The effect of UGT1A and UGT2B polymorphisms on colorectal cancer risk: haplotype associations and gene–environment interactions

Abstract

UDP-glucuronosyltransferases (UGTs) play an important role in the phase II metabolism of exogenous and endogenous compounds. As colorectal cancer (CRC) etiology is thought to involve the biotransformation of dietary factors, UGT polymorphisms may affect CRC risk by altering levels of exposure. Genotyping of over 1800 Caucasian subjects was completed to identify the role of genetic variation in nine UGT1A and five UGT2B genes on CRC risk. Unconditional logistic regression and haplotype analyses were conducted to identify associations with CRC risk and potential gene-environment interactions. UGT1A haplotype analysis found that the T-G haplotype in UGT1A10 exon 1 (block 2: rs17864678, rs10929251) decreased cancer risk for the colon [proximal (OR = 0.28, 95% CI = 0.11–0.69) and for the distal colon (OR = 0.32, 95% CI = 0.12–0.91)], and that the C-T-G haplotype in the 3′ region flanking the UGT1A shared exons (block 11: rs7578153, rs10203853, rs6728940) increased CRC risk in males (OR = 2.56, 95% CI = 1.10–5.95). A haplotype in UGT2B15 containing a functional variant (rs4148269, K523T) and an intronic SNP (rs6837575) was found to affect rectal cancer risk overall (OR = 2.57, 95% CI = 1.21–5.04) and in females (OR = 3.08, 95% CI = 1.08–8.74). An interaction was found between high NSAID use and the A-G-T haplotype (block 10: rs6717546, rs1500482, rs7586006) in the UGT1A shared exons that decreased CRC risk. This suggests that UGT genetic variation alters CRC risk differently by anatomical sub-site and gender and that polymorphisms in the UGT1A shared exons may have a regulatory effect on gene expression that allows for the protective effect of NSAIDs on CRC risk.

Figure 1

Linkage disequilibrium (LD) plot of SNPs in the UGT1A gene loci on 2q37. Their respective haplotypes were identified by Haploview using controls from the study population. All SNPs shown passed Hardy-Weinberg Equilibrium analysis and were genotyped at a rate >90% in the present study. D′ values are displayed in the squares (empty squares have a pairwise D′=1.00). Red squares show high pairwise LD, gradually coloring down to white squares of low pairwise LD. Blue squares indicate high LD, but low significance. Blue triangles indicate the SNPs in high LD that were grouped into individual haplotype blocks, including the division of haplotype block 7 shown by different colored triangles into 4 blocks because of limited computational power. Lines that extend from the LD plot are dashed as they do not always match the exact chromosomal beginning and end position of each haplotype block.

Figure 2

Schematic representation of the effect the UGT2B gene family on rectal cancer risk produced by the PheWAS software (Pendergrass et al., 2012). Forest plot showing the odds ratios and 95% confidence intervals of the effect of individual UGT2B SNPs (A) and haplotypes in block 1 of UGT2B15 (B) on rectal cancer risk. LD plot demonstrates the haplotype blocks within the region and the position of each UGT2B gene [* on genes indicates that this gene has been previously studied for CRC risk associations using the same sample set (Angstadt et al., 2013)]. The P-value graphed as the −1og10 (P-value) was adjusted for multiple testing by the FDR method and the red line denotes the P<0.05 cutoff. Abbreviations are as follows: B = minor allele; Add [Additive Statistical Model, (BB) > (BA) > (AA)]; Dom [(Dominant Statistical Model, (BB + (BA) vs (AA)]; Recc (Recessive Statistical Model, (BB) vs (BA) + (BB)]; MAF (minor allele frequency in population controls). Blank plots in the Additive and Recessive Statistical Model are provided to focus the graphical scale because these SNPs were insignificant and contained a large confidence interval. In addition, rs3924194 and rs7435335 only had two alleles and therefore could not be analyzed in a recessive model.