Abstract
Oxidative stress contributes to the pathogenesis of type 2 diabetes (T2D). This study investigated whether single nucleotide polymorphisms (SNPs) at genes encoding glutamate cysteine ligase catalytic (rs12524494, rs17883901, rs606548, rs636933, rs648595, rs761142 at GCLC) and modifier (rs2301022, rs3827715, rs7517826, rs41303970 at GCLM) subunits are associated with susceptibility to type 2 diabetes. 2096 unrelated Russian subjects were enrolled for the study. Genotyping was done with the use of the MassArray System. Plasma levels of reactive oxygen species (ROS) and glutathione in the study subjects were analyzed by fluorometric and colorimetric assays, respectively.The present study found, for the first time, an association of SNP rs41303970 in the GCLM gene with a decreased risk of T2D (P = 0.034, Q = 0.17). Minor alleles such as rs12524494-G GCLC gene (P = 0.026, Q = 0.17) and rs3827715-C GCLM gene (P = 0.03, Q = 0.17) were also associated with reduced risk for T2D. Protective effects of variant alleles such as rs12524494-G at GCLC (P = 0.02, Q = 0.26) and rs41303970-A GCLM (P = 0.013, Q = 0.25) against the risk of T2D were seen solely in nonsmokers. As compared with healthy controls, diabetic patients had markedly increased levels of ROS and decreased levels of total GSH in plasma. Interestingly, fasting blood glucose level positively correlated with oxidized glutathione concentration (rs = 0.208, P = 0.01). Three SNPs rs17883901, rs636933, rs648595 at GCLC and one rs2301022 at GCLM were associated with decreased levels of ROS, while SNPs rs7517826, rs41303970 at GCLM were associated with increased levels of total GSH in plasma. Single nucleotide polymorphisms in genes encoding glutamate cysteine ligase subunits confer protection against type 2 diabetes and their effects are mediated through increased levels of glutathione.
Similar content being viewed by others
Data and/or code availability
We are not allowed to share the raw data.
References
Saeedi P, Petersohn I, Salpea P, Malanda B, Karuranga S, Unwin N et al (2019) Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas. Diabetes Res Clin Pract 157:107843. https://doi.org/10.1016/j.diabres.2019.107843
World Health Organization (2016) Global report on diabetes. World Health Organization, Geneva
Lawlor N, Khetan S, Ucar D, Stitzel ML (2017) Genomics of islet dysfunction and type 2 diabetes. Trends Genet 33(4):244–255. https://doi.org/10.1016/j.tig.2017.01.010
Bellou V, Belbasis L, Tzoulaki I, Evangelou E (2018) Risk factors for type 2 diabetes mellitus: an exposure-wide umbrella review of meta-analyses. PLoS ONE 13(3):e0194127. https://doi.org/10.1371/journal.pone.0194127
Fuchsberger C, Flannick J, Teslovich TM et al (2016) The genetic architecture of type 2 diabetes. Nature 536:41–47. https://doi.org/10.1038/nature18642
Stelzer G, Rosen R, Plaschkes I, Zimmerman S, Twik M, Fishilevich S et al (2019) The genecards suite: from gene data mining to disease genome sequence analysis. Curr Protoc Bioinform 54(1):1–30. https://doi.org/10.1002/cpbi.5
DeFronzo RA, Inzucchi S, Abdul-Ghani M, Nissen SE (2019) Pioglitazone: the forgotten, cost-effective cardioprotective drug for type 2 diabetes. Diabetes Vasc Dis Res 16(2):133–143. https://doi.org/10.1177/1479164118825376
Chatterjee S, Khunti K, Davies MJ (2017) Type 2 diabetes. Lancet 389:2239–2251. https://doi.org/10.1016/S0140-6736(17)30058-2
Koska J, Saremi A, Howell S et al (2018) Advanced glycation end products, oxidation products, and incident cardiovascular events in patients with type 2 diabetes. Diabetes Care 41(3):570–576. https://doi.org/10.2337/dc17-1740
Ozdemır G, Ozden M, Maral H, Kuskay S, Cetınalp P, Tarkun I (2005) Malondialdehyde, glutathione, glutathione peroxidase and homocysteine levels in type 2 diabetic patients with and without microalbuminuria. Ann Clin Biochem 42(2):99–104. https://doi.org/10.1258/0004563053492838
