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Aberrant DNA methylation of CpG islands is a common epigenetic alteration found in cancers. DNA methylation is typically mediated by DNA methyltransferases (DNMTs). Only two studies have evaluated DNMT-3B and/or DNMT-1 gene polymorphisms in relation to breast cancer risk, and results have been inconsistent. We comprehensively evaluated genetic variations in the DNMT-1 and DNMT-3B genes with breast cancer risk among the participants of the Shanghai Breast Cancer Study (SBCS), a large-scale, two-stage, case-control study. Of the 25 SNPs in the DNMT-1 and DNMT-3B genes analyzed, only one (rs8101866) reached a normal significance level (p=0.042). This association, however, was no longer statistically significant after adjustment for multiple comparisons. Our data suggest that there is no apparent association of common DNMT-1 and DNMT-3B polymorphisms with the risk of breast cancer among Chinese women.
Aberrant DNA methylation of CpG islands is a common epigenetic alteration found in cancers . DNA methylation is typically mediated by DNA methyltransferases (DNMTs). DNMT-1 binds methyl groups to hemimethylated DNA during replication for the maintenance of methylation in the genome. DNMT-3B adds methyl groups to unmethylated CpG dinucleotides for de novo methylation . Three single nucleotide polymorphisms (SNPs) in the DNMT-3B promoter region, −149C>T (rs2424913), −283T>C (rs6058870), and −579G>T (rs1569686), have been evaluated as possible genetic susceptibility factors for several types of cancer [2–7]. However, only two studies have evaluated DNMT-3B and/or DNMT-1 gene polymorphisms in relation to breast cancer risk, and results have been inconsistent [5;8].
This study was undertaken to comprehensively assess genetic variations in the DNMT-1 and DNMT-3B genes, and evaluate associations of these variants with breast cancer risk among the participants of the Shanghai Breast Cancer Study (SBCS).
Study subjects were participants of the SBCS, a large-scale, two-phase, population-based, case-control study conducted in urban Shanghai, which has been described previously [9;10]. Briefly, 1,459 (91.1%) cases and 1,556 (90.3%) controls from Phase 1 and 1,989 cases (83.7%) and 1,989 controls (70.4%) from Phase 2 completed in-person interviews. Blood or buccal cell samples were donated by 1,193 cases (81.8%) and 1,310 controls (84.2%) from Phase 1 and 1,932 (97.1%) cases and 1,857 (93.4%) controls from Phase 2. Approval of the study was granted by the relevant review boards in both China and the United States, and written, informed consent was obtained from all participants prior to interview.
Haplotype tagging SNPs (htSNPs) were selected from the Han Chinese data included in the HapMap Project  using the Tagger program  to capture SNPs with a minimum minor allele frequency (MAF) of 0.05 in either DNMT-1 or DNMT-3B (± 5kb) with an r2 of 0.90 or greater. Known or potentially functional SNPs were forced into the htSNP selection process. Eight SNPs for the DNMT-1 gene and 7 SNPs for the DNMT-3B gene were selected in 2006, and were evaluated in 1,062 cases and 1,069 controls from Phase 1, using a Targeted Genotyping System (Affymetrix, Santa Clara, CA) as previously described .
One SNP with a potentially interesting result from Phase 1 (rs6058869) was selected for additional genotyping using a TaqMan assay (assay ID, C__30018043_10) for 1,919 cases and 1,820 controls from Phase 2. The laboratory staff was blinded to the identity of the samples. Quality control (QC) samples were included in the genotyping assays . The concordance rate for the blinded samples was 97.5%.
To increase the density of genetic markers in this study, data from our recently completed Affymetrix Genome-Wide Human SNP Array 6.0 was included for an additional 6 SNPs for the DNMT-1 gene (± 10kb) and 26 SNPs for the DNMT-3B gene (± 10kb) for 4,157 participants, including 1,104 cases and 1,109 controls from Phase 1 and 969 cases and 975 controls from Phase 2.
Hardy-Weinberg equilibrium (HWE) was tested by comparing the observed and expected genotype frequencies of the controls (χ2-test). Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were determined by logistic regression analyses using additive models that included adjustment for age, education, and study phase, when appropriate. All statistical tests were two-tailed, and p-values were considered to be statistically significant when ≤ 0.05.
A total of 6,031 women were included in the current study: 2,291 Phase 1 participants and 3,740 Phase 2 participants. Women in both study phases were generally comparable (data not shown). As expected, breast cancer cases were found to differ from controls in regards to known breast cancer risk factors. Cases were more likely to have an earlier age at menarche, older age at first live birth, a history of breast fibroadenomas, a history of breast cancer in a first degree relative, a higher BMI or WHR, and they were less likely to participate in regular physical activity than controls (data not shown).
