PREEXISTING ANTIBODIES AGAINST VACCINE ANTIGENS ARE PRESERVED IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS AND SJÖGREN’S DISEASE UPON IANALUMAB TREATMENT WHILE AUTOANTIBODIES DECLINE
Bibliographic record
Abstract
O062 / #591 Topic:AS24 - SLE-Treatment ABSTRACT CONCURRENT SESSION 10: INTEGRATING PROTEOMIC & TRANSCRIPTOMICS IN SLE 24-05-2025 10:40 AM - 11:40 AM Background/Purpose Ianalumab, an afucosylated monoclonal antibody, depletes B cells through enhanced antibody-dependent cellular cytotoxicity with concurrent blockade of B-cell-activating factor (BAFF):BAFF-receptor (BAFF-R) mediated signals.[1] It is currently being investigated for the treatment of immune-mediated diseases. Given its novel mechanism of action, it is crucial to assess the effects of ianalumab on preexisting antibodies against vaccine antigens. Herein, we evaluated the impact of ianalumab treatment vs placebo on preexisting antibody levels against 7 pathogens in patients with systemic lupus erythematosus (SLE) and Sjögren’s disease (SjD). Methods A retrospective analysis was conducted on serum samples from 2 randomized, double-blind, placebo-controlled phase 2 studies in patients with SjD ( NCT02962895 ) or SLE ( NCT03656562 ). Patients received either placebo or ianalumab 300 mg subcutaneous monthly for 24 weeks (79 patients with SjD) or for 28 weeks (40 patients with SLE). In the SjD study, patients on 300 mg ianalumab at Week 24 (W24) were re-randomized to receive double-blinded monthly ianalumab 300 mg or placebo until W52. Patients on placebo at W24 were switched to a lower ianalumab dose and were not subject to further testing in this analysis. In the SLE study, all patients switched from double-blind to open-label ianalumab up to W52. Antibodies (IgG isotypes) to vaccine antigens and autoantibodies were measured at baseline, W24 (SjD) or W28 (SLE) and W52. Changes in antibody levels from baseline and proportions of patients maintaining protective levels at W52 were assessed. A total of 3 patients (2 SjD and 1 SLE) received booster doses against diphtheria and tetanus toxoid (TTd) under ianalumab treatment. Results The proportion of patients with SjD and SLE maintaining protective levels of antibodies against TTd, measles, mumps, varicella, rubella, diphtheria and influenza remained stable after ianalumab treatment up to 52 weeks. In patients with SjD, the changes from baseline to W24 were <6% for all antigens in both ianalumab- and placebo-treated patients. In patients with SLE, the changes from baseline to W28 were <10% in both ianalumab- and placebo-treated patients for all antigens besides diphtheria (Figure 1). For diphtheria, up to 18% changes were observed under ianalumab treatment, likely due to the low level of preexisting protection (<50% of patients had protective levels at baseline). In contrast, several autoantibodies showed a significant reduction in ianalumab-treated patients (eg, up to 60% reduction of anti-ribosomal P antibodies at W28) compared to placebo (Figure 1). These results are in line with the ability of ianalumab to deplete memory and antibody-producing cells,[2] while likely not affecting the long-lived bone marrow plasma cells that do not express BAFF-R.[3] Among the 3 patients who received booster dose(s) against diphtheria and TTd during ianalumab treatment, 2 showed a subsequent increase in corresponding titers, whereas the other patient received the booster only 10 days before W52 sampling, likely explaining the lack of increased titers. Figure 1. Titers from vaccine antigens and auto-antibody titers following treatment with ianalumab or placebo over time in patients with SLE. Ratio to baseline of antibodies to vaccine antigens and autoantibodies were measured over time in patients with SLE treated with placebo vs ianalumab. All antibodies measured were IgG. Conclusions Treatment with ianalumab up to 52 weeks did not result in a reduction of the antibody titers to previous immunizations against tetanus, varicella, measles, mumps, rubella, diphtheria, and influenza while having a clear impact on autoantibody levels.References:[1.] McWilliams EM. Blood Adv 2019;3(3):447-60. [2.] Dörner T. Ann Rheum Dis 2024;83:956-7. [3.] Darce JR. J Immunol 2007;179(11):7276-86.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".