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

Authors :
Du M
Jiao S
Bien SA
Gala M
Abecasis G
Bezieau S
Brenner H
Butterbach K
Caan BJ
Carlson CS
Casey G
Chang-Claude J
Conti DV
Curtis KR
Duggan D
Gallinger S
Haile RW
Harrison TA
Hayes RB
Hoffmeister M
Hopper JL
Hudson TJ
Jenkins MA
Küry S
Le Marchand L
Leal SM
Newcomb PA
Nickerson DA
Potter JD
Schoen RE
Schumacher FR
Seminara D
Slattery ML
Hsu L
Chan AT
White E
Berndt SI
Peters U
Source :
PloS one [PLoS One] 2016 Jul 05; Vol. 11 (7), pp. e0157521. Date of Electronic Publication: 2016 Jul 05 (Print Publication: 2016).
Publication Year :
2016

Abstract

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).

Details

Language :
English
ISSN :
1932-6203
Volume :
11
Issue :
7
Database :
MEDLINE
Journal :
PloS one
Publication Type :
Academic Journal
Accession number :
27379672
Full Text :
https://doi.org/10.1371/journal.pone.0157521