Aim: This study aimed to measure and evaluate serum trimethylamine N-oxide (TMAO) levels in patients with COVID-19.

Material and Methods: The patients were divided into three groups according to their polymerase chain reaction (PCR) results and the clinical picture of the disease: Group 1 (negative PCR result, n = 44), Group 2 (positive PCR result and non-severe disease, n = 38) and Group 3 (positive PCR result and severe disease, n = 45).

Results: TMAO levels were significantly different among the three patient groups. Post Hoc Dunn’s analysis revealed a significant difference between Group 1 and Group 2 (p = 0.006), Group 1 and Group 3 (p < 0.001) and Group 2 and Group 3 (p = 0.031). ROC analysis revealed that a cut-off value of 2.92 had a sensitivity of 74.70%, a specificity of 68.18%, a positive predictive value of 81.6% and a negative predictive value of 58.8%.

Discussion: The results of this study demonstrated that TMAO levels increased in the patients with COVID-19, and further TMAO levels increased as the severity of the disease progressed.

Keywords: Biomarkers, COVID-19, Peripheral Blood, Severe, Trimethylamine N-oxide

Introduction

In December 2019, an outbreak of viral pneumonia was reported in Wuhan, Hubei Province, China, and the cause of this outbreak was identified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As the disease rapidly spread worldwide, the World Health Organization (WHO) renamed it coronavirus disease 2019 (COVID-19) in February 2020 [1].
The SARS-CoV-2 virus causes respiratory problems along with shock, acute kidney damage and vascular and thromboembolic complications. In addition, previous studies have reported that endothelial cell infection leads to conditions such as vascular thrombosis, pulmonary edema and the deterioration of pulmonary perfusion in patients with COVID-19. SARS-CoV-2 binds to the angiotensin-converting enzyme 2 (ACE2) protein, entering the host target cells and stimulating interleukin (IL) synthesis and inflammatory activation following interaction with toll-like receptors, further triggering a cascade of responses [2]. In addition to the risk factors of advanced age and underlying chronic diseases (cardiovascular diseases (CVDs), diabetes mellitus (DM), respiratory diseases), several factors that affect the course of COVID-19 have been defined [3].
Diet is a major factor that affects the prevalence of numerous diseases. Intestinal dysbiosis can contribute to the abnormal inflammatory response triggered by SARS-CoV-2 [4]. Trimethylamine N-oxide (TMAO), an oxygenated product of trimethylamine (TMA) generated by intestinal microbiota, is an amine oxide found in our body [5]. Several types of bacteria, including Clostridia, Proteus, Shigella and Aerobacter, are involved in TMA production [6]. TMAO is a naturally occurring osmolyte that protects the intracellular components from destructive stress conditions [7]. In particular, previous studies have shown that TMAO can improve protein stability and prevent the denaturing effect of urea [8]. Both observational and experimental studies have demonstrated the ability of TMAO to cause inflammatory endothelial damage [9,10]. Recent studies have further revealed that TMAO induces pro-inflammatory cytokine release and increases inflammatory response [11]. There have also been studies reporting that TMAO is associated with chronic heart failure, atherosclerosis, peripheral venous disease, pneumonia, chronic kidney disease, colorectal cancer, obesity and Parkinson’s disease [12-14]. Nutritional strategies such as limiting the high intake of choline and carnitine, which are the precursors of TMAO, are viable options for COVID-19 management; however, these molecules are essential for the maintenance of body health. Therefore, the aim of the present study was to determine the serum TMAO levels according to the clinical course of COVID-19 in the patients who were diagnosed with it.

Material and Methods

Ethical approval for this study was obtained from the local ethics committee. The patients who presented to the emergency department with the suspicion of COVID-19 were included in the study. The sample size was calculated using the G*Power version 3.1.9.2 (Germany) software. With a power of 80%, 0.05 level of statistical significance and effect size of 0.6, the sample size for each group was calculated to be 30. The basic characteristics, symptoms the patients presented with at the time of admission to the emergency department and laboratory test results of the patients were recorded in the prepared data form. The patients were divided into three groups according to their polymerase chain reaction (PCR) results and the clinical picture of the disease: Group 1 (negative PCR result, n = 44), Group 2 (positive PCR result with non-severe disease, n = 38) and Group 3 (positive PCR result with severe disease, n = 45). The severity of COVID-19 was defined according to the 2020 WHO Guideline. Severe COVID-19 was defined by any of the following: oxygen saturation <90% in room air, severe respiratory distress symptoms (accessory muscle use, inability to complete full sentences, and severe chest wall indrawing, grunting, central cyanosis in children or the presence of any other general danger signs). Non-severe COVID-19 was defined as the absence of the abovementioned signs of severe or critical COVID-19 [15].

