Relation of ICAM-1 and VCAM-1 markers in COVID-19 patients in Kirkuk province

Abstract

BACKGROUND:

The advent of the Coronavirus Disease 2019 (COVID-19) has presented a substantial and urgent global public health issue. Biomarkers have the potential to be utilized for the identification of endothelium and/or alveolar epithelial damage in instances of COVID-19 infection.

AIM OF THE STUDY:

to evaluate the levels of Intercellular adhesion molecule-1 (ICAM-1) and Vascular cell adhesion molecule (VCAM-1) biomarkers in hospitalized patients who tested positive for COVID-19 infection using Polymerase Chain Reaction (PCR) with the virus specific Immunoglobulins; IgM, and IgG testing. This can help with improved clinical management and treatment programs.

METHODS:

A case-control study that involved 90 hospitalized patients who tested positive for COVID-19 and 40 apparently healthy control patients, subjects in both groups underwent nasopharyngeal swabs for PCR and blood sample collection for evaluation of serum; IgM, IgG, ICAM-1 and VCAM-1 levels.

RESULTS:

Males made up the vast majority of the patients (78.9%), with only a minor percentage of females (21.1%) $P$ value 0.1641. Furthermore, every patient in this study had a minimum of one risk factor for COVID-19. The investigator’s results show that COVID-19 patients had higher amounts of endothelial cell adhesion indicators (ICAM-1 and VCAM-1) with mean values of 126.27 $\pm$ 89.51 ng/mL and 109.74 $\pm$ 96.57 ng/mL respectively. While, ICAM-1 and VCAM-1, were present at normal levels in the control group with difference $P$ value 0.0028 and 0.0032 in comparison to the patient’s group respectively.

CONCLUSIONS:

The adhesive markers ICAM and VCAM play a crucial role in the development of COVID-19 and the strong endothelial activation and dysfunction linked to both acute and persistent immunological responses is shown by the substantial correlation found in COVID-19 patients between the presence of IgM and IgG antibodies and higher levels of ICAM-1 and VCAM-1.

Keywords

COVID-19 RS-CoV-2 IgM/IgG antibody ICAM-1 VCAM-1

1. Introduction

The COVID-19 virus has emerged as a prominent viral pathogen in contemporary times, disseminating among communities from the onset of 2020 and is identified as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [1]. This transmission and the disease is of importance particularly among older individuals and those with underlying medical disorders, such as chronic diseases, diabetes, High blood pressure, severe pneumonia, cancer, and chronic renal inflammation [2]. The SARS-CoV-2 virus can induce acute respiratory distress syndrome, commonly known as COVID-19 ARDS, that might require mechanical ventilation to alleviate the respiratory distress with an increased chance of mortality [3].

The coronaviruses are grouped in the Nidovirales order, specifically in the Coronaviridae family [4]. Coronaviruses are physically small, with dimensions ranging from 65–125 nm [5]. They are encoded by a single-stranded RNA molecule, which typically measures 26–32 kilobases in length [6]. Bats serve as reservoir hosts for several zoonotic viruses, including a newly formed recombinant SARS-like coronavirus that shares significant genetic similarities with both SARS-CoV as well as SARS-CoV-2 [7]. The growing number of “super variants” poses a substantial threat to the health of individuals worldwide [8]. According to in vitro experiments, it has been observed that this genetically modified virus can engage with the human ACE2 receptor, suggesting a higher likelihood of it posing an elevated risk of emergence [9].

Previous studies have observed a higher presence of vascular and inflammatory elements, Vascular cell adhesion molecule (VCAM-1), interleukin (IL)-8, and monocyte-chemoattractant protein (MCP-1) in lung tissue affected by COVID-19 [4]. Both Intercellular adhesion molecule-1 (ICAM-1) and Vascular cell adhesion molecule (VCAM-1) are members of the immunoglobulin superfamily of Cell Adhesion Molecules (CAM), which plays an important role in both acute and chronic illnesses by facilitating the robust attachment of white blood cells to the cells lining of blood vessels (endothelial cells) [10]. During inflammation, ICAM-1 and VCAM-1 facilitate the process and enhance leukocyte proliferation [10]. The endothelial injury is associated with an induction of ICAM-1 and VCAM-1 expression, which could be useful as a biomarker for monitoring an individual’s rate of healing or assessing the severity of an illness [11].

