The association between gsto1 polymorphisms and arsenic methylation of prenatal arsenic exposed infants

Tạ Thị Bình Tạ Thị Bình Tạ Thị Bình, Trần Phương Thảo, Nguyễn Khắc Hải, Nguyễn Huy Hoàng

Abstract


The trace element arsenic naturally presents in the environment. Arsenic is the essential factor to the human body at low level, however it causes environmental pollution and have negative effects to health at high level. Recently, arsenic contamination as well as its effects on public health, especially infants and children is increasingly becoming important and serious issues in worldwide. Glutathione S-transferase omega-1 (GSTO1) is a phase II enzymatic detoxification of xenobiotics in variety of animals including humans; to catalyze the arsenic methylation. The difference of urinary arsenic component in each individual may relate to the genetic polymorphism. To evaluate the variations of single nucleotide polymorphisms of GSTO1, PCR-RFLP technology was ultilized. Single nucleotide polymorphisms (SNPs) genotype of 150 cohort blood samples at GSTO1 Thr->Asn (rs15032), GSTO1 Ala->Val (rs11509439) and GSTO1 Ala->Asp (rs4925) were detected. The association between GSTO1 polymorphisms and prenatal arsenic exposure was evaluated by statistical analysis such as SPSS software version 20, t-test and oneway ANOVA. The results showed that GSTO1 Ala->Asp (rs4925) was statistically associated with MMA/iAs (p = 0.041). Differences between ratio of MMA/iAs and genotypes were checked by Tukey-Kramer method, along with oneway ANOVA showed that Individuals taking the AA genotype had higher MMA/ iAs ratio than individuals carrying the CC genotype, with a statistically significant association (p = 0.044), also clearly higher than the individuals carrying AC genotype, significant at p = 0.046. Therefore, it is possible that individuals carrying the AA genotype in the polymorphism have higher arsenic excretion than individuals with CC and AC genotypes

Keywords


Arsenic exposure, GSTO1, PCR-RFLP, single nucleotide polymorphism, statistically analysi

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DOI: https://doi.org/10.15625/1811-4989/15/2/12337