Independent, Diplotype and Haplotype Association Analyses of the Selected MTHFR SNPs with the Risk of Breast Cancers in a South-Asian Population

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Abstract

PURPOSE MTHFR is a pivotal enzyme in the folic acid cycle. In specific populations, two functional SNPs in the encoding gene, i.e. rs1801133 (677C/T) and rs1801131 (1298A/C), have shown associations with different diseases including cancers. In the present study, the role of these SNPs was analyzed in breast cancer cases from Pakistani population. PARTICIPANTS AND METHODS The pilot study includes 187 participants with 124 breast cancer patients and 63 matched individuals as controls. PCR-RFLP methods validated by Sanger sequencing were used for the polymorphic investigations. Hardy-Weinberg Equilibrium was tested by chi-squared goodness-of-fit test. Independent and combined associations were evaluated by Cochran-Armitage trend-test. Semi-parameteric haplotype analysis was carried out and odds ratios with 95% confidence interval were tabulated. Linkage disequilibrium between two loci was calculated. p-values <0.05 were significant. RESULTS Both MTHFR 677C/T and MTHFR 1298A/C SNPs were in Hardy-Weinberg Disequilibium. Cochran-Armitage trend test showed lack of independent associations of these SNPs with the risk for breast cancers. The diplotype analysis revealed that 677CC+1298AC increased the risk of breast cancers significantly [OR: 2.553 (95% CI: 1.177-5.541)], while 677CT+1298AA had a protective effect [OR: 0.537 (95% CI: 0.404-0.713)]. Haplotype analysis did not show any significant association. Interestingly, despite the proximity, these loci were not linked (r 2 = 0.042 and 0.046 in cases and controls, respectively). CONCLUSION Here, we report association analysis of two putative candidate SNP markers in the MTHFR gene with breast cancers in a South-Asian population. To the best of our knowledge, two diplotype combinations show unique associations with breast cancer susceptibility in this population, which have not been reported earlier. The study implies translational potentials of these polymorphisms for breast cancer management.

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last seen: 2026-05-19T01:45:01.086888+00:00