Development of a liquid chromatography–mass spectrometry based targeted metabolomics method for discovering diagnostic biomarkers in Kawasaki disease

Xialin Luo, Jiaqi Tian, Qing Li, Zhonggan Jin, Xiaoyu Fan, Hong Zhang, Haitao Lv*, Yi Ju*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

Abstract

Kawasaki disease (KD) has emerged as the leading cause of acquired heart disease in children, primarily due to the absence of highly sensitive and specific biomarkers for early and accurate diagnosis. To address this issue, a simple and comprehensive targeted metabolomics method employing ultra high-performance liquid chromatography coupled with Q-TRAP mass spectrometry has been developed to identify new metabolite biomarkers for KD. This method enables the simultaneous quantification of 276 metabolites, covering 60 metabolic pathways, with a particular emphasis on metabolites relevant to KD. The use of nine ISs and commercial quality control samples significantly enhances both accuracy and precision. Through validation and application to serum samples from patients with KD, seventeen differential serum metabolites were identified. The altered metabolites are primarily associated with three functional metabolic pathways: tricarboxylic acid cycle, tryptophan metabolism, and bile acid metabolism, all of which are believed to be involved in the inflammatory and immune responses in KD patients. Ultimately, eight differential metabolites (indole-3-propionic acid, thiamine, indolepyruvic acid, levodopa, l-selenomethionine, isocitric acid, trans-aconitate, and N-acetylasparagine) were identified that could potentially serve as diagnostic biomarkers with the area under the curve values exceeding 0.9. Our targeted metabolomics approach demonstrates applicability in identifying potential metabolite biomarkers for KD and holds great promise in unraveling the intricate pathophysiology of the disease.
Original languageEnglish
Article number465619
Number of pages9
JournalJournal of Chromatography A
Volume1741
Early online date20 Dec 2024
DOIs
Publication statusE-pub ahead of print - 20 Dec 2024

User-Defined Keywords

  • Kawasaki disease
  • Liquid chromatography
  • Mass spectrometry
  • Metabolite biomarkers
  • Metabolomics

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