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Association of glutathione S-transferases M1 and T1 gene polymorphisms with the risk of metabolic syndrome in an Iranian population
Laleh Rafiee1, Pedram Shokouh2, Hamidreza Roohafza2, Marjan Mansourian3, Shaghayegh Haghjooy Javanmard1
1 Applied Physiology Research Centre, Department of Physiology, Isfahan University of Medical Sciences, Isfahan, Iran
2 Cardiovascular Research Centre, Isfahan Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran
3 Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan, Iran
| Date of Submission | 20-Dec-2014 |
| Date of Acceptance | 23-Feb-2015 |
| Date of Web Publication | 22-Mar-2016 |
Correspondence Address:
Dr. Shaghayegh Haghjooy Javanmard
Physiology Research Centre, Isfahan University of Medical Sciences, Hezarjarib, Isfahan
Iran
 Source of Support: The present study was financially supported by grants
from Physiology Research Centr of the Isfahan University of Medical Sciences, Conflict of Interest: None  | Check |
DOI: 10.4103/2277-9175.179185
Background: Glutathione S-transferases (GSTs) are important factors in cell sensitivity to oxidative stress and susceptibility to cardiometabolic disorders. We aimed to investigate the GSTM1 and T1 gene polymorphisms, as well as their interactions in metabolic syndrome (MetS) patients and healthy individuals in an Iranian population.
Materials and Methods: The study sample comprised of 220 healthy individuals (mean age: 41.9 – 15.1 years) and 165 MetS patients (mean age: 49.7 – 11.5 years). The diagnostic criteria for MetS were defined following the criteria provided by the modified National Cholesterol Education Program Adult Treatment Panel III. Genotyping of GSTM1 and T1 genes were performed using polymerase chain reaction.
Results: Our analyses have shown that neither GSTM1 (odds ratio [OR] =0.89, 95% confidence interval [CI]: 0.59 – 1.33, P = 0.57) nor GSTT1 (OR = 1.26, 95% CI: 0.76 – 2.02, P = 0.38) null genotypes were associated with increased risk. Moreover, no significant differences were observed between various combinations of GST genotypes.
Conclusion: Contrary to our primary hypothesis, what we found disaffirms any kind of association between GSTM1 and T1 polymorphisms and the risk of MetS. However, being the first polymorphism study of GSTs in MetS patients, further studies are required to confirm our results in other populations. Keywords: Gene deletion, genetic polymorphism, glutathione transferase, metabolic syndrome X
How to cite this article:
Rafiee L, Shokouh P, Roohafza H, Mansourian M, Javanmard SH. Association of glutathione S-transferases M1 and T1 gene polymorphisms with the risk of metabolic syndrome in an Iranian population. Adv Biomed Res 2016;5:63 |
How to cite this URL:
Rafiee L, Shokouh P, Roohafza H, Mansourian M, Javanmard SH. Association of glutathione S-transferases M1 and T1 gene polymorphisms with the risk of metabolic syndrome in an Iranian population. Adv Biomed Res [serial online] 2016 [cited 2023 Sep 27];5:63. Available from: https://www.advbiores.net/text.asp?2016/5/1/63/179185 |
| Introduction | |  |
Redox state of cells is the balance between oxidation/reduction reactions that is determined by the rate of reactive oxygen species production and antioxidant capacity of cells. Impairment of this balance in favor of oxidative processes is called oxidative stress (OS). While reactive oxygen species play crucial roles in multiple physiologic systems, under the conditions of OS, they can damage redox-sensitive molecules and consequently, interfere with cell signaling and gene regulation systems.[1] The contribution of OS in the pathophysiology of several human diseases such as diabetes and atherosclerosis is well-documented.[2]
The glutathione (GSH) buffer system along with superoxide dismutase is the main intracellular antioxidant.[3] Apart from its antioxidant activities, GSH has an essential role in the detoxification of xenobiotics through the action of glutathione S-transferases (GSTs).[4] GSTs are a multi-gene super family of dimeric phase II enzymes that catalyze the production of thioether bond between the cysteine on the GSH and an electrophilic compound. Eight classes of cytosolic GSTs are recognized in mammalian cells consisted of alpha, kappa, mu, omega, pi, sigma, theta, and zeta; each are divided into subclasses.[5]
