The Coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerging from Asia and spreading worldwide in 2019, caused socio-economic and health problems globally. The development of effective and safe vaccines for the prevention of infection and onset of severe complications of the disease seemed to be the only solution for the newly emerged situation [1].

As vaccination started, individual cases of thromboembolic incidents, suspected to be caused by vaccination, were recorded and the mRNA BNT162b2 vaccine attracted a great public attention [2,3].

Searching for the cause of the incidents by analyzing the mechanism of natural infection described by Giardini et al. and by contextualizing it with the mechanism of action of the vaccine, we hypothesized that vaccination imitates natural infection through the synthesis of the spike protein. The spike protein binds to angiotensin converting enzyme 2 (ACE2), which might cause dysregulation of the renin-angiotensin system (RAS) and increase the effects of angiotensin II (Ang II) binding to its angiotensin type 1 receptor (AT1R). Consequently, this could lead to increased angiogenic factors soluble fms-like tyrosine kinase-1 (sFlt-1) production, which could result in angiogenic dysregulation, oxidative stress, inflammation, endothelial disruption, hypercoagulability, and micro- and macrovascular thrombosis [4-7].

By analyzing the pathophysiology of COVID-19, a significant similarity with preeclampsia, a pregnancy-specific disorder, has been observed through the dysregulation of the RAS. Since placental growth factor (PlGF) and sFlt-1 are assessed during preeclampsia screening, clinically significant changes in these factors' concentrations after vaccination would indicate vaccination-induced angiogenic imbalance caused by the synthesis of the spike protein, encoded by the mRNA in the mRNA BNT162b2 vaccine, triggering mechanisms similar to those seen in natural infection [8-12].

Since patients with certain comorbidities develop a more severe clinical presentation of the disease, their vaccination was recommended. Among numerous comorbidities described as COVID-19 risk factors, this study specifically highlighted hypertension, older age, and higher body mass index (BMI) as conditions characterized by disrupted angiogenic balance, suggesting that the potential effect of the vaccine would be more noticeable in these individuals [13-15].

The study hypothesizes that the mRNA BNT162b2 vaccine causes changes in PlGF and sFlt-1 concentrations and that these changes will be more noticeable in subjects with preexisting endothelial disruption.

Based on the hypothesis, the objectives of this study were:

• To examine whether vaccination causes clinically significant changes in PlGF and sFlt-1 concentrations;
• To investigate if there is a clinically significant difference in PlGF and sFlt-1 concentrations between subgroups of participants without hypertension and those with hypertension;
• To examine if there is a clinically significant correlation between PlGF and sFlt-1 and age/ body mass index at defined time points of vaccination

Subjects

Thirty-three adult subjects included in this study were selected from a bigger prospective observational clinical study conducted from April to August 2021 at the University Hospital Centre Sestre milosrdnice, Zagreb, Croatia. Subjects were vaccinated with mRNA BNT162b2 vaccine (Pfizer, BioNTech, Germany), according to the vaccination program issued by the Ministry of Healthcare of the Republic of Croatia.

The study’s main exclusion criteria were: COVID-19 disease overcome within 6 months prior to vaccination, active malignant disease, recent major surgery (within one month prior to vaccination), thromboembolic incident 3 months prior to the vaccination, dialysis, peripheral artery disease, diabetes requiring insulin therapy, active immunologic disorder, pregnancy, puerperium, oral contraceptive therapy, anticoagulant therapy, nonsteroidal antirheumatic therapy, immune thrombocytopenia and hemophilia. Subjects with acute infection were excluded from the study, based on predefined vaccination criteria.

This study was performed in accordance with the Declaration of Helsinki and all subjects signed their informed written consent. The study was approved by the University Hospital Centre Ethic committee.

Samples

Blood samples were collected from 7 a.m. to 9 a.m. after an overnight fasting. Subjects were sampled at five different time points: 1) T0- within 24 hours before 1st vaccination, 2) T1- 7 days after 1st dose, 3) T2 - 14 days after 1st dose 4) T3 - 7 days after 2nd dose and 5) T4 - 14 days after 2nd dose of vaccination. The period between two mRNA vaccinations was 21 days. At each time point, 15 mL of venous blood was collected in Vaccuette® test tubes (Greiner Bio-One, Kremsmünster, Austria) without anticoagulant. Tubes were centrifuged for 10 minutes on 1800 x g within 3 hours after venipuncture using Hettich Rotanta 460RC centrifuge and the specimens of the serum were stored at -80°C until analysis.

