Metabolomic profiling of coronary and radial artery samples identifies biomarkers and diagnostic models for coronary microvascular dysfunction

Abstract Background Coronary microvascular dysfunction (CMVD) significantly contributes to cardiovascular morbidity and mortality but remains challenging to diagnose. As an independent predictor of adverse cardiovascular events, CMVD is associated with an increased risk of myocardial infarction and heart failure, necessitating effective diagnostic strategies. Metabolomics can uncover unique metabolic signatures linked to disease states, offering a sensitive approach to discovering novel biomarkers for CMVD. Aims To identify specific metabolites and metabolic pathways altered in CMVD, assess their potential as diagnostic biomarkers, and evaluate the diagnostic accuracy of models combining metabolites from coronary and radial artery samples, using a novel coronary angiography-derived index of microcirculatory resistance (IMR) as the diagnostic reference. Methods In this prospective study, 68 patients undergoing coronary angiography and IMR measurement were enrolled and divided into discovery (n = 40) and validation (n = 28) cohort. In two cohorts, patients were classified into two groups: normal, defined as having an IMR <25 in any of the three main coronary arteries, and abnormal, defined as having an IMR ≥25 in any of these arteries. Blood samples were collected from both coronary and radial arteries, and untargeted metabolomic analysis was performed using liquid chromatography-mass spectrometry. KEGG pathway enrichment analysis was performed on differential metabolites from coronary artery samples and radial artery samples, using data combined from the diagnostic and validation cohorts and all detected metabolites as the background reference. Results Ten differential metabolites were consistently identified in coronary artery samples across both cohorts; three metabolites (N-palmitoylglycine, L-gulose, and 3-hydroxybenzoic acid) were downregulated, and seven were upregulated in patients with abnormal IMR. Two metabolites (glycine and 2-hydroxyethanesulfonic acid) were consistently altered in radial artery samples. KEGG pathway enrichment analysis identified significant involvement in oxidative stress, amino acid biosynthesis, and fatty acid metabolism. Significant correlations were observed between specific metabolites and clinical parameters such as glycated hemoglobin levels, lipoprotein(a), body mass index, and inflammatory markers. Diagnostic models combining metabolites from both coronary and radial artery samples achieved an area under the ROC curve of 0.850 in the discovery cohort and 0.893 in the validation cohort. Conclusion Metabolic alterations involving oxidative stress, inflammation, and energy metabolism are significantly associated with CMVD. Specific metabolites identified may serve as potential biomarkers for CMVD diagnosis. Combining metabolites from both coronary and radial artery samples enhances diagnostic accuracy, suggesting the feasibility of less invasive diagnostic approaches for CMVD.Graphic abstract Study protocol