DOI 10.1016/j.hroo.2026.03.009
Circulating metabolomic profile and its association with atrial fibrillation and systemic inflammation.
Аннотация
BACKGROUND
Atrial fibrillation (AF) is a prevalent arrhythmia associated with chronic inflammation and metabolic dysregulation. Metabolic and inflammatory pathways may influence atrial electrophysiology and structural remodeling, contributing to AF onset and persistence, yet key circulating signatures remain poorly defined.
OBJECTIVE
The purpose of this study was to characterize systemic inflammatory markers and circulating metabolomic profiles in patients with paroxysmal and persistent AF compared with non-AF controls.
METHODS
In this prospective study, 101 patients were enrolled (mean age 59.9 ± 14.7 years; 73/101 [72%] male), including 41 with paroxysmal AF, 30 with persistent AF, and 30 controls. Fasting plasma samples were analyzed using targeted gas chromatography-mass spectrometry to quantify 156 metabolites and multiplex flow cytometry to profile 13 inflammatory cytokines.
RESULTS
Interleukin-18 (IL-18) concentrations were significantly elevated in patients with AF compared with controls (P = .009), with highest levels observed in those with persistent AF. No significant differences were observed in IL-6 or high-sensitivity C-reactive protein. 9 metabolites showed significant differential abundance between patients with AF and controls. Metabolites including pyridoxine, N-acetylglutamine, 3-dehydroquinate, d-glucose, glucosamine, ascorbic acid, and galacturonic acid were reduced in AF, while capric acid and caprylic acid were elevated. β-Alanine was the only metabolite increased in persistent AF relative to both patients with paroxysmal AF and controls. Trimethylamine-N-oxide concentrations did not differ significantly between groups.
CONCLUSION
This study identifies distinct metabolic and inflammatory signatures in AF, with IL-18 and specific energy-related metabolites emerging as potential markers of disease phenotype. These hypothesis-generating findings warrant validation in larger cohorts.
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