Soliman GZA (2008) Blood lipid peroxidation (superoxide dismutase, malondialdehyde, glutathione) levels in Egyptian type 2 diabetic patients. Singapore Med J 49(2):129
Al-Maskari MY, Waly MI, Ali A, Al-Shuaibi YS, Ouhtit A (2012) Folate and vitamin B12 deficiency and hyperhomocysteinemia promote oxidative stress in adult type 2 diabetes. Nutrition 28(7–8):e23–e26. https://doi.org/10.1016/j.nut.2012.01.005
Lutchmansingh FK, Hsu JW, Bennett FI et al (2018) Glutathione metabolism in type 2 diabetes and its relationship with microvascular complications and glycemia. PLoS ONE 13(6):e0198626. https://doi.org/10.1371/journal.pone.0198626
Spanidis Y, Mpesios A, Stagos D et al (2016) Assessment of the redox status in patients with metabolic syndrome and type 2 diabetes reveals great variations. Exp Ther Med 11(3):895–903. https://doi.org/10.3892/etm.2016.2968
Flohé L (2018) Glutathione. CRC Press, Boca Raton
Koide SI, Kugiyama K, Sugiyama S et al (2003) Association of polymorphism in glutamate-cysteine ligase catalytic subunit gene with coronary vasomotor dysfunction and myocardial infarction. J Am Coll Cardiol 41(4):539–545. https://doi.org/10.1016/S0735-1097(02)02866-8
Nakamura SI, Kugiyama K, Sugiyama S et al (2002) Polymorphism in the 5′-flanking region of human glutamate-cysteine ligase modifier subunit gene is associated with myocardial infarction. Circulation 105(25):2968–2973. https://doi.org/10.1161/01.CIR.0000019739.66514.1E
Skvortsova L, Perfelyeva A, Khussainova E, Mansharipova A, Forman HJ, Djansugurova L (2017) Association of GCLM-588C/T and GCLC-129T/C promoter polymorphisms of genes coding the subunits of glutamate cysteine ligase with ischemic heart disease development in kazakhstan population. Dis Markers. https://doi.org/10.1155/2017/4209257
Pereira MM, Gelbart T, Ristoff E et al (2007) Chronic non-spherocytic hemolytic anemia associated with severe neurological disease due to γ-glutamylcysteine synthetase deficiency in a patient of Moroccan origin. Haematologica 92(11):e102–e105. https://doi.org/10.3324/haematol.11238
Baum L, Chen X, Cheung WS et al (2007) Polymorphisms and vascular cognitive impairment after ischemic stroke. J Geriatr Psychiatry Neurol 20(2):93–99. https://doi.org/10.3324/haematol.11238
Do KQ, Bovet P, Cabungcal JH et al (2009) Redox dysregulation in schizophrenia: genetic susceptibility and pathophysiological mechanisms. Handb Neurochem Mol Neurobiol. https://doi.org/10.1007/978-0-387-30410-6_8
Tosic M, Ott J, Barral S et al (2006) Schizophrenia and oxidative stress: glutamate cysteine ligase modifier as a susceptibility gene. Am J Hum Genet 79(3):586–592. https://doi.org/10.1086/507566
Azarova I, Bushueva O, Konoplya A, Polonikov A (2018) 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 10(5):398–407. https://doi.org/10.1111/1753-0407.12623
Ghaheri M, Kahrizi D, Yari K, Babaie A, Suthar RS, Kazemi E (2016) A comparative evaluation of four DNA extraction protocols from whole blood sample. Cell Mol Biol 62(3):120–124. https://doi.org/10.14715/cmb/2016.62.3.20
Shin S, Hudson R, Harrison C, Craven M, Keleş S (2019) atSNP Search: a web resource for statistically evaluating influence of human genetic variation on transcription factor binding. Bioinformatics 35(15):2657–2659. https://doi.org/10.1093/bioinformatics/bty1010
Pujato M, Kieken F, Skiles AA, Tapinos N, Fiser A (2014) Prediction of DNA binding motifs from 3D models of transcription factors; identifying TLX3 regulated genes. Nucleic Acids Res 42(22):13500–13512. https://doi.org/10.1093/nar/gku1228
Willi C, Bodenmann P, Ghali WA, Faris PD, Cornuz J (2007) Active smoking and the risk of type 2 diabetes: a systematic review and meta-analysis. JAMA 298(22):2654–2664. https://doi.org/10.1001/jama.298.22.2654
