Evaluation of the Levels of Selected Cytokines and Their Possible Influence on the Development of Cardiovascular and Pulmonary Complications in Patients after COVID-19
by
Anita Stanjek-Cichoracka
1,2,*, 
Jacek T. Niedziela
3,4,
Anna Łaszewska
2,
Zofia Mędrala
3,
Alicja Nowowiejska-Wiewióra
3,
Jacek Kaczmarski
5,
Alicja Grzanka
6 and
Mariusz Gąsior
3,4 1
Department of Biophysics, Faculty of Pharmaceutical Sciences in Sosnowiec, Medical University of Silesia in Katowice, Jedności 8, 41-200 Sosnowiec, Poland
2
Laboratory of Transplant Immunology, Silesian Centre for Heart Diseases, 41-800 Zabrze, Poland
3
3rd Department of Cardiology, Silesian Center for Heart Disease, 41-800 Zabrze, Poland
4
3rd Department of Cardiology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-752 Katowice, Poland
5
Department of Laboratory Diagnostics of Environmental and Civilization Diseases, Section of Coagulation Disorders, Silesian Center for Heart Disease, 41-800 Zabrze, Poland
6
Department of Allergology, Faculty of Medical Sciences in Zabrze, Medical University of Silesia, 40-752 Katowice, Poland
*
Author to whom correspondence should be addressed.
Medicina 2024, 60(3), 353; https://doi.org/10.3390/medicina60030353
Submission received: 18 January 2024
/
Revised: 11 February 2024
/
Accepted: 19 February 2024
/
Published: 21 February 2024
(This article belongs to the Section Genetics and Molecular Medicine)
Abstract
:Background and Objectives: The aim of this study was to evaluate the levels of selected cytokines and their possible influence on the development of cardiovascular and pulmonary complications in patients hospitalized at the Silesian Centre for Heart Disease in Zabrze after having undergone COVID-19. Materials and methods: The study included 76 randomly selected patients from the SILCOVID-19 database. The median time from symptom onset to the study visit was 102 (86–118) days. The median age of the study group was 53 (44–60) years. Assays of a panel of 30 cytokines were carried out in the serum of patients on a Luminex100 platform using the Milliplex MAP kit from Merck KGaA Germany. Results: There were no statistically significant differences in most of the cytokines analyzed between patients with confirmed or excluded lung lesions or cardiac abnormalities. Additionally, no statistically significant differences in cytokine concentrations according to gender, age, comorbidity of diabetes, renal disease, hypertension, increased risk of thrombotic disease, or psychological disorders were demonstrated. There were high concentrations of cytokines such as platelet-derived growth actor-AA (PDGF-AA), monocyte chemoattractant protein-1 (MCP-1), monokine-induced gamma interferon (MIG), and vascular endothelial growth factor-A (VEGF-A). Conclusions: No direct impact of the dependencies between a panel of cytokines and the incidence of cardiovascular and pulmonary complications in patients hospitalized at the Silesian Centre for Heart Disease in Zabrze after having undergone COVID-19 was demonstrated. The demonstration of high levels of certain cytokines (PDGF-AA, VEGF, MIG, and IP10) that are of significance in the development of many lung diseases, as well as cytokines (MCP-1) that influence the aetiopathogenesis of cardiovascular diseases seems to be highly concerning in COVID-19 survivors. This group of patients should receive further monitoring of these cytokine levels and diagnostic imaging in order to detect more severe abnormalities as early as possible and administer appropriate therapy.
1. Introduction
The COVID-19 pandemic, its aetiopathogenesis, the risk factors influencing the course of the disease, and the development of complications have been the subject of much research. This research includes the spectrum of clinical symptoms that appear in a given patient and its dependence on genetic factors, the proper functioning of the immune system, and the presence of comorbidities [1,2].
In the available literature, there are many papers on the evaluation of the profile of different cytokines in the acute phase of COVID-19. These studies have shown that inflammatory biomarker levels are elevated in patients with COVID-19 and that higher levels of inflammatory cytokines are consistently associated with a more severe disease course and poorer treatment outcomes. This data has sparked interest in the “cytokine storm” as a major factor influencing disease severity in COVID-19 [3,4].
Once the acute phase of the disease is over, some patients experience symptoms that may persist for months, referred to as long COVID. This condition affects the functioning of many organs, but its causes are not fully understood. Patients with symptomatic COVID-19 have an excessive inflammatory response in the acute phase, and this perhaps represents a potential cause, affecting immune cell function even after recovery [5].
“Long COVID” can be defined as the signs, symptoms, and sequelae that continue or develop after acute COVID-19 or SARS-CoV-2 infection for any period; they are generally multisystemic and might present with a relapsing–remitting pattern and a progression or worsening over time, with the possibility of severe and life-threatening events even months or years after infection [6].
In the long-term follow-up of post-COVID complications, the fibrotic lesions observed in the lungs appear to be of particular importance.
These processes appear to be closely related to the severity of the course of COVID-19, genetic and idiopathic factors, the presence of chronic diseases, age, and sex [7,8].
