Anselm Jorda,Felix Bergmann,Robin Ristl,Helga Radner,Daniela Sieghart,Daniel Aletaha,Markus Zeitlinger
Association between reactogenicity and immunogenicity after BNT162b2 booster vaccination: a secondary analysis of a prospective cohort study
Adverse events,Antibody titers,COVID-19,SARS-CoV-2,Side effects,Symptoms,Vaccine
Objectives A weak correlation between symptom severity and antibody levels after primary immunization against COVID-19 has already been shown. This study aimed to describe the association between reactogenicity and immunogenicity after booster vaccination. Methods This secondary analysis of a prospective cohort study included 484 healthcare workers who received a booster vaccination with BNT162b2. Anti-receptor binding domain (RBD) antibodies were assessed at baseline and 28 days after booster vaccination. Side effects were graded (none, mild, moderate, or severe) and reported daily for 7 days after booster vaccination. Spearman correlation coefficient (rho) was used to determine the correlations between the severity of each symptom and anti-RBD levels before vaccination and 28 days after. The Bonferroni method was used to adjust p values for multiple comparisons. Results Most of the 484 participants reported at least one local (451 [93.2%]) or systemic (437 [90.3%]) post-booster symptom. No correlations between the severity of local symptoms and antibody levels were found. Except for nausea, systemic symptoms showed weak but statistically significant correlations with 28-day anti-RBD levels (fatigue [rho = 0.23, p < 0.01], fever [rho = 22, p < 0.01], headache [rho = 0.15, p 0.03], arthralgia [rho = 0.2, p < 0.01], myalgia [rho = 0.17, p < 0.01]). There was no association between post-booster symptoms and pre-booster antibody levels. Discussion This study showed only a weak correlation between the severity of systemic post-booster symptoms and anti-SARS-CoV-2 antibody levels at 28 days. Therefore, self-reported symptom severity cannot be used to predict immunogenicity after booster vaccination.
Association between reactogenicity and immunogenicity after BNT162b2 booster vaccination: a secondary analysis of a prospective cohort study

A weak correlation between symptom severity and antibody levels after primary immunization against COVID-19 has already been shown. This study aimed to describe the association between reactogenicity and immunogenicity after booster vaccination.

This secondary analysis of a prospective cohort study included 484 healthcare workers who received a booster vaccination with BNT162b2. Anti-receptor binding domain (RBD) antibodies were assessed at baseline and 28 days after booster vaccination. Side effects were graded (none, mild, moderate, or severe) and reported daily for 7 days after booster vaccination. Spearman correlation coefficient (rho) was used to determine the correlations between the severity of each symptom and anti-RBD levels before vaccination and 28 days after. The Bonferroni method was used to adjust p values for multiple comparisons.

Most of the 484 participants reported at least one local (451 [93.2%]) or systemic (437 [90.3%]) post-booster symptom. No correlations between the severity of local symptoms and antibody levels were found. Except for nausea, systemic symptoms showed weak but statistically significant correlations with 28-day anti-RBD levels (fatigue [rho = 0.23, p < 0.01], fever [rho = 22, p < 0.01], headache [rho = 0.15, p 0.03], arthralgia [rho = 0.2, p < 0.01], myalgia [rho = 0.17, p < 0.01]). There was no association between post-booster symptoms and pre-booster antibody levels.

This study showed only a weak correlation between the severity of systemic post-booster symptoms and anti-SARS-CoV-2 antibody levels at 28 days. Therefore, self-reported symptom severity cannot be used to predict immunogenicity after booster vaccination.