Biochemical analysis

Blood samples were taken from all the patients on admission. The samples were then centrifuged for 10 min at 3000 rpm, and the serum was stored at −80°C in aliquots till the day of analysis. The TMAO levels were measured using enzyme-linked immunosorbent assays (Catalogue No: 201-127378, Shanghai Sunred Biological Technology Co., Ltd., Shanghai, China) according to the manufacturer’s instructions.
The white blood cell (WBC, normal range [NR]: 3.7–10.1 10e3/uL,), hemoglobin (HGB, NR: 12–18.1 g/dL,), hematocrit (HCT, NR: 35–53.7%) and platelet (PLT, NR: 140–360 10e3/uL) levels were determined using Alinity HQ (Abbott, USA).
The serum blood urea nitrogen (BUN, NR: 19–50 mg/d), creatinine (NR: 0.55–1.02 mg/dL), alanine aminotransferase (ALT, NR: 7–40 U/L), aspartate aminotransferase (AST, NR: 13–40 U/L), lactate dehydrogenase (LDH, NR: 120–246 U/L), C-reactive protein (CRP, NR: 0–0.5 mg/dL), bilirubin (NR: 0,3–1,2 mg/dL) and ferritin (NR: ferritin: 22–322 ng/mL) levels were measured by conventional laboratory methods on Atellica Solution (Siemens Healthineers, Germany).
The tests for plasma fibrinogen levels (NR: 160–450 mg/dL), D-dimer levels (NR: 0–0.55 mg/L), prothrombin time (PTT) (NR: 10.5–15.5 sec), activated partial thromboplastin time (aPTT, NR: 22–36 sec) and International Normalized Ratio (INR, NR: 0.8–1.2) were conducted using the Sysmex CS2100i device (Sysmex, Japan).

Statistics

Statistical analysis was performed using the SPSS 21.0 (IBM Corporation, Armonk, NY, USA) and MedCalc (Version 10.1.6.0, Ostend, Belgium) packages. Numerical data were expressed as mean ± standard deviation. Qualitative data were expressed as numbers and percentages. The Shapiro–Wilk test was used to assess whether the data conformed to a normal distribution. The Kruskal–Wallis test was used to compare the variables between the three groups. Following the Kruskal–Wallis test, binary comparisons were made using the Post Hoc Dunn’s test. For the comparison of categorical data, Pearson’s Chi-square test was used if the percentages of less than five theoretical frequencies were less than 20% and Fisher’s exact test was used otherwise. Following the Chi-square test, binary comparisons were made using the Post Hoc Z test. Spearman’s correlation analysis was performed to determine the relationship between the TMAO levels and other continuous variables. Receiver operating characteristic (ROC) curve analysis was performed to determine whether the TMAO levels could be used to distinguish between the patients with PCR positive and negative results. The ROC curve analysis results were presented as % specificity, % sensitivity (area under the ROC curve [AUC], p, 95% confidence interval [CI]). p < 0.05 was accepted as statistically significant in all analyses.

Results

Of the 127 patients included in our study, 44 were in Group 1 (F/M = 13/31), 38 in Group 2 (F/M = 17/21) and 45 in Group 3 (F/M = 22/23). No difference was found among the groups regarding sex (p = 0.147), but the mean age was significantly different among the three groups (p < 0.001). The patients presented to the emergency department with fever, cough, shortness of breath, sore throat, runny nose, fatigue, muscle–joint pain, headache, loss of taste and smell and diarrhoea. The most frequent symptoms in Group 1 were shortness of breath and muscle–joint pain, in Group 2, the most frequent symptoms were fatigue and cough and in Group 3, the most frequent symptoms were cough and shortness of breath. The frequency of cough, shortness of breath and fatigue was significantly higher in Group 3 than in the other groups. Symptoms of the patients at admission and their accompanying comorbidities are presented in Table 1.
Although a significant difference in the WBC, prothrombin time (PT) and INR values between the patient groups was observed, all the values were within normal clinical ranges. The D-dimer, ferritin, CRP, urea and creatinine values were significantly higher in the patients with severe COVID-19. The basic hemogram and biochemical examination results of the patients are given in Table 2.
The Kruskal–Wallis test results showed that the TMAO levels were significantly different among the three patient groups. Dunn’s Post Hoc analysis revealed a significant difference between Group 1 and Group 2 (p = 0.006), Group 1 and Group 3 (p < 0.001) and Group 2 and Group 3 (p = 0.031) (Figure 1).
ROC analysis was performed to determine the TMAO concentration that can be used to distinguish PCR positive (Groups 2 and 3) and negative patients (Group 1). ROC analysis revealed that a cut-off value of >2.92 ng/mL had a sensitivity of 74.70%, specificity of 68.18%, a positive predictive value of 81.6% and a negative predictive value of 58.8%. (AUC = 0.753, 95% Cl: 0.669–0.825, p < 0.001) (Figure 2).
No significant correlation was found between the TMAO levels and the levels of D-dimer (r = −0.004, p = 0.970), CRP (r = 0.161, p = 0.147) and WBC (r = 0.042, p = 0.705) in the patients with positive PCR results for COVID-19.