Polymorphisms of GSTM1 (a member of class mu; MIM: 138350) and GSTT1 (a member of class theta; MIM: 600436) exist in all human populations.[6] Different alleles are found at the locus of GSTM1 (1P13.3) including gene deletion (GSTM1-0) and functional mutations (GSTM1a and GSTM1b).[7] The same is the case for GSTT1 at 22q11.2, for which GSTT1-0 allele represents deletions of the gene.[8] GSTM1 and T1 genes deletions result in a loss of enzymatic activity.[9] It has been demonstrated that GST null-genotypes are important factors in cell sensitivity to OS and susceptibility to cardiovascular and metabolic disorders.[10],[11]
A growing body of evidence indicates a link between OS and all individual components of the metabolic syndrome (MetS).[12],[13],[14] MetS is a cluster of metabolic and cardiovascular risk factors assumed to be caused by two major etiologies: Abdominal adiposity and insulin resistance.[15] It is believed that genetic and environmental factors both play roles in the development of the syndrome. Although the heritability of MetS is not thoroughly investigated, it is clear that all components of the syndrome are strongly heritable.[16] The association of polymorphisms of alpha-1 (A1), mu-1 (M1), P1, and T1 subclasses with some of the MetS components and complications have already been studied.[11],[17],[18],[19]
To the best of our knowledge, there is no published study investigating the distribution of GSTM1 and T1 null-genotypes in MetS patients to date. Therefore, we made an effort to assess GSTM1 and T1 polymorphisms and their interactions in Iranian MetS patients and to compare them with non-MetS controls.
| Materials and Methods | | |
Study population
The present study was performed in Physiology Research Center at the Isfahan University of Medical Sciences, between December 2010 and May 2011. Study subjects were randomly chosen among the participants of Isfahan Cohort Study (ICS).[20] The ICS participants aged between 18 and 65 years were all randomly selected from the community of three counties in central Iran in the first stage of Isfahan Healthy Heart Program (IHHP). Methodological details of IHHP could be found elsewhere.[21]
Enrolled subjects who were identified as having MetS were regarded as cases and others as controls. MetS was defined following the criteria provided by the modified National Cholesterol Education Program Adult Treatment Panel III adjusted to indices of obesity for Asians.[22] Participants with any of the followings were not eligible for the study: Diabetes mellitus, neoplastic disorders, any debilitating medical condition, and pregnancy or lactation. The study protocol was in compliance with the declaration of Helsinki and approved by the Ethics Committee of Isfahan University of Medical Sciences. An informed written consent was obtained from all participants.
Demographic and laboratory assays
Venous blood samples were obtained after at least 12 h of overnight fasting and collected into ethylene diamine tetra acetic acid tubes. Immediately after collection, whole blood was stored at-20°C until use. Serum total, low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), and triglycerides levels were measured by Hitachi 902 auto-analyzer (Japan) using Pars Azmoon (Iran) analytical kits. Plasma fasting glucose measurement was done using the same machine and Biosystem (France) kits. All the measurements were carried out in Isfahan Cardiovascular Research Institute laboratory, which is continuously controlled by the National Reference Lab of Iran (Tehran-Iran) and INSTAND e.V. Laboratory (Düsseldorf-Germany). Anthropometric variables were measured according to standard methods by a trained nurse by means of a calibrated scale and an anthropometer and a calibrated scale. Blood pressure was measured in the right arm at sitting position after a 10-min rest using a standard mercury sphygmomanometer. The body mass index (BMI) was calculated using the formula: Weight (kg)/height 2 (m 2).
Genotyping
Genomic deoxyribonucleic acid (DNA) for polymerase chain reaction (PCR) was isolated from whole blood using blood mini kit (PrimePrep Genomic DNA Isolation Kit, Genet Bio Inc.,). According to the manufacture protocol, Lysis buffer was added to 100 µl of whole blood and incubated in 560 c, after the addition of ethanol, supernatant was transferred to spin columns then washed twice; at the end the DNA was eluted.