The ongoing, unprecedented vaccination campaign against COVID-19 has raised questions about the correlation between the extent of symptoms after vaccination and the level of protection conferred by the vaccine. To address these concerns, several studies have investigated the association between reactogenicity and immunogenicity after primary immunization with the different COVID-19 vaccines [[1], [2], [3], [4], [5]]. These studies have suggested a weak but consistent association between the occurrence and severity of post-vaccination symptoms and antibody levels, most of which were measured 4 weeks after vaccination. However, in many parts of the world, primary immunizations are largely complete, and recent developments suggest that COVID-19 vaccines, similar to influenza vaccines, will require seasonal or periodic boosters. To date, only two studies have examined the interplay between reactogenicity and immunogenicity after COVID-19 booster vaccination [6,7]. These studies had small sample sizes (47 and 62, respectively), which limited the strengths of their findings. Surprisingly, one of these studies claimed that the association between post-booster symptoms and antibody levels disappeared after booster vaccination [6]. The second study focused only on fever and also failed to detect a statistically significant association between the presence of fever and antibody levels at 4 weeks [7]. These conflicting results highlight the need for further investigation into the relationship between reactogenicity and immunogenicity after booster vaccination. In this regard, we performed a secondary analysis of a prospective cohort study of healthcare workers to elucidate the relationship between reactogenicity and immunogenicity after BNT162b2 booster vaccination. Our study aimed to provide a more comprehensive understanding of the immune response to COVID-19 booster vaccination and to clarify the potential impact of post-vaccination symptoms on antibody production. Overall, these findings may help inform patient counselling and management in clinical practice, particularly when it comes to managing patient expectations and concerns about the effectiveness of COVID-19 vaccines.

The main study was a single-centre, prospective, open-label cohort study that was originally designed to examine the immunogenicity and tolerability after a concomitant administration of BNT162b2 (Pfizer-BioNTech) and seasonal influenza vaccine compared with the administration of BNT162b2 alone [8]. Here, we performed a post-hoc analysis to investigate the association between post-booster symptoms and immunogenicity after booster vaccination with BNT162b2 (Pfizer-BioNTech). To obtain a homogenous study population, we included only the study arm that received a booster with BNT162b2 alone. The study included healthcare workers aged 18 years or older and affiliated with the Medical University of Vienna and the Vienna General Hospital, who received their primary immunization with BNT162b2 (Pfizer-BioNTech) or ChAdOx1 (AstraZeneca) at least 4 months before screening. The study protocol and all relevant documents were approved by competent authorities (Eudra-CT: 2021-005094-28) and the local ethics committee (MUV-EK: 1954/2021). All participants gave their oral and written consent before enrolment into the study.

Blood was collected immediately before and 4 weeks (28 ± 4 days) after booster vaccination with BNT162b2. IgG antibodies against the receptor binding domain of the viral spike protein (anti-RBD antibodies) and antibodies against the SARS-CoV-2 nucleocapsid protein were measured. Anti-RBD antibodies were quantified using the Elecsys® Anti-SARS-CoV-2-S immunoassay (upper limit of quantification of 75 000.0 BAU/mL) [9]. We determined anti-nucleocapsid antibodies using the qualitative Elecsys® Anti-SARS-CoV-2 assay to assess whether participants had previously been infected with SARS-CoV-2 [10]. Both assays were performed on a cobas® e801 analyzer (Roche Diagnostics, Rotkreuz, Switzerland). Patients with incomplete immunogenicity data were removed from the analysis.

During the first 7 days after the booster vaccination, all participants were required to submit a daily report of their post-booster symptoms using an electronic diary. Solicited adverse events included local symptoms (pain, erythema, and pruritus) and systemic symptoms (fatigue, fever, headache, nausea, arthralgia, and myalgia). All adverse events were graded according to the toxicity grading criteria of the Food and Drug Administration [11]. Symptoms were classified on a severity scale as none, mild, moderate, or severe. Injection site erythema was graded according to its diameter: mild, 2–5 cm; moderate, 5.1–10 cm; and severe, >10 cm. Body temperatures of 38.0–38.4°C, 38.5–38.9°C, and >38.9°C were graded as mild, moderate, and severe fever, respectively. Participants also indicated whether they had seen a doctor, taken analgetic or antipyretic medication, and/or called in sick during the first week after vaccination. Patients who did not report their symptoms at least once were excluded from the analysis.

