The Role of T-cell Costimulation in the Pathogenesis of Kawasaki Disease
Bibliographic record
Abstract
Kawasaki disease (KD) is a multisystem vasculitis that mainly targets the coronary arteries in young children. Both environmental factors along with genetic factors play a role in the susceptibility, severity and response to treatment of KD. Regardless of the initial trigger of the immune response in KD, the role of costimulatory signals remain a critical component in the survival of T-cells and the pathogenesis of the disease. Genome wide association studies have found costimulatory molecules to be associated with KD. In this work we show that, enhanced costimulation rescued superantigen-stimulated T-cells from apoptosis. CD28 mediated signaling resulted in up-regulation of the anti-apoptotic factors, Bcl-xL and cFLIP. Bcl-xL expression was dependent on costimulatory signals and decreased with administration of CTLA-4Ig. Furthermore, expression of survival molecules cFLIP, MCL1 and NAIP were significantly upregulated in patients who did not respond to IVIG treatment. Taken together, our findings point to the important role of costimulation in the immunopathology of KD. Moreover, activation of another costimulatory molecule CD40 (via CD40L) resulted in significantly elevate lymphocyte proliferation in combination with superantigen activation. However, splenocytes from CD28 knockout mice do not exhibit this elevated response and the CD28 antagonist CTLA4-Ig was able to mimic the effects seen in the splenocytes from CD28 knockout mice. This suggests that CD28 is the intermediary that mediates the proliferative effects of CD40 activation. Furthermore, the role of platelets the largest source of sCD40L was examined. Through co-culturing experiments CD40L on activated platelets was shown to promote both splenocyte proliferation and T-cell survival upon SAg stimulation. In vivo experiments using the LCWE mouse model of KD demonstrated that coronary aneurysms are reduced in the absence of CD40L. Hence, our results indicate that costimulation mediates T-cell survival in both mice and man developing KD and regulates disease severity and treatment response, pointing to a potential new target for treatment. These studies add to our understanding of the molecular mechanisms underpinning the immunopathology of KD and identify potential biomarkers of disease and novel targets for therapy.
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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 | 0.001 |
| 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".