To determine the GSTT1 and GSTM1 genotypes of the subjects, PCR amplification was performed using the following primers: GSTT1 forward primer 5′-TTC CTT ACT GGT CCT CAC ATC TC-3′, and reverse primer 5′-TCA CCG GAT CAT GGC CAG CA-3′; GSTM1 forward primer 5' AGA CAG AAG AGG AGA AGA TTC 3', and reverse primer 5' TCC AAG TAC TTT GGC TTC AGT 3'. Albumin gene sequence amplification was used as an internal control in the PCR reactions, for which the primers were: Forward primer 5′-GCC CTC TGC TAA CAA GTC CTA C-3′, and reverse primer 5′-GCC CTA AAA AGA AAA TCG CCA ATC-3′. Each 25 μl of PCR reaction contained 50-100 ng of genomic DNA, 0.25 mM of each dNTP, 10 pmol of each primer, 1 U Taq DNA polymerase, 1.5 mM MgCl2, and 10X PCR buffer (Cinagen Co., Iran). The PCR reaction conditions were explained previously.[23] The absence of amplified product was considered as the homozygous null genotype of GSTM1 and T1. It is noteworthy that this technique cannot distinguish between heterozygote and homozygote carriers of the positive genotypes. Successful amplification by albumin specific primer confirmed the proper function of the PCR reaction. Samples with ambiguous results were re-tested, and a random 15% of all tests were repeated, no discrepancy was discovered upon replicate testing.
Statistical analysis
The data were coded and stored in a computer database. Statistical analysis was performed using the Statistical Package for Social Sciences software version 15.0 (SPSS Inc., Chicago, Illinois, USA). Comparisons of selected quantitative characteristics between cases and controls were done by independent t-test. The relative associations between GST genotypes and MetS risk were assessed using multiple logistic regression method to calculate odds ratios (ORs) and 95% of confidence intervals (CIs). For all analyses, statistical significance was assessed at a level of 0.05 (2-tailed).
| Results | | |
A total of 385 individuals (165 MetS patients and 220 controls) were genotyped for the two GST subclasses. Comparison of the two groups considering age, sex, BMI, waist circumference, serum triglyceride, total cholesterol, HDL-C, LDL-C, fasting plasma glucose, and systolic and diastolic blood pressures showed statistically significant differences [Table 1]. | Table 1: Comparison of characteristics of individuals with and without MetSa,b
Click here to view |
In order to show the influence of the absence of GSTM1 and T1 expression on the assessed variables, the differences between individuals with various GST genotypes were compared. As could be seen in [Table 2], no pronounced differences were found between groups. | Table 2: Differences in selected characteristics of participants based on GST genotype
Click here to view |
Detailed genotype distributions are shown in [Table 3]. The prevalence of GSTM1 null genotype was 46.7% in the patients and 52.3% in the control group. As shown, the differences were not significant (OR = 0.89, 95% CI: 0.59–1.33, P = 0.57). GSTT1 null genotype was detected in 75.5% of the controls and 75.8% of the patients. In the same manner to the M1 subclass, the difference between two groups never reached a significant level (OR = 1.26, 95% CI: 0.76–2.02, P = 0.38). | Table 3: Association between polymorphisms of GSTM1 and T1 and risk of MetS
Click here to view |
To determine whether different combinations of genotypes from the GST genes are involved in the development of the syndrome, we analyzed the association between the combinations of genotypes and the risk of MetS which is presented in [Table 4]. According to the table, there were no associations between the combinations of genotypes and the risk of MetS.
| Discussion | | |
The prevalence of null genotypes of GSTM1 and T1 among the subjects of the present study was in accordance with our previous report from another Iranian population.[23] Unexpectedly, we failed to track any anthropometric and/or metabolic influences caused by the polymorphism of two subclasses of GST genes. Furthermore, in our multivariate analyses, no association was found between GSTM1 and T1 polymorphisms and the risk of MetS regardless of age and sex. Whether this failure was a consequence of our sample size or not is a matter of question, which awaits elucidation by future larger-sample studies.
The essential role of OS in dysregulation of adipocytokines and the development of insulin resistance as the first level, and MetS as the second level of metabolic abnormalities is previously demonstrated.[24] GSTs as the main enzymes of glutathione buffer system play crucial roles in maintaining the redox balance of cells. Therefore, their enzymatic inactivity caused by gene deletions should be associated with the consequences of OS. Pursuant to this justification, the investigation of the association of GST polymorphisms with the risk of the components and construct of the MetS sounds reasonable.
