Genetic Polymorphism in Glutathione Transferases (GST): Population distribution of GSTM1, T1, and P1 conjugating activity

Abstract

Glutathione transferases (GST) catalyze the conjugation of glutathione (GSH) with electrophiles, many of which may otherwise interact with protein or DNA. In select cases such as halogenated solvents, GST-mediated conjugation may lead to a more toxic or mutagenic metabolite. Polymorphisms that exert substantial effects on GST function were noted in human populations for several isozymes. This analysis focuses on three well-characterized isozymes, GSTM1, T1, and P1, in which polymorphisms were extensively studied with respect to DNA adducts and cancer in molecular epidemiologic studies. The current review and analysis focused upon how polymorphisms in these GST contributed to population variability in GST function. The first step in developing this review was to characterize the influence of genotype on phenotype (enzyme function) and the frequency of the polymorphisms across major population groups for all three GST. This information was then incorporated into Monte Carlo simulations to develop population distributions of enzyme function. These simulations were run separately for GSTM1, T1, and P1, and also for the combination of these isozymes, to assess the possibility of overlapping substrate specificity. Monte Carlo simulations indicated large interindividual variability for GSTM1 and T1 due to the presence of the null (zero activity) genotype, which is common in all populations studied. Even for GSTM1 or T1 non-null individuals, there was considerable interindividual variability with a bimodal distribution of enzyme activity evident. GSTP1 polymorphisms are associated with somewhat less variability due to the absence of null genotypes. However, in all cases simulated, the estimated variability is sufficiently large to warrant consideration of GST function distributions in assessments involving GST-mediated activation or detoxification of xenobiotics. Ideally, such assessments would involve physiologically based toxicokinetic (PBTK) modeling to assess population variability in internal dose.