Genetic association and computational analysis of MTHFR gene polymorphisms rs1801131 and rs1801133 with breast cancer in the Bangladeshi population.

Methylenetetrahydrofolate reductase (MTHFR) plays a crucial role in regulating one-carbon metabolism. Polymorphisms within the MTHFR gene have been found to increase the risk of breast cancer in different populations. In this study, we evaluated the association of polymorphisms of the MTHFR gene (rs1801133 and rs1801131) with the risk of breast cancer in the Bangladeshi population. This case‒control study included 202 breast cancer patients and 104 healthy controls. After the organic extraction of DNA, genotyping was performed via the PCR-RFLP method. Sanger sequencing was performed to validate the RFLP data. Statistical analyses were performed to evaluate the associations of the polymorphisms. Different computational tools were used to predict the structural and functional consequences of the SNPs. Our study revealed that the MTHFR gene polymorphism rs1801131 is associated with an increased risk of developing breast cancer (p < 0.001, OR = 3.85, 95% CI = 2.06-7.25 for the AC genotype and p < 0.001, OR = 7.82, 95% CI = 2.69-22.05 for the CC genotype). An association was also observed in the dominant model (AC + CC) (p < 0.001, OR = 4.19, 95% CI = 2.28-7.78). For rs1801131, premenopausal status was significantly associated with breast cancer risk (p < 0.001). For rs1801133, no significant association was found with breast cancer risk (p > 0.05, OR = 1.57, 95% CI = 0.90-2.74 for the CT genotype; p > 0.05, OR = 1.35, 95% CI = 0.36-4.92 for the TT genotype). Computational analyses predicted rs1801131 to be tolerated and rs1801133 to be deleterious. Structural analyses demonstrated no significant changes in protein structure but revealed alterations in neighboring interactions according to both bond distances and angles. In conclusion, rs1801131 but not rs1801133 is significantly associated with breast cancer risk in the Bangladeshi population. Moreover, in silico analyses demonstrated changes in the interaction pattern of polymorphic residues with adjacent amino acids.
(© 2024. The Author(s).)