Discussion

The results of the present study showed that the TMAO levels were significantly increased in the patients with COVID-19 and the severity of the infection exacerbated this effect. The gastrointestinal tract is home to a complex, highly diverse microbial ecosystem that interacts with the host and ensures the establishment and permanence of immune homeostasis. It is known that dysbiosis and intestinal microbial metabolites act on systemic immunity, contributing to or protecting against the development of inflammatory events and diseases. Intestinal microbial metabolites affect the immune response of the lungs [16]. There have been limited studies on the underlying mechanism of TMAO level change in lung diseases. Ottiger et al. evaluated 317 patients with community-acquired pneumonia and found that the TMAO levels increased significantly in the non-surviving patients than in the surviving patients. They further reported that the TMAO levels were associated with long-term fatal outcomes in patients with pneumonia without prominent coronary artery disease [17]. Although the pathology of COVID-19 primarily involves the lungs, its complications increase in the presence of systemic diseases. It has been reported that the effects of COVID-19 are more adverse in those with impaired immune responses and comorbidities, such as obesity, atherosclerosis, type 2 DM and hypertension (HT) [18]. In the present study, a significant difference was found in the occurrence of HT, DM and CVD between the patients with severe and non-severe COVID-19. Furthermore, the comorbidity rate was higher in the patients with severe COVID-19. However, although the TMAO levels were significantly different between the patients without COVID-19 and with severe COVID-19, no difference was found in the comorbidities HT, chronic obstructive pulmonary disease and CVD except for DM. Hence, only DM among the comorbidities can have a potential effect on the TMAO levels in the patients with severe COVID-19. In addition, high TMAO levels are associated with abnormal inflammation that is exacerbated by SARS-CoV-2 infection [4]. Therefore, besides comorbidities, the increased levels of TMAO may be due to the close relationship of the disease with inflammatory processes.
Intestinal microbial metabolites can affect other organs besides the lungs. Although its advantages and disadvantages in the human body remain controversial and its underlying molecular mechanisms remain unclear, studies have shown that TMAO, a microbial metabolite, is linked to cardiovascular and metabolic diseases. Previous studies have reported the ability of TMAO to cross the blood-brain barrier, and in vitro studies have revealed that it supports cellular α-synuclein clustering, neuroinflammation, mitochondrial dysfunction and neuronal aging [19]. In the study by Sankowski et al [20], increased TMAO levels were observed in the cerebrospinal fluid and plasma of the patients with Parkinson’s disease. Kuhn et al [21] investigated the relationship of TMAO, which plays a role in inflammation and neuroinflammation, with another inflammatory indicator, CRP, and reported no increase in the high-sensitivity CRP levels despite an increase in the TMAO plasma concentration. Furthermore, Ottiger et al found that although the baseline CRP levels were higher in patients with community-acquired pneumonia, TMAO levels were significantly increased in patients who died [17]. In the present study, however, it was determined that the CRP level was significantly increased in patients with severe COVID-19, but there was no significant correlation between the TMAO and CRP levels in the patients with COVID-19.
TMAO is known to increase the risk of atherothrombosis, and Zhu et al [22] showed that intestinal microorganisms directly contributed to platelet hyper-reactivity and increased thrombosis potential through the production of TMAO. The authors also found that TMAO-administered mice displayed significantly increased cell permeability and neo-intimal formation associated with increased IL-1β production in the intima. IL-1β is a powerful tissue factor inducer and also an indirect indicator of increased atherothrombosis risk caused by the increased levels of TMAO. Similarly, fibrinolysis has been associated with poor prognosis in patients with COVID-19. For these reasons, increased D-dimer levels are associated with poor prognosis in COVID-19 due to the extensive production of thrombins and the suspicion of fibrinolysis, which led the authors to assume that increased D-dimer concentrations were indicative of the existence of venous thromboembolisms, which can lead to ventilation–perfusion incompatibility [23]. Zang et al [24] evaluated 343 patients with COVID-19 and found that the mortality rate was higher in the patients with D-dimer levels of ≥2.0 μg/mL compared with the patients with D-dimer levels of <2.0 μg/mL. Similar to this result, in another study, ≥1.0 μg/mL D-dimer levels at the time of admission were associated with higher intra-hospital mortality in patients with COVID-19 [3]. In the present study, despite significant differences in the initial TMAO levels among the patient groups, no significant difference was found between the patients with severe and non-severe COVID-19 despite the initially higher D-dimer levels in the patients with severe COVID-19. No significant difference was found in the initial D-dimer levels between the surviving and non-surviving patients. Furthermore, no correlation was found between the TMAO and D-dimer levels.
The results of this study showed that the levels of TMAO, a pro-inflammatory substance produced by intestinal microbiota, which is a part of the immune system, were increased in the patients with COVID-19, and the TMAO levels further increased as the severity of the disease progressed.

