Polyclonal Vβ21.3 expansion in multisystem inflammatory syndrome in children despite SARS-CoV-2 vaccination
Bibliographic record
Abstract
Multisystem inflammatory syndrome in children (MIS-C) is a severe SARS-CoV-2-associated condition that shares clinical features with Kawasaki disease (KD), characterised by a distinct polyclonal expansion of Vβ21.3+ T cells. We report five patients diagnosed with breakthrough MIS-C despite COVID-19 immunisation, all within a limited time period at the beginning of the Omicron wave, to assess whether breakthrough MIS-C cases share the same TCR Vβ21.3 skewing seen in non-vaccinated MIS-C cases. We retrospectively reviewed five MIS-C patients hospitalised between December 2021 and April 2022 despite previous immunisation against SARS-CoV-2 (BNT162b2, an mRNA vaccine against S-protein). Immunophenotyping, including TCR Vβ subset distribution, was performed in four patients.Patients (100% male, 12.2-17.2 years) had a natural breakthrough SARS-CoV-2 infection following prior immunisation (between August 2021 and February 2022). Recent infection was proven by positive SARS-CoV-2 PCR and/or IgG antibodies against the nucleocapsid protein. Blood samples of four patients were available. All presented with Vβ21.3+ T cell expansion, similar to MIS-C patients and in contrast to vaccinated historical KD patients (n=10). The two patients with the earliest sampling post-illness displayed frequencies of Vβ21.3+ T cells exceeding the reference mean value+10×SD. These Vβ21.3+ T cells showed increased surface expression of activation (HLA-DR, CD38) and exhaustion (PD-1, TIM-3) markers.In conclusion, breakthrough MIS-C patients presented with features consistent with unvaccinated MIS-C patients, including the hallmark Vβ21.3+ T cell expansion, indicating that prior immunisation with an mRNA vaccine targeting the Wuhan strain did not fully protect against MIS-C at the wave of a novel emerging variant early 2022. Trial registration number: NL41023.018.12.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".