Abstract Body (Do not enter title and authors here): Background Coronary spastic angina (CSA) is a functional coronary disorder characterized by transient epicardial constriction in the absence of significant atherosclerosis. However, its clinical phenotypes remain poorly defined, and the contributions of metabolic and inflammatory factors to CSA susceptibility and vascular dysfunction are not fully understood.
Hypothesis We hypothesized that distinct CSA phenotypes can be identified through multidimensional profiling of metabolic and inflammatory stress, and that these phenotypes are associated with differences in endothelial function and spasm risk.
Methods We analyzed data from the FUJI-SPASM study, a prospective single-center registry of 1,125 patients undergoing intracoronary acetylcholine testing. Among them, 568 patients without obstructive coronary artery disease who presented ischemic symptoms were included. Unsupervised k-means clustering was applied to 19 standardized clinical and biochemical variables, including lipid and apolipoprotein profiles, glycemic indices (HOMA-IR, HbA1c), inflammatory markers (CRP, fibrinogen), and demographic factors. Principal component analysis (PCA) was then performed to extract latent axes of biological variation.
Results Clustering identified two phenotypes. Cluster 0 (metabolic phenotype) showed elevated triglycerides, non-HDL-C, apoB, apoC2, apoC3, FFA, and HOMA-IR. Cluster 1 (inflammatory phenotype) was characterized by higher CRP, fibrinogen, older age, and higher smoking. The frequency of CSA did not significantly differ between clusters (46% vs. 39%, p = 0.10). PCA revealed two principal components: PC1, primarily loaded with atherogenic lipids and insulin resistance indices, and PC2, characterized by positive loadings for CRP and fibrinogen and inverse loadings for HDL-related apolipoproteins—representing metabolic and inflammatory burdens, respectively. In a subanalysis of 159 patients with flow-mediated dilation (FMD) data, those with high PC1 and PC2 scores had significantly lower FMD values (p < 0.001) and higher CSA positivity (p < 0.05), suggesting cumulative vascular impact of metabolic and inflammatory stress.
Conclusion This study identified two clinically relevant CSA phenotypes defined by metabolic and inflammatory profiles. PCA further demonstrated that a dual burden of these biological stresses is closely linked to endothelial dysfunction and increased CSA risk. These findings support a phenotype-based, multidimensional approach to CSA evaluation.