Genetic Variants in Glutamate Cysteine Ligase Confer Protection Against Type 2 Diabetes

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Genetic variants in glutamate cysteine ligase confer protection against type 2 diabetes

Article in Molecular Biology Reports · August 2020 DOI: 10.1007/s11033-020-05647-5

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ORIGINAL ARTICLE

Genetic variants in glutamate cysteine ligase confer protection against type 2 diabetes

Iuliia Azarova1,2 · Elena Klyosova2 · Victor Lazarenko3 · Alexander Konoplya1 · Alexey Polonikov4,5

Received: 19 March 2020 / Accepted: 8 July 2020 © Springer Nature B.V. 2020

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 modifer (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 fuorometric and colorimetric assays, respectively.The present study found, for the frst 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 efects 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 efects are mediated through increased levels of glutathione.

Keywords Type 2 diabetes mellitus · Oxidative stress · Reactive oxygen species · Glutathione · Glutamate cysteine ligase · Single nucleotide polymorphism

Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11033-020-05647-5) contains supplementary material, which is available to authorized users.

* Iuliia Azarova Kursk State Medical University, 18 Yamskaya St., Kursk, [email protected]; [email protected] Russian Federation 305041 Elena Klyosova 3 Department of Surgical Diseases of Postgraduate Faculty, [email protected] Kursk State Medical University, 3 Karl Marx Street, Kursk, Russian Federation 305041 Victor Lazarenko [email protected] 4 Department of Biology, Medical Genetics and Ecology, Kursk State Medical University, 3 Karl Marx Street, Kursk, Alexander Konoplya Russian Federation 305041 [email protected] 5 Laboratory of Statistical Genetics and Bioinformatics, Alexey Polonikov Research Institute for Genetic and Molecular Epidemiology, [email protected]; [email protected] Kursk State Medical University, 18 Yamskaya St., Kursk, Russian Federation 305041 1 Department of Biological Chemistry, Kursk State Medical University, 3 Karl Marx Street, Kursk, Russian Federation 305041 2 Laboratory of Biochemical Genetics and Metabolomics, Research Institute for Genetic and Molecular Epidemiology,

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Introduction Methods

Diabetes is one of the fastest growing health challenges Study population of the twenty-frst century, with the number of adults liv- ing with diabetes having more than tripled over the past The study protocol conforms to the ethical guidelines of the 20 years. Today, International Diabetes Federation calculates Declaration of Helsinki and was approved by the Regional that 9.3% of adults aged 20–79 years—a staggering 463 mil- Ethics Review Committee of Kursk State Medical Uni- lion people—sufer from diabetes worldwide, and more than versity. Written informed consent was obtained from each 8 million of them live in Russia [1]. T2D is a multifactorial participant before enrollment in the study. A total of 2096 disease with a strong genetic component [2, 3]. According unrelated Russian individuals were recruited into the study, to the GeneCards database, more than 700 genetic markers including 1032 T2D patients and 1064 age- and sex-matched are associated with T2D susceptibility [4], and a majority healthy individuals. T2D patients were admitted to the Divi- of these genetic variants have been implicated in pancreatic sion of Endocrinology of the Kursk Emergency Hospital β-cell dysfunction and peripheral insulin resistance [5, 6]. from November 2016 to December 2018. T2D was diag- There are many hypotheses regarding pathogenesis of nosed on the basis of WHO criteria [2]: fasting blood glu- T2D, including impaired pro- and antioxidant balance char- cose (FBG) level ≥ 7.0 mmol/L or random blood glucose acterized by increased reactive oxygen species (ROS) pro- level ≥ 11.1 mmol/L and/or glycated hemoglobin HbA1c duction and decreased antioxidant defense [7–9]. The redox level ≥ 6.5%. The control group included healthy volun- homeostasis has been investigated in numerous studies and it teers who presented at the Kursk Blood Transfusion Station has been revealed that patients with T2D have lower plasma within the same time frame as well as healthy individuals GSH levels [10–13] and higher static oxidation reduction recruited in our previous studies [23]. Subjects of the control potential [14] in comparison to healthy subjects. However, group had normal FBG levels and 75-g oral glucose toler- the causes and molecular mechanisms responsible for these ance test results. All study subjects were mainly from the metabolic changes in patients with type 2 diabetes remain Kursk region (Central Russia). Demographic, clinical and unclear. laboratory characteristics of the study groups are shown in Glutathione (GSH) is one of the major cellular antioxi- Table 1. A positive history of diabetes was greater in the dants and can be produced from glutamate, cysteine and case group than in the control group. Most patients with dia- glycine via the GSH cycle or via a regeneration reaction betes sufer from hypertension, and approximately one-third from the oxidized form of GSSG. Glutamate cysteine ligase of them had coronary artery disease (CAD). The number (GCL) is the enzyme catalyzing the frst rate-limiting step of smokers was higher among healthy subjects than among for a de novo biosynthesis of GSH [15]. Catalytic and mod- patients with diabetes. Two-thirds of the patients were ifer subunits of the enzyme are encoded by two distinct females. Most patients (88%) were overweight or obese. genes such as GCLC and GCLM, respectively. Functional Compared with the control group, diabetic patients showed polymorphisms of these genes could affect the enzyme signifcantly increased levels of glycated hemoglobin, FBG, activity and hence the production of GSH. Several stud- triacylglycerols, total cholesterol, low-density lipoproteins, ies reported the associations of rs17883901 at GCLC and and creatinine (Table 1). The levels of high-density lipopro- rs41303970 at GCLM genes with myocardial infarction and teins were higher in healthy subjects than in patients with acute coronary syndrome [16–18]. Other variants of GCL T2D. genes are associated with hemolytic anemia [19], stroke [20], blood cholesterol level, and schizophrenia [21, 22]. The relationship between these genes and T2D susceptibility Genetic analysis has been insufciently investigated. The present study was designed to investigate associa- Ten common tagSNPs at the GCLC (rs12524494, tions of SNPs rs12524494, rs17883901, rs606548, rs636933, rs17883901, rs606548, rs636933, rs648595, rs761142) and rs648595, rs761142 at GCLC and rs2301022, rs3827715, GCLM (rs2301022, rs3827715, rs7517826, rs41303970) rs7517826, and rs41303970 at GCLM with susceptibility to genes were selected for the study (Suppl. Table 1A). Func- T2D and to assess the impact of these gene polymorphisms tional SNPs were selected using a set of web-based SNP on pro- and antioxidant status and metabolic parameters in selection tools available at SNPinfo Web Server (https:// diabetic patients. snpinfo.niehs.nih.gov). The selection of SNPs was based on their predicted functional characteristics, minor allele frequency (MAF > 5% in Europeans) and haplotype tag- ging properties.