Scientific Responsibility Statement

The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.

Animal and human rights statement

All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. No animal or human studies were carried out by the authors for this article.

Funding: None.

Conflict of interest

None of the authors received any type of financial support that could be considered potential conflict of interest regarding the manuscript or its submission.

References

1. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395(10223):497-506.
2. Conti P, Ronconi G, Caraffa A, Gallenga CE, Ross R, Frydas I, et al. Induction of pro-inflammatory cytokines (IL-1 and IL-6) and lung inflammation by Coronavirus-19 (COVI-19 or SARS-CoV-2) anti-inflammatory strategies. J Biol Regul Homeost Agents. 2020; 34(2):327-31.
3. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China a retrospective cohort study. Lancet. 2020;395(10229):1054-62.
5. Ufnal M, Zadlo A, Ostaszewski R. TMAO A small molecule of great expectations. Nutrition. 2015; 31(11-12):1317-23.
6. Zeisel SH, Wishnok JS, Blusztajn JK. Formation of methylamines from ingested choline and lecithin. J Pharmacol Exp Ther. 1983; 225(2):320-4.
7. Yancey PH. Organic osmolytes as compatible, metabolic and counteracting cytoprotectants in high osmolarity and other stresses. J Exp Biol. 2005; 208(Pt 15):2819-30.
8. Zou Q, Bennion BJ, Daggett V, Murphy KP. The molecular mechanism of stabilization of proteins by TMAO and its ability to counteract the effects of urea. J Am Chem Soc. 2002; 124(7)1192-202.
9. Seldin MM, Meng Y, Qi H, Zhu W, Wang Z, Hazen SL, et al. Trimethylamine N-Oxide Promotes Vascular Inflammation Through Signaling of Mitogen-Activated Protein Kinase and Nuclear Factor-kappaB. J Am Heart Assoc. 2016 Feb 22;5(2): DOI: 10.1161/JAHA.115.002767.
10. Sun X, Jiao X, Ma Y, Liu Y, Zhang L, He Y, et al. Trimethylamine N-oxide induces inflammation and endothelial dysfunction in human umbilical vein endothelial cells via activating ROS-TXNIP-NLRP3 inflammasome. Biochem Biophys Res Commun. 2016; 481(1-2)63-70.
11. Chen ML, Zhu XH, Ran L, Lang HD, Yi L, Mi MT. Trimethylamine-N-Oxide Induces Vascular Inflammation by Activating the NLRP3 Inflammasome Through the SIRT3-SOD2-mtROS Signaling Pathway. J Am Heart Assoc. 2017; 6(9). DOI: 10.1161/JAHA.117.006347.
12. Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med. 2013;19(5):576-85.
13. Tang WH, Wang Z, Kennedy DJ, Wu Y, Buffa JA, Agatisa-Boyle B, et al. Gut microbiota-dependent trimethylamine N-oxide (TMAO) pathway contributes to both development of renal insufficiency and mortality risk in chronic kidney disease. Circ Res. 2015; 116(3)448-55.
14. Bae S, Ulrich CM, Neuhouser ML, Malysheva O, Bailey LB, Xiao L, et al. Plasma choline metabolites and colorectal cancer risk in the Women’s Health Initiative Observational Study. Cancer Res. 2014; 74(24)7442-52.
15. Agarwal A, Rochwerg B, Lamontagne F, Siemieniuk RA, Agoritsas T, Askie L, et al. A living WHO guideline on drugs for covid-19. BMJ. 2020; 370. DOI: 10.1136/bmj.m3379.
16. Donati Zeppa S, Agostini D, Piccoli G, Stocchi V, Sestili P. Gut Microbiota Status in COVID-19 An Unrecognized Player Front Cell Infect Microbiol. 2020;10:576551.
17. Ottiger M, Nickler M, Steuer C, Odermatt J, Huber A, Christ-Crain M, et al. Trimethylamine-N-oxide (TMAO) predicts fatal outcomes in community-acquired pneumonia patients without evident coronary artery disease. Eur J Intern Med. 2016; 36:67-73.
18. Chiappetta S, Sharma AM, Bottino V, Stier C. COVID-19 and the role of chronic inflammation in patients with obesity. Int J Obes (Lond). 2020; 44(8):1790-92.
19. Uversky VN, Li J, Fink AL. Trimethylamine-N-oxide-induced folding of alpha-synuclein. FEBS Lett. 2001; 509(1):31-5.
20. Sankowski B, Księżarczyk K, Raćkowska E, Szlufik S, Koziorowski D, Giebułtowicz J. Higher cerebrospinal fluid to plasma ratio of p-cresol sulfate and indoxyl sulfate in patients with Parkinson’s disease. Clin Chim Acta. 2020; 501:165-73.
21. Kühn T, Rohrmann S, Sookthai D, Johnson T, Katzke V, Kaaks R, et al. Intra-individual variation of plasma trimethylamine-N-oxide (TMAO), betaine and choline over 1 year. Clin Chem Lab Med. 2017; 55(2):261-8.
22. Zhu W, Gregory JC, Org E, Buffa JA, Gupta N, Wang Z, et al. Gut Microbial Metabolite TMAO Enhances Platelet Hyperreactivity and Thrombosis Risk. Cell. 2016;165(1):111-24.
23. Jose RJ, Manuel A. COVID-19 cytokine storm the interplay between inflammation and coagulation. Lancet Respir Med. 2020; 8(6)e46-e47.
24. Zhang L, Yan X, Fan Q, Liu H, Liu X, Liu Z, et al. D-dimer levels on admission to predict in-hospital mortality in patients with Covid-19. J Thromb Haemost. 2020; 18(6):1324-29.

