Serum Metabolomic Profiling for Acute Myocardial Infarction Based on Nuclear Magnetic Resonance Spectroscopy
Bing He, Zhengyi Sun, Chunyu Wang, Yiting Wang, Xuewen Li, Qi Zhou, Zhiguo Zhang, Jiancheng XuABSTRACT
Acute myocardial infarction (AMI) is a leading cause of mortality and morbidity worldwide, and early accurate diagnosis is critical for improving patient prognosis. Current clinical diagnostic methods have inherent limitations and delays, creating an urgent need for reliable novel biomarkers. This study aims to identify differential biomarkers between AMI patients and healthy controls using nuclear magnetic resonance ( 1 H NMR) serum metabolic profiling and to explore their associated metabolic pathways. Serum samples from 32 AMI patients and 42 healthy controls were analyzed based on 1 H NMR spectroscopy. Potential biomarkers of AMI were identified and screened using multivariate data analysis. MetaboAnalyst 5.0, an online software, was used for serum metabolic pathway analysis. Moreover, Spearman correlation analysis revealed the correlation between the potential biomarkers and clinical biochemical variables. Finally, the diagnostic model was further constructed using the receiver operating characteristic (ROC) curves to validate the diagnostic performance of the potential biomarkers for AMI. By integrating multivariate analysis, pathway enrichment, and correlation analysis with clinical parameters, this study identified coordinated metabolic reprogramming across energy, amino acid, and lipid metabolism in patients with AMI. We identified 13 representative metabolites as potential biomarkers for AMI patients. Compared with the healthy control group, the AMI group showed upregulation of 10 metabolites and downregulation of 3 metabolites. Furthermore, the diagnostic model constructed based on key metabolites can effectively distinguish between AMI patients and healthy controls. This study revealed metabolomic signatures of AMI, identified potential targets for novel early diagnostic biomarkers, and provided a reference for metabolomics research in cardiovascular diseases.