T-Cell Immune Responses and Immunological Factors Associated with Coronavirus Disease 2019 Progression as Predictors for the Severity of the Disease in Hospitalized Patients

Coronavirus disease 2019 (COVID-19) is an emergent public health problem globally caused by SARS-CoV-2, a virus widely known for excessive mutagenic ability, epidemiological rapid growth, and high capacity to infect hosts from different species [1, 2]. COVID-19 exhibits a wide range of clinical manifestations, and in terms of severity, it varies from an asymptomatic course of infection to severe respiratory failure, ultimately needing an intensive care unit (ICU) [3]. The disease severity and its outcome are associated with many factors including age, gender, obesity, and underlying medical conditions (e.g., cancer, immunodeficiency, diabetes, hypertension, and cardiovascular disease) [4].

Studies have reported infected epithelial cells with SARA-CoV-2 by secretion of inflammatory cytokines like IL-8 can recruit and activate both innate and adaptive immune cells to start the antiviral responses [5]. Basically, in antiviral responses, the adaptive immune system polarizes T-cell differentiation to the Th1 and Th17 populations to neutralize the infection by expressing IFN-γ, TNF-α, IL-22, and IL-17 [6]. Additionally, the Th2 population by coordination of humoral responses via producing IL-4 and IL-6 has a role in the clearance of infection [7]. In contrast, in such conditions, Treg cells have key roles in the maintenance of immune hemostasis by producing TGF-β and IL-10 [8].

Moreover, recent studies have shown uncontrolled and exacerbated antiviral responses can enhance the recruitment of neutrophils, monocytes, and other immune cells which leads to the creation of cytokine storms by overproduction of IFN-γ, TNF-α, GM-CSF, MCP-1, IL-6, IL-2, and IL-8 [6]. The cytokine storm is a major life-threatening condition associated with COVID-19 [9]. These features highlighted the magnitude of the effect of immunological response, particularly T helper cell responses in the determination of the severity and outcome of the disease.

We carried out this experiment due to contradictory results obtained from recent studies on immunological responses against SARA-CoV-2 and also the lack of a proper classification of patients. The present study has aimed to investigate the role of T helper polarizations in the severity of COVID-19 as well as the correlation between T helper polarizations and laboratory indicators and its association with the outcome of the disease in hospitalized patients with COVID-19.

In this study, the 79 hospitalized patients suffering from COVID-19 (67 non-ICU hospitalized and 12 ICU hospitalized) were recruited from Kosar Hospital, Semnan, Iran, from 7 April to 3 May 2021. All enrolled patients were confirmed positive for COVID-19 by the combination of checking clinical symptoms and RT-PCR. A group of healthy individuals (n = 20) was enrolled as the control group.

The inclusion criteria for enrolling patients were laboratory and clinical evaluation for confirming positive COVID-19 and being over 18 years old. Additionally, patients with a history of cancer and infectious disease including hepatitis, HIV, and brucellosis were excluded from this experiment. Moreover, healthy participants were all over 18 years old, had no underlying medical conditions and infectious diseases. Of note, all patients and healthy individuals were not vaccinated for COVID-19.

The present study aimed to describe differences in demographics, clinical presentation, and immunological factors between the severe and critical spectrum of COVID-19 severity as well as comparison with healthy subjects. Consequently, patients were divided into severe and critical groups. Patients who exhibited more severe weakness, persistent pressure in the chest, the onset of confusion or altered level of consciousness, needed a ventilator machine and intensive critical care were placed in the critical group (n = 12). Patients who showed shortness of breath, respiratory rate ≥30 beats/min, and progression of lung lesions ≥50% were placed in the severe group [10]. Informed written consent was obtained from all participants, and the Ethical Committee of the Semnan University of Medical Science approved the study (IR.SEMUMS.REC.1399. 8). The clinical characteristics and laboratory findings were shown in Table 1, and also, comorbidities and symptoms were provided in Table 2.

