ArticlePloS one2025
Identification of potential biomarkers associated with immune cell infiltration patterns in Kawasaki disease via bioinformatics.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Identification and functional characterization of ASCC2 as a diagnostic biomarker and immune regulatory hub in Kawasaki disease.Clinical rheumatology · 2026Article
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4 authors.
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Abstract
Inflammation and immune dysregulation play critical roles in Kawasaki disease (KD) pathogenesis, yet specific biomarkers and immune signatures remain elusive. This study aims to identify key biomarkers and characterize immune cell infiltration scores in KD using bioinformatic approaches. The GSE73461 dataset, downloaded from the Gene Expression Omnibus (GEO) database, includes 78 KD patients and 55 normal controls collected by Imperial College London from 2015 to 2023, and was analyzed to identify differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant involvement of these DEGs in acute inflammatory responses, plasma membrane components, PI3K-Akt signaling, and cytokine interactions. Protein-protein interaction (PPI) network was constructed, and five candidate hub genes (AURKB, BUB1, CCL2, IL-4, and TOP2A) were identified. Immune cell infiltration analysis gusing the XCell algorithm showed increased levels of Monocytes, neutrophils, and other immune cells in KD, while B cells and T cells were decreased. Correlation analysis indicated that these candidate hub genes are associated with immune dysregulation and inflammation in KD. These findings provide potential diagnostic biomarkers and therapeutic targets for KD, warranting further validation in larger studies.
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