SARS-CoV-2 mRNA vaccine-induced immune responses in rheumatoid arthritis
Bibliographic record
Abstract
Our objective was to characterize T and B cell responses to vaccination with SARS-CoV-2 antigens in immunocompromised rheumatoid arthritis (RA) patients. In 22 RA patients, clinical and biological variables were analyzed before and 4 weeks after each of 3 messenger RNA (mRNA) vaccine doses and compared with unmatched healthy individuals. Sequentially sampled peripheral blood mononuclear cells and sera were collected to determine immune profiles and to analyze the T cell response to a spike peptide pool and B cell specificity to the receptor-binding domain (RBD). Anti-spike antibodies were detectable in 6 of 22 RA patients after 1 dose of vaccine with increasing titers after each booster dose, although the overall response was lower compared with that in healthy control individuals. Responding patients after the first dose were more likely to have RA antibodies and a higher baseline proportion of circulating follicular B cells. In RA patients, the mRNA vaccine elicited a robust CD4+ T response to a spike peptide pool following the first and second doses. Consistent with the serologies, RBD-specific B cells exhibited a modest increase after the first dose and the second dose resulted in marked increases only in a fraction of the RA patients to both ancestral and omicron RBD. Our results highlight the importance of multidose COVID-19 vaccination in RA patients to develop a protective humoral response. However, these patients rapidly develop specific T CD4+ responses, despite delayed B cell responses.
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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".