A total of 47 SNPs were genotyped in the current study, however, of these, 20 were found to have MAFs of less than 0.05 in our study population (rs2424906, rs17123571, rs2424907, rs6119951, rs6058880, rs6058883, rs6058887, rs2424913, rs6119285, rs1040555, rs8115360, rs6057648, rs2424921, rs2424930, rs6119967, rs7263832, rs6058897, rs437302, rs406193, and rs242542), and two were found to deviate from HWE in controls (rs8111085 and rs16999358). These 22 SNPs were excluded from the analysis. Therefore, 12 SNPs in the DNMT-1 gene and 13 SNPs in the DNMT-3B gene were included in the analyses. The linkage disequilibrium structure of the 25 polymorphic loci is shown in Fig. 1.
As shown in Table 1, associations with breast cancer risk were evaluated among 2,131 participants from Phase 1 for 11 SNPs, among 4,157 participants from Phase 1 and Phase 2 for an additional 14 SNPs from the Genome-Wide Human SNP Array 6.0, and among 5,870 Phase 1 and Phase 2 participants for one SNP with an interesting preliminary result that was selected for validation (DNMT-3B rs6058869). This SNP and others with potentially interesting results are shown stratified by SBCS study phase in Table 2. Four SNPs (rs11085587, rs6058869, rs4911259, and rs6058893) with significant effects among Phase 1 participants were found to not have consistent results among Phase 2 participants. Although the variant allele of rs8101866 was associated with increased breast cancer risk in combined analyses (p = 0.042), the association was not statistically significant after adjusting for multiple comparisons.
Of the 25 SNPs in the DNMT-1 and DNMT-3B genes analyzed in this large, two-stage, case-control study, only one (rs8101866) was reached a normal significance level (p=0.042). This association, however, was no longer statistically significant after adjustment for multiple comparisons. Given the size of our study population, at the p = 0.05 significance level, this analysis had a greater than 93% power to detect an OR of 1.3 for a SNP with a MAF of 0.10, greater than 76% power to detect an OR of 1.2 for a SNP with a MAF of 0.15, and greater than 81% power to detect an OR of 1.2 for a SNP with a MAF of 0.20.
DNA methylation plays a significant role in the development and progression of various cancers, and DNMTs are crucial for DNA methylation. Increased DNMT-1 and DNMT-3B activity has been detected in several tumors, indicating that these two genes may contribute to tumorgenesis [5;14–16]. Three DNMT-3B SNPs have been previously evaluated in relation to cancer risk. Located in the promoter, the DNMT-3B −149 C>T (rs2424913) polymorphism has been shown to result in a 30% increase in promoter activity . Carriers of the T allele have been reported to have significantly increased risk of lung, prostate, and head and neck cancers [6;7;18]. However, the C allele has been associated with an increased risk of breast cancer among British women in a small case-control study (352 cases and 258 controls) . This SNP was not genotyped in the current study due to its low MAF among Han Chinese (MAF = 0.011) (www.hapmap.org). Another functional DNMT-3B SNP, −283 T>C (rs6058870), has been shown to result in approximately 50% decreased promoter activity in in vitro analyses. Furthermore, the lower activity T allele has been associated with a decreased risk of lung cancer . A third polymorphism, −579 G>T (rs1569686), which does not change promoter activity, has been associated with susceptibility to colorectal cancer . Neither of these SNPs were included in the HapMap project, and therefore were not selected for genotyping in the current study. The coverage of genetic variations of these two genes is high, since the SNPs that were included in the current study were selected based on HapMap SNPs with a MAF greater than 0.05 and an r2 of 0.90 or greater in these two genes. DNMT-1 gene polymorphisms have not been previously reported in relation to breast cancer risk. In our study, no DNMT-1 or DNMT-3B polymorphisms were significantly associated with breast cancer risk. In a study conducted among 4,474 breast cancer cases and 4,580 controls, Cebrian et al.  observed no association with any SNPs or common haplotypes of the DNMT-1 gene with breast cancer risk. One SNP (rs406193) in the DNMT-3B gene was significantly associated with breast cancer risk (P-trend = 0.003). This association, however, was no longer statistically significant after adjustment for multiple comparisons (P-trend = 0.124) . Moreover, no association with any common haplotypes of the DNMT-3B gene and breast cancer risk was observed .
Strengths of our study include its comprehensive and systematic approach to characterizing genetic variations across the DNMT-1 and DNMT-3B genes. Further, a two-stage design was used to reduce type I errors, and the sample sizes in both stages were large, so that type II errors were also reduced. The population-based, case-control study design and high participation rate minimized selection bias. The strong design of the study lends credibility to our findings that there is no apparent association of common DNMT-1 and DNMT-3B polymorphisms with the risk of breast cancer among Chinese women.
We thank the participants and research staff of the Shanghai Breast Cancer Study for their contributions and commitment to this project, Regina Courtney and Qing Wang for laboratory assistance, and Bethanie Hull for her assistance in thepreparation of this manuscript. Genotyping assays were conducted at the Vanderbilt Microarray Shared Resource and the Survey and Biospecimen Shared Resource; both are supported in part by the Vanderbilt-Ingram Cancer Center (P30 CA68485).
Financial Support: This research was supported by National Cancer Institute grants R01 CA064277, R01 CA090899, and R01 CA122756.
Conflict of Interest Statement: The authors have no conflicts of interest to declare.