Skip to main content
NCBI home page
Cell Stress & Chaperones logoLink to Cell Stress & Chaperones
. 2023 Feb 17;28(2):191–199. doi: 10.1007/s12192-023-01330-3

Investigation of inflammation, oxidative stress, and DNA damage in COVID-19 patients

Muhammet Yusuf Tepebaşı 1,✉, İlter İlhan 2, Esra Nurlu Temel 3, Okan Sancer 4, Önder Öztürk 5
PMCID: PMC9936118  PMID: 36797451

Abstract

COVID-19 disease, which spreads worldwide, is a disease characterized by widespread inflammation and affects many organs, especially the lungs. The resulting inflammation can lead to reactive oxygen radicals, leading to oxidative DNA damage. The pneumonia severity of 95 hospitalized patients with positive RT-PCR test was determined and divided into three groups: mild, moderate, and severe/critical. Inflammation markers (neutrophil–lymphocyte ratio, serum reactive protein, procalcitonin, etc.) were determined, and IL-10 and IFN-γ measurements were analyzed using the enzyme-linked immunosorbent assay method. In evaluating oxidative damage, total thiol, native thiol, disulfide, and ischemia-modified albumin (IMA) levels were determined by measuring spectrophotometrically. The comet assay method’s percentage of tail DNA obtained was used to determine oxidative DNA damage. As a result, when the mild and severe/critical groups were compared, we found that total thiol, native thiol, and disulfide levels decreased significantly in the severe/critical group due to the increase in inflammation markers and cytokine levels (p < 0.05). We could not detect any significance in IMA levels between the groups (p > 0.05). At the same time, we determined an increase in the tail DNA percent level, that is, DNA damage, due to the increased oxidative effect. As a result, we determined that inflammation and oxidative stress increased in patients with severe pneumonia, and there was DNA damage in these patients.

Keywords: COVID-19, Inflammation, Oxidative stress, DNA damage

Introduction

COVID-19, which affected the whole world and was declared a pandemic in 2020, has a wide range of effects, from mild illness to severe infections resulting in death. Respiratory viral infections can cause genomic instability by causing excessive cytokine release with increased levels of inflammation, redox, and immune response instability. The data obtained from previous studies revealed that the release of cytokines is excessively increased in COVID-19 infection, which can lead to death from acute lung injury, and increased oxidative stress plays a role in the pathogenesis of the disease (Delgado-Roche and Mesta 2020; Lorente et al. 2021; Khomich et al. 2018).

COVID-19 virus binds to the angiotensin-converting enzyme 2 (ACE2) receptor in the alveolar epithelial cells, enters the cell, and multiplies (Huang et al. 2020). With the release of new viral particles from the cell, the cellular and humoral immune response is further activated and increased. As a result, cells such as macrophages, neutrophils, and T cells are activated, and cytokines and chemokines are released from immune effector cells (Sarzi-Puttini et al. 2020). The T cells consist of two subgroups: Th1 and Th2. Th1 cells exert their effects on proinflammatory cytokines (IFN-γ, TNF-α, etc.), while Th2 cells exert their effects on anti-inflammatory (IL-10, IL 13, etc.) cytokines. Studies on proinflammatory and anti-inflammatory cytokines in COVID-19 have revealed that IL-10, although usually anti-inflammatory, increases in severely ill patients, increasing CD4 + and CD8 + T cells that produce interferon-gamma (Wang et al. 2020; Lu et al. 2021).

Reactive oxygen species (ROS) occur during events such as electron transport, phagocytic activation against natural stimuli, viral infections, neutrophil infiltration, biosynthesis, and degradation (Delgado-Roche and Mesta 2020). Thiols are organic molecules containing the sulfhydryl [− SH] group, which constitutes an important part of protective antioxidant levels against oxidative stress and is important in defense against radical oxygen species (Erel and Neselioglu 2014). The oxidant molecules released in the oxidative formed oxidize the thiol groups of the proteins and cause the formation of reversible disulfide [–S–S–] bonds. Disulfide bonds are reduced to thiol groups, providing thiol-disulfide homeostasis (Mete et al. 2021). Thiol-disulfide balance, which has oxidant and antioxidant effects, has an important function in detoxification, antioxidant protection, apoptosis, enzymatic regulation, and cellular signaling mechanisms (Oe and Erdoğan 2020). Studies on the thiol-disulfide balance in patients with COVID-19 have shown that this balance is impaired (Mete et al. 2021; Erel et al. 2021). Another biomarker of oxidative stress is ischemia-modified albumin (IMA) (Bolatkale et al. 2017). In the case of ischemia, the IMA molecule is formed as a result of the structural changes that occur at the last metal-binding amino-terminal in the serum albumin structure (Aykac et al. 2021).

