4.7 Article

Plasma metabolic profiling of patients with tetralogy of fallot

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CLINICA CHIMICA ACTA
卷 548, 期 -, 页码 -

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ELSEVIER
DOI: 10.1016/j.cca.2023.117522

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Congenital heart disease; Tetralogy of fallot; Metabolomics; Absolute quantitative; Mass spectrometry

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This study investigated the plasma metabolic profiles to identify key metabolites for early diagnosis of Tetralogy of Fallot (TOF), a common congenital heart disease. The researchers found significant metabolic differences between TOF patients and normal controls, specifically in nicotinamide and purine metabolism pathways. The study suggests that plasma FAD could serve as a highly valuable biomarker for differentiating TOF from normal. These findings contribute to the development of reliable biomarkers and improving early screening for TOF.
Background: Tetralogy of Fallot (TOF) is a common congenital heart disease with high mortality. However, the medical imageology and liquid biopsy techniques present certain limitations. Thus, this study investigated the plasma metabolic profiles to distinguish key metabolites for early diagnosis of TOF.Methods: In total, 69 patients with TOF and 43 normal controls were enrolled for targeted metabolomics based on liquid chromatography-tandem mass spectroscopy (LC-MS/MS). Absolute quantification of metabolites was performed using our standard database. The differentially expressed metabolites (DEMs) were screened by fold change (FC), VIP value and pearson correlation coefficient of OPLS-DA model. Receiver operating characteristic curve (ROC) was used to evaluate predictive ability of DEMs.Results: Different metabolic profiles were presented between TOF and Normal. The pathway analysis showed that significantly changed metabolites were enriched in nicotinamide and purine metabolism. Many intermediates product of purine and amido acid were higher in TOF than in Normal group, while energy substrates and electron carriers were lower in TOF than in Normal group. ROC analysis revealed a high diagnostic value of plasma FAD for differentiating TOF from Normal (AUC = 1).Conclusion: Our study quantitatively characterized plasma metabolites in patients with TOF and may help to develop reliable biomarkers that contribute to the early TOF screening.

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