The outcome measures of this study were the baseline and 28-day antibody levels. The exposure variable was the post-vaccination symptom severity (none, mild, moderate, or severe). The primary outcome of this study was the correlation between the severity of local and systemic post-booster symptoms and 28-day antibody levels. The secondary analysis was the correlation between post-booster symptoms and pre-booster antibody levels. As an exploratory analysis, we created a multivariate linear regression model with the 28-day antibody level as the dependent variable. Moreover, we assessed the correlation between the systemic symptom severity and the relative increase in antibodies (i.e. the ratio between 28-day to pre-booster antibody levels).

Characteristics of participants are described by mean and standard deviation, median and interquartile range, or absolute numbers and percentages (%). We reported the pooled and separate frequency of local and systemic post-booster symptoms. For each symptom, the highest level of severity (none, mild, moderate, or severe) within 7 days after vaccination was used for the analysis. Because antibody concentrations showed normal distribution after log10-transformation, we reported geometric means and medians of antibody levels at baseline and after 28 days. The correlation between symptom severity and antibody levels was calculated using the non-parametric Spearman correlation test. Correlation coefficients (rho) of 0.1 to <0.2, 0.2 to <0.4, 0.4 to <0.7, and ≥0.7 were interpreted as very weak, weak, moderate, and strong correlations, respectively [12]. The Bonferroni method was used to adjust p values for multiple comparisons. Adjusted p values below 0.05 were considered statistically significant. We performed a multivariate linear regression analysis with log10-transformed 28-day antibody levels as the dependent variable. We included covariates that were considered to have a potential impact on immunogenicity after vaccination: baseline demographics (age, sex, body mass index) [13]; previous SARS-CoV-2 infection; analgetic or antipyretic medication after vaccination [14]; primary immunization compound (BNT162b2 or ChAdOx1) [15]; and chronic comorbidities (hypertension, pulmonary diseases, heart diseases, and thyroid disorders) [16]. We also included all post-booster symptoms, which showed a statistically significant correlation with 28-day antibody levels in univariate analyses. Diagnostic plots (Fig. S1) were visually assessed, and linear regression assumptions were considered to be adequately met. No influential data points were detected. Residual distribution was close to normal. Coefficients of the linear regression model were exponentiated and interpreted as the percentage increase in anti-RBD levels per-unit increase of the independent variable. To assess the risk of multicollinearity in the model, we calculated the univariate correlation coefficients between the independent variables and the variance inflation factor (VIF). The VIF indicates how much the variance of an estimated regression coefficient is increased because of collinearity. In this study, we considered VIF values of >2.5 as meaningful collinearity and values > 10 as significant collinearity. To assess the potential impact of selection bias on our findings, we performed two sensitivity analyses, which assumed that patients, who were excluded because they did not report symptoms, experienced either no systemic symptoms (Model 1) or severe systemic symptoms (Model 2). All analyses were carried out using RStudio (R version 4.1.2 [1 November 2021]).

In the primary study, 558 patients received the BNT162b2 vaccine. Nineteen patients were excluded because they did not receive their primary immunization with AstraZeneca or BNT162b2. Thirty-four patients had missing baseline (n = 2) or follow-up (n = 32) antibody levels. Twenty-one patients did not report symptoms and were removed from the analysis. A total of 484 participants were included in the final analysis. The characteristics of the study participants are provided in Table 1 . Most participants were healthy and had no chronic diseases (340 [70.2%] of 484). The most common conditions were hypertension (48 [9.9%] of 484) and thyroid disorders (51 [10.5%] of 484). As determined by the presence of anti-nucleocapsid antibodies at baseline, few had previous infections with SARS-CoV-2 (24 [5.0%] of 484). Of the 484 participants, primary immunization was performed with BNT162b2 (Pfizer-BioNTech) in 148 (30.6%) participants and with ChAdOx1 (AstraZeneca) in 336 (69.4%) participants.