The available literature shows that “long COVID” also contributes to cardiovascular dysfunction, causing cardiac arrhythmias, thromboembolic disorders, myocarditis, and ischemic heart disease, among others. The risk of these diseases is increased in people with severe COVID-19 and those with comorbidities such as hypertension, kidney disease, obesity, hyperlipidemia, and diabetes [9].
Assessing the cytokine profile can also help in identifying markers of future health problems and EQQ, thus assisting in planning an appropriate treatment plan and preventing long-term health effects in patients after COVID-19.
The aim of this study was to evaluate the levels of selected cytokines and their possible influence on the development of cardiovascular and pulmonary complications in patients hospitalized at the Silesian Centre for Heart Disease in Zabrze after having undergone COVID-19.
2. Materials and Methods
This Silesian study on COVID-19 complications (SILCOV-19) was a prospective observational registry-based study focusing on the complications after COVID-19 in the Silesian population in Poland. Two hundred adult patients with confirmed symptomatic SARS-CoV-2 infection in the past were enrolled between June 2020 and March 2021 in the third department of Cardiology at the Silesian Centre for Heart Disease in Zabrze, the Faculty of Medical Sciences in Zabrze and the Medical University of Silesia in Katowice. The following inclusion criteria were used: (1) age of 18 years or more, (2) SARS-CoV-2 RNA confirmed via a polymerase chain reaction (PCR) in the acute phase of the disease, (3) the presence of the clinical symptoms associated with COVID-19 in the acute phase of the disease, and (4) two negative SARS-CoV-2 PCR test results following a seven-day period of quarantine after symptom regression. The exclusion criteria included a lack of patient’s informed consent. General information on the SILCOV-19 database was reported previously [10]. The study included 76 randomly selected patients from the SILCOV-19 database. The median age of the study group was 53 (44–60) years. The median time from symptom onset to the study visit was 102 (86–118) days.
From each patient, 2.7 mL of whole blood was collected into test tubes and centrifuged at 300 g for 10 min at 25 °C to separate the blood cells and serum. The serum obtained was frozen and stored at −80 °C. Portions of serum were thawed immediately before the analysis.
Assays of a panel of 30 cytokines were carried out on a Luminex100 platform using the Milliplex MAP Kit from Merck KGaA, Darmstadt, Germany.
The human cytokine/chemokine/growth factor panel A bead-based multiplex panel, using Luminex® xMAP technology (Luminex Corporation, Austin, TX, USA), enables the simultaneous analysis of multiple cytokines, chemokines, and growth factor biomarkers in human serum, plasma, and cell culture samples. This is an overnight or two-hour incubation assay. This assay requires 25 μL of neat plasma or serum or 25 μL of cell culture supernatant per well.
Luminex xMAP technology is one of the fastest growing and most respected multiplex technologies offering applications throughout the life sciences and capable of performing a variety of bioassays, including immunoassays on the surface of fluorescent-coded magnetic beads known as MagPlex-c microspheres [11].
The selected panel of cytokines allowed for the simultaneous determination of concentrations of 30 analytes: fibroblast growth factor 2 (FGF-2), granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon alpha-2 (IFN-α2), interferon gamma (IFN-γ), interleukin 1 beta (IL-1β), interleukin-1 receptor antagonist protein (IL-1ra), interleukin 2 (IL-2), interleukin 4 (IL-4), interleukin 5 (IL-5), interleukin 6 (IL-6), interleukin 7 (IL-7), interleukin 8 (IL-8), interleukin 9 (IL-9), interleukin 10 (IL-10), interleukin-12 subunit p40 (IL-12 (p40)), interleukin-12 subunit p 70 (IL-12 (p70)), interleukin 13 (IL-13), interleukin 15 (IL-15), interleukin 17E (IL-17E), also known as IL-25 (IL-17E/IL25), interleukin 17F (IL-17F), interleukin 18 (IL18), interferon gamma-induced protein 10 (IP-10), monocyte chemoattractant protein-1 (MCP-1), monokine-induced gamma interferon (MIG), macrophage inflammatory protein-1 alpha (MIP-1α), macrophage inflammatory protein-1alpha (MIP-1β), platelet-derived growth factor-AA (PDGF-AA), tumor necrosis factor alfa (TNF-α), and vascular endothelial growth factor-A (VEGF-A).
The local bioethical committee approved the study (approval No. 17/2020 dated 1 June 2020). The study was registered on ClinicalTrials.gov (NCT04453748, https://clinicaltrials.gov/ct2/show/NCT04453748, accessed on 8 June 2020). The study was performed under the patronage of the Polish Cardiac Society.