SARS-CoV-2 can enter endothelial cells which result in the virus replication and alterations to blood vessels with activation of the endothelium which causes a rise in the formation of clots in both small and major blood arteries [8].

The bronchial endothelium is a tightly regulated organ that carries out several functions in both healthy and diseased states [10]. The cell adhesion molecules described above aid in the transfer of inflammatory cells to the lung and can be produced when certain cytokine circumstances are present [12]. Severe COVID-19 patients have been linked to a phenomenon called “cytokine storm,” which refers to an excessive presence of pro-inflammatory cytokines [13].

This study aimed to evaluate the concentrations of endothelial biomarkers ICAM-1 and VCAM-1 in the bloodstream of patients suffering from COVID-19 and to evaluate their influence on the disease’s prognosis.

2. Methodology

2.1 Study setting and population

A case-control study involved 90 COVID-19 cases and 40 healthy subjects, the patients were having variable degrees of COVID-19 symptoms with some of them being admitted to the Intensive Care Unit (ICU) at Kirkuk Teaching Hospital in Kirkuk province, Iraq, between December 2021 and December 2022. All participants provided informed consent form prior commencing the study.

During a comparable period length, the control group were tested negative for COVID-19 by PCR. To guarantee comparability, key demographic factors including age and gender were used to match the cases and controls.

2.2 Laboratory work

2.2.1 PCR extraction and real-time PCR

Nucleic acid from nasal swab was extracted using viral genomic extraction kit (DNA/RNA viral extraction kit, Zybio^®, China) utilizing EXM3000^® semi-automated machine (Zybio^®, China) in line with the manufacturer’s recommendations.

Viral genomic detection was performed according to manufacturer’s instructions (Zybio SARS-CoV-2 Nucleic Acid Detection Kit). One step viral amplification was performed in SaCycler-96 Real-time PCR Detection System (Sacace^®, Italy) with the 2019-nCoV Real-time PCR kit (Sacace Biotechnologies^® Ltd, Italy). We applied the following thermo-cycling condition; cDNA synthesis at 37^∘C for min., 0^∘C for 5 mins., 95^∘C for 2 mins., 95^∘C for 5 seconds, and 60^∘C for 30 seconds for 45 cycles.

2.2.2 COVID-19 immunological and adhesion markers

Five milliliters of blood was extracted from every participant, samples were separated by serum and then quickly frozen at $-$ 70^∘C for further analysis.

The COVID-19 serum IgG/IgM level were measurred by the Mini-vidas^® equipment (Biomeriux^®, France) using its costume kits.

The meaurment of serum ICAM-1 and VCAM-1 was done by ELISA kits (LABISKOMA^®, Korea) according to the manufacturer’s protocols.

2.2.3 Statistical analysis

The statistical analysis was performed utilizing Graph Pad Prism version 10.1. The comparison was performed using the Chi-square (X2) test and $t$ Test was applied as required to compare between groups with Probability ( $P$ value), less than 0.05 was considered to be statistically significant (S), while a $P$ value less than 0.01 was categorized as highly significant (H.S.), a $P$ value more than 0.05 was considered Non Significant (N.S).

The term “sensitivity” was operationally defined as the ratio of patients correctly recognized as having either current or prior SARS-CoV-2 infections, out of the total number of patients first diagnosed using real-time PCR in respiratory samples. The term “specificity” was operationally defined as the ratio of persons who tested negative for SARS-CoV-2 infection to the total number of individuals in the population.

3. Results

3.1 Sociodemographic characteristics of the study population

The gender distribution among the patients, together with other sociodemographic variables obtained from the research are be shown in Tables 1–3. Among the 90 patients, 71 (78.9%) were male and 19 (21.1%) were female The numerical details are shown in Table 1. According to the present investigation, 34 out of 90 patients, which corresponds to 37.78% of the total, fell within the age range of 41 to 50 years. In contrast, the age group consisting of individuals under 20 years old had the smallest proportion of patients, accounting for 11.54% (15 out of 90 patients) as detailed in Table 2.

Concerning the distribution of residences, it was observed that the majority of COVID-19 patients, accounting for 65.56%, were residing in urban areas, as indicated in Table 2, with $P$ value (0.43).

