Literature DB >> 25876999

Associations between the polymorphisms of GSTT1, GSTM1 and methylation of arsenic in the residents exposed to low-level arsenic in drinking water in China.

Jinyou Yang1, Li Yan2, Min Zhang3, Yijun Wang4, Chun Wang4, Quanyong Xiang5.   

Abstract

We carry out a study to analyze the relation between polymorphisms of GSTT1, GSTM1 and the capacity of arsenic methylation in a human population exposed to arsenic in drinking water. 230 randomly chose subjects were divided into four subgroups based on the arsenic levels, and then the associations between the polymorphisms of GSTT1, GSTM1 and methylation of arsenic were investigated. The levels of inorganic arsenic (iAs), monomethylated arsenic (MMA), dimethylated arsenic (DMA) and total arsenic (TAs) in urine were higher in males than that in females. Moreover, the levels of iAs and TAs in urine in the subjects with genotype of GSTM1(+) were significantly higher than those with GSTM1(-); the level of DMA in the subjects with GSTT1(+) and GSTM1(+) were higher than those with GSTT1(-) and GSTM1(-), although it is not statistically significant. Secondary methylation index (SMI) was significantly higher in the subjects with genotype of GSTT1(+) than those with GSTT1(-). The levels of TAs in urine, together with the genotypes of GSTT1/GSTM1 were associated with the levels of MMA and DMA. Our results suggested that the polymorphisms of GSTT1 and GSTM1 were associated with the methylation of arsenic, especially the levels of DMA and SMI.

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Year:  2015        PMID: 25876999     DOI: 10.1038/jhg.2015.39

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  26 in total

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9.  Urinary arsenic metabolites in children and adults exposed to arsenic in drinking water in Inner Mongolia, China.

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  5 in total

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2.  Differential metabolism of inorganic arsenic in mice from genetically diverse Collaborative Cross strains.

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3.  GSTM1 and GSTT1 Null Genotype Polymorphisms and Susceptibility to Arsenic Poisoning: a Meta-analysis.

Authors:  Baiming Jin; Siyuan Wan; Michael Boah; Jie Yang; Wenjing Ma; Man Lv; Haonan Li; Kewei Wang
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  5 in total

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