Altered germinal center outputs to SARS-CoV-2 mRNA vaccination in inflammatory bowel disease patients treated with anti-TNF biologics 2707
Bibliographic record
Abstract
Abstract Description The impact of anti-cytokine therapies on vaccine-induced immunity is incompletely understood. The IMmune resPonse After Covid-19 vaccination during maintenance Therapy (IMPACT) study investigated the immunogenicity of the SARS-CoV-2 mRNA vaccines in patients with inflammatory bowel disease (IBD), treated with anti-TNF or anti-IL-12/23. Blood was collected pre and post 1-4 doses of BNT162b2 or mRNA-1273 vaccines. IBD patients showed greater waning of cellular and humoral immunity by 3 months post dose 2 compared to healthy controls (HC). Booster doses prolonged responses, albeit anti-TNF treated IBD patients showed reduced antibody titers across 4 vaccine doses. Spike (S)-specific memory B cells (MBCs) from HC, anti-TNF and anti-IL-12/23 treated IBD patients revealed predominant extrafollicular responses in anti-TNF treated patients, as indicated by higher proportions of marginal zone-like B cells and atypical MBCs, and lower proportions of classical MBCs. Anti-TNF treated patients also had lower plasma IgG:IgM ratios. MBCs from anti-TNF patients had less somatic hypermutation and their plasma IgG responses were of lower avidity. Thus, anti-TNF biologics impair humoral immunity to SARS-CoV-2 as revealed by low S-specific Ig titers, decreased affinity maturation, and extrafollicular-skewed memory responses, consistent with the inhibition of germinal center responses by TNF blockade. In contrast, treatment with anti-IL-12/23 had minimal impact on humoral immunity to vaccination. Funding Sources Supported by the Canadian Graduate Scholarship Doctoral Award (MWC), Canadian Institutes of Health research grants VR-1 172 711, GA2-177716 (to THW and ACG) and by a donation from Juan and Stefania Speck. THW holds the Canada Research Chair in Anti-viral Immunity at the University of Toronto; ACG is the Canada Research Chair in Functional Proteomics. Topic Categories Immune Mechanisms of Human Disease (HUM)
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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) | 0.002 | 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".