Free radicals damage the deoxyribose phosphate backbone, which forms the DNA structure, and the specific modification of its bases, and also disrupt the DNA–protein interaction. Oxidation of the deoxyribose skeleton oxidative base modifications can lead to mutations while inducing base release and DNA chain breaks (Fidan 2005). Previous studies have shown that the “Comet” test is suitable for detecting DNA damage due to cellular oxidative stress (Bonassi et al. 2021).

Studies have revealed how proinflammatory and anti-inflammatory cytokines are affected in COVID-19 patients and their effects on oxidative stress parameters. Our study aimed to show the impact of inflammation and oxidative stress on DNA damage in COVID-19 patients.

Materials and methods

Study design

In this study, 95 patients who applied to the Infectious Diseases Department of Süleyman Demirel University Medical Faculty Hospital suspected of COVID-19, whose qRT-PCR test was positive, and who were hospitalized were included. Infection and lung disease specialists evaluated the patient’s clinical information, laboratory, and radiological findings, and they were divided into groups according to pneumonia criteria: mild pneumonia with symptoms such as fever, muscle/joint pains, cough and sore throat, respiratory rate < 30/min, SpO2 > 90 in room air, and mild pneumonia found on chest computed tomography (CT); moderate pneumonia with findings such as fever, muscle/joint pains, cough and sore throat, respiratory rate < 30/min, SpO2 > 90 in room air, and moderate pneumonia on CT; and severe and critical pneumonia with symptoms such as fever, muscle/joint pain, cough, and sore throat, presenting with tachypnea (≥ 30/min) and having common diffuse pneumonia on CT with a SpO2 level below ≤ 90% in room air (World Health Organization 2020; Republic of Turkey Ministry of Health 2020). As a result of these evaluations, the patients were divided into three groups according to the severity of pneumonia (mild n = 29, moderate n = 29, and severe/critical n = 37). In addition, the patients were evaluated in terms of intensive care criteria, oxygen demand, and death despite treatment. Intensive care criteria were determined as respiratory rate ≥ 30/min, PaO2/FiO2 < 300, SpO2 < 90%, or PaO2 < 70 mmHg despite 5 L/min oxygen therapy in the follow-up, mainly with dyspnea and respiratory distress. Oxygen requirement was determined as SpO2 > 90 and respiratory rate 24/min; no oxygen requirement as < 5 L/min and > 5 L/min. Drug treatment of the patients was performed according to the Turkish Ministry of Health guidelines (Republic of Turkey Ministry of Health 2020).

Analysis of parameters

For biochemical and ELISA analyses, approximately 5 mL of peripheral blood was taken into gel biochemistry tubes and centrifuged at 4000 rpm for 10 min. The serum obtained was stored at − 80 °C until the study time. For the comet assay analysis used to evaluate DNA damage, approximately 3 mL of blood was taken into heparinized tubes, and the samples were studied without waiting. For complete blood count parameters, 2 mL of blood was taken into tubes with K-EDTA.

Thiol and native thiol levels were measured spectrophotometrically using the Real Assay Diagnostics Commercial Kit with Beckman Coulter AU5800 autoanalyzer according to the method of Erel and Neselioglu. Disulfide (–S–S–) levels were calculated (total thiol − native thiol/2) (Erel and Neselioglu 2014). Serum HDL, CRP, and albumin were measured spectrophotometrically. Serum IMA levels were measured spectrophotometrically at a wavelength of 470 nm using the method developed by Bar–Or et al., and absorbance units (ABSU) were determined (Bar-Or et al. 2000). Neutrophil–lymphocyte ratio (NLR) and monocyte values were measured with the Beckman Coulter DxI device. Ferritin levels were measured with the Cobas e411 device by immunoassay method.

IL-10 and IFN-γ levels were studied by enzyme-linked immunosorbent assay method following the kit manufacturer’s protocol (MyBioSource, USA). After a plate reader’s absorbance analysis at 450 nm, their concentrations were determined as pg/mL.

