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Published in: Journal of Cardiovascular Translational Research 1/2024

09-08-2023 | Sudden Cardiac Death | Original Article

Metabolomics Profiling Predicts Ventricular Arrhythmia in Patients with an Implantable Cardioverter Defibrillator

Authors: Shengwen Yang, Junhan Zhao, Xi Liu, Jing Wang, Min Gu, Chi Cai, Hongxia Niu, Liang Chen, Wei Hua

Published in: Journal of Cardiovascular Translational Research | Issue 1/2024

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Abstract

Implantable cardioverter defibrillators (ICDs) reduce sudden cardiac death (SCD) when patients experience life-threatening ventricular arrhythmias (LTVA). However, current strategies determining ICD patient selection and risk stratification are inefficient. We used metabolomics to assess whether dysregulated metabolites are associated with LTVA and identify potential biomarkers. Baseline plasma samples were collected from 72 patients receiving ICDs. Over a median follow-up of 524.0 days (range 239.0–705.5), LTVA occurred in 23 (31.9%) patients (22 effective ICD treatments and 1 SCD). After confounding risk factors adjustment for age, smoking, secondary prevention, and creatine kinase MB, 23 metabolites were significantly associated with LTVA. Pathway analysis revealed LTVA associations with disrupted metabolism of glycine, serine, threonine, and branched chain amino acids. Pathway enrichment analysis identified a panel of 6 metabolites that potentially predicted LTVA, with an area under the receiver operating characteristic curve of 0.8. Future studies are necessary on biological mechanisms and potential clinical use.

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Metadata
Title
Metabolomics Profiling Predicts Ventricular Arrhythmia in Patients with an Implantable Cardioverter Defibrillator
Authors
Shengwen Yang
Junhan Zhao
Xi Liu
Jing Wang
Min Gu
Chi Cai
Hongxia Niu
Liang Chen
Wei Hua
Publication date
09-08-2023
Publisher
Springer US
Published in
Journal of Cardiovascular Translational Research / Issue 1/2024
Print ISSN: 1937-5387
Electronic ISSN: 1937-5395
DOI
https://doi.org/10.1007/s12265-023-10413-6

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