Genetic and biochemical investigation of the gamma-glutamylcyclotransferase role in predisposition to type 2 diabetes mellitus

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Abstract

Background. Imbalance in the system of redox homeostasis is an important link in the pathogenesis of type 2 diabetes (T2D). Gamma-glutamyl cyclotransferase is an antioxidant defense enzyme directly involved in the metabolism of glutathione, an endogenous antioxidant.

The aim of the study was to examine the association of single nucleotide polymorphisms (SNP) rs38420 (G > A), rs4270 (T > C), rs6462210 (C > T) and rs28679 (G > A) in GGCT gene with the risk of developing T2D.

Materials and Methods. The study included 1022 T2D patients and 1064 healthy volunteers. Genotyping of GGCT gene loci was performed using iPLEX technology on a MassARRAY Analyzer 4 genome time-of-flight mass spectrometer (Agena Bioscience).

Results. As a result, we identified for the first time the association of SNP rs4270 in the GGCT gene with the risk of T2D in the Russian population. We have also established genetic and environmental interactions associated with predisposition to the disease: protective effect of gamma-glutamyl cyclotransferase gene was observed only in non-smokers under condition of daily consumption of fresh vegetables and fruits, whereas in persons with insufficient consumption of plant foods, as well as in all smoking patients protective effect of GGCT was not observed. In patients with T2D, the level of hydrogen peroxide and glutathione monomer was sharply increased compared to the controls. SNP rs4270 was also found to be associated with elevated levels of reduced glutathione in the plasma of type 2 diabetics.

Conclusion. Thus, for the first time it was established that polymorphic locus rs4270 in the GGCT gene is associated with a predisposition to T2D, but its relationship with the disease is modulated by smoking and fresh plant foods consumption.

About the authors

Iuliia E. Azarova

Kursk State Medical University

Author for correspondence.
Email: azzzzar@yandex.ru
ORCID iD: 0000-0001-8098-8052
SPIN-code: 9173-3698
Scopus Author ID: 57200117409
ResearcherId: S-7266-2018

MD, PhD, Associate Professor of Department of Biological Chemistry of KSMU, Head of Laboratory of Biochemical Genetics and Metabolomics of Research Institute for Genetic and Molecular Epidemiology

Russian Federation, Kursk

Elena Yu. Klyosova

Kursk State Medical University

Email: ecless@yandex.ru
ORCID iD: 0000-0002-1543-9230
SPIN-code: 5121-7160

Biotechnologist of the Laboratory of Biochemical Genetics and Metabolomics of Research Institute of Genetic and Molecular Epidemiology of KSMU

Russian Federation, Kursk

Mikhail I. Churilin

Kursk State Medical University

Email: mpmi2@yandex.ru
ORCID iD: 0000-0002-6064-986X
SPIN-code: 7728-6220
ResearcherId: 779606

Assistant Lecturer of Department of Infectious Diseases

Russian Federation, Kursk

Tatiana A. Samgina

Kursk State Medical University

Email: tass@list.ru
ORCID iD: 0000-0002-7781-3793
SPIN-code: 9973-9738

MD, PhD, Associate Professor, Associate Professor of Department of Surgical Diseases No. 2

Russian Federation, Kursk

Alexander I. Konoplya

Kursk State Medical University

Email: konoplya51@mail.ru
ORCID iD: 0000-0003-4748-8405
SPIN-code: 9631-2390
Scopus Author ID: 6602518934
ResearcherId: H-2197-2013

MD, PhD, Professor, Professor of Department of Biological Chemistry

Russian Federation, Kursk

Alexey V. Polonikov

Kursk State Medical University

Email: polonikov@rambler.ru
ORCID iD: 0000-0001-6280-247X
SPIN-code: 6373-6556
Scopus Author ID: 6506508435
ResearcherId: R-7537-2016

MD, PhD, Professor, Professor of Department of Biology, Medical Genetics and Ecology, Head of Laboratory of Statistical Genetics and Bioinformatics of Research Institute for Genetic and Molecular Epidemiology