To detect DNA damage, the comet assay protocol by Singh et al. was modified, and tail DNA percent was detected (Singh et al. 1988). Histopaque 1077 (Sigma-Aldrich Co., LLC.) and then blood samples (1:1 ratio) were slowly added to the Eppendorf tube. After centrifugation at 2000 rpm for 20 min, the cloudy white portion containing the leukocytes remaining between the blood cells and the histopaque was transferred to the new Eppendorf tube. Phosphate buffer was added to the obtained cells at a ratio of 1:1 and centrifuged at 2500 rpm for 10 min. The supernatant was discarded, and 30–40 µL of PBS was added to the cells. Fifteen microliters of cell suspension and low-melting-point agarose were mixed with 100 µL in the new Eppendorf tubes. The suspension mix, two slides for each sample, was spread on the slides, the surface pre-coated with 1% normal-melting-point agarose. After placing the coverslips on the slides, they were left on ice for a while, and the coverslips were then carefully removed. Slides were incubated in cold lysis solution for 1 h at 4 °C in the dark and then placed in an electrophoresis tank containing cooled electrophoresis buffer and incubated at 4 °C for 20 min in the dark. Electrophoresis was carried out in the same solution at 300 mA for 25 min. The resulting slides were washed with neutralization buffer, and 20 µg/mL of ethidium bromide was added. Imaging was done with a Zeiss Imager A1 fluorescence microscope, and photographs were taken. Photographs of 100 cells were taken randomly for each slide. Tail DNA percentage parameters were determined by analyzing with the Open Comet evaluation program.

Statistical analysis

Statistical analysis of categorical variables was done with chi-square or Fisher’s test. Normal distribution analyses of numerical parameters were done by the Kolmogorov–Smirnov test. Kruskal–Wallis test was used in all groups that did not have a normal distribution. Statistically significant groups were evaluated with each other using the Mann–Whitney U test. Spearman’s correlation analysis was used in the correlation analysis. All statistical analyses were performed using IBM SPSS Statistics 18.0 software, and p < 0.05 was considered significant.

Results

In the study, 95 patients who were hospitalized and diagnosed with COVID-19 infection as a result of the RT-PCR test were grouped according to the severity of the disease (mild n = 29, moderate n = 29, severe/critical n = 37). Age, gender, and comorbidities were determined in the groups, and statistical analyses were performed (Table 1). A significant increase was found between the ages of the patient groups in those who were mild-severe/critical and moderate-severe/critical (p = 0.031 and p = 0.036). However, there was no difference between the groups regarding gender (p > 0.05). While all 29 patients with mild pneumonia were cured, 3 of 29 patients with moderate pneumonia and 3 of 37 patients with severe/critical pneumonia died.

Table 1.

Clinical characteristics of patients with COVID-19

Mild (n = 29) Moderate (n = 29) Severe/critical (n = 37) p value
Age 57.41 ± 18.79 60.69 ± 13.11 67.511 ± 2.98

p > 0.05a

p = 0.0310b

p = 0.0359c
Gender (M/F) 19/10 17/12 21/16 p > 0.05
Comorbidities
Diabetes 4 11 17

p = 0.0357a

p > 0.05b,c
KOAH 5 5 4 p > 0.05a,b,c

Cardiovascular

disease

 2 2 6 p > 0.05a,b,c
Malignancy 5 3 9 p > 0.05a,b,c

Chronic kidney

disease

 1 1 5 p > 0.05a,b,c
At least two diseases 12 8 24

p > 0.05a,b

p = 0.0032c
Open in a new tab

aMild vs. moderate

bMild vs. severe/critical

cModarete vs. severe/critical

The mean values of the laboratory findings in the patient groups were determined and compared statistically. When NLR, CRP, ferritin, and procalcitonin values were compared between the groups, it was determined that there was a significant increase between the mild vs. severe/critical and moderate vs. severe/critical groups (p < 0.05) (Table 2). There was no significant difference in monocyte/HDL, hemoglobin, thrombocyte, and D-dimer values (p > 0.05).

Table 2.

Laboratory findings in patient groups

Mild (n = 29) Moderate (n = 29) Severe/critical (n = 37) p value
NLR 4.277 ± 3.578 6.336 ± 5.010 9.595 ± 6.404

p > 0.05a

p < 0.001b

p = 0.033c
CRP (mg/lt) 43.44 ± 50,61 63.91 ± 62.26 101.2 ± 68.95

p > 0.05a

p < 0.001b

p = 0.005c
Ferritin (µg/L) 498.6 ± 670.6 493.2 ± 492.0 827.2 ± 583.2

p > 0.05a

p = 0.001b

p = 0.004c
Monocyte/HDL 0.019 ± 0.015 0.014 ± 0.010 0.027 ± 0.046 p > 0.05a,b,c
Hemoglobin (g/dl) 12.30 ± 2.48 12.79 ± 2.22 11.45 ± 2.49 p > 0.05a,b,c
Platelets (× 103/mm3) 205 ± 106 177 ± 67 197 ± 98 p > 0.05a,b,c
D-dimer 916.4 ± 1100 613.9 ± 639 1873 ± 6149 p > 0.05a,b,c
Procalcitonin 0.5452 ± 0.89 0.5376 ± 1.25 0.7078 ± 1.043

