Crucial transcripts predict response to initial immunoglobulin treatment in acute Kawasaki disease

Abstract

Although intravenous immunoglobulin (IVIG) can effectively treat Kawasaki disease (KD), 10–20% of KD patients show no beneficial clinical response. Developing reliable criteria to discriminate non-responders is important for early planning of appropriate regimens. To predict the non-responders before IVIG treatment, gene expression dataset of 110 responders and 61 non-responders was obtained from Gene Expression Omnibus. After weighted gene co-expression network analysis, we found that modules positively correlated with the non-responders were mainly associated with myeloid cell activation. Transcripts up-regulated in the non-responders, IL1R2, GK, HK3, C5orf32, CXCL16, NAMPT and EMILIN2, were proven to play key roles via interaction with other transcripts in co-expression network. The crucial transcripts may affect the clinical response to IVIG treatment in acute KD. And these transcripts may serve as biomarkers and therapeutic targets for precise diagnosis and treatment of the non-responders.

Negative Regulation of the IL-1 System by IL-1R2 and IL-1R8: Relevance in Pathophysiology and Disease

“…At the transcriptional level, IL1R2 was part of a signature related to myeloid cell activation which was highly expressed in non-responder Kawasaki patients following immunoglobulin infusion ( 89 ), and of a signature associated with immune infiltrate in acute myocardial infarction ( 90 ). Finally, transcriptional and protein analysis showed that IL-1R2 was a favorable prognostic marker in ulcerative colitis, being up-regulated in intestinal mucosal cells from ulcerative colitis patients in remission phase ( 91 ).…”

Boolean analysis of the transcriptomic data to identify novel biomarkers of IVIG response

“…Several studies have attempted to identify biomarkers of IVIG response in various autoimmune diseases. In accordance with the therapeutic use of IVIG in autoimmune and inflammatory diseases, most of these markers followed the trend of either inflammatory cells like platelet, lymphocyte and neutrophil counts or molecules that are the hall marks of inflammation such as alanine aminotransferase, matrix metalloproteinase-8 C-reactive protein, neutrophilderived elastase, inflammatory cytokines and chemokines or their receptors (IL-6, IL-1, TNF, G-CSF, CCR2), damage-associated molecular patterns like High mobility group box protein 1 (HMGB-1), S100 calcium-binding protein A8 (S100A8), S100A9 [13][14][15][16][17][18][19]. However, specificity and/or sensitivity of these markers are the major issues.…”

Single-Cell Analysis Reveals the Role of the Neuropeptide Receptor FPR2 in Monocytes in Kawasaki Disease: A Bioinformatic Study

“…Furthermore, correlation analysis can identify modules and genes that are significantly associated with clinical features. WGCNA has been used to identify key transcription factors that predict response to initial immunoglobulin therapy in acute KD [ 21 ]. Therefore, we believe that in combination with scRNA-seq analysis and bioinformatic techniques, WGCNA can facilitate investigations into the role of neuropeptide-related genes in the monocyte-mediated pathogenesis of KD.…”