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Table 1 Demographic and Baseline characteristics Controls n = 1064 T2D patients n = 1032 P value* clinical characteristics of the study patients Age, mean ± Std.Dv 61.00 ± 7.82 61.42 ± 10.58 0.308 Males, n (%) 392 (36.8) 363 (35.2) 0.453 Females, n (%) 672 (63.2) 669 (64.8) Body mass index (kg/m2), mean ± SD 27.04 ± 3.55 32.08 ± 6.71 < 0.0001 Consumers of fresh fruits and vegetables, n (%) 886 (83.3) 504 (48.8) < 0.0001 Smokers, (ever/never), n (%) 308 (28.9) 232 (22.5) 0.0009 Duration of diabetes, me [Q1;Q3] – 10.03 [4; 14] – Positive family history of diabetes, n (%) 3 (0.8%) 400 (38.8) – Arterial hypertension, n (%) – 991 (96.0) – CAD, n (%) – 310 (30.0)

HbA1C (%), Me [Q1;Q3] 4.58 [4.11; 4.87] 9.10 [7.90; 11.00] < 0.0001 Fasting blood glucose (mmol/L), Me [Q1;Q3] 4.71 [4.39; 4.84] 12.00 [9.49; 14.90] < 0.0001 Total cholesterol (mmol/L), Me [Q1;Q3] 3.06 [2.86; 3.12] 4.93 [4.14; 5.90] < 0.0001 LDL (mmol/L), Me [Q1;Q3] 1.74 [1.60; 1.79] 3.10 [2.50; 4.05] < 0.0001 HDL (mmol/L), Me [Q1;Q3] 1.47 [1.36; 1.62] 0.84 [0.73; 1.00] < 0.0001 Triacylglycerols (mmol/L), Me [Q1;Q3] 1.15 [0.98; 1.23] 2.17 [1.55; 2.93] < 0.0001 Creatinine, µmol/L, Me [Q1;Q3] 85,7 [77.6; 98.0] 96.0 [84.0; 112.0] < 0.0001 Uric acid, µmol/L, Me [Q1;Q3] 314.4 [252.2; 329.4] 336.0 [267.6; 410.2] 0.12

ROS ( H2O2), µmol/L, Me [Q1;Q3] 2.47 [1.98;3.69] 3.44 [2.49;4.48] 0.0002 Total GSH/GSSG, µmol/L, Me [Q1;Q3] 1.93 [0.84;5.75] 1.62 [0.55;3.79] 0.02

CAD coronary artery disease, HbA1C glycated hemoglobin, LDL low-density lipoproteins, HDL high-density lipoproteins, ROS reactive oxygen species, GSH/GSSG total glutathione *Bold is statistically signifcant P value

Blood samples were collected from all study participants. (Cell Biolabs, USA; Abcam, USA). Plasma samples were Genomic DNA was purifed from whole blood samples aliquoted and stored at − 80 °C until further use. For total by phenol–chloroform extraction [24]. The quality of the GSH determination, plasma was immediately deproteinized extracted DNA was evaluated by the degree of purity and with 5% metaphosphoric acid. For GSH sub-fraction meas- concentration of the solution on a NanoDrop spectrophotom- urement (reduced GSH /oxidized GSH), plasma was depro- eter (Thermo Fisher Scientifc, USA). Prior to genotyping teinized with trichloroacetic acid. The total GSH levels were all DNA samples were diluted to concentration of 10 ng/µL. determined by colorimetric assay using the OxiSelect™ Genotyping of the polymorphisms was performed by Total Glutathione (GSSG/GSH) Assay Kit (Cell Biolabs, iPLEX technology with the Mass Array System (Agena USA). Reduced and oxidized GSH were measured using Bioscience). The primer sequences used for genotyping a fuorometric GSH/GSSG Assay Kit (Abcam, USA). The the GCL genes are shown in Supplementary Table 1B. ROS levels were quantifed by fuorometric assay using the To ensure quality control, the genotyping analysis was OxiSelect™ In Vitro ROS/RNS Assay Kit (Cell Biolabs, performed blindly with respect to the case–control status. USA). The assay employs a proprietary quenched fuoro- Approximately 10% of the samples were randomly selected genic probe, dichlorodihydrofuorescin DiOxyQ (DCFH- for repeat genotyping, and the repeatability test resulted in DiOxyQ), which is a specifc ROS/RNS probe. It is frst a 100% concordance rate. primed with a quench removal reagent, and subsequently stabilized in the highly reactive DCFH form. In this reactive Biochemical analysis state, ROS and RNS species, can react with DCFH, which is rapidly oxidized to the highly fuorescent 2′,7′-dichloro- Plasma ROS levels were assessed in 426 T2D patients and dihydrofuorescein (DCF). The standard curve of H2O2 was 153 healthy volunteers, whereas GSH levels were assessed in used to quantify the free radical content in the blood plasma 258 patients and 137 controls recruited at the fnal phase of samples. Absorbance at 405 nm and fuorescence at 480 nm this study (from September 2018 to December 2018). Fast- excitation/530 nm emission were measured on a microplate ing venous blood samples were collected in standard ster- reader Varioscan Flash (Thermo Fisher Scientifc, USA). ile tubes with lithium heparin and immediately centrifuged Plasma concentrations of glucose, glycated hemoglobin, at 3500 rpm according to the manufacturer`s instructions total cholesterol, high-density lipoproteins, low-density