Up to this point, no more than a handful of studies have implemented to investigate the relationship between GST polymorphisms and some MetS components. Oniki et al. have reported that the risk of hypertension is increased in carriers of nonfunctional alleles of GSTA1, GSTM1, and GSTT1.[18] Similarly, double deletion genotypes of the GSTM1 and T1 were reported to have a significant association with hypertriglyceridemia and low HDL-C levels.[17] Another study by Yalin et al. has concluded that GSTM1 null-genotype is significantly associated with diabetes mellitus in a Turkish population.[11] It should be noted that even in this limited number of relevant studies, some extent of discrepancy exists. As Delles et al. could not find any association between GSTM1 null-genotype and hypertension.[25]
Contrary to our supposition, our findings have shown no relationship between MetS and GSTM1 and/or GSTT1 null-genotypes. These findings might be explained by the multifactorial and polygenic nature of this syndrome. As known, MetS is a constellation of metabolic abnormalities; each dealing with multiple genetic variations. Accordingly, each individual genetic variant generally has only a modest effect. Besides, environmental factors and life-style, which were not assessed in this study, may play important roles in the expression of syndrome traits. This fact along with the genetic heterogeneity of human populations, make it possible to obtain disparate results in similar polymorphism studies in different populations.
Here, another point that has the merit to be mentioned is the existence of a fundamental disagreement about the concept of the MetS. Some authors believe that the cardiovascular risk associated with the MetS do not exceed the risk explained by the sum of its components. This notion was supported by the results of three studies [26],[27],[28] when adjusted for the specific components of the syndrome.[29] Considering of these considerable pieces of evidence, these questions may arise: Are the components of the syndrome genetically and pathologically related? Could polymorphism of a gene be related to some components but not with the whole syndrome? More investigations are surely, required before these questions could be answered. Clarification of these types of questions is essential before getting any conclusion from the studies of similar design.
The current study is subject to some limitations. First is our limited sample size. Maybe significant associations could be found in greater samples. Second is that the life-style factors were not assessed in this study. As mentioned before, these factors have substantial effects on the severity and age of onset of phenotypic traits of the MetS.
To our knowledge, this is the first polymorphism study of GSTs in MetS patients. Hence, it could be considered as an outset of future studies. Replicated results in other populations would help in better understanding of the genetic basis of MetS and identifying new targets for pharmacologic therapy.
| References | | |
| 1. | Beckman KB, Ames BN. Oxidative decay of DNA. J Biol Chem 1997;272:19633-6.  |
| 2. | Vendemiale G, Grattagliano I, Altomare E. An update on the role of free radicals and antioxidant defense in human disease. Int J Clin Lab Res 1999;29:49-55. |
| 3. | Jefferies H, Coster J, Khalil A, Bot J, McCauley RD, Hall JC. Glutathione. ANZ J Surg 2003;73:517-22. |
| 4. | Diaz Vivancos P, Wolff T, Markovic J, Pallardó FV, Foyer CH. A nuclear glutathione cycle within the cell cycle. Biochem J 2010;431:169-78. |
| 5. | Awasthi YC, Sharma R, Singhal SS. Human gluthatione S-transferases: Mini review. Int J Biochem 1994;26:295-308. |
| 6. | Saadat M, Zendeh-Boodi Z. Association between genetic polymorphism of GSTT1 and depression score in individuals chronically exposed to natural sour gas. Neurosci Lett 2008;435:65-8. |
| 7. | Ryberg D, Skaug V, Hewer A, Phillips DH, Harries LW, Wolf CR, et al. Genotypes of glutathione transferase M1 and P1 and their significance for lung DNA adduct levels and cancer risk. Carcinogenesis 1997;18:1285-9. |
| 8. | Webb G, Vaska V, Coggan M, Board P. Chromosomal localization of the gene for the human theta class glutathione transferase (GSTT1). Genomics 1996;33:121-3. |
