Comparison of T cells mediated immunity and side effects of mRNA vaccine and conventional COVID-19 vaccines administrated in Jordan

ABSTRACT

Various COVID-19 vaccines can affect the immune system. Discrepancies have been noted in immune system characteristics, such as T-lymphocyte levels, between vaccinated and non-vaccinated individuals. This study investigates the variations in immune responses among the four administered COVID-19 vaccines, influencing factors, and clinical outcomes in Jordan. A total of 350 adults, who were at least two doses vaccinated, were interviewed and blood samples were collected for subsequent laboratory analyses. The study involved the quantification of T-cells specifically targeting anti-SARS CoV-2 using Flow cytometry analysis. BNT162b2 (Pfizer) recipients displayed significantly higher CD3⁺/CD4⁺ T-helper cell responses (90.84%, 87.46% – 94.22%) compared to non-Pfizer-BioNTech recipients {BBIBP-CorV (Sinopharm) and Sputnik V (Gamaleya Research Institute), then ChAdOx1 nCoV-19 (AstraZeneca)} (83.62%, 77.91% − 89.33%). The CD3⁺/CD8⁺ (T cytotoxic) level was notably elevated in non-Pfizer-BioNTech recipients {Sinopharm and Sputnik V then ChAdOx1 nCoV-19 AstraZeneca (73.94%, 69.38% − 78.49%) compared to BNT162b2 (Pfizer) recipients (58.26%, 53.07% − 63.44%). The CD3⁺ (T-cells) level showed no significant difference between BNT162b2 recipients (73.74%) and non-Pfizer-BioNTech recipients (77.83%), with both types generating T-cells. Comparing two doses of non-Pfizer-BioNTech vaccines with the third dose of BNT162b2 recipients (Pfizer), no difference in the type of immune reaction was observed, with non-Pfizer-BioNTech recipients still stimulating endogenous pathways like cell-mediated cytotoxic effects for cells. All COVID-19 vaccines administered in Jordan were effective, with respect to the total number of T cells. Non-Pfizer-BioNTech had higher in toxic T-cells and Pfizer-BioNTech was higher in helper T-cells that stimulate plasma cells to produce antibodies.

KEYWORDS:

• COVID-19 vaccines
• Jordan
• T-cells
• flow cytometry analysis

Introduction

Since late 2019, COVID-19, a member of the Coronaviridae family, known as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has significantly impacted the world.¹ Declared a pandemic by the World Health Organization on March 11, 2020, it prompted urgent global efforts for a solution, resulting in the development of vaccines. As of June 14, 2023, the WHO reported 767,984,989 confirmed COVID-19 cases, 6,943,390 deaths, and 13,397,153,690 vaccine doses administered.² Preventive measures include mask-wearing, social distancing, hand hygiene, and vaccination.³ Initially, a SARS-CoV-2 vaccine was not expected within 18 months, but due to the rapid spread, various vaccines were developed globally. Approved vaccines, starting from June 24, 2020, in China to January 3, 2021, in the UK.^4,5 By August 19, 2022, Jordan recorded 1,731,549 positive cases 14,105 deaths, and 45,538,733 individuals fully vaccinated.⁶ The ongoing approval and utilization of various vaccine brands, as endorsed by the Jordan Food and Drug Administration in February 2021, demonstrate global collaborative efforts in combatting the pandemic.⁷

The effect of vaccines at the immunological level can be measured by the cellular and humoral body responses. Such effects happen in cascades starting from the vaccine releasing the main compound of the virus (S spike and nucleocapsid proteins) to the host cell issuing a response from the innate immune system via the cytotoxic-T cells, helper-T cells, and the antigen presenting cells (APC). The cascade ends by activating the B-cells and consequent production of the antibodies against the virus which is the desired result that can be gauged by serological tests. The viral infection is thus controlled by the adaptive immune response, which also dictates clinical recovery.⁸

In this study, we investigated the presence and titers of T-cells and T cells subsets in different recipients who have received a minimum of two doses from; BNT162b2 (Pfizer, New York, NY, USA), BBIBP-CorV (Sinopharm, Beijing, China), and Sputnik V (Gamaleya Research Institute, Moscow, Russia), then ChAdOx1 nCoV-19 (AstraZeneca, Cambridge, UK) depending on the immunological response, factors affecting immunological response and the clinical response.