1 3 Molecular Biology Reports lipoproteins, triacylglycerols, creatinine and uric acid were The regulatory potential of GCLC and GCLM polymor- determined on a semi-automatic biochemical analyzer Clima phisms was assessed with atSNP search online resource MC-15 (RAL, Spain) with the use of the Diacon-DS com- (https://atsnp.biostat.wisc.edu). atSNP search is a bioinfor- pany reagent kits (Russia). matics tool designed for statistically evaluating infuence of human genetic variation (SNPs) on transcription factor Statistical analysis (TF) binding [25]. TF2DNA database was used to verify binding specifcities of TFs [26]. The transcriptome data on The analysis of the frequency distribution of genotypes and various tissues of patients with T2D were analyzed using its correspondence to the Hardy–Weinberg equilibrium the T2DiaCoD database (Gene Atlas of Type 2 Diabetes was carried out using the chi-square test. The association Mellitus Associated Complex Disorders, https://t2diacod. between gene polymorphisms, their combinations and the igib.res.in/). Comparative Toxicogenomics Database (https risk of T2D was evaluated by multiple logistic regression ://ctdbase.org/ ) was utilized to assess the impact of chemical analysis with calculation of odds ratios (OR) and 95% con- compounds of tobacco smoke on expression/activity of the fdence intervals (95% CI) adjusted for age, sex, and body studied genes. mass index (BMI). Haplotypes of the GCLC and GCLM genes and linkage disequilibrium (LD) were estimated and compared between the groups using the chi-square test. Statistical calculations were performed using STATISTICA Results for Windows 10.0 package and SNPStats software available online at www.snpstats.net. Association analysis of the GCLC and GCLM gene Biochemical parameters were analyzed for normality by polymorphisms with T2D risk the Kolmogorov–Smirnov test. Parameters with a normal distribution were described as a mean ± standard deviation; Genotype and allele frequencies for the studied SNPs are Student’s test was used to assess the statistical signifcance given in Table 2. The rs41303970-G/A genotype of the of diferences in normally distributed traits between the GCLM gene was signifcantly associated with a decreased study groups. Not normally distributed traits (expressed risk of T2D after adjusting for age, gender, and BMI by mul- as a median with lower and upper quartiles, Q1–Q3) were tiple logistic regression analysis (OR 0.80, 95CI 0.64–0.99, compared between the groups using the Mann–Whitney test. P = 0.034, Q = 0.17). Frequency of minor allele rs41303970- Statistical power was estimated using the genetic associa- A was signifcantly higher in the control group compared to tion study power calculator (https://csg.sph.umich .edu/abeca cases (P = 0.008, Q = 0.16). Alternative alleles rs12524494- sis/gas_power_calculator/). An association analysis of the G in GCLC gene and rs3827715-C in GCLM gene were also selected polymorphisms with the T2D risk could detect the associated with reduced risk for T2D and remained signif- genotype relative risk of 1.26–1.51 assuming 80% power and cant after FDR correction (Q < 0.2). a 5% type I error (α = 0.05) on the basis of the sample sizes There is an increasing body of evidence that smoking of 1032 people with T2D and 1064 healthy controls. Statis- exacerbates oxidative stress that plays an important role tical signifcance was established at the P < 0.05 level. The in the development of T2D [27, 28] probably through a false discovery rate (FDR) method proposed by Benjamini depletion of the endogenous GSH pool. Considering that and Hochberg was applied in cases in which multiple tests smoking is a well-known risk factor for T2D and that its were performed, and Q-values calculated, with signifcance adverse efect is due to enhanced generation of ROS, fur- set at Q ≤ 0.2. ther analysis was performed separately in smokers and non- All study investigations were done at Research Institute smokers. Smoking-stratifed analysis results are presented for Genetic and Molecular Epidemiology of Kursk State in Suppl. Table 2. The protective efects of rs12524494-G Medical University. and rs41303970-A alleles on the disease risk were observed solely in a subgroup of nonsmokers, whereas no signifcant Bioinformatics analysis association with T2D risk was seen in smoker carriers for these alleles. However, these associations did not survive The STRING tool (https://string-db.org) was used to visu- after FDR correction (Q > 0.2). alize protein–protein interactions in the network centered SNPs rs12524494, rs606548, rs636933, rs648595, on the GCL subunits. The Gene Ontology enrichment tool rs761142 of GCLC were in a positive LD (D′ < 0.8, (https://geneontology.org) was used to identify ontology P < 0.0001), a situation when the wild-type allele at one site terms describing the biological functions of the proteins. is more likely to be associated with the wild-type allele at