Statistical Analysis
The normality of the variables was evaluated using the Shapiro–Wilk test. All continuous variables had a non-normal distribution and were presented as a median (interquartile range [IQR]). The categorical variables were shown as percentages. The patients with normal (≤5 mg/dL) and elevated (>5 mg/dL) levels of high-sensitivity C-reactive protein (hsCRP) were compared using the nonparametric Mann–Whitney test for the continuous variables without a normal distribution, and the χ2 test for the categorical data with Yates correction if applicable. The statistical significance was defined as p < 0.05. All statistical analyses were performed using TIBCO Statistica v.13.3.0 (TIBCO Software Inc., Palo Alto, CA, USA)
3. Results
The data from the SILCOV database mentioned earlier was used for a complete analysis of the obtained results. The baseline characteristics are shown in Table 1.
The selected panel of cytokines allowed for the simultaneous determination of concentrations of 30 analytes. However, in further statistical analysis, those proteins whose concentrations were below the sensitivity of the method and the range of the lowest standard of the standard curve were omitted. The concentrations of the following cytokines were analyzed: fibroblast growth factor 2 (FGF-2), interleukin-1 receptor antagonist protein (IL-1ra), interleukin 5 (IL-5), interleukin 6 (IL-6), interleukin 8 (IL-8), interleukin 9 (IL-9), interleukin 10 (IL-10), interleukin-12 subunit p40 (IL-12 (p40)), interleukin 15 (IL-15), interleukin 18 (IL18), interferon gamma-induced protein 10 (IP-10), monocyte chemoattractant protein-1 (MCP-1), monokine-induced gamma interferon (MIG), macrophage inflammatory protein-1 beta (MIP-1β), platelet-derived growth factor-AA (PDGF-AA), tumor necrosis factor alfa (TNF-α), and vascular endothelial growth factor-A (VEGF-A).
The cytokine results for the entire study group are shown in Table 4.
No statistically significant differences in cytokine concentrations according to gender, age (above and below the median), comorbidity of diabetes, renal disease, hypertension, or an increased risk of thrombotic disease were demonstrated.
The study group was also divided according to the high-sensitivity C-reactive protein (hsCRP) results (≤5 mg/dL and >5 mg/dL). The results are shown in Table 5.
The only statistically significant finding was the lower concentration of interferon gamma-induced protein 10 (IP-10) in the group with elevated hsCRP values.
When analyzing the possible complications after COVID-19, the study group was divided according to the values of N-terminal pro-Btype natriuretic peptide (NTproBNP) concentrations (≤125 pg/mL and >125 pg/mL). The results are shown in Table 6.
Statistically significant lower levels of IL-8 and monocyte chemoattractant protein-1 (MCP-1) were found in the group with elevated NTproBNP levels.
In all the patients, left ventricular function was assessed via echocardiography using the global longitudinal strain (GLS) parameter.
The study group was divided according to GLS values ≤ 18 and >18 (Table 7).
Statistically significant higher levels of IL-18, monokine-induced gamma interferon (MIG), and vascular endothelial growth factor-A (VEGF-A) were found in the group of patients with abnormal GLS values.
All of the patients underwent high-resolution computed tomography (HRCT). The analysis of the HRCT results showed the appearance of lesions in lung imaging in 22 patients. In this group, the only statistically lower concentrations were those of macrophage inflammatory protein-1 beta (MIP-1b) and tumor necrosis factor-α human (TNF-α) (Table 8).
When analyzing the concentrations of pro-inflammatory cytokines associated with a “cytokine storm” (IL-1β, IL-1RA, IL-6, IL-8, IL-18, and TNF-a) and cytokines that inhibit these processes (IL-10 and IL-1RA) in both the whole group and the patient subdivisions shown above, no statistically significant differences in their concentrations were noted.
An important value of these studies is the demonstration of high concentrations of cytokines, such as PDGF -AA, MCP-1b, MIG, and VEGF-A, in the whole study group, which may be related to the possible development of further post-COVID complications.
4. Discussion
The so-called “cytokine storm” in the course of COVID-19 infection has been the subject of research conducted by many scientists around the world. It has become important to determine the cytokine profile in active infection.
According to the literature available, changes in cytokine concentrations (especially pro-inflammatory cytokines) relate to patients with confirmed SARS-CoV2 infection versus controls without that pathogen [12]. Some publications have confirmed that an appropriately selected cytokine profile can predict the development of acute respiratory distress syndrome (ARDS) or acute kidney injury [13].
However, studies by Wilson et al. showed that inflammatory cytokine levels were not significantly higher in patients with severe or moderate COVID-19 or critically ill patients with ARDS or sepsis [1].
Another focus of the study was an attempt to answer the question of how cytokines behave in patients after undergoing SARS-CoV-2 infection and whether they have an impact on the development of complications.
In the available literature, it is possible to find data showing that “long COVID” symptoms were reported by up to 80% of patients, irrespective of the severity of the disease, but were more common in patients who required hospitalization [14].
In a study by Santopaulo et al., patients with a severe course of COVID-19 reported a higher number of long-term symptoms, which, however, did not correlate with pro-inflammatory cytokines [15].
In contrast, Ruenjaiman et al. found that SARS-CoV-2 infection had a lasting effect on immunity at the cellular level as well as on cytokine production levels [16].