Materials and methods

Study sample and ethical consideration

In this cross-sectional study conducted in Jordan between May 1st and August 30th, 2023, a group of 350 individuals, who were vaccinated with at least two doses of COVID-19 vaccines were participated. Participants filled in an informed consent prior to participation. A self-prepared questionnaire included demographic data (age, gender, and place of residence); clinical profile (concomitant diseases, drug history and previous COVID-19 infection); vaccine data (type and number of doses of vaccine, side effects). Other factors (smoking, pregnancy history during COVID-19 pandemic, body mass index) were also collected (Appendix A).

350 participants, primarily consisting of Balqa Applied University students, employees, and individuals residing in proximity to the university. The inclusion criteria stipulated that participant had to be Jordanian adults possessing a national ID, having completed two or three doses of vaccination at least two weeks prior, and having received one of the following vaccines: Pfizer-BioNTech, AstraZeneca-Oxford, Sinopharm, or Sputnik V. Moreover, all vaccine recipients had to have received their doses in Jordan and remained viable throughout the entire research duration.

The levels of different types of T cells for the Pfizer vaccine group and the non-Pfizer vaccine group were tested. Additionally, various levels were examined between the numbers of doses and, consequently, predictors for their immunity type were investigated using multivariate logistic regression.

The Ethical Review Committee approval at Al-Balqa Applied University and College of Medicine was granted on February 2, 2022 (Reference No. 125) along with an institutional review board (IRB) at Al-Balqa Applied University (BAU).

Blood collection, lymphocytes isolation and follow up

350 participants completed the registration and data collection phase. However, after preparing the samples for reading by the flow cytometer, only two hundred samples could be read because some of them did not dissolve when using the erythrocyte lysis solution due to some of the participant’s diseases that affected normal RBCs.⁹ T-cells were isolated by peripheral blood drawn into an Ethylene-diaminete-traacetic acid (EDTA) tube, then approximately within three to nine hours one milliliter (mL) of peripheral blood was added to five mL of Erythrocyte lysis solution (BD FACS lysing solution/product in a plastic centrifuge tube and incubated for 30 min with gentle shaking then spun down (SiGMA refrigerated centrifuge IVD version) at 1400rpm/5 min/19°C and the supernatant tipped off. Five mL of phosphate buffer saline {PBS} (ph 7.4 (1X) gibco/product) was added over the isolated sample and shook on a vortex (vortex mixers/thermo fisher scientific) and then centrifuged at 1400rpm/5 min/19°C. This step was repeated three to five times and stopped once a pure sample without blood (only lymphatic cells) was obtained. Finally, 20 mL of PBS was added, and the entire sample was transferred to a flow-cytometer tube. Cells were stained with CD4+ monoclonal antibody (OKT4 (OKT-4)), FITC, eBioscience™, CD3+ monoclonal (UCHT1), APC, eBioscience™ and CD8+a monoclonal antibody (RPA-T8), PE, eBioscience™, then incubated for 30 minutes at room temperature in the dark. After that, they were centrifuged, discarded, and subjected to flow cytometry analysis after adding 20 mL of PBS using BD FACSCanto II flow cytometer (BD, USA). The sample preparation methodology was based on research published on March 4th, 2015.¹⁰

Based on International Society for Advancement of Cytometry. To ensure the T-cell counts are specific for COVID-19 we use different subsets of T cells with extracellular markers in combination intracellular markers. Additionally, identification of very small subsets, including antigen-specific T cells. Together, can be used for comprehensive phenotyping of a T cell subset of interest.¹¹