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İbrahim Halil Yasak, Mustafa Yılmaz, Mehmet Resat Ceylan, İsmail Koyuncu, Eyyup Sabri Seyhanlı. Trimethylamine N-Oxide levels increase in patients with severe and non-severe COVID-19. Ann Clin Anal Med 2023;14(1):30-34

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Aim: Pericardial fluid composition changes in coronary artery disease. This study aims to investigate interleukin 33 (IL 33), total antioxidant status (TAS), total oxidative stress (TOS), and oxidative stress index (OSI) levels in the pericardial fluid and blood plasma of patients who have undergone coronary artery bypass surgery and contribute to the understanding of the pathophysiology of the disease.

Material and Methods: In the study, IL 33, TAS, TOS, and OSI levels were determined in the pericardial fluid and blood plasma of 40 patients who had undergone coronary artery bypass surgery, and the relationship between these parameters was investigated.

Results: IL 33 level in pericardial fluid (51.44 pq/mL) was found to be higher than Plasma IL 33 level (32.31 pq/mL). A significant positive correlation was found between OSI and TOS in pericardial fluid and plasma (p<0.01). A significant negative correlation was found between OSI and TAS in pericardial fluid (p<0.01).

Discussion: IL 33 level was found to be low in patients with coronary artery disease. A higher IL 33 level in pericardial fluid indicates that IL 33 is specific to the heart tissue and passes from the heart tissue to the pericardial space. TOS caused by cellular stress during the inflammation of the coronary arteries directly triggered OSI. IL 33 level may be increased to prevent damage to cells due to TOS and OSI. This study shows us that pericardial fluid can reflect physiological and biochemical changes in the heart, and therefore pericardial fluid can be used for diagnostic and therapeutic purposes.

Keywords: Cardiopulmonary Bypass, Coronary Artery Disease, Interleukin 33, Oxidative Stress, Pericardial Fluid

