The Biochemical, Antibody and Cytokine Response to COVID-19 Vaccination in a Western Australia Cohort

Jurissa M Lang

Background: Vaccination is a key strategy to prevent SARS-CoV-2 infection, avoid “long COVID-19” and mitigate the impact of COVID-19. Immune-cell metabolism plays a role in the response to vaccines, and metabolic phenotyping provides insights into immune response characteristics. Previous studies have shown links between lipid metabolism and post-vaccination immunity, suggesting a broader connection between metabolism and immune responses (3-5). This study aims to investigate the longitudinal serum metabolic, antibody, and cytokine profiles before and after COVID-19 vaccination. Focusing particularly on molecules known to be involved in immunometabolism and systemic inflammatory responses, such as glycoproteins (Glyc), supramolecular phospholipids composite (SPC), and lipoproteins-subfractions to investigate modulating effects from the COVID-19 vaccine humoral immune response. The objective is to identify serum metabolic biomarkers that correlate with the human immune response to the vaccine, considering individual and responder group variability. Methods: This prospective longitudinal study included 33 healthy adults, primarily females with an average age of 36 years. The participants received up to four doses of either Comirnaty (Pfizer-BioNTech/BNT162b2) mRNA or Vaxzevria (ChAdOx1-S AstraZeneca COVID-19 vaccine AZD1222 Vaxzevria™ viral-vector vaccines. Serum samples were collected before COVID-19 vaccination (day 0) and at days 30, 60, 120, 240, and 480. Additionally, serum collection was performed on days 1, 2, 4, 8, and 16 after each vaccination dose. The serum samples were qualitatively analysed for Human Anti SARS-CoV-2 spike-1 IgG titer and 34 cytokine and chemokine analytes. Participants were stratified into three Responder Level groups based on their maximum IgG titer (U/ml) achieved before the second dose: group 1 (≤4.0 U/ml), group 2 (between 4.0-10.0 U/ml), and group 3 (≥10.0 U/ml). Global serum metabolic profiles were generated using 1H-nuclear magnetic resonance (NMR) spectroscopy and quantified for Glyc, SPC, and 112 lipoprotein subfractions. Various statistical analyses, including correlation analysis, Principal Component Analysis (PCA), Orthogonal Projections to Latent Structures - Discriminant Analysis (OPLS-DA), Functional Principal Component Analysis (FPCA), and Gaussian Mixture Modeling (GMM), were conducted to identify differences in metabolites between groups and assess intra-individual/inter-individual and responder group variability. The metabolic profile of the vaccine cohort was compared with gender-matched COVID-19 positive individuals and a healthy COVID-19-naïve and vaccine-naïve cohort. Results: All participants in this study generated a robust humoral immune response after the second Pfizer vaccination. Transient signature increases for cytokine IP10.CXCL10 (implicated in immune-cell recruitment) were observed within 2-days following each dose, irrespective of the IgG Responder-Levels. The side effects reported were diverse and increased in proportion with the administration of each subsequent dose, aligning with published data. Female participants generally reporting more side effects than males. Metabolic profile changes after vaccination were noticeable, within and between the Responder Level groups, but some were unique to individuals. After vaccination, we observed a transient temporal increase in the levels of GlycA and GlycB, with the most notable changes occurring on day 4 following the second dose. SPC features showed a transient temporal decrease after vaccination at day 1 and 2 post vaccination. We found that the vaccine cohort was clearly distinguishable from the COVID-19-positive cohort, it provides support for our observation of only minor alterations in the GlycA, GlycB, and SPC profiles within our vaccine cohort. Conclusion: The metabolic profile undergoes alterations in response to vaccination when compared to baseline (pre-vaccination), however it was not statistically significant. Furthermore, we delved into both intra-individual and inter-individual variability within the cohort, by utilising FPCA and GMM analyses, the investigation effectively explored time-series metabolomic data. Consequently, revealing distinct patterns among participants, our findings provide valuable insights into individualised response patterns within a relatively homogeneous and healthy cohort.

The Biochemical, Antibody and Cytokine Response to COVID-19 Vaccination in a Western Australia Cohort

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