Methods

The Roche Elecsys PlGF and sFlt-1 assays were performed on Roche Cobas analyzer e 801 (Roche Diagnostics GmbH, Mannheim, Germany) using electrochemiluminescence immunoassay (ECLIA) based on the sandwich principle. The analysis was performed according to the manufacturer’s instructions. The PlGF assay has a claimed measuring range of 3 10000 pg/mL, a limit of quantification of 10 pg/mL, an intermediate precision (CV) of 5.1% (at 6.82 pg/mL), and 2.3% (at 9219 pg/mL). The sFlt-1 assay has a declared measuring range of 10?85000 pg/mL, a limit of quantification of 15 pg/mL, an intermediate precision (CV) of 10.2% (at 15.8 pg/mL), and 6.1% (at 70552 pg/mL).

Statistical Analysis

The normality of the data distribution was tested using Kolmogorov-Smirnov test. As the data didn’t show a normal distribution, results are presented as median and interquartile range (IQR). Age is presented as median and ranges from minimum to maximum. Differences between consecutive quantitative dependent PlGF and sFlt-1 measurements were tested using the non-parametric Wilcoxon signed-rank test. The non-parametric Mann-Whitney test was used to test a difference between measurements of non-hypertensive and hypertensive subjects. The value of P < 0.050 was considered statistically significant. The correlations between PlGF and sFlt-1 with age and BMI were tested using Spearman's correlation test. The correlation coefficient (r) was interpreted at the level of P < 0.050 and the strength of the correlations was interpreted according to Colton's criterion. Statistical analysis of the data was performed using the statistical program MedCalc® Statistical Software version 20.218 (MedCalc Software Ltd, Ostend, Belgium; https://www.medcalc.org/; 2023).

The study included 33 subjects, 19 of them were female and 14 were male. The median age of the subjects was 38 years (23-62). Characteristics of the subjects are presented in Table 1.

Table 1: Demographic characteristics of the subjects.

Our study revealed statistically significant, weak positive correlations between age/BMI and PlGF concentrations. Additionally, we observed statistically significant differences in measured parameters between defined measuring points.

Since there are limited data on the impact of vaccination on angiogenesis-related factors PlGF and sFlt-1 and due to the absence of reference values for these factors outside of pregnancy, the obtained results needed to be compared with those of similar studies analysing the impact of natural infection on PlGF and sFlt-1 concentrations, considering the vaccination's imitation of natural infection. Thus, studies focused on the analysis of angiogenic factors in monitoring pneumonia severity and thrombosis outcomes (with and without SARS-CoV-2 infection) helped in interpreting the obtained results.

Giardini et al. analyzed differences in PlGF and sFlt-1 concentrations in 19 COVID-19 positive and 12 COVID-19 negative pneumonia subjects, along with 18 healthy subjects. They found a statistically significant difference in sFlt-1 concentrations between COVID-19 positive and COVID-19 negative subjects with pneumonia, as well as between COVID-19 positive subjects with pneumonia and healthy subjects. In the same study, a statistically significant difference in PlGF levels was found between COVID-19 positive subjects with pneumonia and healthy subjects, but no difference in PlGF concentrations was found between COVID-19 positive and COVID-19 negative subjects with pneumonia, potentially due to the small subject number [6]. Furthermore, Negro et al. investigated the impact of numerous parameters on COVID-19 disease outcomes, particularly those related to endothelial damage, and found that elevated sFlt-1 concentrations were significantly associated with outcomes, especially thrombosis. For thrombosis, they defined sFlt-1 threshold value greater than 165 pg/mL, which is considerably higher than the highest sFlt-1 concentration measured in our study (113 pg/mL) [16]. Additionally, Dupont et al. found higher sFlt-1 concentrations in severe COVID-19 outcomes compared to mild ones [17]. Smadja et al. obtained increase in PlGF concentrations in more severe outcomes among 237 subjects and established an optimal PlGF threshold of 30 pg/mL for assessing COVID-19 mortality. Again, PlGF was considerably higher (30 pg/mL) than the highest PlGF concentration measured in our study (19.0 pg/mL) [18].

The results of our study showed statistically significant differences between time points T3 and T4, possibly due to a stronger immunological response after the second dose of vaccination.  However, the median PlGF (T3: 11.80 pg/mL and T4: 11.70 pg/mL, P = 0.017) and sFlt-1 (T3: 84.70 pg/mL and T4: 82.80 pg/mL, P = 0.005) concentrations did not indicate clinically significant changes [20,21].