p > 0.05a

p = 0.041b

p = 0.049c
Open in a new tab

NLR neutrophil–lymphocyte ratio, CRP serum reactive protein

aMild vs. moderate

bMild vs. severe/critical

cModarete vs. severe/critical

The mean values of oxidative stress parameters (total thiol, native thiol, disulfide, and IMA), cytokine levels (IL-10 and IFN-γ), and the parameters of DNA damage (tail DNA percent) were determined in the groups, and statistical analysis was performed (Table 3) (Fig. 1). There was a significant decrease in total thiol, native thiol, and disulfide levels between the mild and severe/critical groups (p = 0.004, p = 0.006, and p = 0.003, respectively). There was an increase in IMA levels between the groups, but no statistically significant difference was found (p = 0.054). When we compared the IL-10 and IFN-γ levels in the groups, there was a statistically significant increase between the mild vs. severe/critical groups (p = 0.044 and p = 0.025). When the groups were compared in terms of tail DNA percent values, an indicator of DNA damage, we found a significant increase between the mild vs. severe/critical groups (p = 0.022).

Table 3.

Results of IL-10, IFN-γ, oxidative stress, and DNA damage parameters in patient groups

Mild (n = 29) Moderate (n = 29) Severe/critical (n = 37) p value
Total thiol 362.4 ± 26.25 343.0 ± 37.89 250.8 ± 19.88 0.005
Native thiol 266.3 ± 20.66 255.8 ± 31.45 181.9 ± 15.58 0.006
Disulfide 48.05 ± 3.17 43.60 ± 3.590 34.49 ± 2.32 0.004
IMA 228.0 ± 5.99 242.3 ± 4.428 245.4 ± 3.37 0.054
IL-10 2.44 ± 1.57 3.25 ± 3.365 3.62 ± 3.89 0.045
IFN-γ 1.64 ± 0,66 1.87 ± 1.04 2.38 ± 2.13 0.031
Tail DNA percent 0.9397 ± 0.04 0.9597 ± 0.04 1.084 ± 0.04 0.015
Open in a new tab

Values are expressed as mean ± SD and median, p value Kruskal–Wallis analysis

IMA ischemia modified albumin

Fig. 1.

Fig. 1

Open in a new tab

Statistical graph of total thiol, native thiol, disulfide, IMA, IL-10, IFN-γ, and tail DNA percent parameters

Correlation analysis of the relationships of oxidative stress parameters on DNA damage was performed. Negative correlations between total thiol, native thiol, and disulfide levels and tail DNA percentage levels were found (p = 0.029, r =  − 0.224; p = 0.026, r =  − 0.229; and p = 0.021, r =  − 0.219, respectively). There was no significant correlation between IMA levels (p = 0.206, r = 0.131). While CRP and procalcitonin parameters had a significant negative correlation with total thiol, native thiol, and disulfide, no significant correlation was found with IMA (Table 4).

Table 4.

Inflammation, oxidative stress parameters, and tail DNA percent correlation analysis

CRP Procalcitonin IL-10 IFN-γ Tail DNA percent NLR Ferritin
Total thiol r  − 0.241  − 0.264  − 0.220  − 0.114  − 0.224  − 0.023  − 0.248
p 0.019* 0.010* 0.038* 0.289 0.029* 0.825 0.016*
Native thiol r  − 0.241  − 0.257  − 0.206  − 0.122  − 0.229  − 0.022  − 0.256
p 0.019* 0.012* 0.052 0.257 0.026* 0.832 0.012*
Disulfide r  − 0.242  − 0.278  − 0.244  − 0.076  − 0.219  − 0.017  − 0.242
p 0.018* 0.006* 0.021* 0.477 0.021* 0.873 0.018*
IMA r 0.209 0.041 0.043 0.122 0.131 0.028 0.065
p 0.42 0.694 0.690 0.255 0.206 0.791 0.531
CRP r - 0.504 0.065 0.020 0.232 0.293 0.466
p - 0.0001* 0.544 0.850 0.024* 0.004  < 0.001
Procalcitonin r 0.504 - 0.079  − 0.164  − 0.021  − 0.004 0.468
p 0.0001* - 0.462 0.124 0.843 0.971  < 0.001
Open in a new tab

IMA ischemia modified albumin, CRP serum reactive protein, NLR neutrophil–lymphocyte ratio

*p < 0.05

ROC analysis of total thiol, native thiol, disulfide, IMA, IL-10, IF-γ, and tail DNA percent parameters were performed, and cut-off values were determined (Table 5) (Fig. 2).