Flow Cytometry analysis was performed using BD FACSDiva 7.0 software (BD, USA), Appendix B represents an example of flow Cytometry results. Singlets were selected based on FSC-A, and SSC-A. Monocytes, B cells, and dead cells were excluded by several washes and PI-cells. T-cells were further selected for CD4, CD3 and CD8 positivity. Representative flow cytometry analysis of CD4+/CD8+ activated T cells and activated CD69+ T-cells cultured with and without primed WJ-MSCs and MFI ± SD of CD69+ T-cell in CD4+ and CD8+ activated T-cells under the following conditions: activated T-cells alone (black) and activated T-cells co-cultured with primed WJ-MSCs (red). An unpaired t-test was performed to test statistical significance. (details on the machine configuration can be found at: http://www3.niaid.nih.gov/labs/aboutlabs/VRC/flowCytometryCoreLaboratory/).

For laboratory-confirmed COVID-19 infection, participants were contacted by phone, three months after sampling.

Data analysis

Statistical analysis was performed using Statistical Package for Social Sciences (SPSS) version 26. Categorical parameters were presented as absolute numbers with percentages and continuous parameters as medians with interquartile ranges. ANOVA and chi-square test with logistic regressions were used alongside adjusted odds ratio (AOR) with a 95% confidence interval (CI).

Results

The objective of the study was to calculate vaccine effectiveness against infection by measuring the levels of specific immunologic markers (T cells specific to COVID-19) among a sample of healthy vaccinated individuals in flow-cytometry and side effects after receiving at least two doses of any vaccine.

Among the responses (N = 350), just over half of the participants were females (51.7%), and the most common age group was 21–30 years old (43.1%). The participants received the vaccines in this order; (48%) Pfizer- BioNTech, (28.3%) Sinopharm, (12%) Sputnik V and (11.7%) AstraZeneca- Oxford. Furthermore, 50%) of participants had a history of previous COVID-19 infection with (35.4%) had no history, and (14.6%) did not know. When asked about history of infection, (50%) half of the participants said no, (18%) sustained an infection before the first dose, (4.3%) got one after it, (21.7%) after the second dose, and (2.3%) after the third dose while (3.7%) stated “I do not know” Table 1.

Table1. Baseline characteristics of participants.

Baseline Characteristics		N (%)
Gander	Female	181 (51.7%)
	Male	169 (48.3%)
Age	18–30	219 (62.5%)
	31–50	98 (28%)
	>50	33 (9.4%)
	>High school	58 (16.6%)
Educational level	College	56 (16%)
	University	193 (55.1%)
	High-postgraduate	43 (12.3%)
	Low>500 JD	194 (55.4%)
Family income	500–1000	114 (32.6%)
	High>1000	42 (12%)
Place of residence	Urban areas	230 (65.7%)
	Rural areas	120 (34.3%)
Smoking	Yes	41.4% (145)
	No	58.6% (205)
Alcohol	Yes	8% (28)
	No	92% (322)
	A	122 (34.9%)
	B	57 (16.3%)
Blood group	AB	27 (7.7%)
	O	144 (41.1%)
	>18.5	33 (9.4%)
	18.5–25	150 (42.9%)
Body mass index	25.1–30	97 (27.7%)
	>30	70 (20%)
	* NO disease	269 (76.9%)
	* Yes	81 (23.1%)
	Endocrine (including Diabetes Mellitus)	19 (5.4%)
	CVD (including Hypertension)	12 (3.4%)
Chronic diseases	Hyper-Sensitive disease (including asthma)	18 (5.1%)
	Other diseases (including stomach disease)	17 (4.9%)
	Multiple diseases (two diseases and more)	15 (4.3%)
Have you taken influenza vaccine previously (regular)	Yes	86 (24.6%)
	No	264 (75.4%)
Pregnancy during COVID- 19 pandemic?	Yes	17 (4.9%)
	No	164 (46.9%)
	Yes	175 (50%)
Previous COVID-19 infection	No	124 (35.4%)
	I don’t know	51 (14.6%)
Hospital admission	Yes	17 (4.9%)
	No	158 (45.1%)
Oxygen used during treatment at home.	Yes	14 (4%)
	No	161 (46%)
Has anyone in your family been infected by COVID 19?	Yes	249 (71.1%)
	No	101 (28.9%)
	Pfizer-BioNTech	147 (49.5%)
Type of vaccine for just take two doses (297)	Sinopharm	73 (24.6%)
	AstraZeneca-Oxford	36 (12.1%)
	Sputnik V	41 (13.8%)
Type of vaccine for third doses (53)	Pfizer-BioNTech	49 (92.4%)
	Sinopharm	4 (7.6%)