3.2 Clinicopathological characteristics of the study population

Based on the concept of comorbidity, the findings of this study indicate that all individuals diagnosed with COVID-19 had at least one underlying risk factor. Among these patients, 52 individuals (57.78%) were identified as having obesity, 22 individuals (24.44%) had diabetes mellitus, 17 individuals (18.89%) had hypertension, and 12 individuals (13.33%) presented with cardiovascular illnesses, as seen in Table 4.

Table 1
Gender distribution in COVID-19 study groups

Distribution of	Patients		Control		$P$ value
gender	No.	%	No.	%
Male	71	78.9	27	67.5	0.1641
Female	19	21.1	13	32.5
Total	90	100	40	100

Table 2

Distribution of study group according to age

Age/years	COVID-19 +ve (No.)	%	COVID-19 -ve (No.)	%	P value
$<$ 20	4	4.44	11	27.50	0.0013
21–30	12	13.33	7	17.50
31–40	16	17.78	8	20.00
41–50	34	37.78	7	17.50
$>$ 50	24	26.67	7	17.50
Total	90	100	40	100

Table 3

Distribution of residence in the study groups

Distribution of	Patients		Control		$P$ value
residency	No.	%	No.	%
Urban	59	65.56	29	72.50	0.43
Rural	31	34.44	11	27.50
Total	90	100	40	100

Table 4

Comorbidity factors in the study group

Comorbidity	Patients		Control
	No.	%	No.	%
Diabetes	22	24.44	0	0
Hypertension	17	18.89	0	0
Cardiovascular diseases	12	13.33	0	0
Obesity	52	57.78	0	0
Total (130)	90		40

4. Laboratory results

4.1 Molecular diagnosis of COVID-19

Regarding molecular detection of COVID-19, Real time PCR was applied to detect the presence of the viral genome in the nasal swabs. The kit utelizes specifically designed primers and probe to amplify OPFa1b region in the COVID-19 genome on FAM channel (Fig. 1-A) as well as an internal control on HEX channel to assess the quality of the extraction and amplification process (Fig. 1-B). Non template control (NTC) was included and no amplication occured wich shows that our samples are free of contamination as depicted in Fig. 1A and B. We can see that the viral load was different among the examined samples.

4.2 Concordance between PCR and immunological results in patients

The findings of this study indicate a significant correlation ( $P$ value $=$ 0.0391) betwen the patients with molcular diagnosis with COVID-19, 54.44% (49 out of 90) and the presence of COVID-19 IgM antibodies. While only 18.89% (17 out of 90) individual’s COVID-19 IgG antibody test yielded a positive PCR result. PCR positive was seen in 26.67% (24 out of 90) who tested positive for both COVID-19 IgM and IgG antibodies. In the control group, a total of 7 out of 40 patients (17.50%) tested positive for COVID-19 IgG, as indicated in Table 5.

Table 5
Comparison of IgM-IgG antibodies with a PCR results test in the study group

COVID-19 markers	COVID-19 patients (90)		Control (40)
	PCR positive	%	PCR negative	%
COVID IgM +ve	49	54.44	0	0.00
COVID IgG +ve	17	18.89	7	17.50
COVID IgM +IgG+	24	26.67	0	0.00
Total	90	100.00	40	100.00
$P$ value	0.0391

5. Adhesion molecules level in the study population

According to the findings presented in Table 6 individuals diagnosed with COVID-19 had siginficantly higher serum level of ICAM-1 and VCAM-1; 126.27 $\pm$ 89.51 and 109.74 $\pm$ 96.57, respectively in compersion with the healthy group ( $P$ value $=$ 0.0028, 0.0032) sequntially. Indeed the control group had normal levels of endothelial cell adhesion markers as detailed in Table 6.

Table 6
Comparison of markers of endothelial and epithelial dysfunction between patients with COVID-19 and control

Biomarker, Unit	COVID-19 $n=$ (90)		Control $n=$ (40)		$P$ value
	Mean	SD	Mean	SD
ICAM-1, ng/mL	126.27	89.51	22.43	16.94	0.0028
VCAM-1, ng/mL	109.74	96.57	31.82	19.27	0.0032

6. Discussion

Individuals diagnosed with COVID-19 may experience severe outcomes as a result of immune system malfunction linked to heightened cytokine storm [13].

Figure 1.

