Comparison of Omicron breakthrough infection versus monovalent SARS-CoV-2 intramuscular booster reveals differences in mucosal and systemic humoral immunity
Bibliographic record
Abstract
Our understanding of the quality of cellular and humoral immunity conferred by COVID-19 vaccination alone versus vaccination plus SARS-CoV-2 breakthrough (BT) infection remains incomplete. While the current (2023) SARS-CoV-2 immune landscape of Canadians is complex, in late 2021 most Canadians had either just received a third dose of COVID-19 vaccine, or had received their two-dose primary series and then experienced an Omicron BT. Herein we took advantage of this coincident timing to contrast cellular and humoral immunity conferred by three doses of vaccine versus two doses plus BT. Our results show thatBT infection induces cell-mediated immune responses to variants comparable to an intramuscular vaccine booster dose. In contrast, BT subjects had higher salivary immunoglobulin (Ig)G and IgA levels against the Omicron spike and enhanced reactivity to the ancestral spike for the IgA isotype, which also reacted with SARS-CoV-1. Serumneutralizing antibody levels against the ancestral strain and the variants were also higher after BT infection. Our results support the need for the development of intranasal vaccines that could emulate the enhanced mucosal and humoral immunity induced by Omicron BT without exposing individuals to the risks associated with SARS-CoV-2 infection.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".