Predicting the development and progression of primary open-angle glaucoma based on the determination of GST gene polymorphisms
DOI:
https://doi.org/10.31288/oftalmolzh201841116Keywords:
primary open-angle glaucoma, GSTP1, GSTM1 and GSTT1 polymorphisms, speed of the development and progressionAbstract
Background: Epidemiological studies have demonstrated that primary open-angle glaucoma (POAG) is a complex multifactorial disease resulting from interaction of risk factors and gene polymorphisms. Previously, we have demonstrated the role of deletion polymorphisms of glutathione-S-transferase (GST) genes in the development and progression of POAG.
Purpose: To predict the speed of POAG development and the speed of POAG progression as early as at patient presentation based on determination of GST gene (GSTТ1, GSTР1 and GSTM1) polymorphisms.
Materials and Methods: Data of 172 patients (344 eyes) diagnosed with stage 1, 2, 3 or 4 POAG, and of 98 control group volunteers (196 eyes) diagnosed with no POAG, were included in the analysis. Two indices, SDPOAG (speed of POAG development, expressed as stage/life year), and SPPOAG (speed of POAG progression, expressed as stage/disease year), were used as measures for assessing speed of the pathological process. Polymorphisms of GSTP1, GSTM1 та GSTT1 were investigated by real-time polymerase chain reaction (PCR) using TaqMan Mutation Detection Assays (Life Technologies, Carlsbad, CA) and Gene Amp® 7500 PCR System (Applied Biosystems, Foster City, CA).
Results and Discussion: We built an algorithm (computer program) for predicting the speed of the development and progression of POAG, with the potential to calculate these indices as early as at presentation. The GSTP1 Ile105Val polymorphism (with the presence of the mutant Val allele) and GSTM1 and GSTT1 deletion polymorphisms contributed more to prediction of dependent variables, SDPOAG and SPPOAG, than others. We found a significant effect of the combination of independent variables in the regression equation on the dependent variable SDPOAG, with a multiple correlation coefficient R of 0.801, a coefficient of determination R2 of 0.622, and an F value of 77.338 at p<0.0001. In addition, the regression equation for prediction for the speed of the progression of POAG had a multiple correlation coefficient R of 0.857, a coefficient of determination R2 of 0.734, and an F value of 73.450 at p<0.0001.
Conclusion: The objectives of the study (i.e., to predict the age of onset of clinical manifestations of POAG and the speed of the development of POAG, with the potential to calculate them as early as at presentation) have been met.
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