Systems vaccinology of the BNT162b2 mRNA vaccine in humans
Bibliographic record
Abstract
Abstract The emergency use authorization of two COVID-19 mRNA vaccines in less than a year since the emergence of SARS-CoV-2, represents a landmark in vaccinology1,2. Yet, how mRNA vaccines stimulate the immune system to elicit protective immune responses is unknown. Here we used a systems biological approach to comprehensively profile the innate and adaptive immune responses in 56 healthy volunteers vaccinated with the Pfizer-BioNTech mRNA vaccine. Vaccination resulted in robust production of neutralizing antibodies (nAbs) against the parent strain and the variant of concern, B.1.351, but no induction of autoantibodies, and significant increases in antigen-specific polyfunctional CD4 and CD8 T cells after the second dose. The innate response induced within the first 2 days of booster vaccination was profoundly increased, relative to the response at corresponding times after priming. Thus, there was a striking increase in the: (i) frequency of CD14+CD16+ inflammatory monocytes; (ii) concentration of IFN-y in the plasma, which correlated with enhanced pSTAT3 and pSTAT1 levels in monocytes and T cells; and (iii) transcriptional signatures of innate responses characteristic of antiviral vaccine responses against pandemic influenza, HIV and Ebola, within 2 days following booster vaccination compared to primary vaccination. Consistent with these observations, single-cell transcriptomics analysis of 242,479 leukocytes demonstrated a ~100-fold increase in the frequency of a myeloid cluster, enriched in a signature of interferon-response transcription factors (TFs) and reduced in AP-1 TFs, one day after secondary immunization, at day 21. Finally, we delineated distinct molecular pathways of innate activation that correlate with CD8 T cell and nAb responses and identified an early monocyte-related signature that was associated with the breadth of the nAb response against the B1.351 variant strain. Collectively, these data provide insights into the immune responses induced by mRNA vaccines and demonstrate their capacity to stimulate an enhanced innate response following booster immunization.
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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 | 0.000 |
| 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 | 0.000 |
| 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".