Proteomic Signatures of Coronary Artery Disease and Hypercholesterolemia

Abstract

Background: Coronary artery disease (CAD) is the most common type of cardiovascular disease (CVD), it causes narrowing of the blood vessel lumen due to atherosclerotic plaque formation. Atherosclerosis, is strongly influenced by hypercholesterolemia (HC). Proteomics offers advantages over traditional studies that focus on individual biomarkers. This method provides a holistic view by examining the entire proteomic spectrum in a biological sample, making it an indispensable asset for spotting potential novel protein biomarkers directly linked to atherosclerosis occurrence, progression, and complications such as plaque instability or rupture. Methods: Slow Off-rate Modified Aptamer (SOMAmer)-based protein array was used to quantify proteins. Our cross-sectional study involved healthy controls (n=45), and patients diagnosed with HC (n=51) or CAD (n=32). Proteome data was analyzed using multiple statistical methods. Results: The orthogonal partial least square discriminant analysis (OPLS-DA) revealed a clear separation of the 3 study groups based on two principal components, with R2X= 0.267, R2Y= 0.9, and Q2= 0.28, indicating distinct protein alterations between groups. A total of 1,305 proteins were analyzed and 156 of them in CAD vs control, 140 of them in HC vs control, and 326 of the proteins in CAD vs HC comparisons, were significantly differentially expressed with a p-value<0.05. Among those, q-value<0.05 were determined. As a result, in CAD patients, 2 proteins exhibited significantly differential expressions compared to healthy controls. In contrast, HC patients had 15 significantly altered proteins compared to controls. Furthermore, a comparison between CAD and HC patients revealed 87 significantly regulated proteins. The receiver operating characteristic (ROC) was performed on proteins with distinct expressions ( q<0.05) in pairwise group comparisons. The AUC was calculated to identify potential biomarker candidates for the disease groups. In the CAD vs. control analysis, both significant proteins (PCSK9, SDF-1) exhibited an AUC of 0.75. In the comparison between HC and control groups, out of 15 significantly altered proteins, 7 had an AUC of 0.75 or higher (LRP1B, Apo E, QORL1, Apo E3, Apo B, Transferrin, MMP-3). Among the 87 proteins significantly differentially expressed in CAD versus HC, 59 had an AUC ≥ 0.75. Sixteen of these proteins had an AUC ≥ 0.80. Conclusion: Distinct protein patterns associated with each condition were identified. CAD patients showed a significant increase in the cholesterol-metabolizing protein PCSK9 and varying levels of the angiogenesis-related protein SDF-1. Several other proteins (LRP1B, VAV, CSRP3, HSP 60, and TAK1-TAB1) also exhibited unique expressions in disease groups, suggesting potential roles in atherosclerosis development. Moreover, a statistically significant correlation between SDF-1, ApoB levels, and LDL levels was found in CAD patients but not in healthy controls. This discovery phase cohort study unveils potential biomarkers for atherosclerosis within the HC context. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.