The Quality of SARS-CoV-2–Specific T Cell Functions Differs in Patients with Mild/Moderate versus Severe Disease, and T Cells Expressing Coinhibitory Receptors Are Highly Activated
Bibliographic record
Abstract
Abstract Understanding the function of SARS-CoV-2 Ag-specific T cells is crucial for the monitoring of antiviral immunity and vaccine design. Currently, both impaired and robust T cell immunity is described in COVID-19 patients. In this study, we explored and compared the effector functions of SARS-CoV-2–reactive T cells expressing coinhibitory receptors and examine the immunogenicity of SARS-CoV-2 S, M, and N peptide pools in regard to specific effector T cell responses, Th1/Th2/Th17, in COVID-19 patients. Analyzing a cohort of 108 COVID-19 patients with mild, moderate, and severe disease, we observed that coinhibitory receptors (e.g., PD-1, CTLA-4, TIM-3, VISTA, CD39, CD160, 2B4, TIGIT, Gal-9, and NKG2A) were upregulated on both CD4+ and CD8+ T cells. Importantly, the expression of coinhibitory receptors on T cells recognizing SARS-CoV-2 peptide pools (M/N/S) was associated with increased frequencies of cytokine-producing T cells. Thus, our data refute the concept of pathological T cell exhaustion in COVID-19 patients. Despite interindividual variations in the T cell response to viral peptide pools, a Th2 phenotype was associated with asymptomatic and milder disease, whereas a robust Th17 was associated with severe disease, which may potentiate the hyperinflammatory response in patients admitted to the Intensive Care Unit. Our data demonstrate that T cells may either play a protective or detrimental role in COVID-19 patients. This finding could have important implications for immune correlates of protection, diagnostic, and prophylaxis with respect to COVID-19 management.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".