RT-PCR technique amplification of target gene with Log graph type, represents (A). HEX channel (internal control), and (B). FAM channel (target gene ORFa1b).

The majority of severe cases were attributed to the excessive activation of cytokine storm, leading to the progression of acute lung damage and subsequent acute respiratory distress syndrome (ARDS) [14]. The concept of age is crucial in comprehending variations in morbidity [15]. Age serves as an indicator of the progressive accrual of enduring harm during an individual’s lifespan, hence exhibiting a strong correlation with the prevalence of chronic ailments and impairments [15]. Dowd et al., utilized the age-specific case-fatality rates of COVID-19 derived from Italy and applied them to populations who are comparatively younger and less healthy [16]. While, another study revealed that the highest percentage of age was between 20 and 30 years old, with mean ages were (25.2 $\pm$ 5.7) and (51%) were male [17].

According to gender distribution, our data illustrated that males were more affected than females, that agree with study in Kirkuk province who concluded that the infection in men are more, especially those over the age of 61 years of them and those who have other comorbidities such as high blood pressure, heart diseases and diabetes [18].

The variation in the data regarding to gender could be due to the X chromosome as well as sex hormones, which are important in innate and adaptive immunity [19]. Also, men showed a high level of angiotensin converting enzyme 2 (ACE 2) receptors, which can increase the likelihood of infection and mortality rates [20]. Also, it is attributed to the fact that males have more associated disorders like diabetes, hypertension which could negatively impact the immune status of the individuals which is directly or indirectly influence the viral-load and the ability of the immune system to control or clear the virus [21].

Our study findings indicate that a significant majority of COVID-19 patients, namely 65.56%, were living in urban areas. This aligns with a previous study that indicated that biggest number of patients, 56.2%, were inhabitants of the Kirkuk districts and sub-districts [18].

A positive association was observed between the number of persons residing in a single home and the likelihood of COVID-19 transmission within the family [22]. Additionally, a recent study conducted by researchers indicated that a significant proportion of patients (58.6%) were residing in the city center of Basrah [23]. This finding aligns with the current study’s observations. The geographical distribution of cases, however, cannot be defined appropriately given such a tiny number of cases [24]. According to Akinseind et al., there is a positive and substantial association between urban living, insurance coverage, and COVID-19 mortality [25]. This may potentially contribute to the enhancement of pandemic preparedness in the face of future waves of COVID-19 or other outbreaks of infectious diseases.

According to comorbidity factors, diabetes causes a decline in the immune system of affected individuals, resulting in symptoms such as fever, dry cough, tiredness, and runny nose, which are commonly associated with viral respiratory infections. Nevertheless, the presence of muscular discomfort, sore throat, nausea, vomiting, and diarrhea might potentially suggest a more distinct illness [26].

Our study showed a significant relationship between the presence of COVID-19 and the following comorbidities: obesity (57.78%), diabetes (24.44% hypertension (18.89%) and cardiovascular diseases (13.33%). Different research indicates that the simultaneous existence of diabetes, hypertension, obesity, and smoking among persons diagnosed with COVID-19 is linked to 8%, 7%, 11%, and 2% of overall mortality cases, respectively [27].

According to a recent meta-analysis, individuals diagnosed with COVID-19 who also had pre-existing conditions such as cardiovascular disease, cerebrovascular accident, and chronic renal disease had a higher incidence of death [28]. The presence of obesity is linked to chronic, low-level inflammation throughout the body, which significantly contributes to the development and progression of respiratory disorders. Individuals who received a diagnosis of COVID-19 and have underlying obesity may experience an amplified inflammatory response, perhaps resulting in an excessive inflammatory reaction [29]. There were no statistically significant distinctions seen in terms of age, smoking habits, cardiovascular disease, or autoimmune illness between patients and control individuals [30].

In our work, the frequency of different antibodies varied significantly ( $P$ value of 0.0391); none of the control participants tested positive for COVID IgM antibodies while 54.44% of COVID-19 patients did. There was considerable overlap in the presence of COVID IgG antibodies, which were found in 18.89% of COVID-19 patients and 17.50% in the control group. Furthermore, compared to none of the controls, 26.67% of COVID-19 patients had positive results for both IgM and IgG antibodies. It was interesting to find that all patients who are clinically and immunologically confirmed COVID-19 had positive PCR while it was negative in all the control making it 100% sensitive and specific test.