Table 5.

ROC analysis results between mild vs. severe/critical groups of total thiol, native thiol, disulfide, IMA, IL-10, IFN-γ, and tail DNA percent values

AUC (95% CI) Cut-off level Sensitivity (%) Specificity (%) p value
Total thiol 0.7409 (0.61–0.86)  < 289.9 67.57 68.97 0.001*
Native thiol 0.7358 (0.61–0.85)  < 211.0 67.57 68.97 0.001*
Disulfide 0.7451 (0.62–0.87)  < 38.58 70.27 72.41 0.001*
IMA 0.6687 (0.53–0.80)  > 241.7 59.46 62.07 0.019*
IL-10 0.6969 (0.56–0.83)  > 3.14 58.06 82.76 0.009*
IFN-γ 0.6841 (0.54–0.82)  > 1.82 54.84 75.86 0.014*
Tail DNA percent 0.6869 (0.55–0.81)  > 0.9950 70.27 68.97 0.010*
Open in a new tab

IMA ischemia modified albumin

*p < 0.05

Fig. 2.

Fig. 2

Open in a new tab

ROC graphs of total thiol, native thiol, disulfide, IMA, IL-10, IF- γ, and tail DNA percent parameters

Discussion

In our study, we grouped COVID-19 patients according to the degree of pneumonia and investigated the effects of inflammation and oxidative stress on DNA. NLR, CRP, ferritin, and procalcitonin are routinely studied to detect inflammation, and IL-10 and IFN-γ levels were determined. The effect of inflammation on oxidative stress and DNA damage was determined.

Studies have shown that NLR, CRP, ferritin, and procalcitonin are useful for detecting inflammation. It is stated that NLR can be used as a biomarker, especially in inflammatory, metabolic, and cancer diseases (Imtiaz et al. 2012; Guthrie et al. 2013). A study conducted in 2020 found that the NLR parameter increased during COVID-19 and stated that it would be helpful in the diagnosis and follow-up (Jimeno et al. 2021). In other studies, ferritin, CRP, and procalcitonin levels were high in COVID-19 patients who needed intensive care (Çakırca et al. 2021; Yildiz et al. 2021). Our study found significantly higher NLR, CRP, ferritin, and procalcitonin levels in the mild-severe and moderate-severe patient groups, in line with other studies (Table 2). The high parameters showed us that inflammation increased due to the increase in pneumonia in patients. It has been stated that IL-10, generally known as a cytokine with anti-inflammatory properties, increases in direct proportion to the severity of the disease in individuals with COVID-19 (Huang et al. 2020; Han et al. 2020; Zhao et al. 2020; Rojas et al. 2017). The reason why IL-10 is a proinflammatory and immune activator in COVID-19 is explained by the increase of some cytokines and chemokines in these patients with severe and critical pneumonia, as well as the rise of IFN-γ-producing effector CD4 + and CD8 + T cells in the peripheral blood (Wang et al. 2020; Lu et al. 2021; Xu et al. 2020). IFN-γ, synthesized by CD4 + T, CD8 + T cells, and NK, is the most important macrophage-stimulating cytokine and plays an important role in viral infections (Akamatsu et al. 2021). In some studies on IFN-γ in COVID-19 patients, although there was an increase in the severe group, no statistically significant results were found, while statistically significant increases were found in some studies (Wan et al. 2020; Shi et al. 2020; Zhu et al. 2020). In our research, when we compared the IL-10 and IFN-γ levels in the groups we formed according to the severity of the disease, we compared the mild vs. severe/critical groups, and we found a significant increase in the severe/critical group in line with the studies (Table 3).

Thiols play an important role in the antioxidant defense system against oxidation products formed in acute inflammation and cytokine storm (Moriarty-Craige and Jones 2004). In studies on thiol and disulfide in COVID-19 patients, significant decreases were found in total thiol and native thiol levels in patients who need intensive care and those with severe disease. It was stated that the disulfide levels of these patients did not change in some publications, increased in some publications, and decreased in some publications (Erel et al. 2021; Aykac et al. 2021; Çakırca et al. 2021; Erol et al. 2022). When we compared the mild and severe/critical groups in our study, we found that total thiol, native thiol, and disulfide levels decreased significantly (Table 3). This decrease in disulfide levels in patients with severe pneumonia was thought to be a result of the conversion of proteins to advanced oxidation products (Otal et al. 2021). While IMA levels, one of the indicators of oxidative stress in COVID-19 patients, were high in some studies, no significant increase was found in others (Aykac et al. 2021; Yildiz et al. 2021; Erol et al. 2022). Although it increased with the severity of the disease in our study, we could not detect statistical significance (Table 3).

