Back to Search Start Over

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

Authors :
Mengmeng Du
Shuo Jiao
Stephanie A Bien
Manish Gala
Goncalo Abecasis
Stephane Bezieau
Hermann Brenner
Katja Butterbach
Bette J Caan
Christopher S Carlson
Graham Casey
Jenny Chang-Claude
David V Conti
Keith R Curtis
David Duggan
Steven Gallinger
Robert W Haile
Tabitha A Harrison
Richard B Hayes
Michael Hoffmeister
John L Hopper
Thomas J Hudson
Mark A Jenkins
Sébastien Küry
Loic Le Marchand
Suzanne M Leal
Polly A Newcomb
Deborah A Nickerson
John D Potter
Robert E Schoen
Fredrick R Schumacher
Daniela Seminara
Martha L Slattery
Li Hsu
Andrew T Chan
Emily White
Sonja I Berndt
Ulrike Peters
Source :
PLoS ONE, Vol 11, Iss 7, p e0157521 (2016)
Publication Year :
2016
Publisher :
Public Library of Science (PLoS), 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).

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
11
Issue :
7
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.f07d22c53e704733b34d5a12a9ca49fb
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0157521