Russian Federation, Kursk

References

  1. Cho NH, Shaw JE, Karuranga S, et al. IDF IDF Diabetes atlas: global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018;138:271-281. https://doi.org/10.1016/j.diabres.2018.02.023.
  2. Дедов И.И., Шестакова М.В., Викулова О.К. и др. Сахарный диабет в Российской Федерации: распространенность, заболеваемость, смертность, параметры углеводного обмена и структура сахароснижающей терапии по данным федерального регистра сахарного диабета, статус 2017 г. // Сахарный диабет. – 2018. – Т. 21. – № 3. – С. 144-159. [Dedov II, Shestakova MV, Vikulova OK, et al. Diabetes mellitus in Russian Federation: prevalence, morbidity, mortality, parameters of glycaemic control and structure of glucose lowering therapy according to the Federal Diabetes Register, status 2017. Diabetes mellitus. 2018;21(3):144-159. (In Russ.)]. https://doi.org/10.14341/dm9686.
  3. Buniello A, MacArthur JAL, Cerezo M, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 2019;47(D1):D1005-D1012. https://doi.org/10.1093/nar/gky1120.
  4. Shah M, Vella A. What is type 2 diabetes? Medicine. 2014;42(12):687-691. https://doi.org/10.1016/j.mpmed.2014.09.013.
  5. Defronzo RA. Banting Lecture. From the triumvirate to the ominous octet: a new paradigm for the treatment of type 2 diabetes mellitus. Diabetes. 2009;58(4):773-795. https://doi.org/10.2337/db09-9028.
  6. Newsholme P, Cruzat VF, Keane KN, et al. Molecular mechanisms of ROS production and oxidative stress in diabetes. Biochem J. 2016;473(24):4527-4550. https://doi.org/10.1042/BCJ20160503C.
  7. Malik VS, Popkin BM, Bray GA, et al. Sugar-sweetened beverages, obesity, type 2 diabetes mellitus, and cardiovascular disease risk. Circulation. 2010;121(11):1356-1364. https://doi.org/10.1161/CIRCULATIONAHA.109.876185.
  8. Cederberg H, Stančáková A, Kuusisto J, et al. Family history of type 2 diabetes increases the risk of both obesity and its complications: is type 2 diabetes a disease of inappropriate lipid storage? J Intern Med. 2015;277(5):540-551. https://doi.org/10.1111/joim.12289.
  9. Orlowski M, Meister A. The gamma-glutamyl cycle: a possible transport system for amino acids. Proc Proc Natl Acad Sci USA. 1970;67(3): 1248-1255. https://doi.org/10.1073/pnas.67.3. 1248.
  10. Azarova I, Bushueva O, Konoplya A, Polonikov A. Glutathione S-transferase genes and the risk of type 2 diabetes mellitus: role of sexual dimorphism, gene-gene and gene-smoking interactions in disease susceptibility. J Diabetes. 2018;10(5):398-407. https://doi.org/10.1111/1753-0407.12623.
  11. Азарова Ю.Э., Клесова Е.Ю., Конопля А.И. Роль полиморфизмов генов глутаматцистеинлигазы в развитии сахарного диабета 2 типа у жителей Курской области // Научный результат. Медицина и фармация. – 2018. – Т. 4. – № 1. – C. 39-52. [Azarova YuE, Klyosova EYu, Konoplya AI. The role of polymorphisms of glutamate-cysteine ligase in type 2 diabetes mellitus susceptibility in Kursk population. Research result. Medicine and pharmacy. 2018;4(1): 39-52. (In Russ.)]. https://doi.org/10.18413/ 2313-8955-2018-4-1-39-52.
  12. Organization WT. Global report on diabetes: executive summary (No. WHO/NMH/NVI/16.3). World Health Organization; 2016. https://doi.org/10.30875/3fa8639a-en.
  13. Xu Z, Taylor JA. SNPinfo: integrating GWAS and candidate gene information into functional SNP selection for genetic association studies. Nucleic Acids Res. 2009;37(Web Server Issue):W600-605. https://doi.org/10.1093/nar/gkp290.