The specific aim of this study was to determine if there is a clinically significant, vaccination induced difference in angiogenic factors' concentration between subgroups of subjects with/without hypertension. In the analysis of comorbidities in SARS-CoV-2 infected patients, Smadja et al. detected hypertension presence in 56.2% of critical patients, which shows the importance of analyzing hypertension as a risk comorbidity for COVID-19 (18). For comparison, Giardini et al. analyzed PlGF and sFlt-1 concentrations in symptomatic and asymptomatic SARS-CoV-2 infected pregnant women. Pathological pregnancy is a COVID-19 risk factor due to preeclampsia manifesting in hypertension. The expected assumption was that the presence of hypertension symptoms would be followed by an increase in the concentration of these factors. Contrary to expectations, Giardini et al. found greater increase in the concentration of PlGF and sFlt-1 in asymptomatic SARS-CoV-2 pregnant women compared to symptomatic ones. This could be associated with the gestational week stage of analyzed asymptomatic pregnant women, delayed analysis of factors in symptomatic pregnant women, and the overall complexity of coagulation processes during pregnancy (6). Considering the pathophysiology of pathological pregnancy and its impact on PlGF and sFlt-1 concentrations, an increase in these factors and more pronounced thromboembolic side effects would be expected in vaccinated pregnant women. Pratama et al. analyzed the effectiveness and side effects of vaccination in pregnant women through a large systematic review and confirmed the safety of their use [19].

Our subjects did not notice symptomatic changes in blood pressure values after vaccination, and no statistically significant differences in PlGF and sFlt-1 concentrations were found between the two analyzed subgroups.

Furthermore, while analyzing older age and higher BMI as a risk factors for COVID-19, assuming a synergistic effect of vaccination on endothelial damage and related side effects, the aim was to examine the correlation between age/BMI with PlGF/sFlt-1 concentrations. Negro et al. found a significant difference in COVID-19 outcomes considering age, demonstrating that individuals aged over 65 years are at risk for worse outcomes associated with endothelial damage (16). In contrast, the analysis by Smadja et al. shows no significant difference in age between critical and stable patients, which could be because of a higher proportion of comorbidities in critical patients included in their study, such as obesity, hyperlipidemia, diabetes and chronic kidney disease [18].

In our study, a weak positive correlation was found between PlGF concentration and age at the measurement point T0 (r = 0.37, P = 0.033), T1 (r = 0.36, P = 0.043) and T3 (r = 0.43, P = 0.014). However, this was not considered as statistically significant vaccination caused correlation. Also, no correlation between age with sFlt-1 were found.

Smadja et al. found that 37.1% of severe patients were obese (BMI > 30 kg/m2), in contrast to 18.8% of stable obese patients who had a lower proportion of other comorbidities (18). Due to the pro-inflammatory state, similar to previously analyzed risk factors, a synergistic effect on the presumed mechanism was expected.

In our study, a weak positive correlation was found between PlGF and BMI at T1 (r = 0.42, P = 0.015), T2 (r = 0.40, P = 0.020) and T4 (r = 0.37, P = 0.036). No correlation was found between the BMI and sFlt-1 concentrations. As these correlations are weak, potentially attributed to elevated PlGF concentrations in obese individuals, we assume they are not vaccination-depended. The pathological influence of vaccination through the presumed mechanism was refuted for this risk group.

The advantage of this study is its strict exclusion criteria, which reduced the influence of multiple diseases on validity of the obtained results. For extra confirmation of the obtained results, we analyzed specific subgroups of subjects with the expectation of a more pronounced impact of vaccination.

However, an evident limitation of the research is the lack of information about prior COVID-19 infections. The study's small subject number was compensated by conducting a prospective analysis at five time points. Another lack of study design is not determining concentrations immediately after vaccination, which could have confirmed the absence of an acute increase in concentrations. This study did not exclude changes in the concentrations of other factors involved in hemostasis regulation after vaccination. Furthermore, the study would benefit from including a larger number of participants. In order to suggest a potential mechanism, it would also be helpful to create a panel of laboratory tests that could be used in specific time intervals for participants who develop some form of thromboembolic incident. However, practically it is challenging due to the low occurrence of these events and the inability to predict thromboembolic incidents.

Despite statistically significant changes in angiogenic factor concentrations, a detailed analysis revealed that these changes were not clinically relevant. Therefore, it was concluded that the presumed mechanism of the thromboembolic effect of vaccination was not confirmed in this study, but further researches are needed to investigate benefit of using drugs that prevent thromboembolic incidents by inhibiting this mechanism. Other researchers could investigate other potential causal mechanisms.

Funding

The study was performed as an integral part of the research project entitled „ The effect of BNT162b2 and Ad26.CoV2.S coronavirus vaccines on the parameters of hemostasis and inflammation “ that is approved and funded by the Foundation of Croatian cooperative group for hematologic diseases KROHEM.

Conflict Of Interest

None declared.