Studies have shown that inflammation and oxidative stress in viral infections have genotoxic effects (Pánico et al. 2022). Chronic inflammation increases the formation of reactive oxygen species (Bartsch and Nair 2004). Oxidative stress can induce various types of damage, including in the double-strand DNA, DNA–protein crosslinks, and oxidation products of sugar groups (Peng et al. 2021). Studies have shown that oxidative DNA damage contributes to the development of neurological diseases and several types of cancer (37,38). DNA damage caused by oxidative stress can be determined by tail DNA percent levels (de Oliveira Gonçalves et al. 2022). A study conducted in 2021 stated that DNA and RNA oxidative damage is associated with mortality in COVID-19 patients (Lorente et al. 2021). In our research, we determined that the DNA damage was increased between the mild and severe/critical groups (Table 3).

In the correlation analysis we conducted to determine the relationship between inflammation and oxidative stress, we determined that CRP, procalcitonin, IL-10, and ferritin parameters had a significant negative correlation with total thiol, native thiol, and disulfide levels. In addition, we found that total thiol, native thiol, and disulfide levels, which are oxidative stress markers, show a significant negative correlation with the tail DNA percent parameter, which is an indicator of DNA damage (Table 4).

In addition, as a result of the analysis we made to determine the power to distinguish the mild and severe/critical groups, we determined that total thiol, native thiol, disulfide, IMA IL-10, IFN-γ, and tail DNA percent parameters have statistically significant power (Table 5). We determined that our results agree with other publications analyzing the usability of thiol as a biomarker in assessing the severity of COVID-19 (Erel et al. 2021).

Our study has certain limitations. In this study, which was carried out in a single center, the relationship between oxidative stress, inflammation, and DNA damage parameters in patients with comorbidities such as diabetes, malignancy, and chronic kidney failure, the chronic obstructive pulmonary disease could not be studied due to the relatively small number of patients. In addition, the effects of drugs used in treating the disease (such as enoxaparin and favipiravir) on the level of oxidant and antioxidant enzymes and DNA are not apparent.

Conclusion

In our study, we aimed to determine whether the inflammation and the resulting oxidation products, depending on the degree of pneumonia, cause oxidative DNA damage in patients with COVID-19 disease and hospitalized in the intensive care unit. As a result, we found that increased inflammation and reactive oxygen species due to the increase in pneumonia increased in those with severe/critical pneumonia, which in turn damaged DNA. We think it would be helpful to follow up on the DNA damage in these patients regarding neurodegenerative diseases and cancer development.

Author contribution

All of the authors contributed to the design of the study, the collection of samples, the analysis, and the interpretation of data.

Data Availability

Data supporting the findings of this study are available upon reasonable request from the author.

Declarations

Ethical approval

This study was conducted by the Declaration of Helsinki and was approved by the Süleyman Demirel University, Faculty of Medicine Ethics Committee (Date 13 July 2021, No.: 235).

Informed consent

Written informed consent was obtained from all patients before they participated in the study.

Conflict of interest

The authors declare no competing interests.