Introduction

Recently, pericardial fluid (PF) can be used in addition to blood and heart tissue for the diagnosis of cardiovascular diseases (CVD). PF analysis provides an understanding of many pathophysiological mechanisms in various pericardial and CVD. In many studies conducted to compare cardiac biomarkers, better results were obtained from PF studies than blood plasma.
The PF contains a variety of paracrine modulators, such as coronary vasomotor tone, coronary vasomotor tone, heart rate, blood pressure cardiomyocyte function and prostanoids, natriuretic peptides and endothelins [1]. Although the PF’s protein concentration is lower than the plasma, the electrolyte content is considered to be an ultrafiltrate of this liquid blood plasma because it is close to the plasma [2].
CVD can be diagnosed by using various components released from the heart muscle to the circulation and pericardial cavity [2]. In the pathophysiology of CVD, important information about the disease can be obtained by examining the PF, which is the closest place to the heart tissue. For example, the presence of atrial natriuretic factor and brain natriuretic factor approximately 12 times higher in PF in heart failure suggests that these factors play a pathophysiological role as an autocrine or paracrine factor in heart failure [3]. Little is known about the immunological environment of PF, which has been studied in many ways [4, 5].
Interleukin 33 (IL 33) is a member of the IL-1 family that regulates the host response to infectious, inflammatory and immunological events; It is a bifunctional protein that acts as an intracellular nuclear factor with transcriptional properties and a proinflammatory cytokine.
Recently, serious studies have been started on IL 33 due to its effect on CVD [6]. IL 33 is released during cellular damage and stress; It has a cardioprotective effect by binding to a heterodimeric receptor complex consisting of ST2 and IL-1R accessory protein (IL-1RAP). Since the expression of IL 33 is intense in coronary artery endothelium, coronary artery smooth muscle cells, cardiomyocytes and cardiac fibroblasts, the role of IL 33 in various cardiovascular disorders should be investigated [7, 8].
IL 33 has a protective effect in conditions such as atherosclerosis, obesity, Type II diabetes and cardiac remodeling [9]. IL 33 decreases the development of atherosclerosis by increasing the production of oxidized-LDL antibodies stimulated by IL-5 [10]. In addition, it has been reported that IL 33, which increases the interaction of fibroblast and cardiomyocyte, has a beneficial role in heart failure [8]. Decreased expression of IL 33 with angiogenic or inflammatory stimuli indicates a possible role of IL 33 in endothelial cell activation and angiogenesis [11].
In a study in rats, treatment with IL 33 prevented hypertrophy in pressure-loading models of the ventricles. In hypoxia, IL 33 saved cardiomyocytes from apoptosis. Treatment with IL 33 in ischemia-reperfusion during myocardial infarction (MI) reduced the size of the infarct, corrected ventricular dilatation, suppressed caspase 3, and increased apoptosis inhibitors [12].
Despite the information available, data on IL 33 is currently insufficient. Although the presence of IL 33 has been investigated and detected in many living materials in many previous studies, its presence in PF has not been investigated. Since PF is difficult to obtain. For this reason, it is important to examine the presence of IL 33 in the PF of coronary artery patients undergoing open-heart surgery, where PF is easy to obtain. This research is important because the mechanism of increase-decrease of IL 33 is not known, there is no IL 33 study in PF and there are unanswered questions about the effect pathway of IL 33.

Material and Methods

Ethical committee approval

The present study was approved by the local ethics committee (Approval number: 25.01.2016-16/01/13).

Patients included in the study

Forty patients (28 males+12 females, mean age: 60.04 years) who underwent coronary artery bypass surgery with the cardiopulmonary bypass method were included in this study.

Obtaining blood and PF

Blood samples taken from the patients before surgery were transferred to glass tubes (10 ml, Vacutainers/BD Biosciences) with sterile and gel-free heparin (0.2 ml, Nevparin injectable 25000 IU/5 mL) and were transferred to the laboratory with ice packs. After the centrifugation step (5000 rpm, 5 min), the supernatant part of the blood (plasma) was taken into a sterile Eppendorf tube (1.5 mL, Eppendorf) and kept at -80oC until the study day. Median sternotomy was first performed to obtain PF from the patients. Then the pericardium was opened and the PF was aspirated with a sterile syringe. PF was then transferred to sterile glass tubes (10 mL, Vacutainers/BD Biosciences) and stored in an ice-filled container. The supernatant portion of the PF centrifuged at 4000 rpm (5 min) was transferred to a sterile Eppendorf tube (1.5 mL, Eppendorf) and stored at -80oC until the study day.

Quantification of IL 33 in plasma and PF with ELISA

For the detection of IL 33 in plasma and PF, the commercial kit Human IL 33 (Interleukin 33) (Elabscience, catalog number, E-EL-H2402 www.elabscience.com) ELISA Kit was used.
Measurement of Total Oxidant Status (TOS), Total Antioxidant Status (TAS) and Oxidative Stress Index (OSI) in Plasma and PF

TOS Level Measurement

TOS levels were determined using a new automatic measurement method developed by Erel [13]. Results were expressed as μmol H2O2 Equivalent/L.

TAS Level Measurement

TAS levels were determined using a new automatic measurement method developed by Erel [14]. Results are expressed as mmol Trolox Equivalent/L.

OSI Measurement

OSI, which is accepted as an indicator of Oxidative Stress, is expressed as a percentage of the ratio of TOS levels to TAS levels. While calculating OSI in the examples, TAS levels were multiplied by 10 and TOS levels and units were equalized. Results are expressed as Arbitrary Units (AU) [15, 16].

Statistical Analysis

Statistical analyzes were performed using the SPSS Version 25 (IBM, SPSS Inc. Chicago USA) computer program. The significance of the difference between the means of the groups was compared with the One-Way ANOVA test. The relationship between the parameters was investigated by Pearson’s correlation analysis. Values less than p < 0.05 were considered statistically significant.