Vaccines side effects

The most important side effects following the vaccine administration were as follows: n = 63 (18%) had a reaction at the injection area (localized pain, swallowing and blushing), n = 61 (17.4%) had fatigue, n = 30 (8.6%) had Fever, n = 119 (34%) had more than one symptoms and some of the individuals reported experiencing allergic responses, and Irregular periods after receiving the vaccine in female. None of the individuals reported experiencing loss of consciousness, internal bleeding, or blood clot development. Moreover, n = 77 (22%) had no side effects Figure 1.

Figure 1. Vaccines side effects frequencies.

Recipients of Sputnik V and AstraZeneca vaccines described more side effects than those who received the Pfizer vaccine. However, vaccination of Sinopharm had the fewest adverse reactions reported.

52.4% vaccinated with Pfizer vaccine suffered from localized pain and fatigue that had a higher prevalence compared to Sinopharm, AstraZeneca and sputnik which had 47%. However, Sinopharm, AstraZeneca, and sputnik vaccination users reported more frequent adverse effects such as fever, exhaustion, headaches, myalgia, and chills, (p value = .009) Figure 2.

Figure 2. Percentages of side effects of different vaccines.

Risk factors for post vaccination side effects

The results of the chi-square test showed that females, individuals under 51 years old and people who live in urban areas (cities) are the most susceptible to side effects after vaccination with a p- value of (0.001/0.027/0.05), respectively, Table 2. However, blood type and history of COVID-19 infection do not show any relationship between them and the side effects of the vaccine.

Table 2. Association of side effects and different factors.

		Side effects
Factor analyzed		No side effects N (%)	Yes N (%)	P-value
Age	18–30	19.6% (44)	180 (80.4%)	.027
	31–50	24.7% (23)	70 (75.3%)
	<50	30.3% (10)	23 (69.7%)
Gander	Female	16.6% (30)	151 (83.4%)	.001
	Male	27.8% (47)	122 (72.2%)
Family income	>500 JD	41(21.1%)	153 (78.9%)	.427
	=1000JD	23 (20.2%)	91 (79.8%)
	<1000JD	13 (31%)	29 (69%)
Place of residence	Urban areas	52 (22.6%)	178 (77.4%)	.050
	Rural areas	25 (20.8%)	95 (79.2%)
Smoking	Yes	37 (25.5%)	108 (74.5%)	.157
	No	40 (19.5%)	165 (80.5%)
Blood group	A	22 (18%)	100 (82%)	.191
	B	14 (24.6%)	43 (75.4)
	AB	6 (22.2%)	21 (77.8)
	O	35 (24.3%)	65 (75.7)
BMI	>18.5	9 (27.3%)	24 (72.7%)	.676
	18.5–25	36 (24%)	114 (76%)
	21.1–30	16 (16.5%)	81 (83.5)
	<30	16 (22.9%)	54 (77.1%)

Alteration of T-cell count among individuals vaccinated with COVID-19 vaccines

Investigation of circulating SARS-CoV-2-specific CD3+, CD4+, and CD8+ counts in different COVID-19 vaccines measured in 200 blood samples leads to the conclusion that there difference between vaccines in some subsets of T cells in significant way with p-value less than 0.05.