In our study, there were no statistically significant differences in most of the cytokines analyzed between the patients with confirmed or excluded lung lesions (based on HRCT) or cardiac function (GLS or NTproBNP testing).
In our study, the results of the cardiovascular tests did not reveal any severe complications. Only 18% of the study group had elevated NT BNP values and demonstrated GLS changes, which may indicate the development of heart failure.
On the basis of HRCT, it was shown that 28% of the studied patients had fibrotic lesions in their lungs.
Data on functional or radiological long-term complications are currently available in hospitalized individuals with COVID-19 pneumonia or SARS [17,18].
Additionally, no statistically significant differences in cytokine concentrations according to gender, age, comorbidity of diabetes, renal disease, hypertension, increased risk of thrombotic disease, or psychological disorders were demonstrated.
However, the demonstration of high concentrations of PDGF-AA, MCP-1b, MIG, and VEGF-A, among others, is highly concerning.
One of the chemokines that was assayed in the patients of the study group and whose levels were high was MCP-1 (with a median of 297.147 pg/mL). It is a monocyte chemotactic protein that plays a key role in the pathogenesis of cardiovascular diseases. MCP-1, through its chemotactic activity, induces the diapedesis of monocytes and macrophages from the blood vessel lumen into the subendothelium, where foam cells are formed, resulting in atherosclerotic plaque formation. Macrophages, on the other hand, are responsible for plaque instability, which can result in an ischemic episode or recurrent restenosis after angioplasty. There are many reports on the function of MCP-1 in ischemia/reperfusion or rejection of the transplanted heart [19,20,21].
There were no statistically significant differences between MCP-1 levels and GLS changes or high NTproBNP values, but consideration should be given to extending the cardiovascular diagnosis of patients in the study group.
Our own studies have shown high concentrations of PDGF-AA. The median concentration in the study group was 2968.137 pg/mL.
PDGF-AA is a dimorphic isoform of platelet-derived growth factor, which regulates cell differentiation and division. It also plays an important role in angiogenesis. It has an important function in the pathogenesis of fibrosis. These isoforms promote the proliferation and chemotaxis of myofibroblasts [22,23].
PDGF is also a well-recognized factor mediating airway inflammation and remodeling in asthma. PDGF stimulates airway smooth muscle cell (ASMC) proliferation and ASMC migration into the epithelium, as well as increased collagen synthesis in the lungs. Most studies on PDGF in asthma have not suggested that this factor is a possible biomarker of disease severity [24].
However, it is this growth factor that is thought to be one of the main contributors to airway remodeling.
The importance of this remodeling in asthma is well acknowledged, and new therapies should also aim to deal with it [25,26,27].
In the long term, PDGF-AA should be monitored in the study group and complemented by imaging and functional tests, e.g., spirometry.
Our studies also showed high concentrations of VEGF-A (with a median of 177.832 pg/mL), MIG (with a median of 372.420 pg/mL), and IP10 (with a median of 61.698 pg/mL) in the whole group.
Vascular endothelial growth factor (VEGF) is a pluripotent growth and permeability factor that has broad effects on endothelial cell function. This protein is also associated with angiogenesis but is often treated as a marker of cancer development. Lung tissue is very abundant in this protein. Many different lung cells produce VEGF and respond to it. VEGF is crucial for lung development and serves as a sustaining factor for lung function in adulthood. In addition to the physiological functions of this protein, there is growing evidence that VEGF also plays a role in several acute and chronic lung diseases, such as acute lung injury, severe pulmonary hypertension, and emphysema [28,29].
MIG, also known as C-X-C motif chemokine ligand 9 (CXCL9), is an inflammatory chemokine and a key component of the inflammatory response, attracting primarily T lymphocytes and NK cells. MIG has angiostatic properties, plays an important role in the inflammatory response, and performs functions that may contribute to lung carcinogenesis. The overexpression of MIG observed prior to the diagnosis of lung cancer may also reflect compensatory efforts on the part of the immune system to prevent ongoing pro-angiogenic changes in the tissue microenvironment [30,31,32,33].
Related to MIG is also IP-10. IP-10 is an important mediator of the recruitment of activated lymphocytes to the lungs in lung diseases and is involved in the response to mycobacterium tuberculosis, among others. Data in the literature suggests that IP-10 is a potential marker for lung diseases. IP10 is recognized as a biomarker of human rhinovirus infection in COPD exacerbation, and the importance of this interleukin in pulmonary fibrosis is being investigated [26].
In their study, Tamayo-Velasco et al. further demonstrated the usefulness of IP-10 as an excellent marker in clinical practice for the diagnosis of COVID-19 in the hospital setting. According to these researchers, IP-10 can be used as a complementary tool in clinical practice, especially in emergency departments [12].
It seems that an appropriately selected panel of cytokines could provide a useful predictive tool to assess the occurrence of possible complications after COVID-19.