In order to indicate laboratory data and PBMC isolation, 10 mL peripheral blood samples were taken from all subjects on the first day of hospitalization. The Ficoll-Hypaque density method was used to isolate PBMCs from whole blood. First, the PBS-diluted blood samples were laid over the Ficoll-Hypaque (Histosep, Iran) and centrifuged for 30 min, 400g at RT. Subsequently, the supernatants were taken out; then the mononuclear cells were transported to another tube and finally washed twice using PBS (300 g, 10 min, RT).

In order to assess the relative expression of genes of interest, total RNA isolation from PBMCs was performed using BIOzol reagent (Stem Cell Technology Research Center, Iran) according to instructions provided by the manufacturer. The quality and quantity of purified RNA were determined by gel electrophoresis and NanoDrop spectrophotometer, respectively. All purified RNA samples were reserved at −80° C until further use for cDNA synthesis and real-time PCR. Afterward, 1 µg of RNA from each sample was reverse transcribed to cDNA using a cDNA synthesis kit (Parstous, Iran). SYBR green master mix (Parstous, Iran) and specific primers were used to perform real-time PCR. 40 cycles of PCR were carried out on a real-time PCR detection system (Applied Biosystems, USA). Briefly, reaction mixture contained 10 µL 2× SYBR green master mix, 0.4 µL 50×ROX dye, 0.35 µL specific forward primer, 0.35 µL specific reverse primer, and 8 µL DEPC water for each well; at last, 1 µL of cDNA was added to 19 µL of the reaction mixture, giving a final volume of 20 µL. Subsequently, the PCR tube was placed in the real-time PCR detection system and went through a cycling program as follows: one cycle of denaturation at 94°C for 10 min followed by 40 cycles of amplification at 95°C for 15 s, specific annealing temperature for 30 s and 72°C for 60 s. The level of gene expression was normalized to the housekeeping gene (GAPDH), and the comparative threshold cycle (ΔΔCT) method was used to interpret the results.

All data were expressed as the number (%) and mean ± SEM. Data comparison was conducted between groups using independent t test, Mann-Whitney test, and the one-way ANOVA for multiple comparisons. Categorical variables were expressed as numbers (%) and compared using the χ² test. Furthermore, the correlations between different variables were tested by Spearman’s correlation analysis. Additionally, the odds ratio was used to express the relative measure of an effect between a binary outcome variable and a predictor variable. Also, multivariate analysis was performed using logistic regression model. Data analysis was performed with StepOne Software v2.1, Prism 8.0.2 (GraphPad v7, USA), and SPSS (SPSS, v22, USA). The p value of less than 0.05 was considered to be statistically significant.

Our study comprised 79 hospitalized COVID-19 patients (37 males, 42 females) who were divided into severe and critical groups, along with 20 healthy subjects as the control group. The severe group consisted of 31 male and 36 female patients with a mean age of 55 ± 16 years, while the critical group consisted of 6 male and 6 female patients with a mean age of 70 ± 15.5 years. The intergroup comparison showed that subjects in the severe group were notably younger than those who were in the critical group (p < 0.05). The control group included 11 male and 9 female participants with a mean age of 61.8 ± 12.0 which had no differences in terms of age compared with both critical and severe groups. Additionally, there were no significant differences in the time from symptom onset to hospitalization between the severe and critical groups (3.34 ± 1.3 days and 2.91 ± 1.7 days, respectively). It was noted that participants in the control group did not have any underlying medical issues or comorbidities. In addition, as shown in Table 2, patients in the severe and critical groups were similar in having comorbidities such as hypertension, diabetes, cardiovascular disease, asthma, and chronic kidney disease. Moreover, the rate of obesity was significantly higher in the critical group compared to the severe group (p < 0.01). Hypertension (38.8% severe, 50% critical cases), coronary heart disease (23.8% severe, 33.3% critical cases), and diabetes (28.8% severe, 16.6% critical cases) were the most common comorbid conditions. In terms of symptoms, as shown in Table 2, the percentage of patients who experienced hemoptysis, sweating, and shortness of breath in the critical group was dramatically higher than that in the severe group. On the contrary, other symptoms such as fever, headache, and fatigue were more common in the severe group.

