Inositol-Triphosphate 3-Kinase C Mediates Inflammasome Activation and Treatment Response in Kawasaki Disease
Bibliographic record
Abstract
Kawasaki disease (KD) is a multisystem vasculitis that predominantly targets the coronary arteries in children. Phenotypic similarities between KD and recurrent fever syndromes point to the potential role of inflammasome activation in KD. Mutations in NLRP3 are associated with recurrent fever/autoinflammatory syndromes. We show that the KD-associated genetic polymorphism in inositol-triphosphate 3-kinase C (ITPKC) (rs28493229) has important functional consequences, governing ITPKC protein levels and thereby intracellular calcium, which in turn regulates NLRP3 expression and production of IL-1β and IL-18. Analysis of transcript abundance, protein levels, and cellular response profiles from matched, serial biospecimens from a cohort of genotyped KD subjects points to the critical role of ITPKC in mediating NLRP3 inflammasome activation. Treatment failure in those with the high-risk ITPKC genotype was associated with the highest basal and stimulated intracellular calcium levels and with increased cellular production of IL-1β and IL-18 and higher circulating levels of both cytokines. Mechanistic studies using Itpkc-deficient mice in a disease model support the genomic, cellular, and clinical findings in affected children. Our findings provide the mechanism behind the observed efficacy of rescue therapy with IL-1 blockade in recalcitrant KD, and we identify that regulation of calcium mobilization is fundamental to the underlying immunobiology in KD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".