Tryptophan metabolism-related biomarkers ADM, MCEMP1, and TSPO in acute myocardial infarction: insights from bioinformatics and machine learning

Background Emerging evidence indicates that intermediates of tryptophan metabolism were decreased in acute myocardial infarction (AMI) patients. However, underlying mechanisms linking tryptophan metabolism to AMI pathogenesis remain poorly characterized. This study systematically investigates the role of tryptophan metabolism in AMI through multi-omics integration. Methods Tryptophan metabolism-related genes (TMRGs) were retrieved from the MSigDB database and analyzed using weighted gene co-expression network analysis and differential expression analysis to identify AMI-associated candidates. Four machine-learning algorithms (LASSO regression, XGBoost, RF, and SVM-RFE) were applied to screen biomarkers and construct a diagnostic model, which was subsequently validated by qPCR. Gene set enrichment, immune infiltration, and regulatory network analyses were performed to elucidate biomarker functions. Molecular docking identified potential target drugs, followed by 100 ns molecular dynamics simulations of drug molecules and target proteins using the GAFF force field. Single-cell data were employed to identify key cell populations and transcriptional regulators. Results Five candidate biomarkers were identified, among which ADM, MCEMP1, and TSPO were selected to establish a diagnostic model with potential clinical utility. Immune infiltration analysis implicated monocytes and neutrophils in AMI progression and demonstrated their significant correlation with these biomarkers. Molecular docking revealed a strong binding affinity between TSPO and ONO-2952, which was confirmed as stable by molecular dynamics simulations. Single-cell and SCENIC analyses further highlighted monocytes as central players in AMI and identified TFEC and CEBPD as key transcription factors regulating biomarker expression. Discussion Our findings suggest that dysregulation of tryptophan metabolism contributes to AMI progression mainly through immune cell activation and inflammatory remodeling. The identified biomarkers-ADM, MCEMP1, and TSPO-may bridge metabolic disturbances and immune dysfunction, providing mechanistic insights into AMI pathology. Furthermore, the interaction between TSPO and ONO-2952 highlights the therapeutic potential of targeting metabolic-immune crosstalk in cardiovascular disease. Conclusion This study comprehensively investigates the association between tryptophan metabolism and acute myocardial infarction, identifying three biomarkers and two therapeutic targets. Our findings provide a novel perception of AMI pathogenesis and give to the diagnosis of AMI.