The laboratory findings of all participants in our study were analyzed upon admission. We observed that many laboratory results were significantly different between participating groups. In comparison with patients in the severe group, critical subjects had a higher level of CRP, AST, ALT, ALP, ESR, an increase in counts of neutrophils and platelets, and a lower count of lymphocytes. Moreover, as shown in Table 1, both hospitalized groups had a significant decrease in the level of oxygen, a lower percentage of lymphocytes, and a notable increase in neutrophil percentage, hepatic enzymes, and CRP level compared to the control group. The intergroup comparison showed that there were no differences in the percentage of monocytes, level of hemoglobin, BUN, creatinine, and body temperature between participating groups (Table 1).

We evaluated the expression of transcription factors related to the differentiation of Th1, Th2, Th17, and Treg populations in PBMCs from all participants at the time of admission. T-bet expression, the key regulator of Th1 population development, was notably increased in critical and severe groups compared to the control group (p < 0.001, p < 0.05, respectively). There were no significant differences in T-bet expression between the severe and critical groups (Fig. 1a). It was further noted that the relative expression of FoxP3, the master regulator of Treg cell differentiation, was significantly decreased in the critical subjects in comparison with the severe and control groups (p < 0.05, p < 0.0001, respectively), while there were no differences between the severe and control groups (Fig. 1b). In terms of expression of RORγt and GATA3, Th17 and Th2 differentiation factors, RORγt was expressed at a significantly higher rate in the critical group compared to the severe and control groups (p < 0.05, p < 0.0001, respectively). Also, patients who had critical conditions showed upregulation in GATA3 expression compared to the severe and control groups (p < 0.05, p < 0.0001, respectively). Additionally, the expressions of RORγt and GATA3 were notably higher in the severe group compared to healthy subjects (p < 0.05, p < 0.001, respectively) (Fig. 1c, d).

To investigate the impact of expression of transcription factors related to the differentiation of Th1, Th2, Th17, and Treg populations on the hepatic enzymes and CRP levels in all participating subjects, the Pearson correlation coefficient was performed. As shown in Table 3, the results revealed that GATA3 expression showed a significant positive correlation with AST, ALP, ESR, and CRP levels. Likewise, the T-bet expression showed a positive correlation with the ALP level. Also, a positive correlation was observed between RORγt expression and CRP and ALT levels. Regarding O₂ saturation levels, RORγt, T-bet, and GATA3 expression levels demonstrated a negative correlation with it; however, FoxP3 showed a positive correlation with the O₂ saturation level. Taken together, the results showed that GATA3 expression was the most efficient variable that affected liver damage, inflammation, and O₂ level in blood which made this factor the most determinative factor affecting the outcome of the disease.

The univariate logistic regression analysis showed that the severity of COVID-19 (whether patients needed critical care or not) was associated with GATA3 (OR = 9.09, p < 0.05), lymphocyte counts (OR = 0.74, p < 0.01), and RORγt (OR = 3.63, p < 0.05). The multivariate logistic regression analysis, after adjusting potential factors including GATA3, RORγt, and lymphocyte counts, indicated that RORγt (OR = 10.32, p < 0.05) and GATA3 (OR = 50.15, p < 0.05) were the independent risk factors for progression of the disease. In contrast, lymphocyte count (OR = 0.72, p < 0.05) was the independent protective factor against disease progression (Table 4).

Due to an increase in the incidence of COVID-19, a heavy burden is imposed on medical sources. More investigations are necessary for the identification of the exact pathogenic mechanisms as well as the immunological factors that significantly affect the progression of the disease [11]. Epidemiological studies have reported that patients with underlying medical issues including hypertension, cardiovascular disease, diabetes, cancer, obesity, and immunodeficiencies showed a higher risk of developing severe and critical forms of COVID-19 [4, 12].

In the present study, we noticed that participants in the critical group were significantly older than patients in the severe group. Furthermore, the rate of obesity was higher in the critical group compared to the severe group. On the other hand, the critical and severe groups were similar in having comorbidities. It has been shown that age and underlying medical issues can affect the outcome of COVID-19 through immune responses. Indeed, these factors were associated with high levels of pro-inflammatory mediators and reactive oxygen species that resulted in development of uncontrolled immune responses, tissue injuries, and impaired viral clearance, contributing to the poor prognosis of the disease in the elderly [13, 14]. Moreover, the localized inflammatory responses in the adipose tissue led to the production of leptin and the reduction of adiponectin resulted in an increase in the systemic level of TNF-α and IL-6. These factors caused systemic inflammation and affect the severity of COVID-19 [15].