Results

The minimum, maximum, mean and standard deviation results of the patients included in the study (28 males, 12 females, mean age: 60.04 Years), the number of coronary vessels, IL 33, TAS, TOS and OSI are shown in Table 1. The number of bypassed coronary arteries in the operated patients varied between 2 and 4. As a result of the statistical evaluation of the data obtained from the study, the correlation values between IL 33, TAS, TOS and OSI in the PF and Plasma of the patients are shown in Table 2. According to the statistical evaluation of the findings, a positive significant correlation (r= 0.978, p<0.01) was found between OSI and TOS in plasma. There was a negative significant correlation between OSI and TAS in PF (r= -0.509, p<0.01). A positive significant correlation (r= 0.722, p<0.01) was found between OSI and TOS in PF. Although there was a negative correlation between Pericardial IL 33 and Plasma IL 33 (r=-340), no statistically significant correlation was found between these two parameters (p=0.121, p>0.05) (Figure 1). As a result of the statistical evaluation of the data obtained from the study, the relationship between the number of coronary vessels bypassed during the operation and plasma and Pericardial IL 33 is shown in Table 3.

Discussion

In many previous studies, various angiogenic growth factors, cytokines, natriuretic peptides and classical vasoactive hormones were found in higher concentrations in PF compared to plasma [17]. In our study, IL 33, TOS and OSI levels in PF were found to be higher. TAS level was lower in PF. According to these data obtained, TOS caused by cellular stress during the inflammation of the coronary arteries directly triggered OSI, and the level of IL 33 may have increased in order to prevent damage to the cells due to TOS and OSI.
It has not been determined exactly in which diseases IL 33 is high or low and according to what. These observations suggest that IL 33 may have a complex regulatory role in CAD.
In a study conducted in patients with CAD, it was reported that IL 33 expression was high, circulating IL 33 levels were associated with the pathogenesis of atherosclerosis in patients with acute coronary syndrome and could be used as diagnostic indicators in terms of a new index value in these diseases [18].
In a study conducted in the Chinese Han population, the level of IL 33 in the plasma was found to be 233.67 pg/ml in coronary artery diseases [19]. In a study conducted on ischemic heart patients, serum IL 33 level was found to be 103.33 pg/ml in AMI patients, 157.60 pg/ml in stable angina patients, 122.21 pg/ml in unstable angina patients, and 61.85 pg/ml in control group patients [20]. In our study, however, the plasma IL 33 level was found to be lower (32.31 pg/ml). This shows us that the IL 33 level of patients who had coronary artery bypass surgery decreased.
In a study examining the relationship between oxidative stress and IL 33, it was found that IL 33 directly reduced oxidative stress [21]. In our study, it was determined that the IL 33 level increased in PF compared to plasma, against increased oxidative stress. This shows us that IL 33 level increases in case of oxidative stress.
In our study, IL 33, which is produced by many organs, should normally be found higher in plasma, but, surprisingly, it is found more in PF, which is in line with previous studies. The main factor in this situation may be the passage of IL 33 from the heart tissue to the PF. Perhaps IL 33 produced during cellular stress does not function in heart cells and may have leaked into the pericardial space. The high level of IL 33 in PF, which is the tissue closest to the heart, strengthens the acceptance of this fluid as an ultrafiltrate of blood plasma.
Although it is said that IL 33 protects the cell against stress, in fact, the good or bad aspects of high or low IL 33 need to be investigated. For example, cells with high IL 33 probably have a lot of cellular stress, so a high IL 33 actually indicates that that cell is under intense stress. Therefore, a high IL 33 may not mean good. A low IL 33 indicates less stress in the cell, which may actually be a good situation. In order to better evaluate the function of IL 33 in the cell, it would be better to study different cellular stress parameters with IL 33 in another study.
According to the results of the study, Plasma IL 33 level was high and PF IL 33 level was low in patients with a high number of bypassed coronary arteries.

Conclusion

This study showed that the IL 33 concentration of PF is different from the plasma and the IL 33 level is high in coronary artery patients. The reason why IL 33 is found more in PF may be the passage of IL 33 from the heart tissue to the pericardial space. In this study, it was also determined that IL 33 level increased against increasing oxidative stress and generated data about IL 33 level in PF in coronary artery patients. However, cellular-based studies are needed to examine the endogenous role of IL 33 and to determine the mechanism of increase and decrease. In the future, the effects of administration of IL 33 to the plasma or pericardial cavity should be investigated by animal experiments.

Scientific Responsibility Statement

The authors declare that they are responsible for the article’s scientific content including study design, data collection, analysis and interpretation, writing, some of the main line, or all of the preparation and scientific review of the contents and approval of the final version of the article.

