Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation
Authors' conclusion
Poor CCC encompasses distinct immune-metabolic phenotypes that can be accurately classified using integrated proteomic-clinical modeling. This classification enables more precise risk stratification and may guide personalized therapeutic strategies for coronary artery disease patients with inadequate collateralization.
Study context
- Population
- Coronary artery disease patients with good or poor coronary collateral circulation (CCC)80 good CCC, 69 poor CCC
- Participants
- 149 patients
- Exposure
- Poor CCC phenotypes: CDVR vs ITMD
- Cluster 1 (CDVR)n = 39reference
- Cluster 2 (ITMD)n = 30
- Outcome
- Molecular phenotypes in poor CCC
Methodological detailshigh-throughput proteomic profiling, unsupervised consensus clustering, machine learning (XGBoost, SHAP), external validation (MIMIC database)
- High-throughput proteomic profiling
- Unsupervised consensus clustering
- Machine learning (XGBoost, SHAP)
- External validation (MIMIC database)
Main finding
As reported in the abstract
XGBoost model (fasting glucose, eosinophil percentage, HbA1c) discrimination
AUC > 0.91
Observational data: associations, not effects.
Further findings
| Outcome | P value |
|---|---|
| MACE incidenceSignificantly higher with Cluster 2 | Log-rank p < 0.05 |
KEGG pathways in ITMD
- Significant upregulation of platelet activation, diabetic cardiomyopathy and metabolic pathways in ITMD
Original publication
Distinct immune-metabolic phenotypes underlie poor coronary collateral circulation. Cardiovasc Diabetol. Published 18 November 2025. doi:10.
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