Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.

Journal: Frontiers in immunology

PMID: 40276515

Abstract

BACKGROUND: The bile acid metabolism (BAM) and fatty acid metabolism (FAM) have been implicated in Kawasaki disease (KD), but their precise mechanisms remain unclear. Identifying signature cells and genes related to BAM and FAM could offer a deeper understanding of their role in the pathogenesis of KD.

Authors

Chenhui Feng

Capital Institute of Pediatrics-Peking University Teaching Hospital, Beijing, China.
Zhimiao Wei

Department of Cardiovascular Medicine, Children's Hospital Capital Institute of Pediatrics, Beijing, China.
Xiaohui Li

Department of Ophthalmology, Ningbo Yinzhou No.2 Hospital, Ningbo Urology and Nephrology Hospital, Ningbo, Zhejiang, China.

Keywords

Biomarkers Fatty Acids Gene Expression Profiling Humans Machine Learning Monocytes Mucocutaneous Lymph Node Syndrome Sequence Analysis, RNA Single-Cell Analysis Transcriptome

External Resources

View on PubMed Access via DOI PubMed (40276515)

Identification of novel metabolism-related biomarkers of Kawasaki disease by integrating single-cell RNA sequencing analysis and machine learning algorithms.

Abstract

Authors

Keywords

External Resources

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