Fine-mapping of colorectal cancer susceptibility loci at 8q23.3, 16q22.1 and 19q13.11: Refinement of association signals and use of in silico analysis to suggest functional variation and unexpected candidate target genes

Luis Carvajal-Carmona, Jean Baptiste Cazier, Angela M. Jones, Kimberley Howarth, Peter Broderick, Alan Pittman, Sara Dobbins, Albert Tenesa, Susan Farrington, James Prendergast, Evi Theodoratou, Rebecca Barnetson, David Conti, Polly Newcomb, John L. Hopper, Mark A. Jenkins, Steven Gallinger, David J. Duggan, Harry Campbell, David KerrGraham Casey, Richard Houlston, Malcolm Dunlop, Ian Tomlinson

Research output: Contribution to journalArticlepeer-review

49 Scopus citations

Abstract

We have previously identified several colorectal cancer (CRC)-associated polymorphisms using genome-wide association (GWA) analysis. We sought to fine-map the location of the functional variants for three of these regions at 8q23.3 (EIF3H), 16q22.1 (CDH1/CDH3) and 19q13.11 (RHPN2). We genotyped two case-control sets at high density in the selected regions and used existing data from four other case-control sets, compris- ing a total of 9328 CRC cases and 10 480 controls. To improve marker density, we imputed genotypes from the 1000 Genomes Project and Hapmap3 data sets. All three regions contained smaller areas in which a cluster of single nucleotide polymorphisms (SNPs) showed clearly stronger association signals than surrounding SNPs, allowing us to assign those areas as the most likely location of the disease-associated functional variant. Further fine-mapping within those areas was generally unhelpful in identifying the functional variation based on strengths of association. However, functional annotation suggested a relatively small number of functional SNPs, including some with potential regulatory function at 8q23.3 and 16q22.1 and a non-synonymous SNP in RPHN2. Interestingly, the expression quantitative trait locus browser showed a number of highly associated SNP alleles correlated with mRNA expression levels not of EIF3H and CDH1 or CDH3,butofUTP23 and ZFP90, respectively. In contrast, none of the top SNPs within these regions was associated with transcript levels at EIF3H, CDH1 or CDH3. Our post-GWA study highlights benefits of fine-mapping of common disease variants in combination with publicly available data sets. In addition, caution should be exercised when assign- ing functionality to candidate genes in regions discovered through GWA analysis.

Original languageEnglish (US)
Article numberddr190
Pages (from-to)2879-2888
Number of pages10
JournalHuman Molecular Genetics
Volume20
Issue number14
DOIs
StatePublished - Jul 2011
Externally publishedYes

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)
  • Molecular Biology

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