5. Conclusions
No direct impact of the dependencies between a panel of cytokines and the incidence of cardiovascular and pulmonary complications in patients hospitalized at the Silesian Centre for Heart Disease in Zabrze after having undergone COVID-19 was demonstrated. The demonstration of high levels of certain cytokines (PDGF-AA, VEGF, MIG, and IP10) that are of significance in the development of many lung diseases, as well as cytokines (MCP-1) that influence the aetiopathogenesis of cardiovascular diseases seems to be highly concerning in COVID-19 survivors. This group of patients should receive further monitoring of these cytokine levels and diagnostic imaging in order to detect more severe abnormalities as early as possible and administer appropriate therapy.
Author Contributions
Conceptualization, A.S.-C., M.G., A.G. and J.T.N.; Methodology, A.S.-C. and A.Ł.; Formal analysis, A.S.-C. and J.T.N.; Investigation, A.S.-C. and A.Ł. Data curation, Z.M., A.N.-W. and J.K.; Writing—original draft preparation, A.S.-C.; Writing—review and editing, A.S-C. and J.T.N.; Supervision, M.G. and A.G.; Project administration, A.S-C. and J.T.N.; Funding acquisition, M.G., A.G. and J.T.N. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Medical University of Silesia, grant number PCN-1-222/N/2/K.
Institutional Review Board Statement
The study was conducted in accordance with the Declaration of Helsinki. The local bioethical committee approved the study (approval No. 17/2020 dated 1 June 2020). The study was registered on ClinicalTrials.gov (NCT04453748).
Informed Consent Statement
Informed consent was obtained from all the subjects involved in the study.
Data Availability Statement
The data presented in this study are available upon request from the corresponding author.
Conflicts of Interest
The authors declare no conflicts of interest.
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Table 1.
Baseline characteristics of the study group.
| Medical History, Diseases before COVID-19 | |
|---|---|
| Hypertension, n (%) | 28 (36.8) |
| Hyperlipidemia, n (%) | 22 (28.9) |
| Diabetes mellitus, n (%) | 13 (17.1) |
| Smoking, n (%) | 10 (13.2) |
| Coronary artery disease, n (%) | 7 (9.2) |
| Percutaneous coronary intervention, n (%) | 5 (6.6) |
| Myocardial infarction, n (%) | 4 (5.3) |
| Asthma/COPD, n (%) | 1 (1.3) |
| Chronic kidney disease, n (%) | 1 (1.3) |
| Stroke, n (%) | 1 (1.3) |
Abbreviations: COPD, chronic obstructive pulmonary disease.
Table 2.
Results of selected hematological and coagulological laboratory tests in the study group.
| Parameters | N | Median | Q1 | Q3 |
|---|---|---|---|---|
| White blood cells [103/mm3] N:4.3–10 | 76 | 6.1500 | 5.1400 | 7.5100 |
| Neutrophils [103/mm3] N:2.9–4.1 | 76 | 3.7650 | 2.9150 | 4.5250 |
| Lymphocytes [103/mm3] N:1.7–2.8 | 76 | 1.6900 | 1.4050 | 2.2700 |
| Monocytes [103/mm3] N:0.2–0.8 | 76 | 0.4900 | 0.4000 | 0.5500 |
| Eozynofiles [103/mm3] N:0.2–0.4 | 76 | 0.1000 | 0.0500 | 0.1600 |
| Basophils [103/mm3] N:0–0.1 | 76 | 0.0400 | 0.0250 | 0.0600 |
| Red blood cells [106/mm3] N:4.5–5.9 | 76 | 4.6050 | 4.3900 | 4.9250 |
| Hemoglobin [mmol/L] N:8.7–11.2 | 76 | 8.6000 | 8.2000 | 9.1000 |
| Hematocrit [L/L] N:41–53 | 76 | 41.0000 | 39.0000 | 43.0500 |
| Platelets [103/mm3] N:150–350 | 76 | 250.0000 | 211.0000 | 275.5000 |
| Fibrinogen [mg/dL] N:200–400 | 76 | 327.5000 | 285.0000 | 375.5000 |
| D-Dimer [ug/mL] N:0–0.5 | 76 | 0.3000 | 0.2700 | 0.3900 |
Table 3.
Results of selected biochemical laboratory tests in the study group.
