Immune complexes, innate immunity, and NETosis in ChAdOx1 vaccine-induced thrombocytopenia
Bibliographic record
Abstract
AIMS: We recently reported five cases of vaccine-induced immune thrombotic thrombocytopenia (VITT) 7-10 days after receiving the first dose of the ChAdOx1 nCoV-19 adenoviral vector vaccine against corona virus disease 2019 (COVID-19). We aimed to investigate the pathogenic immunological responses operating in these patients. METHODS AND RESULTS: We assessed circulating inflammatory markers by immune assays and immune cell phenotyping by flow cytometry analyses and performed immunoprecipitation with anti-platelet factor (PF)4 antibody in plasma samples followed by mass spectrometry from all five patients. A thrombus was retrieved from the sinus sagittal superior of one patient and analysed by immunohistochemistry and flow cytometry. Precipitated immune complexes revealed multiple innate immune pathway triggers for platelet and leucocyte activation. Plasma contained increased levels of innate immune response cytokines and markers of systemic inflammation, extensive degranulation of neutrophils, and tissue and endothelial damage. Blood analyses showed activation of neutrophils and increased levels of circulating H3Cit, dsDNA, and myeloperoxidase-DNA complex. The thrombus had extensive infiltration of neutrophils, formation of neutrophil extracellular traps (NETs), and IgG deposits. CONCLUSIONS: The results show that anti-PF4/polyanion IgG-mediated thrombus formation in VITT patients is accompanied by a massive innate immune activation and particularly the fulminant activation of neutrophils including NETosis. These results provide novel data on the immune response in this rare adenoviral vector-induced VITT.
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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 | 0.001 |
| 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 | 0.001 | 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".