Proteins were selected for evaluation in this study based on their roles in mechanisms underlying atherogenesis, atherosclerosis and plaque instability including vascular inflammation, thrombosis, aberrant lipid regulation, metabolism hormones, and vascular smooth muscle and extracellular matrix (ECM) remodeling . The 41 preliminary targets we interrogated were restricted by availability of monoclonal antibody pairs optimized for use in the commercial assay platforms. IL-1β, IL-6, IL-10 and VCAM-1, were significantly elevated in patients with CAD in the present study consistent with an injury-induced, inflammatory response [15, 16]. Elevated IL-1β and IL-6 have been associated previously with acute phase protein induction and may explain the concomitant significant increases in fibrinogen and CRP concentration we detected. CRP has long been proposed as a surrogate marker for inflammatory mediators in predicting coronary events while NT-pBNP has been used as an indicator of left ventricular dysfunction in CAD patient cohorts comparable to this study [11, 17, 18]. Both analytes were significantly elevated in the present study among patients requiring therapeutic intervention and CRP was among the best single molecule classifiers delineating 19% of normal samples while detecting 95% of the patients with significant CAD.
Significant reciprocal changes were detected in APO-A1 and APO-B100 in CAD patients consistent with reports defining aberrant lipid transport and accumulation as contributory to atherosclerosis . Mutations in the APO-B100 gene cause autosomal dominant, hereditary familial hypercholesterolemia and premature coronary artery disease due to defective ligand binding [19, 20]. At the same time, elevated APO-A1 is associated with a cardioprotective effect and enhancement of APO-A1 expression has been proposed as a therapeutic strategy to inhibit atheroma formation [19, 21]. The increased APO-B100 and decreased APO-A1 levels in our patients requiring PCI versus normal controls support these previous findings. Myeloperoxidase was also significantly increased in CAD patients associated with its role as a catalyst for lipid peroxidation at inflammation sites and as a marker of plaque instability [22, 23]. Resistin levels were elevated in the PCI patients indicative of 1) metabolic shifts in lipid utilization and adipogenesis and/or 2) an inflammatory response with resistin secreted from macrophages concomitant with the release of proinflammatory cytokines .
Many targets traditionally associated with vascular smooth muscle and ECM remodeling were not significantly altered among these patient groups including matrix metalloproteinases 1, 2, 3, 7, 9 and tissue inhibitors of metalloproteinases 1, 2, 3 and 4. Only osteopontin, which acts as a negative regulator of calcification in bone remodeling, was elevated within this category with the rejoinder that OPN also may act as a chemokine in the cell mediated type 1 immune response associated with inflammatory cell accumulation rather than as a substrate for cell adhesion . Thus, the proteins that demarcated our patient outcome groups were predominantly associated with processes of inflammation and lipid regulation rather than cellular aggregation and ECM remodeling. However, we recognize that the domain of proteins susceptible to interrogation in this study was limited to analytes for which high affinity antibody pairs precisely characterized to two different epitopes were available. The involvement of additional proteins and pathways associated with CAD will likely be reinforced and/or revealed as the inventory of immunoassays becomes more comprehensive.
Our data indicate multiplex proteomics analyses using monoclonal antibodies provide relevant information regarding circulating serum analyte concentrations when assayed at a dilution that allows direct comparison to parallel recombinant calibration standards. Advantages include small serum volumes (< 100 μl) collected by standard clinical protocols, rapid turnaround times (minutes to hours), high sensitivity (pg) and a broad dynamic range (8 logs). Disadvantages include high assay cost, limited target availability and poor concurrence of concentration measurements across dilutions and commercial platforms associated with variations in antibodies, buffers, diluents and capture structures. In the present study, 15 targets were tested at identical serum dilutions using bead-based (Luminex) and planar (Aushon) technologies in 56 identical samples, albeit with different aliquots and in serial studies. A total of 12 assays concurred in detection of statistically significant differences between the 2 patient outcome groups. These results suggest that multiplex immunochemical assays of serum may provide information of diagnostic relevance but that protocols and reagents must be optimized and standardized prior to routine clinical application.
