Systemic and mucosal IgA responses are variably induced in response to SARS-CoV-2 mRNA vaccination and are associated with protection against subsequent infection
Bibliographic record
Abstract
Abstract Although SARS-CoV-2 infects the upper respiratory tract, we know little about the amount, type, and kinetics of antibodies (Ab) generated at this site in response to intramuscular COVID-19 vaccination, and whether these Ab protect against subsequent “breakthrough” infections. We collected longitudinal serum and saliva samples from participants receiving two doses of mRNA COVID-19 vaccines over a 6-month period and measured the relative level of anti-Spike and anti-Receptor Binding Domain (RBD) Ab. We detected anti-Spike/RBD IgG and IgA and associated secretory component in the saliva of most participants receiving 1 dose of mRNA vaccine. Administration of a second dose of mRNA boosted the IgG but not the IgA response, with only 30% of participants remaining positive for IgA at this timepoint. At 6 months post-dose 2, these participants exhibited greatly diminished anti-Spike/RBD IgG and IgA levels concomitant with a reduction in neutralizing activity in the saliva, although the level of secretory component associated anti-Spike was less susceptible to decay. Examining two prospective cohorts of subjects that were monitored for infections post-vaccination, we found that participants who were subsequently infected with SARS-CoV-2 had lower levels of vaccine-induced serum anti-Spike/RBD IgA at 2-4 weeks post-dose 2 compared to participants who did not experience an infection, whereas IgG levels were comparable between groups. These data emphasize the importance of developing COVID-19 vaccines that elicit a durable IgA response. One-Sentence Summary Our study delves into whether intra-muscular mRNA vaccination regimes confer a local IgA response in the oral cavity and whether the IgA response is associated with protection against breakthrough infection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".