Multiple studies have demonstrated that COVID-19 may cause varying degrees of liver injury, particularly in critical cases [16]. These experiments indicated that hepatic enzymes including ALT and AST in critically ill patients were dramatically higher than those in the general ward [17, 18]. We observed similar results: the levels of ALT, AST, and ALP were higher in the critical group compared to the severe subject and these enzymes were elevated in both hospitalized groups in comparison to the healthy subject which were the signs of liver injury. The possible mechanisms of this damage to the liver might be the direct viral invasion of hepatocytes through ACE2r that expresses on the healthy hepatocytes, immune-mediated injury caused by cytokine storm, or underlying liver conditions like alcohol-related liver disease [19, 20].

Our results showed that the CRP level, neutrophil-lymphocyte ratio (NLR), platelet and neutrophil counts were notably higher in the critical group compared to the severe subjects as well as in both hospitalized subjects compared to the control group. Consistently, Feng and colleagues reported that inflammatory mediators such as IL-6, CRP, LDH, and NLR were significantly elevated in patients with COVID-19, leading to worsening of the disease, and they can also be useful predictors for the prognosis of the COVID-19 infection [21]. It has been shown that excessive inflammatory responses induced by neutrophils led to the creation of cytokine storms which have been implicated in COVID-19. Furthermore, the presence of NLR was associated with a more severe form of the disease [22].

T-cell responses have a prominent role in immunity against COVID-19 as well as the progression of this disease. Interestingly, evidence on COVID-19 has shown that dysfunction or excessive immune response can contribute to the creation of cytokine storms, leading to rising in inflammatory mediators including IL-6, IL-8, MIP-1A, GM-CSF, and IFN-γ which caused massive damage to the respiratory system and tissue to break down [7, 23, 24].

Studies have reported that Th1 responses play a crucial role in cell-mediated immunity against intracellular pathogens [25]. Our results demonstrated that T-bet relative expression was increased in both hospitalized groups compared to the control group. Thereby, it can be concluded that this type of response could augment inflammation by overproduction of IFN-γ in severe and critical forms of COVID-19. Consistent with this result, Berejo-Martin et al. [26] found that in subjects with the severe form of COVID-19, T-bet, IFN-γ, and Th1 populations were significantly increased. The study conducted by Lin and colleagues reported that cytokines like IFN-γ, IL-12, IL-2, and TNF-α were notably raised in patients with COVID-19 compared to healthy subjects [27]. It has been suggested that SARS-CoV-2 could induce polyclonal Th1 responses that led to uncontrolled immune responses and cytokine storms [28].

In the present investigation, we found that GATA3 and RORγt expressions were dramatically increased in the severe and critical groups in comparison with the control group. In addition, expressions of these two factors were significantly elevated in the critical patients compared to the severe group. It has been suggested that the Th2 responses might be triggered by excessive Th1 and Th17 responses [28]. It has been reported that Th2 responses can trigger bronchoconstriction and dyspnea by producing a large number of cationic protein cytokines like IL-6, a key mediator for causing cytokine storms, in critical forms of COVID-19 [29]. Furthermore, Roncati and colleagues [30] demonstrated evidence that Th2 responses could lead to type 3 hypersensitivity taking place inside the vascular walls which is life-threatening. In consistence with our research, Khoshmirsafa and colleagues demonstrated that the gene expressions of RORγt, IFNγ, IL-17, and T-bet were higher in patients with COVID-19 compared to healthy individuals. Khoshmirsafa et al. [31] also showed that RORγt, IL-6, and IL-17 gene expressions in the severe group were higher than in the moderate group, which supported our findings. Multiple studies have indicated that the population of Th17 cells was dramatically increased in COVID-19 patients; this population by production of IL-23 and IL-17 caused enhanced neutrophil migration to the airways, which resulted in edema, pneumonia, and serious respiratory damage in severe and critical patients with COVID-19 [7, 23].