Hence, discernible distinctions in the effects of diverse COVID-19 vaccines emerged. The principal aim of the vaccination endeavors was to enhance the responses of CD4+ T-cells, which exhibited a robust correlation with increased magnitudes of anti-SARS-CoV-2 IgG and IgA titers. Notably, responses of SARS-CoV-2-specific CD3+/CD4+ T-helper cells were notably higher in recipients of the Pfizer-BioNTech vaccine (90.84%, 87.46% − 94.22%) compared to those who received non-Pfizer-BioNTech vaccines (Sputnik and Sinopharm, followed by AstraZeneca-Oxford) (83.62%, 77.91% − 89.33%). This difference was statistically significant (p = .026), as depicted in Table 5.

At, CD3+/CD8+ (T cytotoxic) the important cells which target at least eight SARS-CoV-2 ORFs and spike and M. Responses were also significantly elevated in non-Pfizer-BioNTech recipients (sputnik, Sinopharm and AstraZeneca-Oxford) (73.94%, 69.38% − 78.49%) compared to that at Pfizer-BioNTech (58.26%, 53.07% − 63.44%). (p = .01) illustrated in Table 3.

Table 3. Different T-cells percentage between different COVID-19 vaccines.

		N	Mean (SD)	95% Confidence Interval		F	P-value
				Lower Bound	Upper Bound
CD3^+	Pfizer-BioNTech	110	73.74% (4.83)	68.91	78.57	1.273	.972
	Non-Pfizer-BioNTech	90	77.83% (5.32)	72.51	83.15
CD4^+	Pfizer-BioNTech	110	90.84% (3.38)	87.46	94.22	5.051	.026
	Non-Pfizer-BioNTech	90	83.62% (5.71)	77.91	89.33
CD8^+	Pfizer-BioNTech	110	58.26% (5.185)	53.07	63.44	19.39	.001
	Non-Pfizer-BioNTech	90	73.94% (4.555)	69.38	78.49

Figures 3 and 4 show Flow cytometry analysis of T- helper and T-cytotoxic cells in the peripheral blood of human with CD4+ monoclonal antibody [(OKT4 (OKT-4)), FITC, eBioscience™], CD3+ monoclonal [(UCHT1), APC, eBioscience™] and CD8+a monoclonal antibody [(RPA-T8), PE, eBioscience™] directed to CD4+, CD3+ and CD8+ to determine T cell differentiation count induced by different COVID-19 vaccines. Cells were acquired with a modified FACSAria (BD, San Jose, CA) able to detect 20 parameters (details on the machine configuration can be found at: http://www3.niaid.nih.gov/labs/aboutlabs/VRC/flowCytometryCoreLaboratory/).

Figure 3. Flow cytometry analysis of T- helper cells.

Figure 4. Flow cytometry analysis of T-cytotoxic cells.

Comparison of the effect of the number of doses to COVID-19 vaccines

When comparing two doses of the same vaccines, there is the same difference as total doses which still Pfizer stimulate exogenous pathway to produce antibody and Non-Pfizer recipient stimulate endogenous pathway such as cell-mediated cytotoxic effect for cells (Table 4).

Table 4. Different T-cells percentage between two doses of different COVID-19 vaccines.

		N	Mean	P-value
CD3^+	Pfizer-BioNTech	97	80.4%	.460
	Non-Pfizer-BioNTech	62	82.5%
CD4^+	Pfizer-BioNTech	97	92.2%	.005
	Non-Pfizer-BioNTech	62	84.9%
CD8^+	Pfizer-BioNTech	97	63.6%	.001
	Non-Pfizer-BioNTech	62	76.9%

Comparing two doses of non-Pfizer-BioNTech recipient vaccines and the third doses of BNT162b2 recipient (Pfizer, NY, NY, USA), no change was in the type of immune reaction that is still non-Pfizer-BioNTech recipient stimulate endogenous pathway such as cell-mediated cytotoxic effect for cells (Table 5).

Table 5. Different T-cells percentage depending on third dose.