Numerous studies have provided evidence regarding the diagnostic efficacy of antibody testing in detecting COVID-19 infection. These studies have also concluded that asymptomatic patients, while hospitalized, have consistently low serum levels of SARS-CoV-2 specific IgM/IgG antibodies. Elevated levels of IgM may potentially have significance in the identification of individuals who have experienced recurrent good outcomes before their discharg [31]. However, a recent investigation has discovered that the IgM-IgG test has high accuracy and sensitivity as a diagnostic approach [32]. Utilizing a dual method of nucleic acid and IgM-IgG testing offers a heightened level of sensitivity and accuracy in the diagnosis and timely management of COVID-19 [33]. Hoffman et al., evaluated the specificity of the PCR test on a sample size of 14 individuals who tested negative for COVID-19. The results noted the specificity of both IgM and IgG antibodies was found to be 100%. Additionally, the sensitivity of the test was assessed on COVID-19 cases, resulting in an estimated sensitivity of 87.9% for IgM and 97.2% for IgG [34].

Our finding revealed that, in comparison to controls, COVID-19 patients had substantially higher levels of ICAM-1 and VCAM-1 indicating that these markers may be useful as indicators of the severity and course of the illness. We have thoroughly reviewed the recent publications by Li et al., and Tong et al. [30, 35], which investigates the levels of endothelial cell adhesion molecules in individuals affected by COVID-19. The study revealed that those with mild disease had elevated levels of VCAM-1, ICAM-1, and PECAM-1. Three unforeseen findings were uncovered in the most recent research. First, VCAM-1 and ICAM-1 levels showed higher prevalence in individuals with COVID-19 [3]. Additionally, COVID-19 severity is correlated with levels of several blood biomarkers such as C-reactive protein, IL-18, TNF-a, INF- $\gamma$ , VCAM-1, ICAM-1, and VAP-1. In addition, after recovering from severe COVID-19, individuals showed lower levels of these markers [30]. The development of severe cases of COVID-19 has been linked to the activation of endothelial cells. Antiphospholipid antibodies, factor VIII, and von Willebrand factor may all play a part in the development of coagulopathy in these cases, according to strong evidence [36, 37]. Also, Turner et al., discovered that endothelial cells may produce ACE2, a receptor for SARS-CoV-2, a pathogen responsible for inducing severe acute respiratory syndrome [38]. Next, researchers will look at whether SARS-CoV-2 and ACE2 interact in a way that affects endothelium activation [36]. The development of blood clot formation (thrombosis) can be affected by changes in substances that promote or inhibit clotting owing to the activation of defective cells lining the blood vessels by pro-inflammatory signaling molecules [30, 39].

7. Conclusion

Patients infected with COVID-19 has promenet changes in the immune response and there was a definite association between the immunological markers; ICAM-1 and VCAM-1 with the COVID-19 in the studied population.

Footnotes

Ethical approval

The study protocol, subject information, and consent form were reviewed and authorized by the local ethics committee in accordance with document number 45256, which contains the date of 28/12/2021.

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Relation of ICAM-1 and VCAM-1 markers in COVID-19 patients in Kirkuk province

Abstract

BACKGROUND:

AIM OF THE STUDY:

METHODS:

RESULTS:

CONCLUSIONS:

Keywords

1. Introduction

2. Methodology

2.1 Study setting and population

2.2 Laboratory work

2.2.1 PCR extraction and real-time PCR

2.2.2 COVID-19 immunological and adhesion markers

2.2.3 Statistical analysis

3. Results

3.1 Sociodemographic characteristics of the study population

3.2 Clinicopathological characteristics of the study population

Table 1 Gender distribution in COVID-19 study groups

4.1 Molecular diagnosis of COVID-19

4.2 Concordance between PCR and immunological results in patients

Table 5 Comparison of IgM-IgG antibodies with a PCR results test in the study group

Table 6 Comparison of markers of endothelial and epithelial dysfunction between patients with COVID-19 and control

Footnotes

Ethical approval

References

Table 1
Gender distribution in COVID-19 study groups

Table 5
Comparison of IgM-IgG antibodies with a PCR results test in the study group

Table 6
Comparison of markers of endothelial and epithelial dysfunction between patients with COVID-19 and control