Abstract Background: DNA methyltransferases (DNMTs) control DNA methylation and impact gene expression. Many studies have demonstrated that genetic variants in DNMT genes play a role in cancer development, including breast cancer. However, the impact of SNP-SNP interactions for DNMTs associated with breast cancer risk is unclear. The objective is to evaluate SNP-SNP interactions associated with breast cancer risk. Methods: We selected 14 SNPs in 3 DNMT genes (DNMT1, DNMT3A, and DNMT3B) for the 4,195 women (1:2 match for breast cancer cases and controls), including 1,085 African Americans (AAs) and 3,110 European Americans (EAs) in the Arkansas Rural Community Health (ARCH) cohort. We included different inheritance models (dominant, recessive, and additive) for individual SNP effects, using logistic regressions with breast cancer status (yes/no) as the outcome. Two-way SNP-SNP interactions associated with breast cancer risk were analyzed using the SNP Interaction Pattern Identifier (SIPI) approach developed by our research team. Results: Out of the 14 DNMTs SNPs, we found two SNPs (rs7605753 and rs10196635 in DNMT3A) were individually associated with breast cancer risk (p<0.05) in EAs, however, none was statistically significant in AAs. Interestingly, we applied the SIPI approach, targeting SNP-SNP interactions,19 SNP-SNP interaction pairs for EAs, and 6 pairs for AAs associated with breast cancer risk. These promising SNP interaction pairs had an interaction p-value less than 0.05, far less than the p-values of the 2 constituent SNPs. Also, these promising SNP-SNP interaction pairs are different between races. For example, the EA women with the CC + AT/TT genotype in rs12991495 + rs10196635 (both in DNMT3A) had a higher risk of breast cancer risk than other genotype combinations (Odds ratio [OR]=2.2, p=0.011). On the other hand, the AA women with the TT+AA genotype in the SNP pair of rs2304429 (DNMT3A) + rs2290684 (DNMT1) tend to have a higher breast cancer risk than other genotype combinations in the same pair (OR=4.3, p=0.034). Notably, the individual effects of the two constituent SNPs are not significant (p=0.537 and 0.547). Conclusion: Our findings support that the SNPs in DNMT genes play an essential role in breast cancer risk. SIPI is an excellent tool to evaluate SNP-SNP interactions, which can better predict breast cancer risk. Citation Format: Hui-Yi Lin, L. Joseph Su, Lora J. Rogers, Gail A. Runnells, Ping-Ching Hsu, Shelbie D. Stahr, Tung-Chin Chiang. Interactions of DNMTs genetic variants associated with breast cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1450.
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