| 9. | Pemble S, Schroeder KR, Spencer SR, Meyer DJ, Hallier E, Bolt HM, et al. Human glutathione S-transferase theta (GSTT1): CDNA cloning and the characterization of a genetic polymorphism. Biochem J 1994;300 (Pt 1):271-6. |
| 10. | Abu-Amero KK, Al-Boudari OM, Mohamed GH, Dzimiri N. T null and M null genotypes of the glutathione S-transferase gene are risk factor for CAD independent of smoking. BMC Med Genet 2006;7:38. |
| 11. | Yalin S, Hatungil R, Tamer L, Ates NA, Dogruer N, Yildirim H, et al. Glutathione S-transferase gene polymorphisms in Turkish patients with diabetes mellitus. Cell Biochem Funct 2007;25:509-13. |
| 12. | Furukawa S, Fujita T, Shimabukuro M, Iwaki M, Yamada Y, Nakajima Y, et al. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest 2004;114:1752-61. |
| 13. | Touyz RM. Reactive oxygen species, vascular oxidative stress, and redox signaling in hypertension: What is the clinical significance? Hypertension 2004;44:248-52. |
| 14. | Houstis N, Rosen ED, Lander ES. Reactive oxygen species have a causal role in multiple forms of insulin resistance. Nature 2006;440:944-8. |
| 15. | Cornier MA, Dabelea D, Hernandez TL, Lindstrom RC, Steig AJ, Stob NR, et al. The metabolic syndrome. Endocr Rev 2008;29:777-822. |
| 16. | Song Q, Wang SS, Zafari AM. Genetics of the metabolic syndrome. Hospital Physician 2006;42:51-61. |
| 17. | Maciel SS, Pereira Ada C, Silva GJ, Rodrigues MV, Mill JG, Krieger JE. Association between glutathione S-transferase polymorphisms and triglycerides and HDL-cholesterol. Atherosclerosis 2009;206:204-8. |
| 18. | Oniki K, Hori M, Takata K, Yokoyama T, Mihara S, Marubayashi T, et al. Association between glutathione S-transferase A1, M1 and T1 polymorphisms and hypertension. Pharmacogenet Genomics 2008; 18:275-7. |
| 19. | Martin NJ, Collier AC, Bowen LD, Pritsos KL, Goodrich GG, Arger K, et al. Polymorphisms in the NQO1, GSTT and GSTM genes are associated with coronary heart disease and biomarkers of oxidative stress. Mutat Res 2009;674:93-100. |
| 20. | Sarrafzadegan N, Talaei M, Sadeghi M, Kelishadi R, Oveisgharan S, Mohammadifard N, et al. The Isfahan cohort study: Rationale, methods and main findings. J Hum Hypertens 2011;25:545-53. |
| 21. | Sarraf-Zadegan N, Sadri G, Malek Afzali H, Baghaei M, Mohammadi Fard N, Shahrokhi S, et al. Isfahan Healthy Heart Programme: A comprehensive integrated community-based programme for cardiovascular disease prevention and control. Design, methods and initial experience. Acta Cardiol 2003;58:309-20. |
| 22. | Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome: An American Heart Association/National Heart, Lung, and Blood Institute Scientific Statement. Circulation 2005;112:2735-52. [ PUBMED] |
| 23. | Rafiee L, Saadat I, Saadat M. Glutathione S-transferase genetic polymorphisms (GSTM1, GSTT1 and GSTO2) in three Iranian populations. Mol Biol Rep 2010;37:155-8. |
| 24. | Grattagliano I, Palmieri VO, Portincasa P, Moschetta A, Palasciano G. Oxidative stress-induced risk factors associated with the metabolic syndrome: A unifying hypothesis. J Nutr Biochem 2008;19:491-504. |
| 25. | Delles C, Padmanabhan S, Lee WK, Miller WH, McBride MW, McClure JD, et al. Glutathione S-transferase variants and hypertension. J Hypertens 2008;26:1343-52. |
| 26. | McNeill AM, Rosamond WD, Girman CJ, Golden SH, Schmidt MI, East HE, et al. The metabolic syndrome and 11-year risk of incident cardiovascular disease in the atherosclerosis risk in communities study. Diabetes Care 2005;28:385-90. |
| 27. | Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, et al. Metabolic syndrome and risk of incident cardiovascular events and death: A systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol 2007;49:403-14. |
| 28. | Sattar N, Gaw A, Scherbakova O, Ford I, O'Reilly DS, Haffner SM, et al. Metabolic syndrome with and without C-reactive protein as a predictor of coronary heart disease and diabetes in the West of Scotland Coronary Prevention Study. Circulation 2003;108:414-9. |
| 29. | Inchiostro S, Fadini GP, de Kreutzenberg SV, Citroni N, Avogaro A. Is the metabolic syndrome a cardiovascular risk factor beyond its specific components? J Am Coll Cardiol 2007;49:2465. [ PUBMED] |
[Table 1], [Table 2], [Table 3], [Table 4]
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