Ad26.COV2.S Prevents SARS-CoV-2 Induced Pathways of Inflammation and Thrombosis in Hamsters
Bibliographic record
Abstract
Abstract Syrian golden hamsters exhibit features of severe disease after SARS-CoV-2 challenge and are therefore useful models of COVID-19 pathogenesis and prevention with vaccines. Recent studies have shown that SARS-CoV-2 infection stimulates type I interferon, myeloid, and inflammatory signatures similar to human disease, and that weight loss can be prevented with vaccines. However, the impact of vaccination on transcriptional programs associated with COVID-19 pathogenesis and protective adaptive immune responses is unknown. Here we show that SARS-CoV-2 challenge in hamsters stimulates antiviral, myeloid, and inflammatory programs as well as signatures of complement and thrombosis associated with human COVID-19. Notably, single dose immunization with Ad26.COV2.S, an adenovirus serotype 26 vector (Ad26)-based vaccine expressing a stabilized SARS-CoV-2 spike protein, prevents the upregulation of these pathways such that the gene expression profiles of vaccinated hamsters are comparable to uninfected animals. Finally, we show that Ad26.COV2.S vaccination induces T and B cell signatures that correlate with binding and neutralizing antibody responses. These data provide further insights into the mechanisms of Ad26.COV2.S based protection against severe COVID-19 in hamsters. Author Summary In this study, we show that vaccination with Ad26.COV2.S protected SARS-CoV-2 challenged hamsters from developing severe COVID-19 disease by attenuating excessive proinflammatory responses, such as IL-6 and IL-1, macrophages and neutrophils signaling. Ad26 vaccination also prevented the upregulation of pathways associated with thrombosis such coagulation and clotting cascades associated with infection, and the transcriptomic profiles of vaccinated animals were largely comparable to control uninfected hamsters. In contrast, SARS-CoV-2 challenged unvaccinated hamsters showed significant increase of these proinflammatory and prothrombotic pathways and significant weight loss compared to vaccinated hamsters.
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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 | 0.000 |
| 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".