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Table 2 Genotype and allele frequencies for the studied polymorphisms in T2D patients and healthy controls Gene, polymorphism Genotype. allele Controls n = 1064 n (%)a T2D patients OR (95 CI)b P value Q value n = 1032 n (%)a rs12524494 A/A 843 (93.6%) 801 (96%) 1.00 0.084 0.34 (A > G) G/A 52 (5.8%) 29 (3.5%) 0.57 (0.34–0.95) G/G 6 (0.7%) 4 (0.5%) 0.80 (0.21–3.09) G 0.036 0.022 0.62 (0.41–0.93) 0.026 0.17 rs17883901 G/G 907 (87.2%) 867 (85.1%) 1.00 0.5 0.56 (G > A) G/A 126 (12.1%) 144 (14.1%) 1.17 (0.88–1.55) A/A 7 (0.7%) 8 (0.8%) 1.34 (0.42–4.26) A 0.067 0.079 1.18 (0.93–1.49) 0.186 0.38 rs606548 C/C 952 (93.8%) 957 (93.4%) 1.00 0.54 0.57 (C > T) C/T 61 (6%) 65 (6.3%) 1.06 (0.71–1.57) T/T 2 (0.2%) 3 (0.3%) 2.69 (0.44–16.43) T 0.032 0.035 1.08 (0.77–1.52) 0.705 0.71 rs636933 G/G 626 (61.6%) 606 (58.9%) 1.00 0.37 0.48 (G > A) G/A 338 (33.3%) 364 (35.4%) 1.13 (0.92–1.40) A/A 52 (5.1%) 59 (5.7%) 1.22 (0.80–1.88) A 0.218 0.234 1.10 (0.95–1.27) 0.202 0.38 rs648595 T/T 334 (32%) 309 (30%) 1.00 0.31 0.48 (T > G) G/T 516 (49.4%) 512 (49.7%) 1.11 (0.89–1.38) G/G 194 (18.6%) 209 (20.3%) 1.24 (0.94–1.64) G 0.433 0.451 1.08 (0.95–1.22) 0.23 0.38 rs761142 A/A 586 (56.9%) 577 (56.1%) 1.00 0.37 0.48 (A > C) C/A 381 (37%) 377 (36.6%) 1.05 (0.85–1.29) C/C 63 (6.1%) 75 (7.3%) 1.32 (0.89–1.96) C 0.246 0.256 1.05 (0.92–1.21) 0.46 0.54 rs2301022 C/C 518 (50.3%) 492 (48%) 1.00 0.21 0.38 (C > T) T/C 412 (40%) 430 (42%) 1.20 (0.98–1.47) T/T 100 (9.7%) 102 (10%) 1.05 (0.75–1.48) T 0.297 0.310 1.06 (0.93–1.21) 0.38 0.48 rs3827715 T/T 515 (50.8%) 553 (55.7%) 1.00 0.18 0.38 (T > C) T/C 408 (40.2%) 363 (36.6%) 0.86 (0.70–1.06) C/C 91 (9%) 77 (7.8%) 0.76 (0.53–1.09) C 0.291 0.260 0.86 (0.75–0.99) 0.03 0.17 rs7517826 C/C 385 (38.1%) 453 (44.2%) 1.00 0.11 0.34 (C > A) C/A 490 (48.5%) 443 (43.3%) 0.82 (0.66–1.01) A/A 136 (13.4%) 128 (12.5%) 0.79 (0.58–1.07) A 0.377 0.341 0.86 (0.75–0.97) 0.118 0.34 rs41303970 G/G 550 (62.6%) 343 (68.1%) 1.00 0.034 0.17 (G > A) G/A 266 (30.3%) 141 (28%) 0.80 (0.64–0.99) A/A 62 (7.1%) 20 (4%) 0.66 (0.43–1.02) A 0.222 0.180 0.77 (0.63–0.93) 0.008 0.16

Bold is statistically signifcant P and Q values a Absolute number and percentage of individuals/chromosomes with particular genotype/allele b Odds ratio with 95% confdence intervals adjusted for sex, age and BMI with one degree of freedom the other site. Three SNPs in the GCLM gene (rs3827715, patients and controls are listed in Table 3. There was no dif- rs7517826, rs41303970) were also in positive LD (D′ < 0.8, ference in the distribution of haplotypes of the GCLC gene P < 0.0001). Estimated haplotype frequencies in T2D between the case and control groups (P > 0.05).

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Table 3 Estimated haplotype frequencies in T2D patients and controls Haplotypesa Controls T2D patients OR (95 CI)b P value Q value GCLC (global haplotype association P value: 0.8) rs12524494 rs636933 rs648595 rs761142 rs606548 rs17883901

H1 A G T A C G 0.53 0.5188 1.00 – – H2 A A G C C G 0.1642 0.1699 1.10 (0.90–1.35) 0.34 0.84 H3 A G G A C G 0.1543 0.1562 1.09 (0.89–1.34) 0.39 0.84 H4 A A G C C A 0.03 0.036 1.28 (0.82–1.99) 0.27 0.84 H5 G G G C T G 0.0339 0.0287 0.92 (0.61–1.39) 0.71 0.84 H6 A A G A C G 0.0286 0.0254 0.96 (0.62–1.48) 0.85 0.85 H7 A G T A C A 0.0284 0.0255 1.07 (0.66–1.75) 0.78 0.84 H8 A G G C C G 0.0079 0.0148 1.59 (0.77–3.26) 0.21 0.84 Haplotypesa Controls T2D patients OR (95 CI)b P value Q value GCLM (global haplotype association p value: 0.27) rs7517826 rs3827715 rs2301022 rs41303970

H1 C T C G 0.3428 0.3627 1.00 – – H2 C T T G 0.2577 0.2769 1.03 (0.86–1.24) 0.73 0.84 H3 A C C A 0.1759 0.1464 0.81 (0.66–1.01) 0.047 0.66 H4 A C C G 0.1018 0.0955 0.95 (0.74–1.22) 0.67 0.84 H5 A T C G 0.0598 0.0687 1.07 (0.78–1.47) 0.68 0.84 H6 C T C A 0.0211 0.0136 0.66 (0.37–1.18) 0.16 0.84 H7 A C T A 0.0154 0.0174 1.13 (0.57–2.22) 0.73 0.84 H8 A T T G 0.0195 0.0103 0.77 (0.38–1.56) 0.47 0.84

Bold is signifcant P and Q values T2D type 2 diabetes, OR odds ratio, CI confdence interval a Rare haplotypes with frequency < 0.01 are not shown b Odds ratio with 95% confdence intervals adjusted for age, sex and BMI

