4.6 Article

Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants

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PLOS ONE
卷 11, 期 7, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0157521

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资金

  1. GECCO: National Cancer Institute
  2. GECCO: National Institutes of Health
  3. GECCO: U.S. Department of Health and Human Services [U01 CA137088, R01 CA059045, U01 CA164930]
  4. National Cancer Institute [R25 CA94880, P30 CA008748]
  5. Regional Council of Pays de la Loire
  6. Groupement des Entreprises Francaises dans la Lutte contre le Cancer (GEFLUC)
  7. Association Anne de Bretagne Genetique
  8. Ligue Regionale Contre le Cancer (LRCC)
  9. National Cancer Institute, National Institutes of Health [U01 CA122839]
  10. National Institutes of Health: Australasian Colorectal Cancer Family Registry [U01 CA097735]
  11. National Institutes of Health: Ontario Registry for Studies of Familial Colorectal Cancer [U01 CA074783]
  12. National Institutes of Health: Seattle Colorectal Cancer Family Registry [U01 CA074794]
  13. DACHS: German Research Council (Deutsche Forschungsgemeinschaft) [BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1]
  14. COLO2&3: National Institutes of Health [R01 CA60987]
  15. CCFR: National Institutes of Health (RFA) [CA-95-011]
  16. German Federal Ministry of Education and Research [01KH0404, 01ER0814]
  17. DALS: National Institutes of Health [R01 CA48998]
  18. NHS
  19. PHS: HPFS by National Institutes of Health [P01 CA 055075, UM1 CA167552, R01 137178, P50 CA 127003]
  20. NHS by the National Institutes of Health [P50 CA 127003, R01 CA137178, P01 CA 087969]
  21. National Institutes of Health [CA42182]
  22. Damon Runyon Clinical investigator Award
  23. MEC: National Institutes of Health [R37 CA54281, P01 CA033619, R01 CA63464]
  24. OFCCR: National Institutes of Health [U01 CA074783]
  25. GL2 grant from Ontario Research Fund
  26. Canadian Institutes of Health Research
  27. Cancer Risk Evaluation (CaRE) Program grant from Canadian Cancer Society Research Institute
  28. Senior Investigator Awards from Ontario Institute for Cancer Research
  29. Ontario Ministry of Research and Innovation
  30. PLCO: Intramural Research Program of the Division of Cancer Epidemiology and Genetics
  31. Division of Cancer Prevention, National Cancer Institute, NIH, DHHS
  32. National Institutes of Health (NIH), Genes, Environment and Health Initiative (GEI) [Z01 CP 010200]
  33. NIH [U01 HG004446]
  34. NIH GEI [U01 HG 004438]
  35. PMH-CCFR: National Institutes of Health [R01 CA076366]
  36. VITAL: National Institutes of Health [K05 CA154337]
  37. National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services [HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C]
  38. CORECT: National Cancer Institute, National Institutes of Health under RFA [CA-09-002 (U19 CA148107)]
  39. [K24 DK098311]

向作者/读者索取更多资源

Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs). We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33). We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s).

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