Metabolomics and Biomarkers for Paroxysmal and Persistent Atrial Fibrillation

Author:

Zhang Li‐Li12,Lin Wen‐Hua3,Di Cheng‐Ye3,Hou Hai‐Tao24,Chen Huan‐Xin24ORCID,Zhou Jie24ORCID,Yang Qin24ORCID,He Guo‐Wei124ORCID

Affiliation:

1. Faculty of Graduate Studies Chengde Medical University, Chengde, China, & Department of Cardiovascular Surgery & The Institute of Cardiovascular Diseases, TEDA International Cardiovascular Hospital, Tianjin University & Chinese Academy of Medical Sciences Tianjin China

2. Tianjin Key Laboratory of Molecular Regulation of Cardiovascular Diseases and Translational Medicine Tianjin China

3. Department of Cardiology & The Institute of Cardiovascular Diseases, TEDA International Cardiovascular Hospital Tianjin University & Chinese Academy of Medical Science Tianjin China

4. Department of Cardiovascular Surgery & The Institute of Cardiovascular Diseases, TEDA International Cardiovascular Hospital Tianjin University & Chinese Academy of Medical Science Tianjin China

Abstract

Background Atrial fibrillation (AF) is the most common type of arrhythmia worldwide and is associated with serious complications. This study investigated the metabolic biomarkers associated with AF and the differences in metabolomics and associated metabolic biomarkers between paroxysmal AF (AFPA) and persistent AF. Methods and Results Plasma samples were prospectively collected from patients with AF and patients in sinus rhythm with negative coronary angiography. The patients were divided into 3 groups: AFPA, persistent AF, and sinus rhythm (N=54). Metabolomics (n=36) using ultra‐high‐performance liquid chromatography mass spectrometry was used to detect differential metabolites that were validated in a new cohort (n=18). The validated metabolites from the validation phase were further analyzed by receiver operating characteristic. Among the 36 differential metabolites detected by omics assay, 4 were successfully validated with area under the curve >0.8 ( P <0.05). Bioinformatics analysis confirmed the enrichment pathways of unsaturated fatty acid biosynthesis, glyoxylate and dicarboxylate metabolism, and carbon metabolism. Arachidonic acid was a potential biomarker of AFPA, glycolic acid and L‐serine were biomarkers of AFPA and persistent AF, and palmitelaidic acid was a biomarker of AFPA. Conclusions In this metabolomics study, we detected 36 differential metabolites in AF, and 4 were validated with high sensitivity and specificity. These differential metabolites are potential biomarkers for diagnosis and monitoring of disease course. This study therefore provides new insights into the precision diagnosis and management of AF.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Cardiology and Cardiovascular Medicine

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