| Parameters | N | Median | Q1 | Q3 |
|---|---|---|---|---|
| GGTP [U/l] N:5–61 | 76 | 23.0000 | 17.0000 | 36.5000 |
| AST [U/l] N:10–34 | 76 | 21.0000 | 19.0000 | 25.0000 |
| ALT[U/l] N:6–44 | 76 | 22.0000 | 16.5000 | 31.5000 |
| ALP [U/l] (N:40–129) | 76 | 65.0000 | 57.5000 | 76.0000 |
| Bilirubin [µmoL/L] | 76 | 10.4500 | 7.8000 | 12.8500 |
| Creatinine [mg/dL] | 76 | 0.8371 | 0.7014 | 0.9615 |
| GFR [mL/min × 1.73 m2] | 76 | 113.2665 | 87.7913 | 136.3501 |
| Uric acid [mmol/L] | 76 | 332.0000 | 281.0000 | 395.5000 |
| Total protein in serum [g/L] | 76 | 72.0000 | 69.5000 | 76.0000 |
| Albumin [g/L] | 76 | 47.0000 | 46.0000 | 49.0000 |
| HbA1c [%] | 76 | 5.5000 | 5.2500 | 5.9000 |
| Total cholesterol [mmol/L] | 76 | 5.3350 | 4.3900 | 6.1050 |
| Triglycerides [mmol/L] | 76 | 1.3900 | 0.8750 | 1.9100 |
| HDL-chlesterol [mmol/L] | 76 | 1.5600 | 1.2050 | 1.7950 |
| LDL-cholesterol [mmol/L] | 76 | 3.4950 | 2.6200 | 4.3900 |
| hs CRP [mg/dL] | 76 | 2.3600 | 0.4800 | 5.1900 |
| NT-proBNP [pg/mL] | 76 | 66.8300 | 37.2650 | 110.6000 |
| CK [U/l]] (N:24–193) | 76 | 105.5000 | 85.5000 | 163.0000 |
| CK-MB [ng/mL] (N:0.3–4.87) | 76 | 2.0600 | 1.6950 | 2.7300 |
| Troponin T hs [ng/mL] (pg/mL) (N < 0.014) | 76 | 6.0000 | 4.0000 | 8.0000 |
| LDH [U/l] (N:135–225) | 76 | 185.5000 | 165.0000 | 211.5000 |
| Pancreatic amylase [U/l] (N:15–53) | 76 | 25.0000 | 19.0000 | 32.0000 |
| Ferritin [ng/mL] N:30–400 | 76 | 97.0000 | 55.5000 | 156.0000 |
| Lactates | 70 | 1.4850 | 1.2500 | 2.0000 |
Abbreviations: alanine aminotransferase (ALT), alkaline phosphatase (ALP), aspartate aminotransferase (AST), creatine phosphokinase (CK), creatine kinase myocardial band (CK-MB), gamma-glutamyl transpeptidase (GGTP), glomerular filtration rate (GFR), hemoglobin A 1c (HbA1c), high-sensitivity C-reactive protein (hs CRP), lactate dehydrogenase (LDH), N-terminal pro–B-type natriuretic peptide (NT-proBNP).
Table 4.
Concentrations of the cytokines analyzed for the entire study group.
| Median [pg/mL] | Q1 | Q3 | |
|---|---|---|---|
| FGF-2 | 44.215 | 25.600 | 94.637 |
| IL-1RA | 3.611 | 1.854 | 4.772 |
| IL-5 | 0.602 | 0.335 | 0.858 |
| IL-6 | 0.640 | 0.507 | 1.363 |
| IL-8 | 6.099 | 4.359 | 8.733 |
| IL-9 | 2.315 | 1.268 | 3.915 |
| IL-10 | 2.793 | 1.481 | 3.821 |
| IL-12 (p40) | 18.637 | 9.198 | 24.900 |
| IL-15 | 5.758 | 4.077 | 6.826 |
| IL-18 | 9.343 | 5.934 | 13.375 |
| IP-10 | 61.698 | 49.170 | 88.491 |
| MCP-1 | 297.147 | 224.013 | 387.643 |
| MIG | 372.420 | 294.823 | 618.893 |
| MIP-1b | 23.820 | 17.378 | 35.380 |
| PDGF-AA | 2968.137 | 2313.470 | 3546.726 |
| TNF a | 8.005 | 5.401 | 12.343 |
| VEGF-A | 177.832 | 116.289 | 281.695 |
Table 5.
Cytokine concentrations in patient groups in relation to the hsCRP values.
| hsCRP ≤ 5 n = 23 | hsCRP > 5 n = 53 | ||||||
|---|---|---|---|---|---|---|---|
| Median [pg/mL] | Q1 | Q3 | Median [pg/mL] | Q1 | Q3 | p | |
| FGF-2 | 44.215 | 25.600 | 100.272 | 62.047 | 25.600 | 89.001 | 0.817 |
| IL-1RA | 3.611 | 1.854 | 5.437 | 3.364 | 1.600 | 4.102 | 0.216 |
| IL-5 | 0.514 | 0.242 | 0.773 | 0.640 | 0.426 | 1.270 | 0.113 |
| IL-6 | 0.770 | 0.552 | 1.446 | 0.640 | 0.418 | 1.027 | 0.100 |
| IL-8 | 5.898 | 4.257 | 7.604 | 6.298 | 4.749 | 9.829 | 0.309 |
| IL-9 | 2.221 | 1.387 | 3.915 | 2.944 | 1.148 | 4.366 | 0.557 |
| IL-10 | 2.909 | 1.481 | 3.821 | 2.443 | 1.481 | 3.595 | 0.360 |
| IL-12 (p40) | 18.637 | 9.198 | 26.922 | 14.127 | 9.198 | 18.637 | 0.214 |
| IL-15 | 5.758 | 4.077 | 7.348 | 5.210 | 4.077 | 6.297 | 0.112 |
| IL-18 | 9.168 | 5.860 | 11.140 | 11.256 | 6.508 | 16.601 | 0.218 |
| IP-10 | 66.072 | 55.094 | 96.447 | 53.658 | 39.555 | 70.131 | 0.009 |
| MCP-1 | 289.025 | 230.827 | 358.730 | 312.395 | 217.318 | 427.562 | 0.627 |
| MIG | 405.711 | 294.231 | 639.089 | 347.579 | 295.414 | 550.366 | 0.203 |
| MIP-1b | 23.820 | 19.300 | 33.724 | 22.810 | 14.284 | 40.249 | 0.549 |
| PDGF-AA | 3066.426 | 2277.874 | 3607.844 | 2856.383 | 2407.816 | 3487.384 | 0.483 |
| TNF-a | 8.005 | 5.401 | 11.736 | 8.639 | 5.401 | 12.343 | 0.923 |
| VEGF-A | 179.501 | 126.740 | 280.661 | 170.798 | 94.738 | 283.023 | 0.557 |
Table 6.