The results of this study were somewhat surprising both for discovery of unique proteins as discriminants of CAD and for the absence of statistically significant differences in many targets with established roles in atherosclerosis. For example, osteopontin has been only indirectly associated with atherosclerosis yet exhibited the greatest statistical difference between patient groups (P = 1.75 × 10-12). Osteopontin was first identified as a sialoprotein from mineralized bone matrix and only recently was associated with calcification of plaques in cardiac valves and vessels [25–27]. Similarly, resistin has been linked only indirectly to CAD through a role in metabolic homeostasis and insulin sensitivity . On the other hand, multiple growth factors (VEGF, leptin, ghrelin), lipoproteins (APO-A2, E, serum amyloid A: SAA), cell adhesion molecules (thrombospondin, PECAM-1, ICAM-1, selectins E, L, P) and MMP and TIMP targets associated with ECM remodeling exhibited no statistically significant differences. There are several potential explanations for the latter findings: (1) a rigorous statistical standard was utilized to avoid multiple testing errors and while MMP1, MMP7, ACRP-30, and leptin were borderline for statistical significance (P = 0.015, 0.045, 0.027, 0.027 respectively) they failed to reach the Q = 0.01 level established for significance with adjusted P values ≤ 0.01 in this study; (2) serum may not be an effective transducer of deleterious protein changes participating in structural rearrangements within the coronary vascular anatomy and the extracellular matrix; and (3) the patients comprised a diverse range of coronary obstruction and plaque vulnerability since they were selected for symptoms upon emergent presentation requiring diagnostic coronary angiography without the occurrence of a clinically obvious myocardial infarct or an 'event'. A subset of patients selected for advanced disease might reveal additional protein changes but stray from the intended focus of this study.
A scoring function algorithm was developed, tested and validated for the ability to classify patients symptomatic for heart disease consistent with the outcome of coronary angiography studies and need for interventional therapy. We minimized selection bias by testing a hypothesis driven biomarker panel and avoided overfitting by performing cross validation and follow-up testing utilizing additional serum samples from the cohort. The algorithm was designed to be 'tuned' to increase the sensitivity for capture of patients who required coronary revascularization at the expense of detecting fewer patients who did not require coronary revascularization. All serum signatures with highest classification strength from the training trial (239 samples) included osteopontin and signatures containing 4 or 5 proteins performed best during both training and validation phases. The most efficacious protein signature in validation studies comprised OPN, resistin, MMP7 and IFNγ as a four-marker panel while the addition of either CRP or ACRP-30 yielded comparable results in five protein signatures.
Further validation of the diagnostic accuracy of this approach will require extensive testing in greater numbers of patients at multiple locations as well as a prognostic cohort. It is possible that inclusion of clinical variables and risk factors in the biomarker algorithm or using the algorithm as part of a clinical scoring system will enhance both the fidelity and the efficacy of this approach for diagnostic purposes [29, 30]. In that context, we calculated 10-year Framingham Coronary Heart Disease (CHD) Risk Scores for patients where all clinical variables (gender, age, total cholesterol, HDL, systolic blood pressure, smoking and diabetes status, use of antihypertensive medication) were acquired prior to coronary angiography . This represented 91 patients who subsequently required therapeutic revascularization (CAD: CHD Score = 14.9 ± 8.5) versus 63 patients who were determined to be free of significant coronary artery disease (no CAD: CHD score = 10.2 ± 6.7). The Framingham CHD scores were statistically different between groups (P < 0.001, unpaired Student's t test) but they classified only 16% of the subjects without significant CAD (10 of 63) at a 95% sensitivity for patients with CAD. In contrast, our algorithm incorporating serum values for OPN, RES, CRP, MMP7 and IFNγ identified 63% of the subjects without significant CAD (40 of 63) at 95% sensitivity for patients with CAD. Thus, our multiplex serum protein classifier correctly identified four times as many patients as the Framingham index. The strength of adding clinical variables to our scoring function remains to be determined, but the ability to exempt significant numbers of patients with normal coronary arteries or non-significant CAD from cardiac catheterization with a blood test represents a major economic and health benefit given the growing epidemic of CAD in the US and abroad.