Reduced response to SARS-CoV-2 vaccination is associated with impaired immunoglobulin class switch recombination in SLE patients
Bibliographic record
Abstract
INTRODUCTION: Systemic lupus erythematosus (SLE) patients exhibit B-cell abnormalities. Although there are concerns about reduced antibody responses to SARS-CoV-2 vaccines, detailed data on B-cell-specific responses in SLE remain scarce. Understanding the responsiveness to novel vaccine antigens, and boosters number, is important to avoid unnecessarily prolonged isolation of immunocompromised individuals. We assessed humoral and antigen-specific B-cell subset responses, including changes in isotype switching, prior to and after several doses of SARS-CoV-2 vaccines. METHODS: Blood samples were obtained prior to and after SARS-CoV-2 vaccination from cross-sectional and longitudinal cohorts of previously uninfected patients with SLE (n = 93). Healthy participants receiving SARS-CoV-2 vaccines were recruited as controls (n = 135). We measured serum antibody titres, their neutralizing capacity, and vaccine-specific memory B-cell subsets. RESULTS: Impaired IgG, IgA, and neutralizing responses against the original and various SARS-CoV-2 variants were observed following two doses of vaccine in SLE patients. Follow-up booster doses increased humoral responses compared to baseline, but they remained lower, with poorer neutralisation capacity against most strains, compared to healthy individuals after three or more doses. Analysis of memory B-cell subsets in SLE patients revealed an increase of SARS-CoV-2-specific isotype unswitched IgM+ over SARS-CoV-2-specific isotype switched IgG+/IgA+ memory B-cells compared to healthy individuals. Culturing healthy naive B-cells with high levels of IFNα, a hallmark of SLE pathogenesis, prevented B-cells from switching to IgG under IgG-polarizing conditions. CONCLUSION: SLE patients' protection against SARS-CoV-2 is overall impaired compared to healthy individuals and is associated with a class switch defect possibly due to chronic exposure of B-cells to IFNα.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".