Transcriptomics in Kawasaki Disease

Tai Ming Ko*, Jan Vincent Beltran, Jou Yu Huang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Transcriptomics is the high-throughput characterization of RNA. It has played an important role in defining the pathogenic characteristics of Kawasaki disease. It has aided in clarifying Kawasaki disease etiology and identifying its key mediators, which will further help to compensate for the limitations of existing intravenous immunoglobulin treatments. In addition, transcriptomics is being used for immune monitoring, diagnostic and prognostic biomarker identification. These features can be applied in stratifying patients, monitoring molecular changes related to disease severity, defining personalized treatment strategies, as well as providing clinical evidence. This chapter discusses the progress of transcriptomics in determining Kawasaki disease etiology and pathogenesis and developing diagnostic and predictive biomarkers. We also explore some analytical methods for extracting valuable information from high-dimensional datasets to improve our biological knowledge. Lastly, we discuss the emerging technology of transcriptomics in the study of the diversity of expression quantitative trait loci, B-cell and T-cell receptor repertoires, and assessment of Kawasaki disease heterogeneity using high-throughput single-cell sequencing.

Original languageEnglish
Title of host publicationKawasaki Disease
PublisherSpringer Nature
Number of pages8
ISBN (Electronic)9789811929441
ISBN (Print)9789811929434
StatePublished - 1 Jan 2022


  • CD177
  • Immune receptor repertoire
  • Intravenous immunoglobulin
  • Kawasaki disease
  • Neutrophil
  • Next-generation sequencing
  • RNA
  • Single-cell analysis
  • Transcriptomics


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