Most participants (473 [97.8%] of 484) experienced at least one adverse reaction within 7 days of vaccination (Fig. 1 ). Any severe post-booster symptom occurred in 170 (35.1%) of 484 participants. Any local symptom occurred in 451 (93.2%) of 484 participants. Any systemic symptom occurred in 437 (90.3%) of 484 participants. The most common local symptom was pain at the injection site (445 [91.9%]). The most common systemic symptoms were fatigue (388 [80.2%]) and headache (321 [66.3%]). Analgetic or antipyretic medication for post-booster symptoms was taken by 133 (27.5%) participants. Only 7 (1.4%) of 484 participants consulted a medical doctor.

Fig. 2 depicts the associations between the severity of local post-booster symptoms and antibody levels before and 28 days after booster vaccination. No correlations between the severity of local symptoms and antibody levels were found (Fig. 2).

Fig. 3 depicts the associations between the severity of systemic post-booster symptoms and the antibody levels before and 28 days after booster vaccination. The severity of fatigue, fever, headache, arthralgia, and myalgia showed a very weak or weak but statistically significant correlation with 28-day antibody levels. The strongest correlation with 28-day antibody levels was observed for fatigue (rho = 0.23) and fever (rho = 0.22). No statistically significant correlation between systemic post-booster symptoms and pre-booster antibody levels was found (Fig. 3).

Table 2 lists the multivariate linear regression model. Figure S2 shows the Spearman correlation coefficients between the independent variables of the regression models. Moderate correlations (rho ranging from 0.27 to 0.66) were found between the individual systemic post-vaccination symptoms, with the highest correlation between myalgia and arthralgia (rho = 0.66). The VIF of all included variables was below 2.5, indicating a low risk of multicollinearity (Table 2). Compared with no history of COVID-19, previous COVID-19 was associated with 22.3% (95% CI: 6.5–40.5%) higher 28-day antibody levels. Compared with primary immunization with ChAdOx1, primary immunization with BNT162b2 was associated with 17.1% higher 28-day antibody levels. Each increase in the fatigue severity scale was associated with a 5.9% (95% CI: 2.1–9.9%) increase in antibody levels. Each increase in the fever severity scale was associated with a 6.5% (95% CI: −0.1 to 13.4%) increase in antibody levels.

There was no correlation between the most severe systemic symptom and the ratio between 28-day and pre-booster anti-RBD antibody levels (BAU/mL) (rho = 0.0, p 0.97) (Fig. S3).

Compared with the 484 patients in the main analysis, the 21 patients, who were excluded because of missing symptom reporting, showed significantly higher 28-day antibody levels (geometric mean [95% CI]; 27 712 [20 391–37 661] vs. 18 170 [16 893–19 544]; geometric mean ratio = 1.5 [1.1–2.1]; p 0.011). To assess the potential impact of this imbalance on our main results, we performed two sensitivity analyses using extreme assumptions about the symptoms of the excluded patients. Assuming that all of the 21 excluded subjects experienced any severe systemic post-vaccination symptoms (Model 1), the correlation coefficient between post-vaccination symptoms and 28-day antibody levels was 0.22 (p < 0.001) (Fig. S4). Assuming that all of the 21 excluded subjects experienced no systemic post-vaccination symptom at all (Model 2), the correlation coefficient between post-vaccination symptoms and 28-day antibody levels was 0.14 (p 0.001) (Fig. S4).