Yeh HC, Duncan BB, Schmidt MI, Wang NY, Brancati FL (2010) Smoking, smoking cessation, and risk for type 2 diabetes mellitus: a cohort study. Ann Intern Med 152(1):10–17. https://doi.org/10.7326/0003-4819-152-1-201001050-00005
Henriksen EJ, Diamond-Stanic MK, Marchionne EM (2011) Oxidative stress and the etiology of insulin resistance and type 2 diabetes. Free Radic Biol Med 51(5):993–999. https://doi.org/10.1016/j.freeradbiomed.2010.12.005
Hurrle S, Hsu WH (2017) The etiology of oxidative stress in insulin resistance. Biomed J 40(5):257–262. https://doi.org/10.1016/j.bj.2017.06.007
Rehman K, Akash MSH (2017) Mechanism of generation of oxidative stress and pathophysiology of type 2 diabetes mellitus: how are they interlinked? J Cell Biochem 118(11):3577–3585. https://doi.org/10.1002/jcb.26097
Gadjeva VS, Goycheva P, Nikolova G, Zheleva A (2017) Influence of glycemic control on some real-time biomarkers of free radical formation in type 2 diabetic patients: an EPR study. Adv Clin Exp Med 26(8):1237–1240. https://doi.org/10.17219/acem/68988
Berndt C, Lillig CH (2017) Glutathione, glutaredoxins, and iron. Antioxid Redox Signal 27(15):1235–1251. https://doi.org/10.1089/ars.2017.7132
Franklin CC, Backos DS, Mohar I, White CC, Forman HJ, Kavanagh TJ (2009) Structure, function, and post-translational regulation of the catalytic and modifier subunits of glutamate cysteine ligase. Mol Aspects Med 30(1–2):86–98. https://doi.org/10.1016/j.mam.2008.08.009
Roberts LD, Koulman A, Griffin JL (2014) Towards metabolic biomarkers of insulin resistance and type 2 diabetes: progress from the metabolome. Lancet Diabetes Endocrinol 2(1):65–75. https://doi.org/10.1016/S2213-8587(13)70143-8
Ruiz-Canela M, Guasch-Ferré M, Toledo E et al (2018) Plasma branched chain/aromatic amino acids, enriched Mediterranean diet and risk of type 2 diabetes: case-cohort study within the PREDIMED Trial. Diabetologia 61(7):1560–1571. https://doi.org/10.1007/s00125-018-4611-5
Nishizaki SS, Boyle AP (2017) Mining the unknown: assigning function to noncoding single nucleotide polymorphisms. Trends Genet 33(1):34–45. https://doi.org/10.1016/j.tig.2016.10.008
Yang TT, Suk HY, Yang X et al (2006) Role of transcription factor NFAT in glucose and insulin homeostasis. Mol Cell Biol 26(20):7372–7387. https://doi.org/10.1128/MCB.00580-06
Jackerott M, Møldrup A, Thams P et al (2006) STAT5 activity in pancreatic beta-cells influences the severity of diabetes in animal models of type 1 and 2 diabetes. Diabetes 55(10):2705–2712. https://doi.org/10.2337/db06-0244
Gysemans C, Callewaert H, Moore F et al (2009) Interferon regulatory factor-1 is a key transcription factor in murine beta cells under immune attack. Diabetologia 52(11):2374–2384. https://doi.org/10.1007/s00125-009-1514-5
Vorrink SU, Domann FE (2014) Regulatory crosstalk and interference between the xenobiotic and hypoxia sensing pathways at the AhR-ARNT-HIF1α signaling node. Chem Biol Interact 218:82–88. https://doi.org/10.1016/j.cbi.2014.05.001
García IA, Torres Demichelis V, Viale DL et al (2017) CREB3L1-mediated functional and structural adaptation of the secretory pathway in hormone-stimulated thyroid cells. J Cell Sci 130(24):4155–4167. https://doi.org/10.1242/jcs.211102
Chen F, Sha M, Wang Y et al (2016) Transcription factor Ets-1 links glucotoxicity to pancreatic beta cell dysfunction through inhibiting PDX-1 expression in rodent models. Diabetologia 59(2):316–324. https://doi.org/10.1007/s00125-015-3805-3
Sans CL, Satterwhite DJ, Stoltzman CA, Breen KT, Ayer DE (2006) MondoA-Mlx heterodimers are candidate sensors of cellular energy status: mitochondrial localization and direct regulation of glycolysis. Mol Cell Biol 26(13):4863–4871. https://doi.org/10.1128/MCB.00657-05
Riu E, Ferre T, Mas A, Hidalgo A, Franckhauser S, Bosch F (2002) Overexpression of c-myc in diabetic mice restores altered expression of the transcription factor genes that regulate liver metabolism. Biochem J 368(Pt 3):931–937. https://doi.org/10.1042/bj20020605
