A single BNT162b2 mRNA dose elicits antibodies with Fc-mediated effector functions and boost pre-existing humoral and T cell responses
Bibliographic record
Abstract
Abstract The standard dosing of the Pfizer/BioNTech BNT162b2 mRNA vaccine validated in clinical trials includes two doses administered three weeks apart. While the decision by some public health authorities to space the doses because of limiting supply has raised concerns about vaccine efficacy, data indicate that a single dose is up to 90% effective starting 14 days after its administration. We analyzed humoral and T cells responses three weeks after a single dose of this mRNA vaccine. Despite the proven efficacy of the vaccine at this time point, no neutralizing activity were elicited in SARS-CoV-2 naïve individuals. However, we detected strong anti-receptor binding domain (RBD) and Spike antibodies with Fc-mediated effector functions and cellular responses dominated by the CD4 + T cell component. A single dose of this mRNA vaccine to individuals previously infected by SARS-CoV-2 boosted all humoral and T cell responses measured, with strong correlations between T helper and antibody immunity. Neutralizing responses were increased in both potency and breadth, with distinctive capacity to neutralize emerging variant strains. Our results highlight the importance of vaccinating uninfected and previously-infected individuals and shed new light into the potential role of Fc-mediated effector functions and T cell responses in vaccine efficacy. They also provide support to spacing the doses of two-vaccine regimens to vaccinate a larger pool of the population in the context of vaccine scarcity against SARS-CoV-2.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".