Targeted Quantitative Metabolomics and Lipidomics Reveal Dysregulated Metabolic Networks and a Serum Candidate Biomarker for Atrial Fibrillation.

BACKGROUND

Atrial fibrillation (AF) is the most prevalent clinical arrhythmia with severe cardiovascular complications, yet its metabolic molecular mechanisms remain poorly defined. Omics-based metabolic profiling provides a powerful strategy to systematically decode AF-associated metabolic disorders.

METHODS

In this work, high-coverage targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics and lipidomics were applied to absolutely quantify 746 serum metabolites from AF patients and healthy controls.

RESULTS

We systematically characterized global metabolic perturbations in AF serum, including impaired fatty acid metabolism, suppressed mitochondrial β-oxidation, myocardial lipotoxic lipid accumulation, and systemic depletion of glycerophospholipids. Global multiscale embedded correlation network analysis (MECNA) further identified 11 AF-specific dysregulated metabolic modules and core hub metabolites driving metabolic remodeling. Leveraging binary logistic regression, we constructed and independently validated a two-molecule diagnostic biomarker panel to distinguish AF patients from healthy subjects. The combined biomarkers Phe-Trp and FA 22:5 achieved outstanding diagnostic performance, with area under the curve (AUC) values of 0.964 in the discovery cohort and 0.993 in the validation cohort.

CONCLUSIONS

Collectively, this study adopts high-depth targeted quantitative omics to comprehensively map AF metabolic signatures, dissect disease-relevant metabolic networks, and establish a robust serum biomarker panel with great translational potential for non-invasive AF clinical diagnosis.