Kaneto H, Sharma A, Suzuma K et al (2002) Induction of c-Myc expression suppresses insulin gene transcription by inhibiting NeuroD/BETA2-mediated transcriptional activation. J Biol Chem 277(15):12998–13006. https://doi.org/10.1074/jbc.M111148200
Lee SH, Demeterco C, Geron I, Abrahamsson A, Levine F, Itkin-Ansari P (2008) Islet specific Wnt activation in human type II diabetes. Exp Diabetes Res 2008:728763. https://doi.org/10.1155/2008/728763
Jain SK, Micinski D (2013) Vitamin D upregulates glutamate cysteine ligase and glutathione reductase, and GSH formation, and decreases ROS and MCP-1 and IL-8 secretion in high-glucose exposed U937 monocytes. Biochem Biophys Res Commun 437(1):7–11. https://doi.org/10.1016/j.bbrc.2013.06.004
Parsanathan R, Jain SK (2019) Glutathione deficiency induces epigenetic alterations of vitamin D metabolism genes in the livers of high-fat diet-fed obese mice. Sci Rep 9(1):14784. https://doi.org/10.1038/s41598-019-51377-5
Santesmasses D, Mariotti M, Guigó R (2017) Computational identification of the selenocysteine tRNA (tRNASec) in genomes. PLoS Comput Biol 13(2):e1005383. https://doi.org/10.1371/journal.pcbi.1005383
Spijkerman AM, Nilsson PM, Ardanaz E et al (2014) Smoking and long-term risk of type 2 diabetes: the EPIC-InterAct study in European populations. Diabetes Care 37(12):3164–3171. https://doi.org/10.2337/dc14-1020
Pan A, Wang Y, Talaei M, Hu FB, Wu T (2015) Relation of active, passive, and quitting smoking with incident type 2 diabetes: a systematic review and meta-analysis. Lancet Diabetes Endocrinol 3(12):958–967. https://doi.org/10.1016/S2213-8587(15)00316-2
Eliasson B (2003) Cigarette smoking and diabetes. Prog Cardiovasc Dis 45(5):405–413. https://doi.org/10.1053/pcad.2003.00103
Agarwal R (2005) Smoking, oxidative stress and inflammation: impact on resting energy expenditure in diabetic nephropathy. BMC Nephrol 6(1):13. https://doi.org/10.1186/1471-2369-6-13
Chen C, Tu YQ, Yang P et al (2018) Assessing the impact of cigarette smoking on β-cell function and risk for type 2 diabetes in a non-diabetic Chinese cohort. Am J Transl Res 10(7):2164
Dinardo MM, Sereika SM, Korytkowski M et al (2019) Current smoking: an independent predictor of elevated A1C in persons with type 2 diabetes. Diabetes Educ 45(2):146–154. https://doi.org/10.1177/0145721719829068
Acknowledgements
We thank all the T2D patients, healthy volunteers and staff of the Kursk Emergency Hospital. The study was supported by Russian Science Foundation (№20–15-00227).
Funding
The study was supported by Russian Science Foundation (No. 20-15-00227).
Author information
Authors and Affiliations
Contributions
IA: laboratory investigations, database handling, statistical and bioinformatics analysis, interpretation and discussion of study results, writing and revising the paper; EK: laboratory investigations, database handling, data curation; VL: project administration, instructions of clinical, laboratory and instrumental examination of the study patients; AK: instructions of patients enrollment, consultancy; AP: the study conception and design, supervision of the study, interpretation and discussion of the study results, writing and revising the paper. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Kursk State Medical University (Date: 12.12.2016/No.10).
Informed consent
Informed consent was obtained from all individual participants included in the study.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Azarova, I., Klyosova, E., Lazarenko, V. et al. Genetic variants in glutamate cysteine ligase confer protection against type 2 diabetes. Mol Biol Rep 47, 5793–5805 (2020). https://doi.org/10.1007/s11033-020-05647-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11033-020-05647-5