HLA class I–associated expansion of TRBV11-2 T cells in multisystem inflammatory syndrome in children
Bibliographic record
Abstract
Multisystem inflammatory syndrome in children (MIS-C), a hyperinflammatory syndrome associated with SARS-CoV-2 infection, shares clinical features with toxic shock syndrome, which is triggered by bacterial superantigens. Superantigen specificity for different Vβ chains results in Vβ skewing, whereby T cells with specific Vβ chains and diverse antigen specificity are overrepresented in the T cell receptor (TCR) repertoire. Here, we characterized the TCR repertoire of MIS-C patients and found a profound expansion of TCRβ variable gene 11-2 (TRBV11-2), with up to 24% of clonal T cell space occupied by TRBV11-2 T cells, which correlated with MIS-C severity and serum cytokine levels. Analysis of TRBJ gene usage and complementarity-determining region 3 (CDR3) length distribution of MIS-C expanded TRBV11-2 clones revealed extensive junctional diversity. Patients with TRBV11-2 expansion shared HLA class I alleles A02, B35, and C04, indicating what we believe is a novel mechanism for CDR3-independent T cell expansion. In silico modeling indicated that polyacidic residues in the Vβ chain encoded by TRBV11-2 (Vβ21.3) strongly interact with the superantigen-like motif of SARS-CoV-2 spike glycoprotein, suggesting that unprocessed SARS-CoV-2 spike may directly mediate TRBV11-2 expansion. Overall, our data indicate that a CDR3-independent interaction between SARS-CoV-2 spike and TCR leads to T cell expansion and possibly activation, which may account for the clinical presentation of MIS-C.
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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".