ArticleBMC cancer2026
Association of DNA methyltransferase polymorphisms with breast cancer: a nested case‒control study of the Arkansas Rural Community Health study.
Article in BMC cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundBreast cancer remains the most commonly diagnosed cancer and a leading cause of cancer-related mortality among women in the United States. While many risk factors have been identified, a substantial proportion of breast cancer cases occur in individuals without known risk profiles, underscoring the need to investigate novel genetic and epigenetic contributors. DNA methylation, an epigenetic modification regulated by DNA methyltransferase (DNMT) enzymes, plays a critical role in gene expression and genomic stability.
methodsThis nested case‒control study, conducted within the Arkansas Rural Community Health study (ARCH) cohort, examined the associations between polymorphisms in DNMT1, DNMT3A, and DNMT3B and breast cancer risk. Using TaqMan genotyping and genome-wide association analysis in a sample of 2407 participants (967 cases and 1440 controls), we assessed both individual single-nucleotide polymorphisms (SNPs) and haplotypes.
resultsDNMT3A SNP rs7605753 was significantly associated with increased breast cancer risk according to a recessive model (adjusted odds ratio [aOR]: 1.30; 95% confidence interval [CI]: 1.06, 1.59). Haplotype analysis revealed that DNMT3A haplotype TACGA was associated with increased breast cancer odds compared to the referent haplotype CGCGA (aOR: 1.42; 95% CI: 1.13, 1.79). Stratified analyses indicated that haplotypes CTACGA and CTGCAA were significantly associated with increased breast cancer risk among Black participants, with larger effect estimates than in White participants. No significant associations were observed for DNMT1 or DNMT3B variants.
conclusionsThese findings suggest that genetic polymorphisms in DNMT3A may contribute to breast cancer susceptibility and that racial differences in haplotype distribution and associated risk merit further investigation. Understanding these genetic associations could enhance personalized risk profiling and inform future breast cancer prevention strategies, particularly in understudied and diverse populations.
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