This is the first study to examine the association between reactogenicity and pre-booster and 28-day antibody levels in a large cohort. Two previous smaller studies found no association between symptoms and antibody levels after booster vaccination with BNT162b2 [6]. In contrast, we observed a weak but statistically significant correlation between the severity of systemic symptoms and 28-day antibody levels. However, the associations were subtle and do not suggest a clinically relevant relationship between systemic symptoms and 28-day antibody levels. Furthermore, these findings indicate that absent or mild symptoms do not reflect an inadequate immune response. Symptom severity can therefore not be used to predict the antibody response after booster vaccination with BNT162b2. Notably, we observed no correlation between local post-booster symptoms and antibody levels. Previous studies examining the correlation between reactogenicity and immunogenicity after primary immunization with BNT162b2 also found no correlation between local symptoms and antibody levels [3,5,17,18]. It is unclear why there is no correlation between local reactogenicity and immunogenicity. In contrast to systemic reactogenicity, local reactogenicity may also be affected by injection technique or anatomical aspects, such as proximity to sensory nerve endings or damage to blood vessels caused by the injection. These confounders may obscure the correlation between underlying immunological processes and subjective symptoms. The lack of correlation could also be explained by the fact that the local immunologic response differs markedly from the systemic one. Intramuscular administration of mRNA vaccines causes local inflammation that attracts neutrophils, monocytes, and dendritic cells from the blood to the injection site by the production of chemokines and other inflammatory mediators, such as interleukin-1β, interleukin-6, and CXCL10 [19]. This innate immune response is likely the cause of local symptoms but may not reflect the extent of the humoral response. Antibody production is a feature of adaptive immunity that requires the transport of mRNA-containing lipid nanoparticles or antigen-expressing cells to lymph nodes, where dendritic cells and monocytes contribute to antigen presentation and priming of T cells [19]. Subsequently, T follicular helper cells promote the differentiation of B cells into antibody-producing plasma cells [20]. Co-stimulatory mediator molecules of these cellular interactions, such as type I interferons, TNF-alpha, and interleukin-6, also contribute to systemic symptoms such as fever and may correlate more strongly with the actual antibody response [19,21]. In addition, circulating SARS-CoV-2 antigens have been detected in human plasma after vaccination, which may also enhance systemic symptoms and the humoral immune response [22]. This study has several limitations. First, the explorative nature of this analysis does not allow for proof of causality, which makes the interpretation of our results speculative. Second, we relied on self-reported symptoms and did not record more challenging symptoms such as lymphadenopathy. Considering the important immunological role of local lymph nodes near the injection site, qualitative data on lymph node swelling would have been desirable but not feasible in this study design. Third, although there is reliable evidence of the correlation between antibody levels and protection against COVID-19 [23], the clinical relevance of subtle differences in antibody levels among the degrees of severity of post-booster symptoms is unclear. Fourth, we had to exclude patients who did not report their symptoms after vaccination. This exclusion may have introduced selection bias. However, two sensitivity analyses in which assumptions were made about the symptoms of excluded patients showed little effect on the correlation between post-booster symptoms and 28-day antibody levels. Fifth, the independent variables, especially the systemic symptoms, showed a moderate degree of collinearity, which may otherwise have affected the validity of the regression model. Sixth, data on reactogenicity after the first two vaccinations were not available. We reasoned that a retrospective assessment of post-vaccination symptom severity months later would not have resulted in sufficient data quality.

This study showed only a weak correlation between the severity of systemic post-booster symptoms and anti-SARS-CoV-2 antibody levels after 28 days. Although the association between reactogenicity and immunogenicity would be plausible based on our immunological understanding, the weak correlation precludes the clinically meaningful use of symptom severity for predicting immunogenicity. Importantly, absent or mild systemic symptoms after booster vaccination do not indicate an inadequate immune response.

The primary study was conceptualized by H.R., D.S., D.A., and M.Z.; the secondary analysis presented in this article was conceptualized by A.J., F.B., and M.Z.; the manuscript was written by A.J., F.B., and M.Z.; analyses of the data were performed by A.J. and R.R. All authors contributed to data curation and the design of the paper, revision as well as editing of the paper.

The authors declare that they have no conflicts of interest. The following authors received financial support within the last 3 years: D.A. from AbbVie, Amgen, Janssen, Lilly, Merck Sharp, Novartis, Pfizer, Roche, Sandoz, Sobi Sweden; HR from Gilead, Science GmbH, Janssen, Merck Sharp, and Pfizer.

The study was funded by the Federal Austrian Ministry of Education, Science and Research (21226.), the City of Vienna, and the Medical Scientific Fund of the Mayor of the City of Vienna. The funding source did not influence the study design, conduct, or reporting.