Antibody Responses to SARS-CoV-2 mRNA Vaccines Are Detectable in Saliva
Bibliographic record
Abstract
The approved Pfizer and Moderna mRNA vaccines are well known to induce serum antibody responses to the SARS-CoV-2 Spike (S)-protein. However, their abilities to elicit mucosal immune responses have not been reported. Saliva antibodies represent mucosal responses that may be relevant to how mRNA vaccines prevent oral and nasal SARS-CoV-2 transmission. Here, we describe the outcome of a cross-sectional study on a healthcare worker cohort (WELCOME-NYPH), in which we assessed whether IgM, IgG, and IgA antibodies to the S-protein and its receptor-binding domain (RBD) were present in serum and saliva samples. Anti-S-protein IgG was detected in 14/31 and 66/66 of saliva samples from uninfected participants after vaccine doses-1 and -2, respectively. IgA antibodies to the S-protein were present in 40/66 saliva samples after dose 2. Anti-S-protein IgG was present in every serum sample from recipients of 2 vaccine doses. Vaccine-induced antibodies against the RBD were also frequently present in saliva and sera. These findings may help our understanding of whether and how vaccines may impede SARS-CoV-2 transmission, including to oral cavity target cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".