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

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, comprising 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, but of UTP23 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 assigning functionality to candidate genes in regions discovered through GWA analysis.

Figure 1.

Associations between 8q23.3 SNPs and CRC risk in six case–control studies of European descent. The top part of the figure shows the meta-analysis P-values and their associated beta coefficients. The P-values for rs16892766, the regions’ original tagSNP, and for 8-117694643, rs11986063, rs28535528, rs16888589, rs16888611 and 8-117827346, are shown in red. The x-axis indicates the SNP location (in Mb) based on the human genome build 36. The y-axis indicates the −log10 of the P-value (top) and absolute value of the beta coefficients (bottom) for each SNP. The middle part of the figure shows the approximate locations of the EIF3H and UTP23 genes. The lower part of the figure shows the patterns of LD (r²) in the CEPH population.

Figure 2.

Associations between 16q22.1 SNPs and CRC risk in six case–control studies of European descent. The top part of the figure shows the meta-analysis P-values and their associated beta coefficients. The P-values for rs9929218, the regions’ original tagSNP, and for rs7199991, rs2961, rs35158985, rs9929239, rs9923610, rs2059254, rs1981871 and rs13339591, the most strongly associated SNPs, are shown in red. The x-axis indicates the SNP location (in Mb) based on the human genome build 36. The y-axis indicates the −log10 of the P-value (top) and absolute value of the beta coefficients (bottom) for each SNP. The middle part of the figure shows the approximate locations of the ZPF90, CDH3 and CDH1 genes. The lower part of the figure shows the patterns of LD (r²) in the CEPH population.

Figure 3.

Associations between 19q13.11 SNPs and CRC risk in six case–control studies of European descent. The top part of the figure shows the meta-analysis P-values and their associated beta coefficients. The P-values for rs10411210, the regions’ original tagSNP, and for rs28628368, a RPHN2 nsSNP are shown in red. The x-axis indicates the SNP location (in Mb) based on the human genome build 36. The y-axis indicates the −log10 of the P-value (top) and absolute value of the beta coefficients (bottom) for each SNP. The middle part of the figure shows the approximate location of the RPHN2 gene. The lower part of the figure shows the patterns of LD (r²) in the CEPH population.