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Gene-expression patterns reveal underlying biological processes in Kawasaki disease
Stephen J Popper1, Chisato Shimizu, Hiroko Shike
1Departments of Microbiology and Immunology, and Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA. spopper@stanford.edu
Genome Biology
|December 11, 2007
Summary
Kawasaki disease (KD) involves dynamic gene expression, particularly in neutrophils, impacting treatment response. Understanding these immune responses may reveal biomarkers for predicting patient outcomes.
Area of Science:
- Immunology
- Genomics
- Pediatric Medicine
Background:
- Kawasaki disease (KD) is a leading cause of acquired pediatric heart disease.
- The etiology and mechanisms of KD, including coronary artery aneurysm formation and fever resolution post-intravenous immunoglobulin (IVIG), are not fully understood.
Purpose of the Study:
- To investigate gene expression patterns in children with KD across different illness phases.
- To identify potential biomarkers for predicting clinical outcomes and treatment response in KD.
Main Methods:
- DNA microarrays were used to analyze gene expression in peripheral whole blood from 20 children with KD during acute, subacute, and convalescent phases.
- Gene expression patterns were validated in a second cohort of 64 patients and specific gene transcript levels (CEACAM1) were confirmed using quantitative reverse transcription PCR in a third cohort of 33 patients.
Main Results:
- Acute KD showed increased transcripts related to innate immunity and inflammation, with decreased natural killer and CD8+ T-cell associated transcripts.
- Significant temporal variations in gene expression were observed during the acute phase, stabilizing later.
- Higher CEACAM1 transcripts correlated with increased unsegmented neutrophils, shorter illness duration, elevated C-reactive protein, and non-response to IVIG.
Conclusions:
- Acute KD exhibits dynamic and variable gene expression programs, emphasizing the role of neutrophil activation and apoptosis in its pathogenesis.
- Gene expression profiles hold potential for identifying biomarkers to predict clinical prognosis in systemic inflammatory illnesses like KD.
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