mRNA-1273 vaccinated inflammatory bowel disease patients receiving TNF inhibitors develop broad and robust SARS-CoV-2-specific CD8+ T cell responses
Bibliographic record
Abstract
SARS-CoV-2-specific CD8+ T cells recognize conserved viral peptides and in the absence of cross-reactive antibodies form an important line of protection against emerging viral variants as they ameliorate disease severity. SARS-CoV-2 mRNA vaccines induce robust spike-specific antibody and T cell responses in healthy individuals, but their effectiveness in patients with chronic immune-mediated inflammatory disorders (IMIDs) is less well defined. These patients are often treated with systemic immunosuppressants, which may negatively affect vaccine-induced immunity. Indeed, TNF inhibitor (TNFi)-treated inflammatory bowel disease (IBD) patients display reduced ability to maintain SARS-CoV-2 antibody responses post-vaccination, yet the effects on CD8+ T cells remain unclear. Here, we analyzed the impact of IBD and TNFi treatment on mRNA-1273 vaccine-induced CD8+ T cell responses compared to healthy controls in SARS-CoV-2 experienced and inexperienced patients. CD8+ T cells were analyzed for their ability to recognize 32 SARS-CoV-2-specific epitopes, restricted by 10 common HLA class I allotypes using heterotetramer combinatorial coding. This strategy allowed in-depth ex vivo profiling of the vaccine-induced CD8+ T cell responses using phenotypic and activation markers. mRNA vaccination of TNFi-treated and untreated IBD patients induced robust spike-specific CD8+ T cell responses with a predominant central memory and activated phenotype, comparable to those in healthy controls. Prominent non-spike-specific CD8+ T cell responses were observed in SARS-CoV-2 experienced donors prior to vaccination. Non-spike-specific CD8+ T cells persisted and spike-specific CD8+ T cells notably expanded after vaccination in these patient cohorts. Our data demonstrate that regardless of TNFi treatment or prior SARS-CoV-2 infection, IBD patients benefit from vaccination by inducing a robust spike-specific CD8+ T cell response.
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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".