		N	Mean	P-value
CD3^+	Pfizer-BioNTech	17	76.5%	.195
	Non-Pfizer-BioNTech	23	81.7%
CD4^+	Pfizer-BioNTech	17	92.2%	.14
	Non-Pfizer-BioNTech	23	88.2%
CD8^+	Pfizer-BioNTech	17	60.8%	.18
	Non-Pfizer-BioNTech	23	66.5%

Follow up

After contacting participants by phone, all participants assured that they had no laboratory-confirmed COVID-19 infection within three months of sample collection.

Discussion

Following the urgent needs for the production of vaccines to manage the severe COVID-19 pandemic, various vaccines emerged using diverse manufacturing approaches. Disagreements arose regarding the efficacy of these vaccines and their potential impact on the health of recipients. This research was centered on analyzing the immune reactions elicited by distinct COVID-19 vaccines administered in Jordan. The investigation encompassed 350 vaccinated individuals, considering various variables that could influence the response to vaccinations.

Out of a total of 350 people participated in this study; 168 received the Pfizer-BioNTech vaccine (the age, between18-above 50 years; 50.5% women and SARSCoV-2 prior infection rate was 49.1%), 99 received Sinopharm vaccine (the age, between 18- above 51 years; 48.5% women and SARSCoV-2 prior infection rate was 31.4%), 41 received the Oxford-AstraZeneca vaccine (the age, between 25- above 50 years; 43.9% women and SARSCoV-2 prior infection rate was 10.3%) and 42 received Sputnik V vaccine (the age, years; 25- above 51, 66.6% women and SARSCoV-2 prior infection rate was 9.1%). The findings are consistent with previous a research conducted in IRAN.¹²

People vaccinated with any of the COVID-19 vaccines will be at risk of some side effects. In this research, we found 77 people (22%) who did not suffer from any side effect after receiving the vaccine, while 273 people (78%) suffered from different side effect. Moreover, the most prevalent side effects that appeared on recipients were reaction at the injection site (local pain, swallowing and redness), N = 61 (17.4%), fatigue, N = 30 (8.6%), fever, N = 119 (34%) had more than one symptom. Similar findings were observed in a study conducted in the Czech Republic between workers in medical sector and found side effect after receiving the vaccine like Injection site pain, Fatigue, Headache, Muscle pain, fever, and Chills.¹³ Also, this is parallel with a Jordanian study published in June 2021,¹⁴ and another study in Wuhan, China¹⁵ that showed after administering one dose of AstraZeneca-Oxford, Pfizer-BioNTeck, and SinoPharm vaccines individuals suffered from fatigue (52%), myalgia (44%), headache (42%), and fever (35%).¹⁴

Additionally, in a study conducted in Wuhan, China, the side effects appeared as follows; Fever, headache, fatigue, joint and muscle pain, as manifested in successive proportions (42%/31%/39%/7%) respectively.¹⁵

On the other hand, (52.4%) of the participants vaccinated with Pfizer vaccine suffered from localized pain and fatigue that had a higher prevalence compared to Sinopharm, AstraZeneca-Oxford and Sputnik V (47%). Nevertheless, The Pfizer Company claimed a greater percentage of local responses at the injection area (83.1%) but AstraZeneca-Oxford vaccine had the identical frequency percentage (54%) observed.^15,16

In general, recipients of the Sputnik V and AstraZeneca-Oxford vaccines described more side effects than those who received Pfizer- BioNTeach vaccine, compared to the vaccination of Sinopharm which had the fewest adverse reactions reported.

