Leveraging Redox Signatures from Patient-Derived Vascular and Immune Cells to Unlock Diagnostic and Therapeutic Targets in Coronary Artery Disease

Abstract

Background

Despite major advances in therapy, cardiovascular disease (CVD) remains the leading global cause of death and primary prevention remains inadequate. Increasingly, individuals present with CVD in the absence of standard modifiable risk factors (SMuRFs), exposing limitations in current detection strategies. Coronary artery disease (CAD), driven by atherosclerotic plaque accumulation, is a major contributor. Reliance on symptoms and traditional risk factors fails to identify SMuRF-less individuals, highlighting the need for novel blood-based biomarkers.

The BioHEART-CT study recruits patients with suspected CAD and integrates clinical data, biospecimens, and quantitative CT measures of plaque burden. Endothelial dysfunction and mitochondrial dysregulation are early features of CAD. Endothelial colony-forming cells (ECFCs) retain disease-specific phenotypes and provide a surrogate for patient-specific vascular biology. We previously identified an association between mitochondrial reactive oxygen species (mROS) in ECFCs and CAD severity. To improve clinical translatability, we assessed whether these findings extend to peripheral blood mononuclear cells (PBMCs).

Aims

To identify genetic differences between CAD and non-CAD ECFCs, evaluate mROS for CAD detection, investigate myeloperoxidase (MPO) expression, assess mROS in PBMCs, and examine CCBE1 as a novel biomarker.

Methods and Results

Transcriptomic and functional analyses identified CCBE1 as a differentially expressed mitochondrial regulator and candidate biomarker. A high-throughput imaging assay quantified mROS for scalable screening. MPO expression was inversely associated with CAD. mROS in PBMCs showed limited association with disease, whereas CCBE1 expression in PBMCs was inversely associated with CAD.

Conclusion

This thesis establishes ECFCs as a robust model for biomarker discovery and identifies CCBE1 as a promising minimally invasive biomarker, advancing precision approaches for CAD detection.