Erratum: A new GWAS and meta-analysis with 1000Genomes imputation identifies novel risk variants for colorectal cancer
Year: 2015
Type: erratum
Abstract: Genome-wide association studies (GWAS) of colorectal cancer (CRC) have identified 23 susceptibility loci thus far. Analyses of previously conducted GWAS indicate additional risk loci are yet to be discovered. To identify novel CRC susceptibility loci, we conducted a new GWAS and performed a meta-analysis with five published GWAS (totalling 7,577 cases and 9,979 controls of European ancestry), imputing genotypes utilising the 1000 Genomes Project. The combined analysis identified new, significant associations with CRC at 1p36.2 marked by rs72647484 (minor allele frequency [MAF] = 0.09) near CDC42 and WNT4 (P = 1.21 × 10−8, odds ratio [OR] = 1.21 ) and at 16q24.1 marked by rs16941835 (MAF = 0.21, P = 5.06 × 10−8; OR = 1.15) within the long non-coding RNA (lncRNA) RP11-58A18.1 and ~500 kb from the nearest coding gene FOXL1. Additionally we identified a promising association at 10p13 with rs10904849 intronic to CUBN (MAF = 0.32, P = 7.01 × 10-8; OR = 1.14). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to CRC. Additionally, our analysis further demonstrates that imputation can be used to exploit GWAS data to identify novel disease-causing variants.
Source: Scientific Reports
DOI: 10.1038/srep12372
Authors: Nada A. Al-Tassan, Nicola Whiffin, Fay J. Hosking, Claire Palles, Susan M. Farrington, Sara E. Dobbins, Rebecca Harris, Maggie Gorman, Albert Tenesa, Brian F. Meyer, Salma M. Wakil, Ben Kinnersley, Harry Campbell, Lynn Martin, Christopher G. Smith, Shelley Idziaszczyk, Ella Barclay, Timothy S. Maughan, Richard Kaplan, Rachel Kerr, David Kerr, Daniel D. Buchanan, Aung Ko Win, John Hopper, Mark Jenkins, Noralane M. Lindor, Polly A. Newcomb, Steve Gallinger, David Conti, Fred Schumacher, Graham Casey, Malcolm G. Dunlop, Ian P. Tomlinson, Jeremy P. Cheadle, Richard S. Houlston
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,690
OpenAlex ID: W2590411970