Also, this is parallel with a study published in Apr, 2023 which showed after administering first and second doses, a higher occurrence of individuals possessing at least one adverse side effect was observed among recipients of the Oxford – AstraZeneca (95.8%) and Sputnik V (92.1%) vaccines compared to those who were administered Covaxin (70.5%) or Sinopharm (66.7%) vaccines.¹⁷

During the current research, a number of risk variables for the negative effects of vaccination against COVID-19 disease were identified, including people less than 50 years of age, women, and place of residence. This was in line with a Food and Drug Administration (FDA) report and The Czech Republic likewise made a similar finding that young individuals were more likely to experience side effects after vaccine.¹³

The gender effect on side effects after the vaccination, it was found that females are more susceptible to side effects with a value of p = .001 which is consistent with previous research.¹⁸

Urban people reported exposure to post-vaccination symptoms more than rural people, and this result, can be explained depending on the different lifestyle, physical activity, weather conditions, and the different psychological state between the two regions and this is consistent with previous research.¹⁹

On another hand, there are some variables that show no significant effect on the side effects after vaccination, like; family income, smoking, blood typing and BMI, (p = .427, .157, .191, .676; respectively).

Moreover, this is non-parallel with a Spanish study published in Nov, 2021 that showed that having a non-overweight status was linked to an increased likelihood of experiencing symptoms such as fever ≥ 38°, vomiting, diarrhea, and chills when compared to individuals who were overweight.²⁰

In a meta-analysis concerned with blood typing and side effects conducted in Ljubljana, Slovenia, it was determined that individuals with blood group A exhibited a correlation with more severe disease, whereas those with blood group O demonstrated a protective effect.²¹ But this is contrary to our findings.

None of the individuals reported internal bleeding, or the development of a blood clot, so we did not test D-dimer which is the test used for patients with suspected venous thromboembolism although in previous research in more than 20 countries around the world a number of rare cases of thrombosis are predominantly among female AstraZeneca-Oxford vaccinated recipients aged 51 or younger.²² In addition, several studies found the existence of such case among mRNA vaccines recipients.²³ However, in this research, we did not encounter such a case.

Venous thromboembolism is caused by “vaccine-induced thrombocytopenia” (VITT), an uncommon side effect of the AstraZeneca-Oxford vaccine that pathologically resembles heparin- induced thrombocytopenia (HIT). This occurs when platelet-stimulating antibodies against platelet factor 4 (PF4) cause immune-mediated thrombocytopenia.^24,25

To avoid potential VITT, it is generally advised that those who wish to get vaccinated, especially young women undergo D-dimer and anti-PF4/heparin antibody tests.^24–27

Although the effectiveness and safety of vaccines may vary with different populations and environmental situations, most Phase III clinical studies only evaluate vaccine efficacy and safety in a relatively narrowly defined human and environmental population, e.g., a restricted age range, testing in a small number of countries, with deleting posts who are pregnant or have other serious medical problems, etc.²⁸

In light of this, our study does not exclude any factor that may influence the immune response to understand more about the immune response to different vaccines in the short and long term, therefore, in our study, the focus was on the aspect of adaptive immunity, cellular and humoral immunity, and the influence of external factors on it, which includes T cells.

In our study, we compared the subsets of CD3, CD3+/CD4+ and CD3+/CD8+ T cells responses to different COVID-19 vaccines in Jordan by flow-cytometry through using blood sample. Strikingly, CD3+/CD4+ (T-helper) levels are significantly higher among Pfizer-BioNTeach recipients than non-Pfizer-BioNTeach recipients which elicit exogenous pathway. In the pilot study (n = 200), a mean of 90.84 (IQR: 87.46–94.22) CD3+/CD4+ cells were recovered per Pfizer-vaccinated recipient. Participants were a median age of 25 years old (IQR: 21–30), and the female: male ratio was roughly 1:1. Most participants received (2/3) doses of Pfizer vaccine in the previous few months, and the majority had prior COVID-19 infection. The median BMI was 23 (IQR: 18.5–25). That’s parallel with the antibody response in the Jordanian study that evaluated the effectiveness of four types of vaccines. As a result, the highest median anti-S IgG values were seen in individuals who received BNT162b2 (2.9 AU/mL) because of CD3+/CD4+ (T-helper) by releasing regulatory and pro-inflammatory mediators which activate B-cells to produce virus-specific antibodies by activating T cell-dependent B cells.²⁹

