Comprehensive metabolomic and proteomic analyses reveal candidate biomarkers and related metabolic networks in atrial fibrillation

• Published in: Metabolomics 2019-07, Vol.15 (7), p.96-96, Article 96
• Main Authors: Zhou, Juntuo, Sun, Lijie, Chen, Liwen, Liu, Shuwang, Zhong, Lijun, Cui, Ming
• Format: Article
• Language: English
• Subjects: Aged; Area Under Curve; Atrial Fibrillation - metabolism; Atrial Fibrillation - pathology; Biochemistry; Biomarkers; Biomarkers - blood; Biomedical and Life Sciences; Biomedicine; Cardiac arrhythmia; Case-Control Studies; Cell Biology; Chromatography, High Pressure Liquid; Congestive heart failure; Dementia disorders; Developmental Biology; Enzyme-Linked Immunosorbent Assay; Fatty Acids - analysis; Fatty Acids - metabolism; Female; Fibrillation; Humans; Life Sciences; Lipid metabolism; Male; Mass Spectrometry; Metabolic networks; Metabolic Networks and Pathways; Metabolic pathways; Metabolism; Metabolites; Metabolomics; Metabolomics - methods; Middle Aged; Molecular Medicine; Original Article; Principal Component Analysis; Proteomics; Proteomics - methods; ROC Curve
• ISSN: 1573-3882; 1573-3890
• DOI: 10.1007/s11306-019-1557-7

Introduction Atrial fibrillation (AF) is an abnormal heart rhythm characterized by an irregular beating of the atria and is associated with an increased risk of heart failure, dementia, and stroke. Currently, the perturbation of plasma content due to AF disease onset is not well known. Objectives To investigate dysregulated molecules in blood plasma of untreated AF patients, with the goal of identifying biomarkers for disease screening and pathological studies. Methods LC-MS based untargeted metabolomics, lipidomics and proteomics analyses were performed to find candidate biomarkers. A targeted quantification assay and an ELISA were performed to validate the results of the omics analyses. Results We found that 24 metabolites, 16 lipids and 16 proteins were significantly dysregulated in AF patients. Pathway enrichment analysis showed that the purine metabolic pathway and fatty acid metabolism were perturbed by AF onset. FA 20:2 and FA 22:4 show great linear correlational relationship with the left atrial area and could be considered for AF disease stage monitoring or prognosis evaluation. Conclusion we used a comprehensive multiple-omics strategy to systematically investigate the dysregulated molecules in the plasma of AF patients, thereby revealing potential biomarkers for diagnosis and providing information for pathological studies.