Animal and human rights statement

All procedures performed in this study were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Funding: None

Conflict of interest

The authors declare no conflict of interest.

References

1. Dudzinski DM, Mak GS, Hung JW. Pericardial diseases. Curr Probl Cardiol. 2012;37(3):75–118.
2. Dikme R, Padak M, Göz M, Aydın MS, Göç Ö. Liquid reflecting the heart function: Pericardial fluid. Ann Clin Anal Med. 2019; DOI: 10.4328/ACAM. 20007.
3. Simon D, Gilicze O, Farkas N, Najbauer J, Nemeth P, Lenard L, et al. Correlation of natural autoantibodies and cardiovascular disease-related anti-bacterial antibodies in pericardial fluid of cardiac surgery patients. Clin Exp Immunol. 2018;193(1):55–63.
4. Meng X, Yang J, Dong M, Zhang K, Tu E, Gao Q, et al. Regulatory T cells in cardiovascular diseases. Nat Rev Cardiol. 2016;13(3):167-79.
5. Ketelhuth DF, Hansson GK. Adaptive response of T and B cells in atherosclerosis. Circ Res. 2016;118(4):668–78.
6. Liew FY. IL-33: a Janus cytokine. Ann Rheum Dis. 2012;71(2):101–4.
7. Moussion C, Ortega N, Girard JP. The IL-1-like cytokine IL-33 is constitutively expressed in the nucleus of endothelial cells and epithelial cells in vivo: a novel ‘alarmin’? PLoS One. 2008;3(10):e3331.
8. Sanada S, Hakuno D, Higgins LJ, Schreiter ER, McKenzie AN, Lee RT. IL-33 and ST2 comprise a critical biomechanically induced and cardioprotective signaling system. J Clin Invest. 2007;117(6):1538-49.
9. Miller AM. Role of IL-33 in inflammation and disease. J Inflamm (Lond). 2011;8(1):22.
10. Miller AM, Xu D, Asquith DL, Denby L, Li Y, Sattar N, et al. IL-33 reduces the development of atherosclerosis. J Exp Med. 2008;205(2):339-46.
11. Kuchler AM, Pollheimer J, Balogh J, Sponheim J, Manley L, Sorensen DR, et al. Nuclear interleukin-33 is generally expressed in resting endothelium but rapidly lost upon angiogenic or proinflammatory activation. Am J Pathol. 2008;173(4):1229-42.
12. Domingo A, Pascual-Figal MD, James L, Januzzi MD. The Biology of ST2: The International ST2 Consensus Panel. Am J Cardiol. 2015; 115(Suppl.7): 3B-7B.
13. Erel O. A new automated colorimetric method for measuring total oxidant status. Clin Biochem. 2005; 38(12):1103-11.
14. Erel O. A novel automated direct measurement method for total antioxidant capacity using a new generation, more stable ABTS radical cation. Clin Biochem. 2004;37(4):277–85.
15. Aycicek A, Erel O, Kocyigit A. Increased oxidative stress in infants exposed o passive smoking. Eur J Pediatr. 2005;164:775–8.
16. Aycicek A, Varma M, Ahmet K, Abdurrahim K, Erel O. Maternal active or passive smoking causes oxidative stress in placental tissue. Eur J Pediatr. 2011; 170(5): 645-51.
17. Watanabe M, Kawaguchi S, Nakahara H, Hachimaru T. The roles of natriuretic peptides in pericardial fluid in patients with heart failure. Clin Cardiol. 2009;32(3):159–63.
18. Al Shahi H, Shimada K, Miyauchi K, Yoshihara T, Sai E, Shiozawa T, et al. Elevated Circulating Levels of Inflammatory Markers in Patients with Acute Coronary Syndrome. Int J Vasc Med. 2015;2015:805375.
19. Tu X, Nie S, Liao Y, Zhang H, Fan Q, Xu C, et al. The IL-33-ST2L pathway is associated with coronary artery disease in a Chinese Han population. Am J Hum Genet. 2013;93(4):652-60.
20. Jafarinia M, Firuzsalari FG, Zaringol M, Khalili M. Serum levels of interleukin (IL)-33 in patients with ischemic heart disease. MOJ Immunol. 2018;6(2):29–32.
21. Zhang HF, Xie SL, Chen YX, Mai JT, Wang JF, Zhu WL, et al. Altered serum levels of IL-33 in patients with advanced systolic chronic heart failure: correlation with oxidative stress. J Transl Med. 2012;10:120.

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Ömer Göç, Mustafa Göz, Reşat Dikme, Mahmut Padak. Investigatıon of oxidative stress and Interleukin 33 (IL33) level in pericardial fluid of patients with coronary artery bypass surgery. Ann Clin Anal Med 2023;14(1):55-59

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