Evidence map›Paper›PMID 41906614›Full record

ArticleJACC. Advances2026

Unveiling Phenotypic Heterogeneity in Coronary Spastic Angina Through Multidimensional Risk Profiling: The FUJI-SPASM Study.

Takamitsu Nakamura, Tuan Hoang Nguyen, Takeo Horikoshi, Juntaro Deyama, Manabu Uematsu, Toru Yoshizaki, Tsuyoshi Kobayashi, Kazuto Nakamura, Akira Sato

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Article in JACC. Advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Takamitsu NakamuraDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan. Electronic address: takanaka@yamanashi.ac.jp.
Tuan Hoang NguyenDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Takeo HorikoshiDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Juntaro DeyamaDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Manabu UematsuDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Toru YoshizakiDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Tsuyoshi KobayashiDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Kazuto NakamuraDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.
Akira SatoDepartment of Cardiovascular Medicine, University of Yamanashi Faculty of Medicine, Chuo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCoronary spastic angina (CSA) is a functional coronary disorder causing recurrent ischemia without significant atherosclerosis, but the interaction between metabolic and inflammatory abnormalities remains unclear.

objectivesThe purpose of this study was to identify clinically meaningful CSA phenotypes based on metabolic and inflammatory profiles and to determine phenotype-specific determinants of coronary spasm and endothelial dysfunction.

methodsWe analyzed 568 patients with suspected CSA and no obstructive coronary artery disease from the FUJI-SPASM (Feature-based Understanding of Joint Investigation for coronary Spasm Phenotypes and Associated Stratified Mechanisms) registry. Coronary spasm was assessed using intracoronary acetylcholine provocation testing. Unsupervised k-means clustering was performed using 20 standardized clinical and biochemical variables. Phenotype-specific determinants of spasm were identified using adaptive least absolute shrinkage and selection operator regression followed by multivariable logistic regression within each cluster. Endothelial function was assessed by flow-mediated dilation in a subset of 159 patients.

resultsTwo phenotypes were identified. Cluster 0 (n = 231) showed metabolically dominant profiles with atherogenic dyslipidemia and insulin resistance, whereas cluster 1 (n = 337) showed inflammation-dominant profiles with preserved lipid levels but elevated high-sensitivity C-reactive protein (hs-CRP). Lower high-density lipoprotein cholesterol (HDL-C) was associated with coronary spasm in both clusters, while higher hs-CRP was independently associated with spasm only in the inflammation-dominant cluster. An HDL-C/hs-CRP-based stratification demonstrated a graded increase in spasm prevalence and worsening endothelial function.

conclusionsCSA comprises distinct metabolic and inflammatory phenotypes with differing determinants of coronary spasm and endothelial dysfunction. Reduced HDL-C represents a shared vulnerability across phenotypes, while inflammation confers additional risk. HDL-C/hs-CRP-based stratification provides a clinically accessible framework for individualized CSA risk assessment.

Indexed as

acetylcholine testcoronary spasmendothelial dysfunctioninflammatory phenotypemetabolic phenotypeprincipal component analysis

Identifiers

PMID41906614
PMCPMC13352000

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