  14. Пономаренко И.В. Отбор полиморфных локусов для анализа ассоциаций при генетико-эпидемиологических исследованиях // Научный результат. Медицина и фармация. – 2018. – Т. 4. – № 2. – C. 40-54. [Ponomarenko IV. Selection of polymorphic loci for association analysis in genetic-epidemiological studies. Research result. Medicine and pharmacy. 2018;4(2):40-54. (In Russ.)]. https://doi.org/10.18413/2313-8955-2018-4-2-0-5.
  15. Skol AD, Scott LJ, Abecasis GR, Boehnke M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet. 2006;38(2):209-213. https://doi.org/10.1038/ng1706.
  16. Solé X, Guinó E, Valls J, et al. SNPStats: a web tool for the analysis of association studies. Bioinformatics. 2006;22(15):1928-1929. https://doi.org/10.1093/bioinformatics/btl268.
  17. Hunt SE, McLaren W, Gil L, et al. Ensembl variation resources. Database (Oxford). 2018;2018. https://doi.org/10.1093/database/bay119.
  18. Liu Y, Hyde AS, Simpson MA, Barycki JJ. Emerging regulatory paradigms in glutathione metabolism. Adv Cancer Res. 2014;122:69-101. https://doi.org/10.1016/B978-0-12-420117-0.00002-5.
  19. Bachhawat AK, Yadav S. The glutathione cycle: glutathione metabolism beyond the γ-glutamyl cycle. IUBMB Life. 2018;70(7):585-592. https://doi.org/10.1002/iub.1756.
  20. Kageyama S, Ii H, Taniguchi K, et al. Mechanisms of tumor growth inhibition by depletion of γ-glutamylcyclotransferase (GGCT): a novel molecular target for anticancer therapy. Int J Mol Sci. 2018;19(7). pii: E2054. https://doi.org/10.3390/ijms19072054.
  21. Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607-D613. https://doi.org/10.1093/nar/gky1131.
  22. The Gene Ontology Consortium. The gene ontology resource: 20 years and still going strong. Nucleic Acids Res. 2019;47(D1):D330-D338. https://doi.org/10.1093/nar/gky1055.
  23. Lin Z, Xiong L, Zhou J, et al. γ-Glutamylcyclotransferase knockdown inhibits growth of lung cancer cells through g0/g1 phase arrest. Cancer Biother Radiopharm. 2015;30(5): 211-216. https://doi.org/10.1089/cbr.2014. 1807.
  24. Zhang W, Chen L, Xiang H, et al. Knockdown of GGCT inhibits cell proliferation and induces late apoptosis in human gastric cancer. BMC Biochem. 2016;17(1):19. https://doi.org/10.1186/s12858-016-0075-8.
  25. Dong J, Zhou Y, Liao Z, et al. Role of γ-glutamyl cyclotransferase as a therapeutic target for colorectal cancer based on the lentivirus-mediated system. Anticancer Drugs. 2016;27(10):1011-1020. https://doi.org/10.1097/CAD.0000000000000407.
  26. Matsumura K, Nakata S, Taniguchi K, et al. Depletion of γ-glutamylcyclotransferase inhibits breast cancer cell growth via cellular senescence induction mediated by CDK inhibitor upregulation. BMC Cancer. 2016;16(1):748. https://doi.org/10.1186/s12885-016-2779-y.
  27. GTex Portal. Current Release (V8) [cited 2019 August 25]. Available from: https://www.gtexportal.org.
  28. Gaunt TR, Shihab HA, Hemani G, et al. Systematic identification of genetic influences on methylation across the human life course. Genome Biol. 2016;17:61. https://doi.org/10.1186/s13059-016-0926-z.
  29. Zuo C, Shin S, Keleş S. atSNP: transcription factor binding affinity testing for regulatory SNP detection. Bioinformatics. Bioinformatics. 2015;31(20):3353-3355. https://doi.org/10.1093/bioinformatics/btv328.
  30. Gerber PA, Rutter GA. The role of oxidative stress and hypoxia in pancreatic beta-cell dysfunction in diabetes mellitus. Antioxid Redox Signal. 2017;26(10):501-518. https://doi.org/10.1089/ars.2016.6755.
  31. Inoguchi T, Li P, Umeda F, et al. High glucose level and free fatty acid stimulate reactive oxygen species production through protein kinase C – dependent activation of NAD(P)H oxidase in cultured vascular cells. Diabetes. 2000;49(11):1939-1945. https://doi.org/10. 2337/diabetes.49.11.1939.