We presented evidence that FoxP3 expression was significantly reduced in the critical group compared to the severe and control groups, although no significant differences were observed between the severe and critical groups. Consistently, Sadeghi et al. [32] reported that the Treg population, FoxP3 expression, TGF-β and IL-10 production were notably reduced in patients with COVID-19. Multiple studies have also shown Treg cell percentage and their suppressive activity were significantly decreased in SARS-CoV-2 patients [33]. It has been suggested that TNF-α and IL-6 could reduce suppressive activity in Tregs by preventing of TGF-β and FoxP3 expression [34, 35].

In the present study, we found that GATA3 and RORγt expressions were positively correlated with CRP concentration in SARS-CoV-2 patients. Recent studies showed that patients with elevated CRP levels were more likely to have critical illness and worst clinical outcomes [36, 37]. Furthermore, we observed that there was a positive correlation between GATA3 expression and levels of hepatic enzymes including AST, ALP, and ESR; also, we found that T-bet and RORγt had a positive correlation with ALT and ALP, respectively. It has been demonstrated that acute liver injury, as manifested by the elevated level of hepatic enzymes, was associated with severity and poor prognosis of COVID-19 [18]. Based on these results, elevation in the expression of T-bet, RORγt, and GATA3 could be associated with acute liver injury and poor prognosis of COVID-19.

Additionally, we indicated that lymphocyte percentage, RORγt, and GATA3 relative expression levels were independent predictors for the severity and outcome of COVID-19. It has been reported that lymphopenia, which could be a consequence of pulmonary recruitment and entrapment of lymphocytes or even infection of lymphocytes with SARS-CoV-2 via dipeptidyl peptidase-4 (DPP-4) receptor, was associated with poor prognosis of COVID-19 [38]. Additionally, Khoshmirsafa and colleagues found that IL-17, IL-6, and IL-10 were the risk factors for the progression of the disease [31]. In addition, Th2 and Th17 hyperactivation due to polyclonal activation possibly with superantigens led to high antibody titers and the creation of cytokine storms [34, 38]. On the basis of these findings, lymphopenia and high expression of RORγt and GATA3 could be independent risk factors associated with COVID-19 severity. Consequently, based on the results obtained from the present study besides studies by other researchers in the field of COVID-19, it can be implied whether elevation in Th1, Th2, and Th17 responses or a decrease in Treg counts lead to uncontrolled inflammatory responses, severity, and poor prognosis of COVID-19.

To summarize, we provided evidence that supported the role of excessive and inappropriate T-cell responses in the pathogenesis of COVID-19. Such uncontrolled immune responses were strongly associated with the critical form of illness, serious tissue damage, and organ failure. Given the limitation of the present study, further research is needed to clarify T-cells dynamic in patients during the infection period as well as the memory phase. Analysis of antigen-specific T-cell infiltrate and immune checkpoint molecules involved in T-cell responses against SARS-CoV-2 will provide extensive information and reveal novel opportunities for anticipating and treating COVID-19.

The study complied with the guidelines for human studies and was conducted in accordance with the World Medical Association Declaration of Helsinki. The study protocol was approved by the Ethical Board of the Semnan University of Medical Sciences (IR.SEMUMS.REC.1399. 8). Written informed consent to participate in the study and publication of their clinical details was obtained from all participants.

The authors wish to thank Kosar Hospital and Cancer Research Center of the Semnan University of Medical Sciences for its editorial assistance.

The authors have no conflicts of interest to declare.

This work was supported by a grant from the Semnan University of Medical Sciences (No. 2370).

Rasoul Baharlou conceived and Farhad Malek planned the experiments. Tannaz Abbasi-Dokht and Arefe Vafaeinezhad carried out the experiments. Tannaz Abbasi-Dokht wrote the manuscript. Negin Khalesi contributed to sample preparation. Tannaz Abbasi-Dokht, Rasoul Baharlou, and Dariush Haghmorad contributed to the interpretation of the results. All authors provided critical feedback and helped shape the research, analysis, and the manuscript.

All data generated or analyzed during this study are included in this article. Further inquiries can be directed to the corresponding author.

Edited by: H.-U. Simon, Bern.