Impact of GCL polymorphisms on plasma GSH, ROS (P = 0.047, Table 3) and increased levels of total GSH in and glucose levels plasma (P = 0.024, Suppl. Table 4). However, the latter association did not survive after adjustment for multiple testing The plasma ROS concentration in patients with T2D was (Q > 0.2). signifcantly higher than in healthy controls (P = 0.0002). The levels of total GSH was lower in T2D patients than Bioinformatics analysis in healthy subjects (P = 0.02). We found (Suppl. Table 5) inverse correlation between GSH and ROS levels, whereas Protein–protein interaction analysis performed with the GSH levels were correlated with the blood levels of FBG STRING bioinformatic resource allowed identifying func- (R = 0.208, P = 0.01) and uric acid (R = 0.208, P = 0.032). tional partners of glutamate cysteine ligase proteins. This Three out of six SNPs of GCLC (rs17883901, rs636933, interactomic network (Fig. 1) included 10 enzymes such as rs648595) and SNP of GCLM (rs2301022) were associated glutathione synthetase (GSS), gamma-glutamyltransferase with decreased plasma ROS levels, while SNPs rs7517826 1 (GGT1), gamma-glutamyltransferase 5 (GGT5), gamma- and rs41303970 of GCLM were associated with increased glutamyltransferase 6 (GGT6), gamma-glutamyltransferase in GSH levels (Table 4). 7 (GGT7), cystathionine gamma-lyase (CTH), aminopepti- One of the most common haplotypes spanning minor dase N (ANPEP), catalase (CAT), cytosolic branched- alleles of SNPs rs636933 and rs648595 (alleles with pro- chain-amino-acid transferase (BCAT1), and mitochondrial tective efect on T2D risk) was associated with decreased branched-chain-amino-acid transferase (BCAT2). Gene levels of H2O2 (P = 0.0084, Q = 0.12, Suppl. Table 3). It is Ontology enrichment analysis showed that proteins com- important to note, the C–C-A-A haplotype of GCLM showed prising the network are involved in vital biological pro- an association with the decreased risk of type 2 diabetes cesses including glutathione biosynthesis (Q = 2.36 × 10–16),

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Table 4 Associations of H 2O2 and total glutathione plasma levels with the studied polymorphisms in T2D patients SNP Genotype n Mean (SD), Diference (95% CI) P value Q value µmol/L

H2O2 and GCLC rs12524494 A/A 284 3.81 (0.1) 0.00 0.49 0.67 (A > G) G/A 11 3.98 (0.27) 0.17 (− 0.81 to 1.15) G/G 1 5.68 (0) 1.87 (− 1.33 to 5.08) rs17883901 G/G 350 3.68 (0.08) 0.00 0.033 0.14 (G > A) G/A 50 3.17 (0.17) − 0.48 (− 0.93 to − 0.04) A/A 3 3.55 (0.27) rs606548 C/C 384 3.6 (0.08) 0.00 0.56 0.67 (C > T) C/T 26 3.83 (0.24) 0.23 (− 0.38 to 0.85) T/T 1 4.81 (0) 1.21 (− 1.81 to 4.23) rs636933 G/G 241 3.77 (0.11) 0.00 0.02 0.14 (G > A) G/A 145 3.43 (0.11) − 0.36 (− 0.66 to − 0.06) A/A 25 3.3 (0.3) rs648595 T/T 125 3.9 (0.16) 0.00 0.036 0.14 (T > G) G/T 204 3.54 (0.1) − 0.36 (− 0.71 to − 0.02) G/G 82 3.39 (0.14) − 0.51 (− 0.94 to − 0.09) rs761142 A/A 225 3.69 (0.11) 0.00 0.57 0.67 (A > C) C/A 161 3.52 (0.1) − 0.17 (− 0.48 to 0.14) C/C 26 3.63 (0.27) − 0.06 (− 0.68 to 0.57)

H2O2 and GCLM rs2301022 C/C 193 3.77 (0.12) 0.00 0.032 0.14 (C > T) T/C 170 3.59 (0.11) T/T 43 3.15 (0.16) − 0.53 (− 1.02 to − 0.05) rs3827715 T/T 222 3.53 (0.1) 0.00 0.092 0.23 (T > C) T/C 134 3.9 (0.13) 0.37 (0.04–0.70) C/C 31 3.75 (0.32) 0.21 (− 0.36 to 0.79) rs7517826 C/C 187 3.49 (0.1) 0.00 0.21 0.40 (C > A) C/A 170 3.69 (0.13) 0.20 (− 0.12 to 0.52) A/A 51 3.88 (0.24) 0.39 (− 0.08 to 0.87) rs41303970 G/G 274 3.53 (0.09) 0.00 0.22 0.40 (G > A) G/A 117 3.81 (0.14) 0.29 (− 0.04 to 0.62) A/A 21 3.75 (0.35) 0.23 (− 0.46 to 0.91) Total glutathione and GCLC rs12524494 A/A 166 2.38 (0.13) 0.00 0.69 0.77 (A > G) G/A 10 2.4 (0.58) 0.02 (− 1.05 to 1.08) G/G 1 3.82 (0) 1.44 (− 1.86 to 4.73) rs17883901 G/G 216 2.15 (0.11) 0.00 0.14 0.31 (G > A) G/A 33 2.3 (0.31) 0.15 (− 0.47 to 0.77) A/A 3 0.28 (0.03) − 1.87 (− 3.80 to 0.06) rs606548 C/C 231 2.18 (0.11) 0.00 0.39 0.65 (C > T) C/T 19 2 (0.41) − 0.18 (− 0.97 to 0.62) T/T 2 0.6 (0.35) − 1.58 (− 3.94 to 0.79) rs636933 G/G 141 2.11 (0.14) 0.00 0.51 0.67 (G > A) G/A 98 2.11 (0.18) 0.00 (− 0.44 to 0.44) A/A 15 2.64 (0.4) 0.53 (− 0.38 to 1.43) rs648595 T/T 72 2.22 (0.21) 0.00 0.92 0.97 (T > G) G/T 134 2.11 (0.15) − 0.10 (− 0.59 to 0.39) G/G 47 2.15 (0.24) − 0.07 (− 0.69 to 0.56)

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Table 4 (continued) SNP Genotype n Mean (SD), Diference (95% CI) P value Q value µmol/L

rs761142 A/A 133 2.16 (0.14) 0.00 0.99 0.99 (A > C) C/A 105 2.13 (0.17) − 0.03 (− 0.46 to 0.41) C/C 16 2.14 (0.46) − 0.01 (− 0.90 to 0.87) Total glutathione and GCLM rs2301022 C/C 119 2.03 (0.15) 0.00 0.51 0.67 (C > T) T/C 112 2.27 (0.17) 0.23 (− 0.21 to 0.67) T/T 20 1.94 (0.37) − 0.09 (− 0.90 to 0.71) rs3827715 T/T 143 2.02 (0.14) 0.00 0.078 0.22 (T > C) T/C 76 2.54 (0.21) 0.52 (0.04 to 0.99) C/C 18 1.86 (0.36) − 0.16 (− 1.00 to 0.68) rs7517826 C/C 121 1.86 (0.14) 0.00 0.014 0.14 (C > A) C/A 102 2.51 (0.18) 0.53 (0.11–0.94) A/A 29 1.94 (0.27) rs41303970 G/G 174 2 (0.13) 0.00 0.044 0.14 (G > A) G/A 68 2.53 (0.21) 0.46 (0.01–0.91) A/A 12 2.06 (0.52)

Bold is signifcant P and Q values

alpha-amino acid biosynthetic process (Q = 7.26 × 10–7), rs41303970-A of GCLC was predicted to create a binding response to oxidative stress (Q = 4.40 × 10–4), negative site for transcription factor ZNF143 (P = 0.01). regulation of apoptotic signaling pathway (Q = 1.80 × 10–3), cellular response to glucose stimulus (Q = 4.10 × 10–3), and response to insulin (Q = 2.90 × 10–2). Discussion The atSNP tool allowed identifying a number of transcription factors whose binding sites fall into the DNA The present study observed that T2D patients had motifs spanning the studied SNPs (Suppl. Tables 6, 7). decreased total plasma GSH concentrations and increased Alleles of GCLC and GCLM polymorphisms possessing ROS levels, which are hallmarks of the phenotype of oxi- protective efects against type 2 diabetes are subject of inter- dative stress. As compared to healthy subjects, diabetic est. In parallel, we analyzed tissue-specifc transcriptomic patients were found to have markedly increased levels of data from patients with T2D, a part the T2DiaCoD project hydrogen peroxide (rs17883901, rs636933, rs648595 of with a purpose to identify diferentially expressed genes GCLC and rs2301022 of GCLM) and decreased levels of in pancreatic beta-cells of diabetics. In particular, allele glutathione (rs7517826, rs41303970 of GCLM) in plasma. rs12524494-G of GCLC was predicted to create binding sites The fnding indicates that T2D patients have a relative for 8 transcription factors such as Spi1 (P = 0.02), PRDM1 defciency in glutathione and increased production of reac- (P = 0.009), NFAT (P = 0.009), STAT5A (P = 0.02), HSFY2 tive oxygen species which could account for the trigger- (P = 0.01), SPDEF (P = 0.002), IRF1 (P = 0.009), and SRY ing of oxidative stress, a pathological condition which is (P = 9.10 × 10–5). We predicted that allele rs3827715-C thought to play a role in the pathogenesis of type 2 dia- GCLC could change DNA motif creating binding sites for betes [29–31]. Interestingly, reduced GSH inversely cor- a number of TFs such as AHR::ARNT::HIF1A (P = 0.001), related with ROS, whereas oxidized GSH levels directly CREB3L1 (P = 0.005), CREB3L2 (P = 0.005), ETS correlated with FBG concentrations, indicating an intrigu- (P = 0.001), GRHL1 (P = 0.003), HES7 (P = 0.009), HEY1 ing link between glucose metabolism and redox homeo- (P = 0.001), HIF1A (P = 0.01), HIF1A::ARNT (P = 0.001), stasis. However, it should be noted that hyperglycemia is MLX (P = 0.0009), MYC (P = 0.002), MYC::MAX not the only cause of ROS overproduction. Gadjeva et al. (P = 0.004), TCF3 (P = 0.03), TFCP2 (P = 0.01), VDR [32] used electron paramagnetic resonance to measure (P = 0.03), XBP1 (P = 0.0008) and ZEB1 (P = 0.01). Allele serum ROS in real time before and after insulin therapy

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proteins participating in alpha-amino acid biosynthetic process, response to oxidative stress, negative regulation of the apoptotic signaling pathway, cellular response to glucose stimulus, and response to insulin. These GO terms point out the GCL enzyme plays a role in cellular bio- energetics, fuel molecule metabolism and cell survival. The functional relationship between the GCL subunits and BCAT1, BCAT2 and CTH may be of crucial importance for GSH biosynthesis, as these enzymes can share some substrates. For instance, BCAT1 and BCAT2 produce glutamate in the transamination reaction, whereas CTH forms cysteine. Both glutamate and cysteine are required for GSH cycle initiation. Under conditions of oxidative stress, increased demand for GSH may interfere with branched amino acid transamination. The results of metabolomic analysis [35] showed that increased concentrations of leucine and isoleucine represent strong metabolic predictors Fig. 1 Functional partners of GCLC and GCLM proteins (STRING). for lower insulin sensitivity. An importance of transami- Edges represent protein–protein interactions. Associations are nation reactions for T2D has been recently demonstrated meant to be specifc and meaningful, i.e. proteins jointly contribute by a study of Ruiz-Canela et al. [36] which reported that to a shared function; this does not necessarily mean they are physi- cally binding each other. GCLC glutamate cysteine ligase, catalytic higher levels of baseline branched amino acids are associ- subunit, GCLM glutamate cysteine ligase, modifer subunit, GSS ated with higher risk of T2D. glutathione synthetase, GGT1 gamma-glutamyltransferase 1, GGT5 Since the investigated SNPs are located in non-coding GGT6 gamma-glutamyltransferase 5, gamma-glutamyltransferase genomic regions known to infuence gene expression [37], it 6, GGT7 gamma-glutamyltransferase 7, CTH cystathionine gamma- lyase, ANPEP aminopeptidase N, CAT catalase, BCAT1 cytosolic was important to review the bioinformatics fndings obtained branched-chain-amino-acid transferase, BCAT2 mitochondrial by the atSNP search tool and analyze literature data on branched-chain-amino-acid transferase. Colors of edges represent the molecular/biological functions of TFs in order to unravel following types of interactions. (Color fgure online) the molecular mechanisms by which the studied SNPs are associated with T2D susceptibility. The bioinformatics anal- and clearly showed that free radical generation persists ysis revealed that TFs with binding sites that appear in the even after normalization of the glucose levels. presence of minor alleles are completely diferent from the Glutamate cysteine ligase is a regulatory enzyme cata- spectrum of TFs specifcally associated with the reference lyzing the frst step of de novo GSH biosynthesis. As an alleles. For instance, the alternative allele G of rs12524494 antioxidant, glutathione scavenges ROS, reactive nitrogen at the GCLC gene creates binding sites for 9 TFs, among and sulfur species, and other free radicals are produced which STAT5A is of the most interest, as it is one of the in association with electron transport, xenobiotic metabo- most potent gene expression activators. Reference allele A lism, and infammatory response [33]. The enzyme forms has 6 TFs, four of which are activators. Comparison of the a heterodimeric complex consisting of two distinct gene number of activators binding to minor and wild-type alleles products. The catalytic subunit (GCLC) is the larger of the suggests greater GCLC gene activity in the presence of the two subunits and contains the active site responsible for alternative allele G. Indeed, according to the T2DiaCoD the ATP-dependent reaction between the amino group of database, which deposits the results of tissue-specifc tran- cysteine and the gamma-carboxyl group of glutamate. The scriptome analysis of T2D patients, expression of STAT5, modifer subunit (GCLM) is smaller and increases the cat- which binds to the G allele, is increased in the pancreas of alytic efciency of GCLC through direct interaction with diabetic patients. the subunit [34]. However, functional partners of GCL We predicted that allele rs12524494-G of GCLC could proteins are not limited to the enzymes of the glutathione create transcription factor binding sites (TFBS) for 8 tran- cycle (GSS, GGT1, GGT5, GGT6, GGT7) and include scription factors, and three of them are subject of a great other enzymes supplying the GSH synthesis pathway with interest since they could be directly or non-directly related necessary reactants (e.g., CTH, ANPEP), catalase (CAT), to molecular pathogenesis of T2D. NFAT (nuclear factors of and enzymes metabolizing valine, leucine, and isoleucine activated T-cells) was found to be recruited to the transcrip- (BCAT1 and BCAT2). Gene Ontology enrichment analysis tion loci and regulate resistin gene expression upon insulin allowed identifying that besides proteins directly involved stimulation thereby contributing to glucose homeostasis in GSH metabolism, the GCL partners also included [38]. The levels of STAT5A (signal transducer and activator

1 3 Molecular Biology Reports of transcription 5A) mRNA in pancreatic islets are increased endogenous vitamin D biosynthesis through epigenetically in T2D patients (T2DiaCoD database), and STAT5 activity transcriptional activation of vitamin D-metabolism genes in beta-cells was experimentally proved to infuence the sus- [49]. Transcription factor XBP1 (X-box binding protein 1) is ceptibility to type 1 and type 2 diabetes [39]. Interestingly, a transcription factor functioning during endoplasmic reticu- transcription factor IRF1 (interferon regulatory factor 1) is lum stress by regulating the unfolded protein response (Uni- a key regulator for insulin and chemokine secretion by pan- ProtKB—P17861), and this TF is down-regulated in beta creatic islets under infammatory attack [40]. cells in diabetic patients (T2DiaCoD database). Allele rs3827715-C GCLC was found to create binding Allele rs41303970-A of GCLC was predicted to estab- sites for a number of TFs. ARNT (aryl hydrocarbon recep- lish TFBS for ZNF143. ZNF143 is a zinc fnger protein tor nuclear translocator) together with HIF1A (hypoxia- 143 known to activate the gene for selenocysteine tRNA inducible factor-1α) are thought to be crucial regulators of (UniProtKB—P52747) driving the recoding of highly responses to conditions of reduced oxygen or hypoxia [41]. specifc UGA codons from stop signals to selenocysteine Notably, CREB3L1 (cAMP responsive element binding [50], a cysteine analogue with selenium replacing sulphur. protein 3 like 1) represents a transcription factor known to It was also interesting fnding that T2D-associated allele mediate functional and structural adaptation of the secre- rs41303970-G of GCLM was predicted to create a binding tory pathway in hormone-stimulated cells, particularly in site for transcription factor NFE2L2 (nuclear factor, eryth- thyroid cells [42], suggesting that this function of CREB3L1 roid 2 like 2), whose expression is decreased in pancreatic could also be important in insulin biosynthesis and secre- islets of type 2 diabetics (T2DiaCoD database). According tion. Transcription factor ETS (E26 transformation-spe- to the Comparative Toxicogenomics Database, NFE2L2 cific family) was found to inhibit expression of PDX-1 may activate expression of the GCLM gene as a response to leading to dysfunction of pancreatic beta cells [43]. MLX tobacco smoke exposure suggesting the mechanism of pro- (max-like protein x) is a transcription regulator which is tecting pancreatic islets from oxidative damage through up- known to activate glycolytic target genes [44]. MYC (MYC regulation of modifer subunit of GCL. Smoking increases proto-oncogene, bHLH transcription factor) represents an the production of ROS, exacerbating oxidative stress [51, important transcription factor which could play a role in 52] and overloading the antioxidant system. Smokers exhibit the pathogenesis of T2D. However, two studies published several aspects of insulin resistance [53] and have an oxi- in 2002 obtained controversial results regarding the link dative infammatory state [54]. A study by Cai Chen [55] between an increased expression of MYC and the risk of found decreased sensitivity of islets to glucose stimulus, sug- type 2 diabetes. A study of Riu et al. provided evidence that gesting an adverse efect of smoking on beta-cell function. MYC overexpression in liver may induce glucose uptake Recently, Dinardo et al. [56] stated that smoking is a predic- and utilization directly by altering the expression of meta- tor of elevated HbA1c levels in T2D patients. We believe bolic genes and through the expression of key transcription that this is a potential mechanism by which smoking may factor genes [45]. Meanwhile, a study of Kaneto et al. [46] increase susceptibility to T2D in individuals with decreased reported that increased expression of c-Myc in beta-cells expression of NFE2L2 in the pancreatic tissue via attenu- was found to suppress the insulin gene transcription. TCF3 ated activation of GCLM expression in response to tobacco (transcription factor 3) is a member of the Wnt signaling smoke compounds. pathway (it is known to be involved in lipid metabolism and Thus, present study conducted in Russian population glucose homeostasis) which together with another members found for the frst time that polymorphisms at genes encod- of this pathway were found to be expressed at low levels ing catalytic and modifer subunits of glutamate cysteine in pancreatic islets in healthy individuals, but were found ligase contribute to T2D susceptibility and are related to to be up-regulated specifcally in patients with type 2 dia- fasting blood glucose levels as well as with the plasma lev- betes [47]. ZEB1 (zinc fnger E-box-binding homeobox 1) els of glutathione and hydrogen peroxides in diabetics. The acts as a transcriptional repressor inhibiting expression of study showed that SNPs in noncoding regions of GCLC genes such as interleukin-2, sodium/potassium-transport- and GCLM genes are protective against T2D risk, dem- ing ATPase subunit alpha-1 and E-cadherin (UniProtKB— onstrating that genes encoding GCL play a role in disease P37275). VDR (vitamin D receptor) is a nuclear receptor pathogenesis. In particular, SNP rs12524494 at GCLC and for calcitriol, the active form of vitamin D3 mediating the SNPs rs3827715, rs7517826, rs41303970 at GCLM gene action of this vitamin on cells (UniProtKB—P11473). are associated with decreased risk of T2D. We observed Interestingly, metabolism of vitamin D and glutathione is the alleles rs12524494-G of GCLC and rs41303970-A of strongly interrelated: on the one hand, vitamin D is capable GCLM exhibit protective efects against the disease risk of activating glutathione biosynthesis through up-regulation solely in nonsmokers suggesting the gene-smoking interac- of glutamate cysteine ligase and glutathione reductase [48], tions could be responsible for triggering the disease. Mech- on the other hand, glutathione is essential for the control of anisms responsible for the described protective efects of

1 3 Molecular Biology Reports minor alleles of the studied genes may involve changes in the 5. Fuchsberger C, Flannick J, Teslovich TM et al (2016) The genetic transcription factor network resulting in increased expres- architecture of type 2 diabetes. Nature 536:41–47. https://doi. GCL org/10.1038/nature18642 sion of the genes, augmented GSH production and 6. Stelzer G, Rosen R, Plaschkes I, Zimmerman S, Twik M, Fishi- decreased ROS levels. Further studies are required to sub- levich S et al (2019) The genecards suite: from gene data min- stantiate the comprehensive contribution of genes involved ing to disease genome sequence analysis. Curr Protoc Bioinform in the glutathione metabolism to disease pathogenesis and 54(1):1–30. https://doi.org/10.1002/cpbi.5 7. DeFronzo RA, Inzucchi S, Abdul-Ghani M, Nissen SE (2019) identify new targets and approaches to antioxidant treatment Pioglitazone: the forgotten, cost-efective cardioprotective drug and prevention of type 2 diabetes. for type 2 diabetes. Diabetes Vasc Dis Res 16(2):133–143. https ://doi.org/10.1177/1479164118825376 Acknowledgements We thank all the T2D patients, healthy volunteers 8. Chatterjee S, Khunti K, Davies MJ (2017) Type 2 diabetes. Lancet and staf of the Kursk Emergency Hospital. The study was supported 389:2239–2251. https://doi.org/10.1016/S0140 -6736(17)30058 -2 by Russian Science Foundation (№20–15-00227). 9. Koska J, Saremi A, Howell S et al (2018) Advanced glycation end products, oxidation products, and incident cardiovascular events in Author contributions IA: laboratory investigations, database handling, patients with type 2 diabetes. Diabetes Care 41(3):570–576. https statistical and bioinformatics analysis, interpretation and discussion of ://doi.org/10.2337/dc17-1740 study results, writing and revising the paper; EK: laboratory investiga- 10. Ozdemır G, Ozden M, Maral H, Kuskay S, Cetınalp P, Tarkun I tions, database handling, data curation; VL: project administration, (2005) Malondialdehyde, glutathione, glutathione peroxidase and instructions of clinical, laboratory and instrumental examination of the homocysteine levels in type 2 diabetic patients with and without study patients; AK: instructions of patients enrollment, consultancy; microalbuminuria. Ann Clin Biochem 42(2):99–104. https://doi. AP: the study conception and design, supervision of the study, inter- org/10.1258/0004563053492838 pretation and discussion of the study results, writing and revising the 11. Soliman GZA (2008) Blood lipid peroxidation (superoxide dis- paper. 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