Molecular Study of MTHFR C677T and MTR A2756G Polymorphisms in Alcohol and Tobacco Users from Eastern Uttar Pradesh, India

Abstract

Background: Folate-mediated one-carbon metabolism supports nucleotide biosynthesis and methylation reactions. Functional variants in folate-pathway genes such as methylenete- trahydrofolate reductase (MTHFR) C677T and methionine synthase (MTR) A2756G can alter enzyme activity, affect homocysteine remethylation, and modulate methylation po- tential. Alcohol consumption and tobacco use may further perturb this pathway through nutritional and oxidative-stress mechanisms.

Methods: We analyzed an Eastern Uttar Pradesh cohort of N = 981 adults (age 18– 88 years). Controls were pooled RANDOM and CONTROL individuals (N = 621) and cases were pooled substance users (N = 360) comprising TOBACCO (N = 232), ALCOHOL (N = 30), and ALCOHOL TOBACCO (N = 98). Genotypes were available from PCR-RFLP assays. We computed genotype and minor-allele frequencies, tested Hardy–Weinberg equilibrium (HWE) in controls, performed chi-square association tests, reported odds ratios (ORs) with 95% confidence intervals (CIs), and fitted additive logistic regression adjusted for age and sex.

Results: In controls, minor-allele frequencies were f_T = 0.107 for MTHFR C677T and f_G = 0.099 for MTR A2756G. Pooled cases showed higher minor-allele frequencies (f_T = 0.140 and f_G = 0.136, respectively). Allelic association tests indicated increased odds for the minor allele in cases (MTHFR: OR_T = 1.36 [95% CI 1.03–1.79], p = 0.035; MTR: OR_G = 1.43 [1.08–1.90], p = 0.015). HWE held in controls for MTHFR (p = 0.227) but deviated for MTR (p = 0.008). In age/sex-adjusted additive logistic regression, MTHFR remained associated (adjusted OR per T allele = 1.43, p = 0.015) whereas MTR attenuated (adjusted OR per G allele = 1.24, p = 0.144). Subgroup analyses suggested strongest signals in alcohol-only users (small N).

Conclusions: Variant alleles in one-carbon metabolism genes were modestly enriched among substance users in this Eastern UP dataset, with strongest signals in the alcohol- only subgroup. Replication with biomarker-informed phenotyping and quantitative exposure measures is needed to confirm and interpret these findings.