ArticleScientific reports2018
Combinational Biomarkers for Atrial Fibrillation Derived from Atrial Appendage and Plasma Metabolomics Analysis.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 35 citations in OpenAlex.
- Gut microbiome and atrial fibrillation: mechanistic insights metabolites and comorbidities. Systematic review.Gut microbes · 2025Pooled it
- Targeted Quantitative Metabolomics and Lipidomics Reveal Dysregulated Metabolic Networks and a Serum Candidate Biomarker for Atrial Fibrillation.Metabolites · 2026Article
- Metabolic and Inflammatory Mechanisms Driving Atrial Fibrillation.Annual review of pharmacology and toxicology · 2026Review
- Metabolomics in Atrial Fibrillation: Unlocking Novel Biomarkers and Pathways for Diagnosis, Prognosis, and Personalized Treatment.Journal of clinical medicine · 2024Review
- Integrated untargeted/targeted metabolomics identifies a putative oxylipin signature in patients with atrial fibrillation and coronary heart disease.Journal of translational internal medicine · 2024Article
- Metabolomics and Biomarkers for Paroxysmal and Persistent Atrial Fibrillation.Journal of the American Heart Association · 2024Article
- Metabolomic Profiles, Ideal Cardiovascular Health, and Risk of Heart Failure and Atrial Fibrillation: Insights From the Framingham Heart Study.Journal of the American Heart Association · 2023Article
- The Emerging Role of N-Methyl-D-Aspartate (NMDA) Receptors in the Cardiovascular System: Physiological Implications, Pathological Consequences, and Therapeutic Perspectives.International journal of molecular sciences · 2023Review
- The relationship between atrial fibrillation and NLRP3 inflammasome: a gut microbiota perspective.Frontiers in immunology · 2023Review
- Gut microbiota, dysbiosis and atrial fibrillation. Arrhythmogenic mechanisms and potential clinical implications.Cardiovascular research · 2022Review
- Construction of Prediction Model for Atrial Fibrillation with Valvular Heart Disease Based on Machine Learning.Reviews in cardiovascular medicine · 2022Article
- Association of Bitter Metabolites and Flavonoid Synthesis Pathway in Jujube Fruit.Frontiers in nutrition · 2022Article
- Finding a new job: glutamate signaling acts in atrial cardiomyocytes.Cell research · 2021Article
- Transcriptomic Profiling of Canine Atrial Fibrillation Models After One Week of Sustained Arrhythmia.Circulation. Arrhythmia and electrophysiology · 2021Article
- Multicohort Metabolomics Analysis Discloses 9-Decenoylcarnitine to Be Associated With Incident Atrial Fibrillation.Journal of the American Heart Association · 2021Article
- Choline Metabolism and Risk of Atrial Fibrillation and Heart Failure in the PREDIMED Study.Clinical chemistry · 2021Article
- High Plasma Glutamate and a Low Glutamine-to-Glutamate Ratio Are Associated with Increased Risk of Heart Failure but Not Atrial Fibrillation in the Prevención con Dieta Mediterránea (PREDIMED) Study.The Journal of nutrition · 2020Article
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Authors and funding
7 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Atrial fibrillation (AF) is one of the most common types of arrhythmias and often leads to clinical complications. The objectives of this study were to offer insights into the metabolites of AF and to determine biomarkers for AF diagnosis or prediction. Sixty atrial appendage samples (AF group: 30; non-AF group: 30) and 163 plasma samples (AF group: 48; non-AF group: 115) from 49 AF patients and 116 non-AF patients were subjected to liquid chromatography positive ion electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) metabolomics analysis. Consequently, 24 metabolites in atrial appendage samples and 24 metabolites in plasma samples were found to reflect metabolic differences between AF and non-AF patients (variable importance in projection (VIP) ≥ 1, P ≤ 0.05). Five identical metabolites including creatinine, D-glutamic acid, choline, hypoxanthine, and niacinamide (VIP ≥ 1.5, P < 0.01, FDR < 0.05) in atrial appendage and plasma samples were considered prominent features of AF patients, and the D-glutamine and D-glutamate metabolic pathway was also identified as a feature of AF patients. Finally, in plasma samples, the combination of D-glutamic acid, creatinine, and choline had an AUC value of 0.927 (95% CI: 0.875-0.979, P < 0.001) and displayed 90.5% sensitivity and 83.3% specificity; this group of metabolites was thus defined as a combinational biomarker for the recognition of AF and non-AF patients.
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