Cytokine results in patient groups according to NTproBNP levels.
| NTproBNP ≤ 125 pg/mL N = 62 | NTproBNP > 125 pg/mL N = 14 | ||||||
|---|---|---|---|---|---|---|---|
| Median [pg/mL] | Q1 | Q3 | Median [pg/mL] | Q1 | Q3 | p | |
| FGF-2 | 44.215 | 25.600 | 89.001 | 69.260 | 25.600 | 129.368 | 0.312 |
| IL-1RA | 3.611 | 1.854 | 4.590 | 2.866 | 1.600 | 5.798 | 0.936 |
| IL-5 | 0.602 | 0.426 | 1.107 | 0.514 | 0.242 | 0.688 | 0.359 |
| IL-6 | 0.683 | 0.507 | 1.446 | 0.640 | 0.596 | 0.942 | 0.995 |
| IL-8 | 6.369 | 4.692 | 9.015 | 4.372 | 3.470 | 5.870 | 0.006 |
| IL-9 | 2.592 | 1.387 | 4.366 | 1.823 | 0.640 | 2.592 | 0.094 |
| IL-10 | 2.909 | 1.481 | 3.821 | 2.502 | 1.481 | 3.821 | 0.825 |
| IL-12 (p40) | 16.422 | 9.198 | 26.922 | 18.637 | 9.198 | 20.785 | 0.979 |
| IL-15 | 5.758 | 4.077 | 7.088 | 5.348 | 4.077 | 6.826 | 0.391 |
| IL-18 | 9.154 | 6.008 | 12.929 | 9.604 | 5.477 | 16.486 | 0.989 |
| IP-10 | 61.698 | 52.453 | 85.662 | 58.772 | 38.340 | 92.832 | 0.384 |
| MCP-1 | 309.132 | 238.170 | 414.637 | 223.139 | 179.357 | 301.860 | 0.003 |
| MIG | 399.644 | 295.414 | 629.511 | 356.657 | 200.168 | 550.366 | 0.414 |
| MIP-1b | 24.191 | 19.157 | 36.614 | 19.317 | 14.284 | 27.608 | 0.053 |
| PDGF-AA | 3047.761 | 2425.039 | 3571.481 | 2479.284 | 2064.795 | 3487.384 | 0.152 |
| TNF-a | 8.005 | 5.401 | 12.343 | 7.685 | 5.401 | 16.504 | 0.920 |
| VEGF-A | 179.356 | 115.127 | 283.023 | 171.379 | 130.220 | 275.055 | 0.693 |
Table 7.
Cytokine concentrations in patients in relation to the GLS values.
| NTproBNP ≤ 125 pg/mL N = 62 | NTproBNP > 125 pg/mL N = 14 | ||||||
|---|---|---|---|---|---|---|---|
| Median [pg/mL] | Q1 | Q3 | Median [pg/mL] | Q1 | Q3 | p | |
| FGF-2 | 44.215 | 25.600 | 89.001 | 69.260 | 25.600 | 129.368 | 0.312 |
| IL-1RA | 3.611 | 1.854 | 4.590 | 2.866 | 1.600 | 5.798 | 0.936 |
| IL-5 | 0.602 | 0.426 | 1.107 | 0.514 | 0.242 | 0.688 | 0.359 |
| IL-6 | 0.683 | 0.507 | 1.446 | 0.640 | 0.596 | 0.942 | 0.995 |
| IL-8 | 6.369 | 4.692 | 9.015 | 4.372 | 3.470 | 5.870 | 0.006 |
| IL-9 | 2.592 | 1.387 | 4.366 | 1.823 | 0.640 | 2.592 | 0.094 |
| IL-10 | 2.909 | 1.481 | 3.821 | 2.502 | 1.481 | 3.821 | 0.825 |
| IL-12 (p40) | 16.422 | 9.198 | 26.922 | 18.637 | 9.198 | 20.785 | 0.979 |
| IL-15 | 5.758 | 4.077 | 7.088 | 5.348 | 4.077 | 6.826 | 0.391 |
| IL-18 | 9.154 | 6.008 | 12.929 | 9.604 | 5.477 | 16.486 | 0.989 |
| IP-10 | 61.698 | 52.453 | 85.662 | 58.772 | 38.340 | 92.832 | 0.384 |
| MCP-1 | 309.132 | 238.170 | 414.637 | 223.139 | 179.357 | 301.860 | 0.003 |
| MIG | 399.644 | 295.414 | 629.511 | 356.657 | 200.168 | 550.366 | 0.414 |
| MIP-1b | 24.191 | 19.157 | 36.614 | 19.317 | 14.284 | 27.608 | 0.053 |
| PDGF-AA | 3047.761 | 2425.039 | 3571.481 | 2479.284 | 2064.795 | 3487.384 | 0.152 |
| TNF-a | 8.005 | 5.401 | 12.343 | 7.685 | 5.401 | 16.504 | 0.920 |
| VEGF-A | 179.356 | 115.127 | 283.023 | 171.379 | 130.220 | 275.055 | 0.693 |
Table 8.
