4.7 Article

Fine mapping of genetic susceptibility loci for melanoma reveals a mixture of single variant and multiple variant regions

期刊

INTERNATIONAL JOURNAL OF CANCER
卷 136, 期 6, 页码 1351-1360

出版社

WILEY
DOI: 10.1002/ijc.29099

关键词

melanoma; fine mapping; penalized regression; heritability; genome-wide signal

类别

资金

  1. European Commission [LSHC-CT-2006-018702]
  2. Cancer Research UK Programme Awards [C588/A4994, C588/A10589]
  3. Cancer Research UK Project Grant [C8216/A6129]
  4. US National Institutes of Health [CA83115]
  5. CIDR [HHSN268201100011I]
  6. Wellcome Trust [076113]
  7. SEARCH: Cancer Research UK Genetic Epidemiology of Cancer [C8197/A10123, C490/A11021, C1287/A10122, C1287/A10118, C490/A10119]
  8. Genetic Factors in Telomere Length [C1287/A9540]
  9. European Research Council Advanced Grant [ERC-2011-294576]
  10. Universita degli Studi di Genova Progetti di Ricerca di Ateneo [PRA 2012-2013]
  11. Institut National du Cancer [INCa_5982/PLBIO-2012]
  12. Catalan Government, Spain [AGAUR 2009 SGR 1337]
  13. Ligue Nationale Contre Le Cancer [PRE05/FD, PRE 09/FD]
  14. Programme Hospitalier de Recherche Clinique [AOM-07-195]
  15. European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI)-Netherlands Hub [CO18]
  16. Fondo de Investigaciones Sanitarias [P.I. 09/01393]
  17. Comprehensive Cancer Center, Oslo University Hospital [SE0728]
  18. Norwegian Cancer Society [71512-PR-2006-0356]
  19. Intramural Research Program of the NIH
  20. National Cancer Institute (NCI)
  21. Ministere de l'Enseignement Superieur et de la Recherche
  22. Institut National du Cancer (INCa)
  23. Swedish Cancer Society
  24. Karolinska Institutet's Research Funds
  25. Gunnar Nilsson Foundation
  26. IRCCS Azienda Ospedaliera Universitaria San Martino-IST Istituto Nazionale per la Ricerca sul Cancro, 5 per 1000 per la Ricerca Corrente
  27. Intramural Research Program of National Institutes of Health
  28. National Cancer Institute, Division of Cancer Epidemiology and Genetics
  29. Ligue Nationale Contre Le Cancer Doctoral Fellowship
  30. CIBER de Enfermedades Raras of the Instituto de Salud Carlos III, Spain
  31. MRC [MR/L01629X/1] Funding Source: UKRI
  32. Cancer Research UK [19167, 16561, 10589, 16565] Funding Source: researchfish
  33. Medical Research Council [MR/L01629X/1] Funding Source: researchfish
  34. The Francis Crick Institute
  35. Cancer Research UK [10124] Funding Source: researchfish

向作者/读者索取更多资源

At least 17 genomic regions are established as harboring melanoma susceptibility variants, in most instances with genome-wide levels of significance and replication in independent samples. Based on genome-wide single nucleotide polymorphism (SNP) data augmented by imputation to the 1,000 Genomes reference panel, we have fine mapped these regions in over 5,000 individuals with melanoma (mainly from the GenoMEL consortium) and over 7,000 ethnically matched controls. A penalized regression approach was used to discover those SNP markers that most parsimoniously explain the observed association in each genomic region. For the majority of the regions, the signal is best explained by a single SNP, which sometimes, as in the tyrosinase region, is a known functional variant. However in five regions the explanation is more complex. At the CDKN2A locus, for example, there is strong evidence that not only multiple SNPs but also multiple genes are involved. Our results illustrate the variability in the biology underlying genome-wide susceptibility loci and make steps toward accounting for some of the missing heritability. What's new? In genome-wide association studies, researchers identify genetic variants that frequently associate with a particular disease, though the variants identified may not contribute to the molecular cause of the disease. This study took a closer look at 17 regions associated with melanoma, fine mapping the regions both in people with melanoma and in healthy controls. Though single SNPs account for the association in some regions, they found that in a few regions, several SNPs - and possibly multiple genes - contributed to the association signal. These findings illustrate the importance of not overlooking the interaction between multiple genetic markers when conducting such studies.

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