Acknowledgement

The study was supported by Roche Diagnostics International Ltd and Siemens Healthcare d.o.o. who generously supplied reagents for multiple laboratory parameters.

1. Situation Report-77. World Health Organization 2020.
2. Varga Z, Flammer AJ, Steiger P, Haberecker M, Andermatt R, et al. Endothelial cell infection and endotheliitis in COVID-19. Lancet. 2020; 395: 1417-1418.
3. Park JW, Lagniton PNP, Liu Y, Xu RH. mRNA vaccines for COVID-19: what, why and how. Int J Biol Sci. 2021; 17: 1446-1460.
4. Giardini V, Carrer A, Casati M, Contro E, Vergani P, Gambacorti Passerini C. Increased sFLT-1/PlGF ratio in COVID-19: a novel link to angiotensin II-mediated endothelial dysfunction. Am J Hematol. 2020; 95: E188-E191.
5. Giardini V, Gambacorti-Passerini C, Casati M, Carrer A, Vergani P. Can Similarities between the Pathogenesis of Preeclampsia and COVID-19 Increase the Understanding of COVID-19? Int J Trans. Med. 2022; 2: 186-197.
6. Giardini V, Ornaghi S, Acampora E, Vasarri MV, Arienti F, et al. Letter to the editor: Sflt-1 and plgf levels in pregnancies complicated by sars-cov-2 infection. Viruses. 2021; 13: 2377.
7. Verdecchia P, Cavallini C, Spanevello A, Angeli F. The pivotal link between ACE2 deficiency and SARS-CoV-2 infection. Eur J Intern Med. 2020; 76: 14-20.
8. Maynard SE, Min JY, Merchan J, Lim KH, Li J, et al. Excess placental soluble fmslike tyrosine kinase 1 (sFlt1) may contribute to endothelial dysfunction, hypertension, and proteinuria in preeclampsia. J Clin Investig. 2003; 111: 649-658.
9. Roberts JM. Objective evidence of endothelial dysfunction in preeclampsia. Am J Kidney Dis. 1999; 33: 992-994.
10. Rodriguez M, Moreno J, Hasbun J. RAS in Pregnancy and Preeclampsia and Eclampsia. Int J Hypertens. 2012; 2012: 6.
11. Staff AC. The two-stage placental model of preeclampsia: An update. J Reprod Immunol. 2019; 134-135: 1-10.
12. Mendoza M, Garcia-Ruiz I, Maiz N, Rodo C, Garcia-Manau P, et al. Pre-eclampsia-like syndrome induced by severe COVID-19: A prospective observational study. BJOG. 2020; 127: 1374-1380.
13. Xia S, Zhang X, Zheng S, Khanabdali R, Kalionis B, et al. An Update on Inflamm-Aging: Mechanisms, Prevention, and Treatment. J Immunol Res. 2016; 2016: 12.
14. de Leeuw AJM, Oude Luttikhuis MAM, Wellen AC, Müller C, Calkhoven CF. Obesity and its impact on COVID-19. J Mol Med. 2021; 99: 899-915.
15. Tadic M, Cuspidi C, Grassi G, Mancia G. COVID-19 and arterial hypertension: Hypothesis or evidence?. J Clin Hypertens (Greenwich). 2020; 22: 1120-1126.
16. Negro A, Fama A, Penna D, Belloni L, Zerbini A, et al. SFLT-1 levels in COVID-19 patients: Association with outcome and thrombosis. Am J Hematol. 2021; 96: 41-43.
17. Dupont V, Kanagaratnam L, Goury A, Poitevin G, Bard M, et al. Excess Soluble fms-like Tyrosine Kinase 1 Correlates With Endothelial Dysfunction and Organ Failure in Critically Ill Coronavirus Disease 2019 Patients. Clin Infect Dis. 2021; 72: 1834-1837.
18. Smadja DM, Philippe A, Bory O, Gendron N, Beauvais A, et al. Placental growth factor level in plasma predicts COVID-19 severity and in-hospital mortality. J Thromb Haemost. 2021; 19: 1823-1830.
19. Pratama NR, Wafa IA, Budi DS, Putra M, Wardhana MP, et al. mRNA Covid-19 vaccines in pregnancy: A systematic review. PLoS One. 2022; 17: e0261350.
20. Mulligan MJ, Lyke KE, Kitchin N, Absalon J, Gurtman A, et al. Phase I/II study of COVID-19 RNA vaccine BNT162b1 in adults. Nature. 2020; 586: 589-93.
21. Jackson LA, Anderson EJ, Rouphael NG, Roberts PC, Makhene M, et al. An mRNA vaccine against SARS-CoV-2—preliminary report. N Engl J Med. 2020; 383: 1920-31.