Cytokine concentrations in the patient groups in relation to the HRCT results.
| No Change in HRCT N = 53 | Changes in HRCT N = 22 | ||||||
|---|---|---|---|---|---|---|---|
| Median [pg/mL] | Q1 | Q3 | Median [pg/mL] | Q1 | Q3 | p | |
| FGF-2 | 44.215 | 25.600 | 89.001 | 65.100 | 25.600 | 100.272 | 0.740 |
| IL-1RA | 3.364 | 1.854 | 4.590 | 3.611 | 1.854 | 4.954 | 0.889 |
| IL-5 | 0.602 | 0.335 | 1.107 | 0.621 | 0.426 | 0.773 | 0.958 |
| IL-6 | 0.640 | 0.507 | 1.363 | 0.662 | 0.507 | 1.446 | 0.917 |
| IL-8 | 6.127 | 4.634 | 8.902 | 6.084 | 3.937 | 7.378 | 0.701 |
| IL-9 | 2.221 | 1.148 | 3.603 | 3.194 | 1.387 | 5.354 | 0.314 |
| IL-10 | 2.560 | 1.481 | 3.821 | 2.909 | 2.560 | 5.590 | 0.164 |
| IL-12 (p40) | 16.422 | 9.198 | 22.877 | 18.637 | 6.400 | 22.877 | 0.816 |
| IL-15 | 5.758 | 4.077 | 6.826 | 5.758 | 3.784 | 6.826 | 0.749 |
| IL-18 | 9.517 | 6.067 | 14.539 | 9.343 | 6.008 | 10.735 | 0.456 |
| IP-10 | 62.496 | 52.483 | 85.662 | 60.284 | 48.106 | 92.524 | 0.820 |
| MCP-1 | 305.242 | 238.170 | 412.309 | 271.486 | 191.706 | 355.065 | 0.093 |
| MIG | 429.751 | 303.664 | 614.843 | 356.374 | 252.034 | 835.108 | 0.545 |
| MIP-1b | 25.522 | 19.300 | 37.912 | 22.211 | 14.284 | 25.044 | 0.038 |
| PDGF-AA | 2913.182 | 2253.703 | 3419.289 | 3392.182 | 2652.544 | 3747.071 | 0.161 |
| TNS-a | 8.639 | 6.064 | 12.343 | 6.718 | 4.044 | 9.268 | 0.029 |
| VEGF-A | 179.210 | 124.564 | 278.890 | 152.030 | 106.111 | 401.978 | 0.848 |
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Stanjek-Cichoracka, A.; Niedziela, J.T.; Łaszewska, A.; Mędrala, Z.; Nowowiejska-Wiewióra, A.; Kaczmarski, J.; Grzanka, A.; Gąsior, M. Evaluation of the Levels of Selected Cytokines and Their Possible Influence on the Development of Cardiovascular and Pulmonary Complications in Patients after COVID-19. Medicina 2024, 60, 353. https://doi.org/10.3390/medicina60030353
AMA Style
Stanjek-Cichoracka A, Niedziela JT, Łaszewska A, Mędrala Z, Nowowiejska-Wiewióra A, Kaczmarski J, Grzanka A, Gąsior M. Evaluation of the Levels of Selected Cytokines and Their Possible Influence on the Development of Cardiovascular and Pulmonary Complications in Patients after COVID-19. Medicina. 2024; 60(3):353. https://doi.org/10.3390/medicina60030353
Chicago/Turabian StyleStanjek-Cichoracka, Anita, Jacek T. Niedziela, Anna Łaszewska, Zofia Mędrala, Alicja Nowowiejska-Wiewióra, Jacek Kaczmarski, Alicja Grzanka, and Mariusz Gąsior. 2024. "Evaluation of the Levels of Selected Cytokines and Their Possible Influence on the Development of Cardiovascular and Pulmonary Complications in Patients after COVID-19" Medicina 60, no. 3: 353. https://doi.org/10.3390/medicina60030353
