pathologists throughout Scotland at contributing centers. Lothian Birth Cohort Illumina genotyping was supported by the UK Biotechnology and Biological Sciences Research Council (BBSRC). Phenotype collection in the Lothian Birth Cohort 1921 was supported by the BBSRC, The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Research into Ageing (continues as part of Age UK's The Disconnected Mind project). The work on the Lothian Birth Cohorts was undertaken at the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross-council Lifelong Health and Wellbeing Initiative (G0700704/84698). Funding from the BBSRC, EPSRC, ESRC and MRC is gratefully acknowledged.

For the Cambridge study, we thank the SEARCH study team and all the participants in the study. SEARCH is funded by a grant from Cancer Research UK (C490/A10124).

In Cardiff, the work was supported by the Kidani Trust, Tenovus, Cancer Research Wales, The Bobby Moore Fund from CRUK (C10314/A4886), the Wales Assembly Government NISCHR Cancer Genetics BRU and the Wales Gene Park (all to J.P.C.). We acknowledge the use of DNA from the blood samples collected from COIN and COIN-B funded by Cancer Research UK and the MRC. We also acknowledge the use of DNA from the NBS (UKBS) collection, funded by the Wellcome Trust (076113/C/04/Z), by the Juvenile Diabetes Research Foundation (WT061858) and by the NIHR of England. The COIN-B Collaborative Group includes H. Wasan, T. Maughan, R. Adams, R. Wilson, A. Madi, E. Hodgkinson, M. Pope, P. Rogers and J. Cassidy.

Research was also funded by the European Union FP7 (FP7/207-2013) under grant 258236, FP7 collaborative project SYSCOL.

The Swedish sample and data resource were funded by the Swedish Cancer Society, the Swedish Scientific Research Council and the Stockholm Cancer Foundation. We acknowledge the contribution to recruitment and data collection of the Swedish Low-Risk Colorectal Cancer Study Group.

For the Helsinki study, the work was supported by grants from the Academy of Finland (Finnish Centre of Excellence Program; 2006-2011), the Finnish Cancer Society and the Sigrid Juselius Foundation.

This work of the Colon Cancer Family Registry (CFR) was supported by the US National Cancer Institute, National Institutes of Health (CA-95-011), and through cooperative agreements with members of the Colon CFR and Principal Investigators. Collaborating centers include the Australasian Colorectal Cancer Family Registry (U01 CA097735), the Familial Colorectal Neoplasia Collaborative Group (U01 CA074799), the Ontario Registry for Studies of Familial Colorectal Cancer (U01 CA074783) and the Seattle Colorectal Cancer Family Registry (U01 CA074794). The Colon CFR GWAS was supported by funding from the US National Cancer Institute, National Institutes of Health (U01CA122839 to G.C.).

The Japanese study was conducted as part of the BioBank Japan Project that was supported by the Ministry of Education, Culture, Sports, Science and Technology of the Japanese government.

This study made use of genotyping data from the 1958 Birth Cohort and NBS samples, kindly made available by the Wellcome Trust Case Control Consortium 2. A full list of the investigators who contributed to the generation of the data is available (see URLs). Finally, we would like to thank all individuals who participated in the study.

Author information

Authors and Affiliations

Authors

Consortia

Contributions

The study was designed and financial support was obtained by R.S.H., I.P.T. and M.G.D. The manuscript was drafted by R.S.H., I.P.T. and M.G.D. Statistical and bioinformatics analyses were conducted by S.E.D. and N.W., with contributions from Y.P.M., M.H., M.F., C.S., G.G., R.S.H., P.B., S.S. and I.P.T.

Institute of Cancer Research and local collaborators: Subject recruitment and sample acquisition to NSCCG were undertaken by S.P. The coordination of sample preparation and genotyping was performed by P.B. Sample preparation and genotyping were performed by J.V., A. Lloyd B.O. and N.W. Tumor pathology analyses were performed by I.C. and S.L.

Oxford and local collaborators: Subject recruitment and sample acquisition were performed by E.B., M.G., L.M. and members of the CORGI Consortium and by R.M. and D.J.K. Genotyping was performed and coordinated by L.G.C.-C., A.M.J. and E.D.

Colon Cancer Genetics Group, Edinburgh, and local collaborators: Subject recruitment and sample acquisition were performed by S.F., J.M.S., I.D., H.C. and M.G.D., as well as by members of the SOCCS and COGS recruitment teams. Sample preparation was coordinated by S.M.F. Genotyping was performed and coordinated by S.M.F. and M.G.D. Data curation and analysis in Edinburgh were conducted by A.T., S.M.F., E.T., L.Z., J.P. and S.B. Recruitment sample preparation, wet lab expression analysis and genotyping were performed by L.-Y.O., and C. Smillie, G.G. and C. Semple performed the bioinformatics analyses.

The following authors from collaborating groups conceived the local or national study, undertook assembly of case-control series in their respective regions, collected data and samples and variously undertook genotyping and analysis: C.G.S., H.W., and J.P.C. in Cardiff; L.R.S., J.P.M. and L.A.A. in Finland; and P.P. in Cambridge. All other authors undertook sample collection and phenotype data collection and collation in their respective centers.

Corresponding authors

Correspondence to Malcolm G Dunlop, Ian P Tomlinson or Richard S Houlston.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–4, Supplementary Tables 1–5 and Supplementary Note (PDF 3066 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Dunlop, M., Dobbins, S., Farrington, S. et al. Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk. Nat Genet 44, 770–776 (2012). https://doi.org/10.1038/ng.2293

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.2293

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer