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Oxidative stress and immunological biomarkers in Ankylosing spondylitis patients
Gene Reports 18 (2020) 100574
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Oxidative stress and immunological biomarkers in Ankylosing spondylitis patients
T
Shahla Danaiia, Rozita Abolhasania, Mohammad Sadegh Soltani-Zangbarb,c,d, Majid Zamanic, Amir Mehdizadehe,f, Bahareh Amanifarc, Bahman Yousefig, Mehdi Nazarih, Tannaz Pourlaki, ⁎ Mehrzad Hajialilooc, Mehdi Yousefic,i, a
Gynecology Department, Eastern Azerbaijan ACECR ART Center, Eastern Azerbaijan Branch of ACECR, Tabriz, Iran Student Research committee, Tabriz University of Medical Sciences, Tabriz, Iran c Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran d Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran e Endocrine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran f Comprehensive Health Lab, Tabriz University of Medical Sciences, Tabriz, Iran. g Stem Cell Research Center, Tabriz University of Medical Sciences, Tabriz, Iran h Department of Anesthesiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran i Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran. b
ARTICLE INFO
ABSTRACT
Keywords: Ankylosing spondylitis Oxidative stress Immunological factors Th 17 cells Regulatory T cells
Ankylosing spondylitis (AS) is an inflammatory condition with unrevealed etiology mostly affecting the peripheral joints, the axial skeleton and extra articular structure. In recent years, oxidative stress and immunological factors have been reported as significant factors in AS pathogenesis. The object of this research was to assess the immunological and the oxidative stress factors in AS patients. In this study, 35 patients diagnosed with AS and 40 healthy controls were subjected for clinical examination. Patients were evaluated for Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). The biomarkers of oxidative stress were evaluated by biochemical assays. We evaluated the mRNA level of transcription factors, cytokines, chemokines and related miRNAs. T Helper 17 cells (Th17), regulatory T cells (Treg) proportion and cytokines secretion were also assessed. Higher levels of nitric oxide (NO) (p < 0.0001), superoxide dismutase (SOD) (p = 0.0002), total oxidant status (TOS) (p = 0.0041) and catalase (CAT) (p = 0.0002) were observed in AS patients. However, no significant differences in glutathione peroxidase (GPX) activity level were observed between studied groups. Also, in peripheral blood of AS patients, Th17 (p < 0.0001) and Treg (p = 0.0006) cells were significantly increased and decreased compared to the healthy controls. Nuclear factor (NF)-κB and Activation protein (AP)-1 mRNA expression levels were also increased in AS patients (p = 0.0001 and p = 0.0004, respectively). A significant decrease in miR-146a and miR-223 (p < 0.0001 and p = 0.0025, respectively) and increase in miR-21 (p = 0.0018) expression level were similarly observed in AS patients. Moreover, the secretion of tumor necrosis factor (TNF)-α (p < 0.0001), Interleukin (IL)-1β (p = 0.0002), CCL2 (p < 0.0001), CCL3 (p < 0.0001), CXCL8 (p = 0.0006) and adiponectin (p = 0.0002) were increased in AS patients. Our results showed that immunological and oxidative stress biomarkers play key roles in AS pathogenesis probably mediated by inflammation.
Abbreviations: AS, Ankylosing spondylitis; MetS, Metabolic syndrome; Th17, T Helper 17 cell; Treg, Regulatory T cell; ELISA, Enzyme-linked immune sorbent assay; NF-kB, Nuclear factor κ B; AP-1, Activation protein 1; IL-1β, Interleukin-1β; IL-6, Interleukin-6; TNF-α, Tumor Necrosis Factor α; CCL-2 and 3, C-C Motif Chemokine Ligand 2 and 3; CXCL-8, CXC Motif Chemokine Ligand 8; SOD, Superoxide Dismutase; GPX, Glutathione Peroxidase; CAT, Catalase; NO, Nitrite Oxide; TOS, Total Oxidative Stress; AS-NMS, Ankylosing Spondylitis without Metabolic syndrome; AS-MS, Ankylosing Spondylitis with Metabolic syndrome; BMI, Body Mass Index; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; FBS, Fasting Blood Sugar; HbA1C, Hemoglobin A1C; TG, Triglyceride; HDL, High Density Lipoprotein; BASDAI, Bath Ankylosing Spondylitis Disease Activity Index ⁎ Corresponding author at: Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. E-mail address: [email protected] (M. Yousefi). https://doi.org/10.1016/j.genrep.2019.100574 Received 9 September 2019; Received in revised form 12 November 2019; Accepted 26 November 2019 Available online 28 November 2019 2452-0144/ © 2019 Elsevier Inc. All rights reserved.
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1. Introduction
confirmation was done by a rheumatology specialist according to Assessment of Spondyloarthritis International Society (ASAS) criteria. A group of 40 healthy age and sex-matched subjects was also included as controls. For clinical disease activity analysis, at the study time, bath ankylosing spondylitis disease activity index (BASDAI) was assessed in all patients. The BASDAI disease activity questionnaire consists of six 10 cm horizontal visual analog scales to measure the level of fatigue, level of neck, hip, or back pain, level of pain swelling in joints other than neck, hip, back, level of discomfort an area tender to touch, and the level of morning stiffness and duration of morning stiffness. Each question is scored on a scale of 0 to 10. Aside from the last question, 0 indicates none and 10 indicate very severe. For the last question, 0 is 0 h, 5 is 1 h, and 10 is two or more hours. Before participation in the study, signed informed consent was achieved from all patients. The inclusion criteria were ankylosing spondylitis diagnosis, a BASDAI score ≥4 and willingness to cooperate. Using nutritional supplements, antioxidants, alpha-lipoic acid within a month prior the study, diabetes history, autoimmune and other chronic diseases, pregnancy and lactation were also considered as exclusion criteria. The Research Ethics Committee of Tabriz University of Medical Sciences (IR.TBZMED.REC.1397.167) approved the study. Table 1 represents the key demographic data and some clinical features of AS patients and Healthy individuals.
Ankylosing spondylitis (AS) is a chronic inflammatory disorder, mainly affecting the axial skeleton and the sacroiliac joints (Szalay et al., 2011; Genre et al., 2015). The main clinical features of AS is inflammatory backache, enthesitis and specific organ involvement (Szalay et al., 2011; Ljung et al., 2018). Several pathogenic factors, such as bacterial infection, environmental stimuli, HLA-B27 and HLA-E genetic factors prevalence are responsible for ankylosing spondylitis pathogenesis (Wu et al., 2011). Radiographic imaging is routinely used for severe AS diagnosis and prognosis; however, for early diagnosis and treatment of AS, evaluation of the molecular factors is important (Van Der Linden et al., 1984; Graham and Van, 1989). Currently, studies have focused on the immunological and oxidative stress factors for AS. T cells have a key role in AS pathogenesis because of their role in immune system regulation (Reinherz and Schlossman, 1980). Many researches have assessed the prevalence of Regulatory T cell (Tregs) and T Helper 17 cell (Th17) in autoimmune disorders such as Ankylosing spondylitis (Xueyi et al., 2013). Findings of the most studies have demonstrated that the Th17 and Treg is increased and decreased, respectively, in peripheral blood (PB) of AS patients and this change in immune phenotype and contributing factors may have a crucial role in pathogenesis and progress of the disease (Hajialilo et al., 2019; Wang et al., 2015). Additionally, AS progression may be related to the degree of inflammation. This idea is supported by high expression of tumor necrosis factor (TNF)-α, an indicator of inflammation, in the sacroiliac joints in AS patients (Brandt et al., 2000; Genre et al., 2014). It has also been reported that the in vitro interleukin (IL)-17, the main cytokine of Th17 cells, stimulates the TNF-α and IL-1β production to induce the inflammation and cartilage destruction (Koshy et al., 2002). Moreover, several authors have reported that treatment of AS patients by anti-TNF-α antibodies is an effective approach, causing low level of inflammation and subsequently improvement of the disease (Genre et al., 2015). Several studies on AS patients also have reported reduced Treg cells, which may lead to impaired suppressor activity (Liao et al., 2015). Recent studies have also considered the increased oxidative stress as the pathogenic factor in several inflammatory diseases, including AS (Stanek et al., 2010a). Increased oxidative stress mediators have led to pro-inflammatory cytokines production in these abnormalities (Stanek et al., 2010b). Oxidative stress is characterized by increased reactive oxygen species (ROS) level which disrupts the oxidants and antioxidants balance in the body (Wauquier et al., 2009). One of the important cytokines in ROS production is TNF-α and strategies based on anti-TNF treatment have been demonstrated to improve oxidation status and decreased AS pain and inflammation (Karkucak et al., 2010). Furthermore, oxidative stress elements produced by neutrophil activation play a crucial role in AS pathogenesis (Yazici et al., 2004). However, there are few studies on the role of immunological and oxidative stress factors in AS patients. The purpose of the current study was to assess the overall changes in a variety of oxidative stress and immunological factors involved in pathogenesis of AS. Additionally, Th17 and Treg cells ratio alterations, expression analysis of pro-inflammatory cytokines (TNF-α, IL-1β and IL-6), nuclear factor (NF)-κB and activation protein (AP)-1 transcription factor, chemokines (CCL-2, CCL-3 and CXCL-8) and miRNAs (miR-146a, miR-21 and miR223) in the peripheral blood mononuclear cells (PBMCs) of AS patients were also compared to the healthy control group. Furthermore, we measured the secretion level of adiponectin and oxidative stress biomarkers including total oxidative status (TOS), superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT) and nitric oxide (NO).
2.2. Blood samples and PBMCs isolation 10 ml of peripheral blood was drawn under aseptic precautions from both AS patients and healthy controls. PBMCs were isolated from samples via density-gradient centrifugation (25 min, 450 ×g) using Ficoll separation technique (Biosera, UK). Then, the peripheral blood mononuclear cell layer was isolated. Cells were washed by phosphate buffered saline (PBS) (Sigma-Aldrich, Schnelldorf, Germany) twice and used for further assessments. 2.3. Quantitative real-time PCR Expression level of NF-κB and AP-1 transcription factors, inflammatory cytokines and chemokine's including: IL-1β, TNF-α, IL-6, CCL-2, CCL-3 and CXCL-8 were analyzed using a SYBR green technique with specific primers and quantitative Real-time polymerase chain Table 1 Demographic characteristics of controls and AS patients.
2. Material & methods
Variable
Control (mean ± Sd) N = 40
AS (mean ± Sd) N = 35
Age (year) Sex (men/women) SBP (mmHg) DBP (mmHg) FBS (mg/dl) HbA1C (%) TG (mg/dl) HDL (mg/dl) Level of Fatigute (0−10) Level of Neck Hip back pain (0–10) Level of pain swelling other than Back, Hip, Neck (0–10) Level of discomfort an area tender to touch (0–10) Level of morning stiffness (0–10) Duration of morning stiffness (0–10) BASDAI (0–10)
43.89 ± 12.51 23/17 116.63 ± 16.36 79.16 ± 8.04 90.86 ± 7.5 5.42 ± 0.74 110.2 ± 62.85 56.16 ± 3.8 – – –
43.17 ± 11.32 19/16 128.1 ± 18.55 81.88 ± 6.12 106.14 ± 8.41* 5.61 ± 0.77 178.41 ± 71.66* 41.37 ± 2.89* 3.85 ± 1.11 4.15 ± 1.51 4.1 ± 1.34
–
3.96 ± 1.41
– –
3.81 ± 2.45 0.639 ± 0.43
–
4.93 ± 0.69
Data are presented as number and mean ± SD. *(p < .05) vs Healthy Controls. AS: Ankylosing Spondylitis; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; FBS: Fasting Blood Sugar; HbA1C: Hemoglobin A1C; TG: Triglyceride; HDL: High Density Lipoprotein; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index.
2.1. Study design We assessed a series of 35 AS patients referred to Imam Reza Hospital of Tabriz University of Medical Sciences in this study. AS 2
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TNF-α, IL-6, CCL-2, CCL-3, CXCL-8 and adiponectin secretion were evaluated by ELISA technique and ELISA kit (MyBioSource, San Diego, USA). The levels of the cytokines were assessed in duplicate to improve the accuracy. The Medgenix ELISA reader (BP-800, Biohit, USA) was used to measure absorbance values at 450 nm and the concentrations were evaluated according to the standard curve.
Table 2 Used primer sequences for qPCR. Gene
Sequence (5′ → 3 ′ )
IL-1β
Forward: CTGATGGCCCTAAACAGATGAAG Reverse: GGTCGGAGATTCGTAGCAGCTGGAT Forward: ACTCACCTCTTCAGAACGAATTG Reverse: CCATCTTTGGAAGGTTCAGGTTG Forward: GGCAGGTCTACTTTGGAGTCATTGC Reverse: ACATTCGAGGCTCCAGTGAATTCGG Forward: GCATGAAAGTCTCTGCCG Reverse: GAGTGTTCAAGTCTTCGGA Forward: GCTGCCCTTGCTGTCCTCCTC Reverse: GGTCAGCACAGACCTGCCGG Forward: GCCTGCTGCTCATGGCAGCC Reverse: GCACAGACCTCCTTGCCCCG Forward: AACCCAGAGAGGAAAAGACT Reverse: TGCAGGAAAGGAGAGAGAG Forward: GCTGCTGTGTGGGGATAGAT Reverse: GGCCCAGTCTTTTCCTCTCT Forward: AGAGCTACGAGCTGCCTGAC Reverse: AGCACTGTGTTGGCGTACAG
IL-6 TNF-α CCL-2 CCL-3 CXCL-8 AP-1 NF-κΒ Beta-Actin
2.6. Biochemical analysis of oxidative stress biomarkers The levels of TOS, GPX activity, CAT and SOD activity and NO production were analyzed as oxidative status markers. Total oxidant activity method developed by Erel et al. was used for determination of serum TOS levels. The outcomes were measured in terms of micromolar hydrogen peroxide equivalent/liter (Erel, 2005). For GPX activity evaluation, Paglia and Valentine's kinetic assay was used (Paglia and Valentine, 1967), as the substrate using t-butyl peroxide and normalized to 1 g of hemoglobin [IU/gHb] and measured as micromoles of oxidized NADPH per minute. SOD activity was assayed by Oyanaguis method (Ōyanagui, 1984). Optical absorbance was assessed by Pekrin Elmer analyzer (PerkinElmer Informatics) at 550 nm and the SOD activity was measured in nitric unit. Erythrocyte catalase activity was measured by kinetic way formerly defined by Aebi et al. (Aebi, 1984). Briefly, following RBC hemolysate preparation, absorbance of the samples containing 2 ml of hemolysate and 1 ml of H2O2 were measured in 240 nm at room temperature. For evaluation of NO production, − − NO− 2 and NO3 quantitation were estimated. The absorbance of NO2 and mixture of sulfanilamide and naphthethylenediamine was identified at 540 nm based on Griess reaction (Cortas and Wakid, 1990).
IL-1β: Interleukin-1β; IL-6: Interleukin-6; TNF-α: Tumor Necrosis Factor α; CCL2, 3, 8: CC Motif Chemokine Ligand-2, 3, 8; AP-1: Activation Protein-1; NF-κΒ: Nuclear Factor- κΒ.
reaction (qPCR) system with Light Cycler 2.0 (Roche Applied Science, Germany) in isolated PBMCs in studied groups. Primers sequences are presented in Table 2. First, the samples were homogenized and RNXPLUS Solution (SinaClon, Tehran, Iran) was used for total RNA extraction. Then, cDNA was synthesized with Revert Aid Reverse Transcriptase kit (Thermo Fisher, Waltham, MA, USA). The amplification was also confirmed on 2% agarose gel. Also, miR-21, miR-146a and miR-223 gene expression were assessed using Real-time PCR in AS patients. We used Beta-Actin and RNU6B as controls and the relative gene expression was computed using to 2−ΔΔCT formula.
2.7. Statistical analysis SPSS software (version 23.0; SPSS Inc.) was used to perform statistical analysis. Unpaired t-test was used for data analysis between AS patients and control group. The GraphPad Prism version 7.00 (GraphPad Software, La Jolla, CA, USA, www.graphpad.com) was used for drawing the graphs. p < 0.05 was considered as statistically significant.
2.4. Flow cytometery The ratio of CD4+ TH17 cells as source of IL-17 producing cells and Treg cells (CD4+ CD25+ CD127−) was measured by flowcytometry technique. Anti-intracellular and anti-surface markers were used to assess of TH17 cells quantity. Cells were incubated With phorbol myristate acetate (PMA) (10 ng/ml) and ionomycin (0.5 μM) for 5 h (Sigma-Aldrich, Schnelldorf, Germany) at 37 °C in a 5% CO2 moistened incubator. Formerly after washing the cells, they were incubated for 15 min with anti-CD4-fluorescein isothiocyanate (FITC) (BD Biosciences, San Jose, CA, USA) at 4 °C. Then, the cells were washed two times and permeabilized with a permeabilizing and fixating buffer (eBioscience), and incubated with anti-IL17-phycoerytrin (PE) antibody for intracellular staining at 37 °C for 20 min. FITC and PE-conjugated mouse IgG1κ antibodies were also used as isotype control for background effect normalization. Based on side and forward scatter properties the total lymphocytes were gated. The lymphocytes were more evaluated for CD4 expression, and IL-17 producing lymphocytes were considered as Th17 cells. For Treg cells detection, fluorochrome-conjugated monoclonal antibodies including anti-CD4-FITC, anti-CD25-PE and anti-CD127PerCP-Cy5.5 (eBioscience, San Diego, CA, U.S.A) were added to 1 × 106 PBMCs and incubated for 15 to 30 min at room temperature in a dark place. Then, based on their side and forward scatter properties lymphocytes were gated and CD4+ lymphocytes were analyzed for CD25 and CD127 expression. FACS Calibur flow cytometer (BD Biosciences) and FlowJo software (Becton Dickinson, Mountain View, CA) were used for scanned and data analysis of stained cells.
3. Results 3.1. The expression levels of cytokines, chemokines, transcription factors and associated micro-RNAs in AS patients and healthy controls AP-1 and NF-κB transcription factors, inflammatory cytokines and chemokine's including IL-1β, TNF-α, IL-6, CCL-2, CCL-3 and CXCL-8 as well as miR-146a, miR-21 and miR-223 expression level were assessed and compared between AS patients and healthy group (Fig. 1). Our results showed an increased expression levels of TNF-α and IL-1β, IL-6 cytokines in AS patients in comparison to healthy individuals (p < 0.0001, p < 0.0001 and p < 0.0001, respectively). As expected, AS patients showed higher expression levels of CCL2, CCL3 and CXCL8 chemokines towards healthy individuals (p = 0.0002, p = 0.0007 and p = 0.0035, respectively). Moreover, the expression levels of NF-κβ and AP-1 transcription factors were increased in AS patients towards control group (p = 0.0001 and p = 0.0004, respectively). Additionally, miR-21 showed significant increase in AS patients compared to the healthy group (p = 0.0018). On the other side, miR-223 and miR-146a expression levels which are correlated with inflammatory response suppression were decreased in AS patients compared to healthy individuals (p = 0.0025 and p < 0.0001, respectively). 3.2. Changes in cytokines, chemokines and adiponectin secretion levels in AS patients and healthy controls Cytokines, chemokines and adiponectin secretion were evaluated in AS patients and control group using ELISA method. TNF-α (p < 0.0001) and IL-1β (p = 0.0002) secretion levels were
2.5. Enzyme-linked immunosorbent assay (ELISA ( Serum inflammatory cytokines and chemokine's including IL-1β, 3
Fig. 1. Real time PCR analysis of TNF-α, IL-6 and IL-1β cytokines, CCL-2, CCL-3 and CXCL-8 chemokines, NF-κΒ and AP-1 transcription factors and mir-21, mir-146a and mir-223 miRNA expression in patients and control group. The results showed increased level of CXCL-8, CCL-3, CCL-2, IL-1β, IL-6, TNF-α, NF-κΒ, AP-1 and miR-21 in AS patients compared to control group (p = 0.0035, p = 0.0007, p = 0.0002, p < 0.0001, p < 0.0001, p < 0.0001, p = 0.0001, p = 0.0004, p = 0.0018, respectively). In contrast, the expression of miR-146a and miR-223 were decreased in AS patients compared to healthy controls (p < 0.0001, p = 0.0025, respectively). Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
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Fig 2. The concentrations of serum IL-1β and TNF-α, adiponectin and chemokines (CCL-2, CCL-3 and CXCL-8) in AS patients and healthy controls. Increased concentration of IL-1β, TNF-α, Adiponectin, CCL-2, CCL-3 and CXCL-8 was observed in AS patients compared to control group (p = 0.0002, p < 0.0001, p = 0.0002, p < 0.0001, p < 0.0001, p = 0.0006, respectively). Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
been also reported that the oxidative stress have a significant role in AS pathogenesis (Stanek et al., 2010a; Feijóo et al., 2009). AS is a chronic inflammatory rheumatic disorder mainly described by changes in the sacroiliac joint and the axial skeleton. However, few studies have evaluated the immunological factors changes in AS patients such as elevated levels of Th17 and reduced levels of Treg cells which have been reported in AS patients (Liao et al., 2015). Thus, in this study, the oxidative stress and immunological factors were assessed in AS patients. To this aim, 35 AS patients with the age range of 20–55 and 40 healthy controls participated in this study. To prove a relationship between oxidative stress and AS pathogenesis, the levels of TOS, GPX, SOD, NO and CAT were measured as biomarkers of oxidative stress. Additionally, for immunological evaluation, the proportion of Th17 and Treg cells, NF-κB and AP-1 transcription factor expression, inflammatory cytokines and chemokine's including IL-1β, TNF-α, IL-6, CCL-2, CCL-3 and CXCL-8, adiponectin and miRNAs (miR-146a, miR-21 and miR-223) were measured in the peripheral blood of the participants. Our data revealed that severity of the inflammation and disease symptoms are increased in AS patient compared to healthy controls following elevated level of oxidative stress biomarkers in these patients. In AS patients, the levels of SOD, NO, TOS and CAT were significantly higher compared to healthy group. Furthermore, GPX level showed a higher but not significant activity compared to healthy control group. Karkucak et al. also, evaluated antiTNF agent effects on oxidative status in AS patients. In consistence to our results, they showed that oxidative stress is accelerated in AS group and anti-TNF treatment have beneficial effects on these patients (Karkucak et al., 2010). It has also been reported that increased oxidative stress, may affect the intensification of atherosclerosis in active phase of male AS patients (Stanek et al., 2017). Previous researches have mostly studied the ratio of Th17 (important regulator of autoimmune-inflammatory disorders) and Tregs (immune system suppressor). Different findings have reported the significant increase and decrease of Th17 and Treg cells in AS patients (Szalay et al., 2011; Jandus et al., 2008). In the current study, flowcytometric analysis of PBMCs in AS patients also revealed a significant increase and decrease of peripheral blood Th17 and Treg cells compared to healthy control group, respectively, probably because of contributing factor in disease development.
significantly higher in AS patients in comparison to the healthy group (Fig. 2). Comparison of AS patients and healthy individuals indicated that CCL2, CCL3 and CXCL8 secretion levels were higher in AS patients (p < 0.0001, p < 0.0001 and p = 0.0006, respectively) (Fig. 2). In addition, AS patients showed desirable increase of adiponectin secretion towards healthy group (p = 0.0002) (Fig. 2). 3.3. Analysis of oxidative stress biomarkers in AS patients and control group The activity levels of SOD, CAT and GPX, NO production and TOS were analyzed by biochemical assays. The levels of SOD, CAT and NO in AS patients demonstrated a notable increase in comparison to control group (p = 0.0002, p = 0.0002, p < 0.0001, respectively) (Fig. 3). In contrast, compared to healthy controls, low level of TOS was observed in AS patients (p = 0041). No changes in GPX activity were observed between studied groups (Fig. 3). 3.4. The proportion of circulating Th17 and Treg cells in peripheral blood of AS patients and control individuals Treg and Th17 cells proportion were assessed in PBMCs of AS patients and control individuals by flow cytometry technique. Flow cytometric assessment showed that AS patients had low cellular proportion of Treg cells in comparison to control individuals (p = 0.0006) (Fig. 4). Additionally, flow cytometric evaluation of Th17 cells showed a higher ratio of these cells in AS patients compared to the healthy individuals (p < 0.0001) (Fig. 4). 4. Discussion Oxidative stress is a disorder described by increased level of reactive oxygen species (ROS) or insufficient antioxidant defense and can be evaluated by total oxidant status (TOS), total antioxidant status (TAS) and its systematic reflections (Stanek et al., 2010a; Stanek et al., 2010b). ROS is released into the extracellular space and damages the nearby tissues in inflammation and phagocytosis reactions, increasing the level of acute-phase proteins (Guillot et al., 2014). On the other hand, it has 5
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Fig. 3. Comparison of oxidative stress biomarkers in AS patients and healthy controls. The higher levels of SOD, Catalase, TOS and NO were observed in AS patients compared to healthy controls (p = 0.0002, p = 0.0002, p = 0.0041 and P < 0.0001, respectively). No significant differences were observed in GPX activity between groups. Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
Additionally, the TNF-α, IL-1β and IL-6 cytokines, CCL2, CCL3 and CXCL8 chemokines and adiponectin were assessed in AS patients and healthy controls. Previous studies showed that TNF-α, is a cytokine that is overproduced in chronic inflammatory/autoimmune disease (Kassiotis and Kollias, 2001). Various studies have also demonstrated increased level of TNF-α in AS patients playing a role in AS pathogenesis (Gratacos et al., 1994; Mohammadi et al., 2018a). IL-1β is another cytokine in acute and chronic inflammatory and autoimmune disorders (Lea and Lee, 2012). TNF-α and IL-1β have been associated with matrix degradation and these cytokines can induce production and release of the NO mediator (LeGrand et al., 2001). Also, many studies have revealed that IL-1β locus is associated with AS susceptibility (Maksymowych et al., 2006). IL-6 is a cytokine with a
significant role in inflammation balance and immune regulation (Fessler et al., 2013). There are correlation between IL-6 and inflammatory parameters such as CRP and ESR (Bal et al., 2007). In AS, IL-6 is found to be associated with clinical parameters and activity of the disease (Gratacos et al., 1994). Recently, the studies on cytokines have also verified that the IL-6 expression is significantly higher in AS than that of the control group (Vaez et al., 2017). Adiponectin is the most abundant adipokine usually produced and released by fat tissue which is correlated with adiposity and involved in the inflammation regulation (Procaccini et al., 2013). Numerous studies have reported the increased adiponectin levels in autoimmune disease and this type of adipokine may be related to disease activity or severity (Toussirot et al., 2012; Syrbe et al., 2015). Hartle A et al. study also 6
Fig. 4. Representative flow cytometry plots for identifying Th17 cells and CD4+ CD25+ CD127-Treg cells in PBMCs. A) The cells were first gated based on the side scatter and CD4-FITC, and then based on IL-17-PE and CD4-FITC for Th17 cells. For Tregs, cells were gated based on their forward and side scatters profile, then, cells were analyzed for positive CD4 and CD25 expression and negative CD127 marker. B) As shown in the figure, there is a significant increase in the frequency of Th17 cells between AS and control groups (p < 0.0001). The frequency of Treg cells also showed remarkable decrease in AS patients towards healthy controls (p = 0.0006). Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
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shows the role of adiponectin in inflammation in AS patients (Hartl et al., 2017). Our study showed an increased TNF-α, IL-1β and IL-6 mRNA expression levels in AS patients compared to healthy group. In addition, the CCL2, CCL3 and CXCL8 chemokines mRNA expression levels were increased in AS patients. Analysis of AS patients' peripheral blood also indicated a desirable elevation in TNF-α, IL-1β and IL-6 as well as CCL2, CCL3, CXCL8 chemokines and adiponectin secretion level. NF-κB and AP-1 mRNA expression levels as well as miR-146a, miR21 and miR-223 were also evaluated in AS patients. The NF-κB is a transcription factor mediating the expression of cytokines involved in the inflammatory diseases, such as AS, pathogenesis (Kim et al., 2005; Collantes et al., 1998). Additionally, TNF-α, an important cytokine in AS, can also induce NF-κB production (Kim et al., 2005). The results of our study also showed an increased expression of NF-κB and AP-1 genes in AS patients. MicroRNAs are non-coding, small RNAs which play crucial role in post-transcriptional level of gene regulation by binding to the 3′-untranslated regions of different target mRNAs (Bushati and Cohen, 2007). Most evidences have demonstrated that the abnormal miRNA expression is involved in AS pathogenesis (Lai et al., 2013). Our qPCR data demonstrated an increased miR-21 and decreased miR-223 and miR-146a in AS patients compared to healthy control group. Previous studies have also reported that the expression of miR-21 in AS patients was upper than healthy control group and this microRNA might cause bone erosion in these patients (Huang et al., 2014). Additionally, miR-21 with suppressive effect on programmed cell death (PDCD)-4 has also been role in osteoclasts activation (Li et al., 2016). Therefore, these data suggested that the expression of miR-21 might have a role in AS development (Mohammadi et al., 2018b). MiR-146a is usually expressed in Tregs and downregulation of this microRNA will induce the Tregs pro-inflammatory phenotype through increased signal transducer and activator transcription 1 (STAT1) expression (Zhou et al., 2015). Furthermore, the expression of miR-223, which represses the IL-1β production from inflammasome, has also been reduced in AS patients compare with healthy group (Marques-Rocha et al., 2015).
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Increased numbers of circulating polyfunctional Th17 memory cells in patients with seronegative spondylarthritides. Arthritis Rheum. 58 (8), 2307–2317. Karkucak, M., Capkin, E., Alver, A., Akyuz, A., Kiris, A., Ak, E., et al., 2010. The effect of anti-TNF agent on oxidation status in patients with ankylosing spondylitis. Clin. Rheumatol. 29 (3), 303–307. Kassiotis, G., Kollias, G.T.N.F., 2001. receptors in organ-specific autoimmune disease: multi-layered functioning mirrored in animal models. J. Clin. Invest. 107 (12), 1507–1508. Kim, T.-H., Stone, M.A., Rahman, P., Yoo, D.-H., Park, Y.-W., Payne, U., et al., 2005. Interleukin 1 and nuclear factor-kappaB polymorphisms in ankylosing spondylitis in Canada and Korea. J. Rheumatol. 32 (10), 1907–1910. Koshy, P., Henderson, N., Logan, C., Life, P., Cawston, T., Rowan, A., 2002. Interleukin 17 induces cartilage collagen breakdown: novel synergistic effects in combination with proinflammatory cytokines. Ann. Rheum. Dis. 61 (8), 704–713. Lai, N.S., Yu, H.C., Chen, H.C., Yu, C.L., Huang, H.B., Lu, M.C., 2013. Aberrant expression of micro RNA s in T cells from patients with ankylosing spondylitis contributes to the immunopathogenesis. Clin. Exp. Immunol. 173 (1), 47–57. Lea, W., Lee, Y.H., 2012. The associations between interleukin-1 polymorphisms and susceptibility to ankylosing spondylitis: a meta-analysis. Joint Bone Spine. 79 (4), 370–374. LeGrand, A., Fermor, B., Fink, C., Pisetsky, D.S., Weinberg, J.B., Vail, T.P., et al., 2001. Interleukin‐1, tumor necrosis factor α, and interleukin‐17 synergistically up‐regulate nitric oxide and prostaglandin E2 production in explants of human osteoarthritic knee menisci. Arthritis Rheum. 44 (9), 2078–2083. Li, Z., Wong, S.H., Shen, J., Chan, M.T., Wu, W.K.K., 2016. The role of MicroRNAS in ankylosing spondylitis. Medicine 95 (14). Liao, H.-T., Lin, Y.-F., Tsai, C.-Y., Chou, C.-T., 2015. Regulatory T cells in ankylosing spondylitis and the response after adalimumab treatment. 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5. Conclusion In conclusion, our study results show that oxidative stress and immunological factors play important roles in AS pathogenesis which are probably mediated by inflammation. More researches are still required to clarify the role of oxidative stress and immunological biomarkers in AS etiopathogenesis and novel therapeutic methods development. Author contributions Shahla Danaii and Rozita Abolhasani: wrote the article and helped in some immunological tests. Mohammad Sadegh Soltani-Zangbar: contributed in manuscript preparation according to journal format and helped in molecular tests. Majid Zamani and Tannaz Pourlak helped in Biochemical assays. Bahareh Amanifar: helped in clinical examinations and sample collection. Mehrzad Hajialiloo: contributed in sample collection and clinical examinations. Mehdi Nazari contributed in acquisition of data and Amir Mehdizadeh contributed in data analysis. Bahman Yousefi participated in the final edition of the manuscript. Mehdi Yousefi: principal investigator and supervised the study. Acknowledgement This study was supported by Tabriz University of Medical Sciences, Tabriz, Iran (Grant No. 59657). Declaration of competing interest Authors declare no conflict of interests. 8
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S. Danaii, et al. Maksymowych, W.P., Rahman, P., Reeve, J.P., Gladman, D.D., Peddle, L., Inman, R.D., 2006. Association of the IL1 gene cluster with susceptibility to ankylosing spondylitis: an analysis of three Canadian populations. Arthritis Rheum. 54 (3), 974–985. Marques-Rocha, J.L., Samblas, M., Milagro, F.I., Bressan, J., Martínez, J.A., Marti, A., 2015. Noncoding RNAs, cytokines, and inflammation-related diseases. FASEB J. 29 (9), 3595–3611. Mohammadi, H., Babaie, F., Hemmatzadeh, M., Azizi, G., Hajaliloo, M., Ebrahimi, A.A., et al., 2018a. Evaluation of ERAP1 gene single nucleotide polymorphism in impressing the inflammatory cytokine profile of ankylosing spondylitis patients. Iran. J. Allergy Asthma Immunol. 17 (5), 464–474. Mohammadi, H., Hemmatzadeh, M., Babaie, F., Gowhari Shabgah, A., Azizi, G., Hosseini, F., et al., 2018b. MicroRNA implications in the etiopathogenesis of ankylosing spondylitis. J. Cell. Physiol. 233 (8), 5564–5573. Ōyanagui, Y., 1984. Reevaluation of assay methods and establishment of kit for superoxide dismutase activity. Anal. Biochem. 142 (2), 290–296. Paglia, D.E., Valentine, W.N., 1967. Studies on the quantitative and qualitative characterization of erythrocyte glutathione peroxidase. J. Lab. Clin. Med. 70 (1), 158–169. Procaccini, C., De Rosa, V., Galgani, M., Carbone, F., La Rocca, C., Formisano, L., et al., 2013. Role of adipokines signaling in the modulation of T cells function. Front. Immunol. 4, 332. Reinherz, E.L., Schlossman, S.F., 1980. The differentiation and function of human T lymphocytes. cell. 19 (4), 821–827. Stanek, A., Cieślar, G., Romuk, E., Kasperczyk, S., Sieroń-Stołtny, K., Birkner, E., et al., 2010a. Decrease in antioxidant status of plasma and erythrocytes from patients with ankylosing spondylitis. Clin. Biochem. 43 (6), 566–570. Stanek, A., Cielar, G., Strzelczyk, J., Kasperczyk, S., Sieroñ-Stoltny, K., Wiczkowski, A., et al., 2010b. Influence of cryogenic temperatures on inflammatory markers in patients with ankylosing spondylitis. Pol. J. Environ. Stud. 19 (1). Stanek, A., Cholewka, A., Wielkoszyński, T., Romuk, E., Sieroń, K., Sieroń, A., 2017. Increased levels of oxidative stress markers, soluble CD40 ligand, and carotid intimamedia thickness reflect acceleration of atherosclerosis in male patients with ankylosing spondylitis in active phase and without the classical cardiovascular risk
factors. Oxidative Med. Cell. Longev. 2017. Syrbe, U., Callhoff, J., Conrad, K., Poddubnyy, D., Haibel, H., Junker, S., et al., 2015. Serum adipokine levels in patients with ankylosing spondylitis and their relationship to clinical parameters and radiographic spinal progression. Arthritis Rheum. 67 (3), 678–685. Szalay, B., Mészáros, G., Cseh, A., Acs, L., Deák, M., Kovács, L., et al., 2011. Adaptive immunity in ankylosing spondylitis: phenotype and functional alterations of T-cells before and during infliximab therapy. Clin. Dev. Immunol. 2012. Toussirot, E., Binda, D., Gueugnon, C., Dumoulin, G., 2012. Adiponectin in autoimmune diseases. Curr. Med. Chem. 19 (32), 5474–5480. Vaez, F., Farazmand, A., Shaaheen, S., Mostafaei, S., Jamshidi, A., Vojdanian, M., et al., 2017. Upregulation of transforming growth factor-B1 gene in ankylosing spondylitis patients. Rheumatol. Res. 2 (3), 103–107. Van Der Linden, S., Valkenburg, H.A., Cats, A., 1984. Evaluation of diagnostic criteria for ankylosing spondylitis. Arthritis Rheum. 27 (4), 361–368. Wang, C., Liao, Q., Hu, Y., Zhong, D., 2015. T lymphocyte subset imbalances in patients contribute to ankylosing spondylitis. Exp. Ther. Med. 9 (1), 250–256. Wauquier, F., Leotoing, L., Coxam, V., Guicheux, J., Wittrant, Y., 2009. Oxidative stress in bone remodelling and disease. Trends Mol. Med. 15 (10), 468–477. Wu, Y., Ren, M., Yang, R., Liang, X., Ma, Y., Tang, Y., et al., 2011. Reduced immunomodulation potential of bone marrow-derived mesenchymal stem cells induced CCR4+ CCR6+ Th/Treg cell subset imbalance in ankylosing spondylitis. Arthritis Res. Ther. 13 (1), R29. Xueyi, L., Lina, C., Zhenbiao, W., Qing, H., Qiang, L., Zhu, P., 2013. Levels of circulating Th17 cells and regulatory T cells in ankylosing spondylitis patients with an inadequate response to anti− TNF-α therapy. J. Clin. Immunol. 33 (1), 151–161. Yazici, C., Kose, K., Calis, M., Kuzuguden, S., Kirnap, M., 2004. Protein oxidation status in patients with ankylosing spondylitis. Rheumatology 43 (10), 1235–1239. Zhou, Q., Haupt, S., Kreuzer, J.T., Hammitzsch, A., Proft, F., Neumann, C., et al., 2015. Decreased expression of miR-146a and miR-155 contributes to an abnormal Treg phenotype in patients with rheumatoid arthritis. Ann. Rheum. Dis. 74 (6), 1265–1274.
9
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Oxidative stress and immunological biomarkers in Ankylosing spondylitis patients
T
Shahla Danaiia, Rozita Abolhasania, Mohammad Sadegh Soltani-Zangbarb,c,d, Majid Zamanic, Amir Mehdizadehe,f, Bahareh Amanifarc, Bahman Yousefig, Mehdi Nazarih, Tannaz Pourlaki, ⁎ Mehrzad Hajialilooc, Mehdi Yousefic,i, a
Gynecology Department, Eastern Azerbaijan ACECR ART Center, Eastern Azerbaijan Branch of ACECR, Tabriz, Iran Student Research committee, Tabriz University of Medical Sciences, Tabriz, Iran c Connective Tissue Diseases Research Center, Tabriz University of Medical Sciences, Tabriz, Iran d Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran e Endocrine Research Center, Tabriz University of Medical Sciences, Tabriz, Iran f Comprehensive Health Lab, Tabriz University of Medical Sciences, Tabriz, Iran. g Stem Cell Research Center, Tabriz University of Medical Sciences, Tabriz, Iran h Department of Anesthesiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran i Aging Research Institute, Tabriz University of Medical Sciences, Tabriz, Iran. b
ARTICLE INFO
ABSTRACT
Keywords: Ankylosing spondylitis Oxidative stress Immunological factors Th 17 cells Regulatory T cells
Ankylosing spondylitis (AS) is an inflammatory condition with unrevealed etiology mostly affecting the peripheral joints, the axial skeleton and extra articular structure. In recent years, oxidative stress and immunological factors have been reported as significant factors in AS pathogenesis. The object of this research was to assess the immunological and the oxidative stress factors in AS patients. In this study, 35 patients diagnosed with AS and 40 healthy controls were subjected for clinical examination. Patients were evaluated for Bath Ankylosing Spondylitis Disease Activity Index (BASDAI). The biomarkers of oxidative stress were evaluated by biochemical assays. We evaluated the mRNA level of transcription factors, cytokines, chemokines and related miRNAs. T Helper 17 cells (Th17), regulatory T cells (Treg) proportion and cytokines secretion were also assessed. Higher levels of nitric oxide (NO) (p < 0.0001), superoxide dismutase (SOD) (p = 0.0002), total oxidant status (TOS) (p = 0.0041) and catalase (CAT) (p = 0.0002) were observed in AS patients. However, no significant differences in glutathione peroxidase (GPX) activity level were observed between studied groups. Also, in peripheral blood of AS patients, Th17 (p < 0.0001) and Treg (p = 0.0006) cells were significantly increased and decreased compared to the healthy controls. Nuclear factor (NF)-κB and Activation protein (AP)-1 mRNA expression levels were also increased in AS patients (p = 0.0001 and p = 0.0004, respectively). A significant decrease in miR-146a and miR-223 (p < 0.0001 and p = 0.0025, respectively) and increase in miR-21 (p = 0.0018) expression level were similarly observed in AS patients. Moreover, the secretion of tumor necrosis factor (TNF)-α (p < 0.0001), Interleukin (IL)-1β (p = 0.0002), CCL2 (p < 0.0001), CCL3 (p < 0.0001), CXCL8 (p = 0.0006) and adiponectin (p = 0.0002) were increased in AS patients. Our results showed that immunological and oxidative stress biomarkers play key roles in AS pathogenesis probably mediated by inflammation.
Abbreviations: AS, Ankylosing spondylitis; MetS, Metabolic syndrome; Th17, T Helper 17 cell; Treg, Regulatory T cell; ELISA, Enzyme-linked immune sorbent assay; NF-kB, Nuclear factor κ B; AP-1, Activation protein 1; IL-1β, Interleukin-1β; IL-6, Interleukin-6; TNF-α, Tumor Necrosis Factor α; CCL-2 and 3, C-C Motif Chemokine Ligand 2 and 3; CXCL-8, CXC Motif Chemokine Ligand 8; SOD, Superoxide Dismutase; GPX, Glutathione Peroxidase; CAT, Catalase; NO, Nitrite Oxide; TOS, Total Oxidative Stress; AS-NMS, Ankylosing Spondylitis without Metabolic syndrome; AS-MS, Ankylosing Spondylitis with Metabolic syndrome; BMI, Body Mass Index; SBP, Systolic Blood Pressure; DBP, Diastolic Blood Pressure; FBS, Fasting Blood Sugar; HbA1C, Hemoglobin A1C; TG, Triglyceride; HDL, High Density Lipoprotein; BASDAI, Bath Ankylosing Spondylitis Disease Activity Index ⁎ Corresponding author at: Department of Immunology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran. E-mail address: [email protected] (M. Yousefi). https://doi.org/10.1016/j.genrep.2019.100574 Received 9 September 2019; Received in revised form 12 November 2019; Accepted 26 November 2019 Available online 28 November 2019 2452-0144/ © 2019 Elsevier Inc. All rights reserved.
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1. Introduction
confirmation was done by a rheumatology specialist according to Assessment of Spondyloarthritis International Society (ASAS) criteria. A group of 40 healthy age and sex-matched subjects was also included as controls. For clinical disease activity analysis, at the study time, bath ankylosing spondylitis disease activity index (BASDAI) was assessed in all patients. The BASDAI disease activity questionnaire consists of six 10 cm horizontal visual analog scales to measure the level of fatigue, level of neck, hip, or back pain, level of pain swelling in joints other than neck, hip, back, level of discomfort an area tender to touch, and the level of morning stiffness and duration of morning stiffness. Each question is scored on a scale of 0 to 10. Aside from the last question, 0 indicates none and 10 indicate very severe. For the last question, 0 is 0 h, 5 is 1 h, and 10 is two or more hours. Before participation in the study, signed informed consent was achieved from all patients. The inclusion criteria were ankylosing spondylitis diagnosis, a BASDAI score ≥4 and willingness to cooperate. Using nutritional supplements, antioxidants, alpha-lipoic acid within a month prior the study, diabetes history, autoimmune and other chronic diseases, pregnancy and lactation were also considered as exclusion criteria. The Research Ethics Committee of Tabriz University of Medical Sciences (IR.TBZMED.REC.1397.167) approved the study. Table 1 represents the key demographic data and some clinical features of AS patients and Healthy individuals.
Ankylosing spondylitis (AS) is a chronic inflammatory disorder, mainly affecting the axial skeleton and the sacroiliac joints (Szalay et al., 2011; Genre et al., 2015). The main clinical features of AS is inflammatory backache, enthesitis and specific organ involvement (Szalay et al., 2011; Ljung et al., 2018). Several pathogenic factors, such as bacterial infection, environmental stimuli, HLA-B27 and HLA-E genetic factors prevalence are responsible for ankylosing spondylitis pathogenesis (Wu et al., 2011). Radiographic imaging is routinely used for severe AS diagnosis and prognosis; however, for early diagnosis and treatment of AS, evaluation of the molecular factors is important (Van Der Linden et al., 1984; Graham and Van, 1989). Currently, studies have focused on the immunological and oxidative stress factors for AS. T cells have a key role in AS pathogenesis because of their role in immune system regulation (Reinherz and Schlossman, 1980). Many researches have assessed the prevalence of Regulatory T cell (Tregs) and T Helper 17 cell (Th17) in autoimmune disorders such as Ankylosing spondylitis (Xueyi et al., 2013). Findings of the most studies have demonstrated that the Th17 and Treg is increased and decreased, respectively, in peripheral blood (PB) of AS patients and this change in immune phenotype and contributing factors may have a crucial role in pathogenesis and progress of the disease (Hajialilo et al., 2019; Wang et al., 2015). Additionally, AS progression may be related to the degree of inflammation. This idea is supported by high expression of tumor necrosis factor (TNF)-α, an indicator of inflammation, in the sacroiliac joints in AS patients (Brandt et al., 2000; Genre et al., 2014). It has also been reported that the in vitro interleukin (IL)-17, the main cytokine of Th17 cells, stimulates the TNF-α and IL-1β production to induce the inflammation and cartilage destruction (Koshy et al., 2002). Moreover, several authors have reported that treatment of AS patients by anti-TNF-α antibodies is an effective approach, causing low level of inflammation and subsequently improvement of the disease (Genre et al., 2015). Several studies on AS patients also have reported reduced Treg cells, which may lead to impaired suppressor activity (Liao et al., 2015). Recent studies have also considered the increased oxidative stress as the pathogenic factor in several inflammatory diseases, including AS (Stanek et al., 2010a). Increased oxidative stress mediators have led to pro-inflammatory cytokines production in these abnormalities (Stanek et al., 2010b). Oxidative stress is characterized by increased reactive oxygen species (ROS) level which disrupts the oxidants and antioxidants balance in the body (Wauquier et al., 2009). One of the important cytokines in ROS production is TNF-α and strategies based on anti-TNF treatment have been demonstrated to improve oxidation status and decreased AS pain and inflammation (Karkucak et al., 2010). Furthermore, oxidative stress elements produced by neutrophil activation play a crucial role in AS pathogenesis (Yazici et al., 2004). However, there are few studies on the role of immunological and oxidative stress factors in AS patients. The purpose of the current study was to assess the overall changes in a variety of oxidative stress and immunological factors involved in pathogenesis of AS. Additionally, Th17 and Treg cells ratio alterations, expression analysis of pro-inflammatory cytokines (TNF-α, IL-1β and IL-6), nuclear factor (NF)-κB and activation protein (AP)-1 transcription factor, chemokines (CCL-2, CCL-3 and CXCL-8) and miRNAs (miR-146a, miR-21 and miR223) in the peripheral blood mononuclear cells (PBMCs) of AS patients were also compared to the healthy control group. Furthermore, we measured the secretion level of adiponectin and oxidative stress biomarkers including total oxidative status (TOS), superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT) and nitric oxide (NO).
2.2. Blood samples and PBMCs isolation 10 ml of peripheral blood was drawn under aseptic precautions from both AS patients and healthy controls. PBMCs were isolated from samples via density-gradient centrifugation (25 min, 450 ×g) using Ficoll separation technique (Biosera, UK). Then, the peripheral blood mononuclear cell layer was isolated. Cells were washed by phosphate buffered saline (PBS) (Sigma-Aldrich, Schnelldorf, Germany) twice and used for further assessments. 2.3. Quantitative real-time PCR Expression level of NF-κB and AP-1 transcription factors, inflammatory cytokines and chemokine's including: IL-1β, TNF-α, IL-6, CCL-2, CCL-3 and CXCL-8 were analyzed using a SYBR green technique with specific primers and quantitative Real-time polymerase chain Table 1 Demographic characteristics of controls and AS patients.
2. Material & methods
Variable
Control (mean ± Sd) N = 40
AS (mean ± Sd) N = 35
Age (year) Sex (men/women) SBP (mmHg) DBP (mmHg) FBS (mg/dl) HbA1C (%) TG (mg/dl) HDL (mg/dl) Level of Fatigute (0−10) Level of Neck Hip back pain (0–10) Level of pain swelling other than Back, Hip, Neck (0–10) Level of discomfort an area tender to touch (0–10) Level of morning stiffness (0–10) Duration of morning stiffness (0–10) BASDAI (0–10)
43.89 ± 12.51 23/17 116.63 ± 16.36 79.16 ± 8.04 90.86 ± 7.5 5.42 ± 0.74 110.2 ± 62.85 56.16 ± 3.8 – – –
43.17 ± 11.32 19/16 128.1 ± 18.55 81.88 ± 6.12 106.14 ± 8.41* 5.61 ± 0.77 178.41 ± 71.66* 41.37 ± 2.89* 3.85 ± 1.11 4.15 ± 1.51 4.1 ± 1.34
–
3.96 ± 1.41
– –
3.81 ± 2.45 0.639 ± 0.43
–
4.93 ± 0.69
Data are presented as number and mean ± SD. *(p < .05) vs Healthy Controls. AS: Ankylosing Spondylitis; SBP: Systolic Blood Pressure; DBP: Diastolic Blood Pressure; FBS: Fasting Blood Sugar; HbA1C: Hemoglobin A1C; TG: Triglyceride; HDL: High Density Lipoprotein; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index.
2.1. Study design We assessed a series of 35 AS patients referred to Imam Reza Hospital of Tabriz University of Medical Sciences in this study. AS 2
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TNF-α, IL-6, CCL-2, CCL-3, CXCL-8 and adiponectin secretion were evaluated by ELISA technique and ELISA kit (MyBioSource, San Diego, USA). The levels of the cytokines were assessed in duplicate to improve the accuracy. The Medgenix ELISA reader (BP-800, Biohit, USA) was used to measure absorbance values at 450 nm and the concentrations were evaluated according to the standard curve.
Table 2 Used primer sequences for qPCR. Gene
Sequence (5′ → 3 ′ )
IL-1β
Forward: CTGATGGCCCTAAACAGATGAAG Reverse: GGTCGGAGATTCGTAGCAGCTGGAT Forward: ACTCACCTCTTCAGAACGAATTG Reverse: CCATCTTTGGAAGGTTCAGGTTG Forward: GGCAGGTCTACTTTGGAGTCATTGC Reverse: ACATTCGAGGCTCCAGTGAATTCGG Forward: GCATGAAAGTCTCTGCCG Reverse: GAGTGTTCAAGTCTTCGGA Forward: GCTGCCCTTGCTGTCCTCCTC Reverse: GGTCAGCACAGACCTGCCGG Forward: GCCTGCTGCTCATGGCAGCC Reverse: GCACAGACCTCCTTGCCCCG Forward: AACCCAGAGAGGAAAAGACT Reverse: TGCAGGAAAGGAGAGAGAG Forward: GCTGCTGTGTGGGGATAGAT Reverse: GGCCCAGTCTTTTCCTCTCT Forward: AGAGCTACGAGCTGCCTGAC Reverse: AGCACTGTGTTGGCGTACAG
IL-6 TNF-α CCL-2 CCL-3 CXCL-8 AP-1 NF-κΒ Beta-Actin
2.6. Biochemical analysis of oxidative stress biomarkers The levels of TOS, GPX activity, CAT and SOD activity and NO production were analyzed as oxidative status markers. Total oxidant activity method developed by Erel et al. was used for determination of serum TOS levels. The outcomes were measured in terms of micromolar hydrogen peroxide equivalent/liter (Erel, 2005). For GPX activity evaluation, Paglia and Valentine's kinetic assay was used (Paglia and Valentine, 1967), as the substrate using t-butyl peroxide and normalized to 1 g of hemoglobin [IU/gHb] and measured as micromoles of oxidized NADPH per minute. SOD activity was assayed by Oyanaguis method (Ōyanagui, 1984). Optical absorbance was assessed by Pekrin Elmer analyzer (PerkinElmer Informatics) at 550 nm and the SOD activity was measured in nitric unit. Erythrocyte catalase activity was measured by kinetic way formerly defined by Aebi et al. (Aebi, 1984). Briefly, following RBC hemolysate preparation, absorbance of the samples containing 2 ml of hemolysate and 1 ml of H2O2 were measured in 240 nm at room temperature. For evaluation of NO production, − − NO− 2 and NO3 quantitation were estimated. The absorbance of NO2 and mixture of sulfanilamide and naphthethylenediamine was identified at 540 nm based on Griess reaction (Cortas and Wakid, 1990).
IL-1β: Interleukin-1β; IL-6: Interleukin-6; TNF-α: Tumor Necrosis Factor α; CCL2, 3, 8: CC Motif Chemokine Ligand-2, 3, 8; AP-1: Activation Protein-1; NF-κΒ: Nuclear Factor- κΒ.
reaction (qPCR) system with Light Cycler 2.0 (Roche Applied Science, Germany) in isolated PBMCs in studied groups. Primers sequences are presented in Table 2. First, the samples were homogenized and RNXPLUS Solution (SinaClon, Tehran, Iran) was used for total RNA extraction. Then, cDNA was synthesized with Revert Aid Reverse Transcriptase kit (Thermo Fisher, Waltham, MA, USA). The amplification was also confirmed on 2% agarose gel. Also, miR-21, miR-146a and miR-223 gene expression were assessed using Real-time PCR in AS patients. We used Beta-Actin and RNU6B as controls and the relative gene expression was computed using to 2−ΔΔCT formula.
2.7. Statistical analysis SPSS software (version 23.0; SPSS Inc.) was used to perform statistical analysis. Unpaired t-test was used for data analysis between AS patients and control group. The GraphPad Prism version 7.00 (GraphPad Software, La Jolla, CA, USA, www.graphpad.com) was used for drawing the graphs. p < 0.05 was considered as statistically significant.
2.4. Flow cytometery The ratio of CD4+ TH17 cells as source of IL-17 producing cells and Treg cells (CD4+ CD25+ CD127−) was measured by flowcytometry technique. Anti-intracellular and anti-surface markers were used to assess of TH17 cells quantity. Cells were incubated With phorbol myristate acetate (PMA) (10 ng/ml) and ionomycin (0.5 μM) for 5 h (Sigma-Aldrich, Schnelldorf, Germany) at 37 °C in a 5% CO2 moistened incubator. Formerly after washing the cells, they were incubated for 15 min with anti-CD4-fluorescein isothiocyanate (FITC) (BD Biosciences, San Jose, CA, USA) at 4 °C. Then, the cells were washed two times and permeabilized with a permeabilizing and fixating buffer (eBioscience), and incubated with anti-IL17-phycoerytrin (PE) antibody for intracellular staining at 37 °C for 20 min. FITC and PE-conjugated mouse IgG1κ antibodies were also used as isotype control for background effect normalization. Based on side and forward scatter properties the total lymphocytes were gated. The lymphocytes were more evaluated for CD4 expression, and IL-17 producing lymphocytes were considered as Th17 cells. For Treg cells detection, fluorochrome-conjugated monoclonal antibodies including anti-CD4-FITC, anti-CD25-PE and anti-CD127PerCP-Cy5.5 (eBioscience, San Diego, CA, U.S.A) were added to 1 × 106 PBMCs and incubated for 15 to 30 min at room temperature in a dark place. Then, based on their side and forward scatter properties lymphocytes were gated and CD4+ lymphocytes were analyzed for CD25 and CD127 expression. FACS Calibur flow cytometer (BD Biosciences) and FlowJo software (Becton Dickinson, Mountain View, CA) were used for scanned and data analysis of stained cells.
3. Results 3.1. The expression levels of cytokines, chemokines, transcription factors and associated micro-RNAs in AS patients and healthy controls AP-1 and NF-κB transcription factors, inflammatory cytokines and chemokine's including IL-1β, TNF-α, IL-6, CCL-2, CCL-3 and CXCL-8 as well as miR-146a, miR-21 and miR-223 expression level were assessed and compared between AS patients and healthy group (Fig. 1). Our results showed an increased expression levels of TNF-α and IL-1β, IL-6 cytokines in AS patients in comparison to healthy individuals (p < 0.0001, p < 0.0001 and p < 0.0001, respectively). As expected, AS patients showed higher expression levels of CCL2, CCL3 and CXCL8 chemokines towards healthy individuals (p = 0.0002, p = 0.0007 and p = 0.0035, respectively). Moreover, the expression levels of NF-κβ and AP-1 transcription factors were increased in AS patients towards control group (p = 0.0001 and p = 0.0004, respectively). Additionally, miR-21 showed significant increase in AS patients compared to the healthy group (p = 0.0018). On the other side, miR-223 and miR-146a expression levels which are correlated with inflammatory response suppression were decreased in AS patients compared to healthy individuals (p = 0.0025 and p < 0.0001, respectively). 3.2. Changes in cytokines, chemokines and adiponectin secretion levels in AS patients and healthy controls Cytokines, chemokines and adiponectin secretion were evaluated in AS patients and control group using ELISA method. TNF-α (p < 0.0001) and IL-1β (p = 0.0002) secretion levels were
2.5. Enzyme-linked immunosorbent assay (ELISA ( Serum inflammatory cytokines and chemokine's including IL-1β, 3
Fig. 1. Real time PCR analysis of TNF-α, IL-6 and IL-1β cytokines, CCL-2, CCL-3 and CXCL-8 chemokines, NF-κΒ and AP-1 transcription factors and mir-21, mir-146a and mir-223 miRNA expression in patients and control group. The results showed increased level of CXCL-8, CCL-3, CCL-2, IL-1β, IL-6, TNF-α, NF-κΒ, AP-1 and miR-21 in AS patients compared to control group (p = 0.0035, p = 0.0007, p = 0.0002, p < 0.0001, p < 0.0001, p < 0.0001, p = 0.0001, p = 0.0004, p = 0.0018, respectively). In contrast, the expression of miR-146a and miR-223 were decreased in AS patients compared to healthy controls (p < 0.0001, p = 0.0025, respectively). Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
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Fig 2. The concentrations of serum IL-1β and TNF-α, adiponectin and chemokines (CCL-2, CCL-3 and CXCL-8) in AS patients and healthy controls. Increased concentration of IL-1β, TNF-α, Adiponectin, CCL-2, CCL-3 and CXCL-8 was observed in AS patients compared to control group (p = 0.0002, p < 0.0001, p = 0.0002, p < 0.0001, p < 0.0001, p = 0.0006, respectively). Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
been also reported that the oxidative stress have a significant role in AS pathogenesis (Stanek et al., 2010a; Feijóo et al., 2009). AS is a chronic inflammatory rheumatic disorder mainly described by changes in the sacroiliac joint and the axial skeleton. However, few studies have evaluated the immunological factors changes in AS patients such as elevated levels of Th17 and reduced levels of Treg cells which have been reported in AS patients (Liao et al., 2015). Thus, in this study, the oxidative stress and immunological factors were assessed in AS patients. To this aim, 35 AS patients with the age range of 20–55 and 40 healthy controls participated in this study. To prove a relationship between oxidative stress and AS pathogenesis, the levels of TOS, GPX, SOD, NO and CAT were measured as biomarkers of oxidative stress. Additionally, for immunological evaluation, the proportion of Th17 and Treg cells, NF-κB and AP-1 transcription factor expression, inflammatory cytokines and chemokine's including IL-1β, TNF-α, IL-6, CCL-2, CCL-3 and CXCL-8, adiponectin and miRNAs (miR-146a, miR-21 and miR-223) were measured in the peripheral blood of the participants. Our data revealed that severity of the inflammation and disease symptoms are increased in AS patient compared to healthy controls following elevated level of oxidative stress biomarkers in these patients. In AS patients, the levels of SOD, NO, TOS and CAT were significantly higher compared to healthy group. Furthermore, GPX level showed a higher but not significant activity compared to healthy control group. Karkucak et al. also, evaluated antiTNF agent effects on oxidative status in AS patients. In consistence to our results, they showed that oxidative stress is accelerated in AS group and anti-TNF treatment have beneficial effects on these patients (Karkucak et al., 2010). It has also been reported that increased oxidative stress, may affect the intensification of atherosclerosis in active phase of male AS patients (Stanek et al., 2017). Previous researches have mostly studied the ratio of Th17 (important regulator of autoimmune-inflammatory disorders) and Tregs (immune system suppressor). Different findings have reported the significant increase and decrease of Th17 and Treg cells in AS patients (Szalay et al., 2011; Jandus et al., 2008). In the current study, flowcytometric analysis of PBMCs in AS patients also revealed a significant increase and decrease of peripheral blood Th17 and Treg cells compared to healthy control group, respectively, probably because of contributing factor in disease development.
significantly higher in AS patients in comparison to the healthy group (Fig. 2). Comparison of AS patients and healthy individuals indicated that CCL2, CCL3 and CXCL8 secretion levels were higher in AS patients (p < 0.0001, p < 0.0001 and p = 0.0006, respectively) (Fig. 2). In addition, AS patients showed desirable increase of adiponectin secretion towards healthy group (p = 0.0002) (Fig. 2). 3.3. Analysis of oxidative stress biomarkers in AS patients and control group The activity levels of SOD, CAT and GPX, NO production and TOS were analyzed by biochemical assays. The levels of SOD, CAT and NO in AS patients demonstrated a notable increase in comparison to control group (p = 0.0002, p = 0.0002, p < 0.0001, respectively) (Fig. 3). In contrast, compared to healthy controls, low level of TOS was observed in AS patients (p = 0041). No changes in GPX activity were observed between studied groups (Fig. 3). 3.4. The proportion of circulating Th17 and Treg cells in peripheral blood of AS patients and control individuals Treg and Th17 cells proportion were assessed in PBMCs of AS patients and control individuals by flow cytometry technique. Flow cytometric assessment showed that AS patients had low cellular proportion of Treg cells in comparison to control individuals (p = 0.0006) (Fig. 4). Additionally, flow cytometric evaluation of Th17 cells showed a higher ratio of these cells in AS patients compared to the healthy individuals (p < 0.0001) (Fig. 4). 4. Discussion Oxidative stress is a disorder described by increased level of reactive oxygen species (ROS) or insufficient antioxidant defense and can be evaluated by total oxidant status (TOS), total antioxidant status (TAS) and its systematic reflections (Stanek et al., 2010a; Stanek et al., 2010b). ROS is released into the extracellular space and damages the nearby tissues in inflammation and phagocytosis reactions, increasing the level of acute-phase proteins (Guillot et al., 2014). On the other hand, it has 5
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Fig. 3. Comparison of oxidative stress biomarkers in AS patients and healthy controls. The higher levels of SOD, Catalase, TOS and NO were observed in AS patients compared to healthy controls (p = 0.0002, p = 0.0002, p = 0.0041 and P < 0.0001, respectively). No significant differences were observed in GPX activity between groups. Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
Additionally, the TNF-α, IL-1β and IL-6 cytokines, CCL2, CCL3 and CXCL8 chemokines and adiponectin were assessed in AS patients and healthy controls. Previous studies showed that TNF-α, is a cytokine that is overproduced in chronic inflammatory/autoimmune disease (Kassiotis and Kollias, 2001). Various studies have also demonstrated increased level of TNF-α in AS patients playing a role in AS pathogenesis (Gratacos et al., 1994; Mohammadi et al., 2018a). IL-1β is another cytokine in acute and chronic inflammatory and autoimmune disorders (Lea and Lee, 2012). TNF-α and IL-1β have been associated with matrix degradation and these cytokines can induce production and release of the NO mediator (LeGrand et al., 2001). Also, many studies have revealed that IL-1β locus is associated with AS susceptibility (Maksymowych et al., 2006). IL-6 is a cytokine with a
significant role in inflammation balance and immune regulation (Fessler et al., 2013). There are correlation between IL-6 and inflammatory parameters such as CRP and ESR (Bal et al., 2007). In AS, IL-6 is found to be associated with clinical parameters and activity of the disease (Gratacos et al., 1994). Recently, the studies on cytokines have also verified that the IL-6 expression is significantly higher in AS than that of the control group (Vaez et al., 2017). Adiponectin is the most abundant adipokine usually produced and released by fat tissue which is correlated with adiposity and involved in the inflammation regulation (Procaccini et al., 2013). Numerous studies have reported the increased adiponectin levels in autoimmune disease and this type of adipokine may be related to disease activity or severity (Toussirot et al., 2012; Syrbe et al., 2015). Hartle A et al. study also 6
Fig. 4. Representative flow cytometry plots for identifying Th17 cells and CD4+ CD25+ CD127-Treg cells in PBMCs. A) The cells were first gated based on the side scatter and CD4-FITC, and then based on IL-17-PE and CD4-FITC for Th17 cells. For Tregs, cells were gated based on their forward and side scatters profile, then, cells were analyzed for positive CD4 and CD25 expression and negative CD127 marker. B) As shown in the figure, there is a significant increase in the frequency of Th17 cells between AS and control groups (p < 0.0001). The frequency of Treg cells also showed remarkable decrease in AS patients towards healthy controls (p = 0.0006). Data are presented as Mean ± SD. p < 0.05 was considered as statistically significant. (Control group, n = 40 and AS group, n = 35).
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shows the role of adiponectin in inflammation in AS patients (Hartl et al., 2017). Our study showed an increased TNF-α, IL-1β and IL-6 mRNA expression levels in AS patients compared to healthy group. In addition, the CCL2, CCL3 and CXCL8 chemokines mRNA expression levels were increased in AS patients. Analysis of AS patients' peripheral blood also indicated a desirable elevation in TNF-α, IL-1β and IL-6 as well as CCL2, CCL3, CXCL8 chemokines and adiponectin secretion level. NF-κB and AP-1 mRNA expression levels as well as miR-146a, miR21 and miR-223 were also evaluated in AS patients. The NF-κB is a transcription factor mediating the expression of cytokines involved in the inflammatory diseases, such as AS, pathogenesis (Kim et al., 2005; Collantes et al., 1998). Additionally, TNF-α, an important cytokine in AS, can also induce NF-κB production (Kim et al., 2005). The results of our study also showed an increased expression of NF-κB and AP-1 genes in AS patients. MicroRNAs are non-coding, small RNAs which play crucial role in post-transcriptional level of gene regulation by binding to the 3′-untranslated regions of different target mRNAs (Bushati and Cohen, 2007). Most evidences have demonstrated that the abnormal miRNA expression is involved in AS pathogenesis (Lai et al., 2013). Our qPCR data demonstrated an increased miR-21 and decreased miR-223 and miR-146a in AS patients compared to healthy control group. Previous studies have also reported that the expression of miR-21 in AS patients was upper than healthy control group and this microRNA might cause bone erosion in these patients (Huang et al., 2014). Additionally, miR-21 with suppressive effect on programmed cell death (PDCD)-4 has also been role in osteoclasts activation (Li et al., 2016). Therefore, these data suggested that the expression of miR-21 might have a role in AS development (Mohammadi et al., 2018b). MiR-146a is usually expressed in Tregs and downregulation of this microRNA will induce the Tregs pro-inflammatory phenotype through increased signal transducer and activator transcription 1 (STAT1) expression (Zhou et al., 2015). Furthermore, the expression of miR-223, which represses the IL-1β production from inflammasome, has also been reduced in AS patients compare with healthy group (Marques-Rocha et al., 2015).
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5. Conclusion In conclusion, our study results show that oxidative stress and immunological factors play important roles in AS pathogenesis which are probably mediated by inflammation. More researches are still required to clarify the role of oxidative stress and immunological biomarkers in AS etiopathogenesis and novel therapeutic methods development. Author contributions Shahla Danaii and Rozita Abolhasani: wrote the article and helped in some immunological tests. Mohammad Sadegh Soltani-Zangbar: contributed in manuscript preparation according to journal format and helped in molecular tests. Majid Zamani and Tannaz Pourlak helped in Biochemical assays. Bahareh Amanifar: helped in clinical examinations and sample collection. Mehrzad Hajialiloo: contributed in sample collection and clinical examinations. Mehdi Nazari contributed in acquisition of data and Amir Mehdizadeh contributed in data analysis. Bahman Yousefi participated in the final edition of the manuscript. Mehdi Yousefi: principal investigator and supervised the study. Acknowledgement This study was supported by Tabriz University of Medical Sciences, Tabriz, Iran (Grant No. 59657). Declaration of competing interest Authors declare no conflict of interests. 8
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