Footnotes

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Akamatsu MA, de Castro JT, Takano CY, Ho PL. Off balance: interferons in COVID-19 lung infections. EBioMedicine. 2021;73:103642. doi: 10.1016/j.ebiom.2021.103642. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Aykac K, Ozsurekci Y, Yayla BCC, et al. Oxidant and antioxidant balance in patients with COVID-19. Pediatr Pulmonol. 2021;56:2803–2810. doi: 10.1002/ppul.25549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bar-Or D, Lau E, Winkler JV. A novel assay for cobalt-albumin binding and its potential as a marker for myocardial ischemia—a preliminary report. J Emerg Med. 2000;19:311–315. doi: 10.1016/S0736-4679(00)00255-9. [DOI] [PubMed] [Google Scholar]
  4. Bartsch H, Nair J. Oxidative stress and lipid peroxidation-derived DNA-lesions in inflammation driven carcinogenesis. Cancer Detect Prev. 2004;28:385–391. doi: 10.1016/j.cdp.2004.07.004. [DOI] [PubMed] [Google Scholar]
  5. Bolatkale M, Duger M, Ülfer G, et al. A novel biochemical marker for community-acquired pneumonia: ischemia-modified albumin. Am J Emerg Med. 2017;35:1121–1125. doi: 10.1016/j.ajem.2017.03.018. [DOI] [PubMed] [Google Scholar]
  6. Bonassi S, Ceppi M, Møller P, et al. DNA damage in circulating leukocytes measured with the comet assay may predict the risk of death. Sci Rep. 2021;11:1–11. doi: 10.1038/s41598-021-95976-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Çakırca G, Damar Çakırca T, Üstünel M et al (2021) Thiol level and total oxidant/antioxidant status in patients with COVID-19 infection. Irish J Med Sci 1–6 [DOI] [PMC free article] [PubMed]
  8. de Oliveira Gonçalves S, da Luz TM, Silva AM, et al. Can spike fragments of SARS-CoV-2 induce genomic instability and DNA damage in the guppy, Poecilia reticulate? An unexpected effect of the COVID-19 pandemic. Sci Total Environ. 2022;825:153988. doi: 10.1016/j.scitotenv.2022.153988. [DOI] [PMC free article] [PubMed] [Google Scholar] [Retracted]
  9. Delgado-Roche L, Mesta F. Oxidative stress as key player in severe acute respiratory syndrome coronavirus (SARS-CoV) infection. Arch Med Res. 2020;51:384–387. doi: 10.1016/j.arcmed.2020.04.019. [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Erel O, Neselioglu S. A novel and automated assay for thiol/disulphide homeostasis. Clin Biochem. 2014;47:326–332. doi: 10.1016/j.clinbiochem.2014.09.026. [DOI] [PubMed] [Google Scholar]
  11. Erel Ö, Neşelioğlu S, Tunçay ME, et al. A sensitive indicator for the severity of COVID-19: Thiol. Turkish J Med Sci. 2021;51:921–928. doi: 10.3906/sag-2011-139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Erol SA, Anuk AT, Tanaçan A, et al. An evaluation of maternal serum dynamic thiol-disulfide homeostasis and ischemia modified albumin changes in pregnant women with COVID-19. Turkish J Obstet Gynecol. 2022;19:21. doi: 10.4274/tjod.galenos.2022.72929. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Fidan AF. DNA hasar tespitinde tek hücre jel elektroforezi. Afyon Kocatepe Üniversitesi Fen Ve Mühendislik Bilim Derg. 2005;8:41–52. [Google Scholar]
  14. Guthrie GJK, Charles KA, Roxburgh CSD, et al. The systemic inflammation-based neutrophil–lymphocyte ratio: experience in patients with cancer. Crit Rev Oncol Hematol. 2013;88:218–230. doi: 10.1016/j.critrevonc.2013.03.010. [DOI] [PubMed] [Google Scholar]
  15. Han H, Ma Q, Li C, et al. Profiling serum cytokines in COVID-19 patients reveals IL-6 and IL-10 are disease severity predictors. Emerg Microbes Infect. 2020;9:1123–1130. doi: 10.1080/22221751.2020.1770129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506. doi: 10.1016/S0140-6736(20)30183-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Imtiaz F, Shafique K, Mirza SS, et al. Neutrophil lymphocyte ratio as a measure of systemic inflammation in prevalent chronic diseases in Asian population. Int Arch Med. 2012;5:1–6. doi: 10.1186/1755-7682-5-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Jimeno S, Ventura PS, Castellano JM, et al. Prognostic implications of neutrophil-lymphocyte ratio in COVID-19. Eur J Clin Invest. 2021;51:e13404. doi: 10.1111/eci.13404. [DOI] [PubMed] [Google Scholar]
  19. Khomich OA, Kochetkov SN, Bartosch B, Ivanov AV. Redox biology of respiratory viral infections. Viruses. 2018;10:392. doi: 10.3390/v10080392. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Lorente L, Martín MM, González-Rivero AF, et al. DNA and RNA oxidative damage and mortality of patients with COVID-19. Am J Med Sci. 2021;361:585–590. doi: 10.1016/j.amjms.2021.02.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Lu L, Zhang H, Dauphars DJ, He Y-W. A potential role of interleukin 10 in COVID-19 pathogenesis. Trends Immunol. 2021;42:3–5. doi: 10.1016/j.it.2020.10.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Mete AÖ, Koçak K, Saracaloglu A, et al. Effects of antiviral drug therapy on dynamic thiol/disulphide homeostasis and nitric oxide levels in COVID-19 patients. Eur J Pharmacol. 2021;907:174306. doi: 10.1016/j.ejphar.2021.174306. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Moriarty-Craige SE, Jones DP. Extracellular thiols and thiol/disulfide redox in metabolism. Annu Rev Nutr. 2004;24:481–509. doi: 10.1146/annurev.nutr.24.012003.132208. [DOI] [PubMed] [Google Scholar]
