An Artificial Intelligence-guided signature reveals the shared host immune response in MIS-C and Kawasaki disease

Pradipta Ghosh1,2, Gajanan D Katkar3, Chisato Shimizu4,5

  • 1Department of Cellular and Molecular Medicine, University of California San Diego, San Diego, USA. prghosh@ucsd.edu.

Insights

Multisystem inflammatory syndrome in children (MIS-C) and Kawasaki disease (KD) are related inflammatory conditions. MIS-C is more severe, sharing immune pathways but differing in specific cytokine profiles and clinical outcomes.

Area of Science:

  • Immunology
  • Pediatrics
  • Virology

Background:

  • Multisystem inflammatory syndrome in children (MIS-C) emerged during the COVID-19 pandemic.
  • MIS-C shares clinical features with Kawasaki disease (KD), a pre-pandemic syndrome.
  • Understanding the relationship between MIS-C, KD, and COVID-19 is crucial for pediatric health.

Purpose of the Study:

  • To compare MIS-C and KD using gene expression signatures.
  • To elucidate the shared and distinct immunopathogenesis pathways.
  • To identify biomarkers for monitoring MIS-C severity.

Main Methods:

  • Utilized viral pandemic (ViP) and severe-ViP gene signatures alongside a KD diagnostic signature.
  • Analyzed whole blood RNA sequences, serum cytokines, and cardiac tissues.
  • Employed computational analysis to compare gene expression patterns.

Main Results:

  • KD and MIS-C lie on a continuum of the immune response to COVID-19.
  • Both syndromes exhibit an IL15/IL15RA-centric cytokine storm, indicating shared pathways.
  • MIS-C demonstrates unique targetable cytokine pathways and greater severity than KD.

Conclusions:

  • MIS-C and KD share immunopathogenesis but diverge in clinical and laboratory parameters.
  • ViP signatures differentiate MIS-C severity and identify potential therapeutic targets.
  • Clinical indicators like reduced cardiac function, thrombocytopenia, and eosinopenia are key for monitoring MIS-C severity.

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