ABSTRACT
OBJECTIVES: The COVID-19 vaccine is currently being administered worldwide to address the ongoing pandemic. Although these vaccines have proven effective in preventing severe disease, the level of immunity required to prevent respiratory mucosal infection remains less well understood. Therefore, it is desirable to develop a noninvasive screening strategy such as oral fluid to monitor secreted antibodies longitudinally as potential surrogates of mucosal immunity. METHODS: We evaluated the anti-spike protein antibodies in gingival crevicular fluid (GCF) and saliva and compared them to immune responses in the blood of 50 healthy health care workers following 2 doses of intramuscular Pfizer/BioNTech-BNT162b2 vaccine. RESULTS: The antibodies to SARS-CoV-2 spike and subdomain proteins (RBD, S1, S2, and NTD) were significantly higher in serum than oral fluids but showed a greater detection rate and higher median titres in GCF than saliva. For all tested SARS-CoV-2 antigens, IgG in GCF (as opposed to saliva) showed a more significant and stronger correlation with IgG in serum. Serum-neutralising antibodies (Nab) titres also displayed a significant and stronger correlation with anti-spike protein and their subdomains in GCF than saliva. Interestingly, the time post-second dose of vaccine and sex had a similar influence on IgG in serum and GCF. However, interferon (IFN)-γ-producing T-cell responses showed no association with SARS-Cov-2 IgG antibodies in serum, GCF, or saliva and neutralisation antibodies in serum. The correlation matrix of all measured parameters grouped serum and GCF IgG parameters separately from salivary IgG parameters indicating that GCF better represents the humoural response in serum than saliva. CONCLUSIONS: Within limitations, we propose that GCF could be a less invasive alternative to serum and more appropriate than saliva to detect antibody responses by current COVID-19 vaccines if the GCF collection procedure could be standardised. Further research is needed to investigate the suitability of GCF for community immune surveillance for vaccines.
ABSTRACT
BACKGROUND: This prospective cohort study aimed to evaluate the antibody responses in non-invasive gingival crevicular fluid (GCF) and unstimulated whole saliva to the SARS-CoV-2 Spike unit 1 receptor-binding domain (S1-RBD) protein following administration of the mRNA BNT162b2 vaccine. METHODS: This longitudinal study recruited 37 participants with no prior COVID-19 exposure (eight people recruited prior to the COVID-19 pandemic - labeled pre-COVID, 16 vaccinated and 13 non-vaccinated participants). An enzyme-linked immunosorbent assay (ELISA) was used to determine antibody levels against S1-RBD in saliva (n=90) and GCF (n=80) samples obtained at 1 and 3 weeks after dose 1, and 3 days, 7 days, and 3 weeks after dose 2. To determine previous SARS-CoV-2 infection status, anti-nucleocapsid (N) Ig levels were determined in samples from the pre-COVID (saliva as reference), non-vaccinated (saliva and GCF), and vaccinated (saliva and GCF) participants at 1-week post-dose 1 using ELISA. RESULTS: Salivary levels of anti-N antibodies measured in samples from vaccinated and nonvaccinated participants were comparable to those in pre-COVID saliva samples collected between October 2018 and September 2019, thus confirming that all study participants had no prior SARS-CoV-2 infection. Overall, the levels of anti-S1-RBD antibodies peaked at 3 weeks after dose 2 in both saliva and GCF for all three immunoglobulin isotypes. Notably, the concentration of anti-S1-RBD antibodies in GCF was significantly higher than in saliva at all time points. CONCLUSION: This study establishes GCF and saliva as viable alternative non-invasive sources to monitor levels of antibodies following vaccination, with GCF demonstrating feasibility as a biofluid source for the detection of antibodies against SARS-CoV-2 S1-RBD antigen.
ABSTRACT
OBJECTIVES: General chronic periodontitis (GCP) is a bacterial inflammatory disease with complex pathology. Despite extensive studies published on the variation in the oral microbiota and metabolic profiles of GCP patients, information is lacking regarding the correlation between host-bacterial interactions and biochemical metabolism. This study aimed to analyze the oral microbiome, the oral metabolome, and the link between them and to identify potential molecules as useful biomarkers for predictive, preventive, and personalized medicine (PPPM) in GCP. METHODS: In this study, gingival crevicular fluid (GCF) samples were collected from patients with GCP (n = 30) and healthy controls (n = 28). The abundance of oral microbiota constituents was obtained by Illumina sequencing, and the relative level of metabolites was measured by gas chromatography-mass spectrometry. Full-mouth probing depth, clinical attachment loss, and bleeding on probing were recorded as indices of periodontal disease. RESULTS: The relative abundances of 7 phyla and 82 genera differed significantly between the GCP and healthy groups. Seventeen differential metabolites involved in different metabolism pathways were selected based on variable influence on projection values (VIP > 1) and P values (P < 0.05). Through Spearman's correlation analysis, microorganisms, metabolites in GCF, and clinical data together showed a clear trend, and clinical data regarding periodontitis can be reflected in the shift of the oral microbial community and the change in metabolites in GCF. A combination of citramalic acid and N-carbamylglutamate yielded satisfactory accuracy (AUC = 0.876) for the predictive diagnosis of GCP. CONCLUSIONS: Dysbiosis in the polymicrobial community structure and changes in metabolism could be mechanisms underlying periodontitis. The differential microorganisms and metabolites in GCF between periodontitis patients and healthy individuals are possibly biomarkers, pointing to a potential strategy for the prediction, diagnosis, prognosis, and management of personalized periodontal therapy.