In contrast, non-Pfizer-BioNTeach vaccines (AstraZeneca, Sputnik, and Sinopharm) were able to induce a much stronger response to CD3+/CD8+ T cells than Pfizer-BioNTeach which elicit endogenous pathway. In the pilot study (n = 200), a mean of 73.94 (IQR: 69.38–78.48) CD3+/CD8+ (T-cytotoxic) T-cells were recovered per non-Pfizer-vaccinated recipient. Most participants received two doses of the same vaccine and the third dose was either Pfizer or Sinopharm, however it did not affect the type of immune response. Most participants had prior COVID-19 infection. The median body mass index (BMI) was 23 years old (IQR: 18.5–25).³⁰

None of the participants suffered reinfection following the vaccine administration. This is due to several reasons, including the fewer count in laboratory tests for COVID-19, in addition to the high immune response that was formed in individuals and thus the lower severity of COVID-19 symptoms, which makes it difficult to differentiate between COVID-19 infection and seasonal influenza. The reason being to raise awareness among individuals about staying healthy. And this is parallel with previous study which showed reduction in re-infection after COVID-19 vaccine.³¹

Conclusions

All the four types of COVID-19 vaccines administered in Jordan were effective. According to the total number of T cells, it was found that there was no difference in the response of the recipients depending on the vaccine type, as all of them were T cells. However, the difference was in the subset of the T cells, where non-Pfizer was higher in toxic T-cells and Pfizer was higher in helper T-cells that stimulate plasma cells to produce antibodies. In general, about vaccine side effect, recipients of the Sputnik V and AstraZeneca-Oxford vaccines described more side effects than those who received Pfizer- BioNTeach vaccine, while Sinopharm had the fewest adverse reactions reported.

Recommendations

1-Measuring the ability of B lymphocytes present in the peripheral blood to express the MHC class I and class II molecules is considered as indirect measuring of its ability to express the antigen. So, the recommendations are:

1. Studying of this ability of other unstudied professional APCs especially dendritic cells.

2. Performing the study on the APCs present in the lymph nodes with consideration for measuring the presence of the antigen peptide on the surfaces of those APCs and the proliferation and activation of T lymphocytes after stimulation for direct measuring of the APCs ability to express the antigen on their surfaces and to be a professional APC.

2-Study T- regulatory cells by flow cytometry in recipients who have high levels of T- cytotoxic cells.

Limitations

Convenient study sample is an obvious limitation. Unknown time or interval between vaccination and collection of samples could affect results. We did not perform the flow cytometry prior to vaccination, so it is impossible to evaluate whether we have detected long lasting immune changes in T cells or if they were induced by the vaccination.

Authors’ contributions

Hatim M Jaber: Supervision, conception and design, analysis, and interpretation of the data

Saja Ebdah: collecting data and samples, lab analysis and drafting of the paper

Sameer A. Al Haj Mahmoud: revising it critically for intellectual content and the final approval of the version to be published.

Luay Abu-Qatouseh: revising it critically for intellectual content and the final approval of the version to be published.

Yazan H. Jaber: revising it critically for intellectual content and the final approval of the version to be published

Consent for publication

All authors agree to be accountable for all aspects of the work.

Ethical approval and informed consent

All study procedures were performed in accordance with the principles of the Declaration of Helsinki. All authors attest they meet the ICMJE criteria for authorship.

Acknowledgments

We thank all people who participated and contributed to our work for their help with the conduction of the study, to Deanship of Scientific Research and innovation, Al-Balqa Applied University.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data reported in this manuscript is available within the article. Any additional data will be made available from the corresponding authors, Dr. Hatim Jaber or Saja Ebdah, upon request.

Supplementary material

Supplemental data for this article can be accessed on the publisher’s website at https://doi.org/10.1080/21645515.2024.2333104

Additional information

Funding

This work was completed in partial fulfilment of an MSc in Medical Laboratory. This work was supported by the Deanship of Scientific Research and innovation, Al-Balqa Applied University, Al-Salt, Jordan. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.