  24. Oe E, Erdoğan S. Thiol-disulfide homeostasis: an integrated approach with biochemical and clinical aspects. Turkish J Med Sci. 2020;50:1728–1738. doi: 10.3906/sag-2003-64. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Otal Y, Kahraman FA, Haydar FG, Erel Ö. Dynamic thiol/disulfide homeostasis as oxidative stress marker in diabetic ketoacidosis. Turkish J Med Sci. 2021;51:743–748. doi: 10.3906/sag-1904-55. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Pánico P, Ostrosky-Wegman P, Salazar AM (2022) The potential role of COVID-19 in the induction of DNA damage. Mutation Research/Reviews in Mutation Research 789,108411 [DOI] [PMC free article] [PubMed]
  27. Peng H, Jie J, Mortimer IP, et al. Reactivity and DNA damage by ındependently generated 2′-deoxycytidin-N 4-yl radical. J Am Chem Soc. 2021;143:14738–14747. doi: 10.1021/jacs.1c06425. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Renaudin X. Reactive oxygen species and DNA damage response in cancer. Int Rev Cell Mol Biol. 2021;364:139–161. doi: 10.1016/bs.ircmb.2021.04.001. [DOI] [PubMed] [Google Scholar]
  29. Republic of Turkey Ministry of Health (2020) COVID-19 (SARS-CoV-2 Enfeksiyonu) erişkin hasta tedavisi. https//covid19saglik gov tr/Eklenti/39061/0/covid-19rehberieriskinhastatedavisipdf pdf 22
  30. Rojas JM, Avia M, Martín V, Sevilla N. IL-10: a multifunctional cytokine in viral infections. J Immunol Res. 2017;1:1–14. doi: 10.1155/2017/6104054. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Sanders OD, Rajagopal L, Rajagopal JA. The oxidatively damaged DNA and amyloid-β oligomer hypothesis of Alzheimer’s disease. Free Radic Biol Med. 2022;179:403–412. doi: 10.1016/j.freeradbiomed.2021.08.019. [DOI] [PubMed] [Google Scholar]
  32. Sarzi-Puttini P, Giorgi V, Sirotti S, et al. COVID-19, cytokines and immunosuppression: what can we learn from severe acute respiratory syndrome? Clin Exp Rheumatol. 2020;38:337–342. doi: 10.55563/clinexprheumatol/xcdary. [DOI] [PubMed] [Google Scholar]
  33. Shi H, He L, Sun W et al (2020) Clinical characteristics and prognostic factors of 148 COVID-19 cases in a secondary epidemic area. Preprints the LANCET, Available SSRN 3572911
  34. Singh NP, McCoy MT, Tice RR, Schneider EL. A simple technique for quantitation of low levels of DNA damage in individual cells. Exp Cell Res. 1988;175:184–191. doi: 10.1016/0014-4827(88)90265-0. [DOI] [PubMed] [Google Scholar]
  35. Wan S, Yi Q, Fan S, et al. Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID-19) infected patients. Br J Haematol. 2020;189:428–437. doi: 10.1111/bjh.16659. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Wang F, Hou H, Luo Y, et al. The laboratory tests and host immunity of COVID-19 patients with different severity of illness. JCI Insight. 2020;5(10):1–11. doi: 10.1172/jci.insight.137799. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. World Health Organization (2020) Technical guidance–coronavirus disease (COVID-19). https://www.who.int/emergencies/diseases/novel-coronavirus-2019/technical-guidance/naming-thecoronavirus-disease-(covid-2019)-and-the-virus-that-causes-it
  38. Xu Z, Shi L, Wang Y, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med. 2020;8:420–422. doi: 10.1016/S2213-2600(20)30076-X. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Yildiz H, Alp HH, Ekin S, et al. Analysis of endogenous oxidative damage markers and association with pulmonary involvement severity in patients with SARS-CoV-2 pneumonia. Infect Dis Now. 2021;51:429–434. doi: 10.1016/j.idnow.2021.06.302. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Zhao Y, Qin L, Zhang P, et al. Longitudinal COVID-19 profiling associates IL-1RA and IL-10 with disease severity and RANTES with mild disease. JCI Insight. 2020;5(13):1–11. doi: 10.1172/jci.insight.139834. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Zhu Z, Cai T, Fan L, et al. Clinical value of immune-inflammatory parameters to assess the severity of coronavirus disease 2019. Int J Infect Dis. 2020;95:332–339. doi: 10.1016/j.ijid.2020.04.041. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

Data supporting the findings of this study are available upon reasonable request from the author.

Articles from Cell Stress & Chaperones are provided here courtesy of Elsevier

RESOURCES