  32. Brownlee M. A radical explanation for glucose-induced beta cell dysfunction. J Clin Invest. 2003;112(12):1788-1790. https://doi.org/ 10.1172/jci200320501.
  33. Lagman M, Ly J, Saing T, et al. Investigating the causes for decreased levels of glutathione in individuals with type II diabetes. PLoS One. 2015;10(3):e0118436. https://doi.org/10.1371/journal.pone.0118436.
  34. Halliwell B, Gutteridge J. Free radicals in biology and medicine. Oxford University Press Oxford; 1999.
  35. Carter P, Gray LJ, Troughton J, et al. Fruit and vegetable intake and incidence of type 2 diabetes mellitus: systematic review and meta-analysis. BMJ. 2010;341:c4229. https://doi.org/10.1136/bmj.c4229.
  36. Boeing H, Bechthold A, Bub A, et al. Critical review: vegetables and fruit in the prevention of chronic diseases. Eur J Nutr. 2012;51(6):637-663. https://doi.org/10.1007/s00394-012-0380-y.
  37. Cooper AJ, Sharp SJ, Lentjes MA, et al. A prospective study of the association between quantity and variety of fruit and vegetable intake and incident type 2 diabetes. Diabetes Care. 2012;35(6):1293-1300. https://doi.org/10.2337/dc11-2388.
  38. Muraki I, Imamura F, Manson JE, et al. Fruit consumption and risk of type 2 diabetes: results from three prospective longitudinal cohort studies. BMJ. 2013;347:f5001. https://doi.org/10.1136/bmj.f5001.
  39. Li M, Fan Y, Zhang X, et al. Fruit and vegetable intake and risk of type 2 diabetes mellitus: meta-analysis of prospective cohort studies. BMJ Open. 2014;4(11):e005497. https://doi.org/10.1136/bmjopen-2014-005497.
  40. Xu L, Li Y, Dai Y, Peng J. Natural products for the treatment of type 2 diabetes mellitus: pharmacology and mechanisms. Pharmacol Res. 2018;130:451-65. https://doi.org/10.1016/j.phrs.2018.01.015.
  41. Cardozo LF, Pedruzzi LM, Stenvinkel P, et al. Nutritional strategies to modulate inflammation and oxidative stress pathways via activation of the master antioxidant switch Nrf2. Biochimie. 2013;95(8):1525-1533. https://doi.org/10.1016/j.biochi.2013.04.012.
  42. Rimm EB, Chan J, Stampfer MJ, et al. Prospective study of cigarette smoking, alcohol use, and the risk of diabetes in men. BMJ. 1995;310(6979):555-559. https://doi.org/ 10.1136/bmj.310.6979.555.
  43. Zhang L, Curhan GC, Hu FB, et al. Association between passive and active smoking and incident type 2 diabetes in women. Diabetes Care. 2011;34(4):892-897. https://doi.org/10.2337/dc10-2087.
  44. Zhu P, Pan XF, Sheng L, et al. Cigarette smoking, diabetes, and diabetes complications: call for urgent action. Curr Diab Rep. 2017;17(9):78. https://doi.org/10.1007/s11892-017-0903-2.
  45. Rajagopalan S, Brook RD. Air pollution and type 2 diabetes: mechanistic insights. Diabetes. 2012;61(12):3037-3045. https://doi.org/10.2337/db12-0190.

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2. GGCT – gamma-glutamylcyclotransferase; OPLAH – 5-oxoprolinase; GCLC – glutamate cysteine ligase, catalytic subunit; GCLM – glutamate cysteine ligase, modifying subunit; GSS – glutathione synthetase; ANPEP – aminopeptidase N; GGT1 – gamma- glutamyltransferase 1; GGT5 – gamma-glutamyltransferase 5; GGT6 – gamma-glutamyltransferase 6; GGT7 – gamma-glutamyltransferase 7

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Copyright (c) 2020 Azarova I.E., Klyosova E.Y., Churilin M.I., Samgina T.A., Konoplya A.I., Polonikov A.V.

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