Sandwich immunoassay for soluble glycoprotein VI in patients with symptomatic coronary artery disease.
Despite promising results, the ROC curves for pGPVI have provided a rather low diagnostic sensitivity and specificity, with limited assessment for clinical decision making processed by flow cytometry. Moreover, the availability of this technical method is limited to a few academic health centers that offer a suitable infrastructure with around-the-clock laboratory facilities. Therefore, the development and validation of an ELISA or sandwich immunoassay would be desirable to reliably detect platelet-specific plasmatic soluble GPVI (sGPVI). Thus, we and others began to determine the concentration of sGPVI in smaller groups of patients (8, 9, 12, 13).
The aim of this project was to develop a sandwich immunoassay to reliably measure sGPVI and validate the novel assay in a large group of patients with symptomatic coronary artery disease (CAD).
Materials and Methods
We evaluated the concentration of sGPVI in 2438 consecutive patients with symptomatic CAD who underwent coronary angiography; 1371 patients presented with SAP, 724 with non-ST-elevation myocardial infarction (NSTEMI), and 343 with ST-elevation MI (STEMI). Categorization of ACS was according to the American Heart Association/American College of Cardiology guidelines (14). Inasubgroup of 1011 patients, we measured the surface expression of pGPVI by flow cytometry in 655 patients with SAP, 276 with NSTEMI, and 80 with STEMI. Exclusion criteria were age <18 years, inability to give or lack of informed consent, and noncoronary cause of chest pain. The study was approved by the local ethics committee of the University Hospital Tubingen and performed in accordance with the Declaration of Helsinki.
SAMPLE COLLECTION AND PLASMA PREPARATION
Blood samples were drawn from the antecubital vein and collected at the time of admission to the hospital. We measured troponin I immediately by use of the TnI-Ultra assay measured on an Advia-Centaur System (both from Siemens Healthcare Diagnostics) and C-reactive protein (CRP) by use of Siemens hsCRP Ad-via2120 (Siemens Medical, Solutions Diagnostics GmbH). Blood for the platelet biomarker assessment in 5-mL heparinized vials (for sGPVI determination) and 5-mL citrate phosphate dextrose adenine vials (for pGPVI determination) was processed and analyzed immediately by flow cytometry to determine the surface expression of platelet receptors (pGPVI and GPIb) as described (4, 5). For analysis of sGPVI, heparin-anticoagulated blood was centrifuged at 3000g for 15 min at 4 [degrees]C. Two thirds of the supernatant were placed in aliquots, immediately frozen in liquid nitrogen, and stored at--78 [degrees]C until analysis. After thawing, samples were spun at 13 000g for 10 min at 4 [degrees]C. We used heparin-plasma samples for the measurement of sGPVI throughout assay development and study.
GENERATION OF MONOCLONAL ANTIBODY AGAINST HUMAN GPVI
Rat monoclonal antibodies (mAbs) against human GPVI were developed and generated as described (15). Seven positive clones of antibodies have been identified against sGPVI (5C4, 5D4, 6C2, 7E11, 8A2, 8C3, and
PREPARATION OF sGPVI-FREE PLASMA
We prepared a HiTrap NHS-activated HP 1-mL column (GE Healthcare) as specified bythe manufacturer using 1 mg mAb (5C4) reactive with human sGPVI. We applied 800 [micro]L plasma to the column and depleted sGPVI and used the sGPVI-depleted plasma as matrix for the determination of assay imprecision, assay recovery, and analyte stability.
BEAD-BASED SANDWICH IMMUNOASSAY FOR sGPVI
Plasma concentrations of sGPVI were determined by use of a bead-based sandwich immunoassay and mAb 8E9 reactive with human GPVI as capture antibody. The antibody was covalently bound to color-coded magnetic polystyrene microspheres (Luminex) as described (16). Dilutions of plasma or standards were incubated together with 2000 antibody-coated microspheres in a 96-well PCR plate (ThermoFisher) in a magnetic particle handler (KingFisher96, ThermoFisher) for 1 h at 25[degrees]C, mixing with medium frequency. BSA-coated microspheres were used as a negative control. After the capturing step, microspheres were transferred to another PCR plate containing a biotinylated GPVI-specific detection antibody (1 mg/L, mAb 8A2) using a magnetic particle handler (KingFisher96, ThermoFisher). Incubation with the detection antibody was carried out for 1 h at 25 [degrees]C. The final detection step was performed by transferring the microspheres into a third PCR plate containing a streptavidin-phycoerythrin conjugate solution (2.5 mg/L, Prozyme) for 45 min at 25 [degrees]C. We transferred the microtiter plate into a Luminex 100 instrument and acquired data according to the manufacturer's instructions. We obtained background data of the assay using microspheres incubated with 10% mouse plasma in Roche Blocking Buffer for ELISA (Roche) containing 0.1% Tween. Recombinant sGPVI was generated as described and used as reference (15). GPVI standard was diluted in Roche Blocking Buffer for ELISA plus 10% mouse serum (Sigma). We calculated plasma concentrations of sGPVI according to a 4-parametriclogarithmic fit of the standard fluorescein.
For imprecision analysis, 3 different amounts recombinant sGPVI were spiked into 2% sGPVIdepleted human plasma (25, 6.25, and 1.55 [micro]g/L) reflecting high, medium, and low plasma concentration. These 3 samples were diluted 50-fold to match the working range of the sandwich immunoassay. We measured intraassay imprecision by 5 determinations per concentration and interassay precision from 5 independent assays. Aliquots of the samples were prepared, frozen, and assayed in 5 replicates on 5 days.
We measured the surface expression of pGPVI and GPIb by 2-color whole-blood flow cytometry, as described (4, 5), using mean fluorescence intensity (MFI) as the index of receptor expression. Fluoresceinisothiocyanate-conjugated anti-GPVI mAb 4C9 was generated and characterized as described (4, 5), and phycoerythrin-conjugated anti-CD42b (clone SZ2) mAbs were purchased from Immunotec (Beckman Coulter).
A P value < 0.05 was considered statistical significant after evaluation with appropriate nonparametric tests. Values are presented as mean (SD). Thus, for pairwise comparisons of SAP, NSTEMI, and STEMI, we applied a Kruskal-Wallis test. For correction of multiple testing of the pairwise comparisons, we performed a Bonferroni-Holm correction. Adjustment by possible confounders, such as medical treatment at the time of admission, classic cardiovascular risk factors, and laboratory markers, was performed by the multifactorial ANOVA for the decadic logarithm of sGPVI. We assessed predictive values of sGPVI and pGPVI for the development of ACS by applying binary logistic regression analysis. Using ROC curves, we determined the optimum cutoff value of sGPVI and pGPVI for ACS. To assess a statistical difference between the areas under the curves (AUCs) of sGPVI and pGPVI in ROC analysis, we applied a DeLong test using Analyse-it for Microsoft Excel (version 2.20) http://www.analyse-it. com/. All other statistical analyses were performed using PASW Statistics software for Windows version 18.0, 2009 (IBM SPSS).
Our study population comprised 2438 consecutive patients with symptomatic CAD who underwent coronary angiography. Thus, patients showed either SAP (n = 1371) or ACS (n = 1067); of the ACS patients, 724 presented with NSTEMI and 343 with STEMI. Details of the demographic data are presented in Table 1.
To develop a sandwich immunoassay for determination of sGPVI in plasma, we screened 7 mAbs against each other for their capability to serve as capture or detector molecules. The assay was developed on a magnetic suspension-bead array platform (Luminex, L100) (16). The best antibody pair was selected according to the best signal-to-noise ratio (S/N) by dividing the fluorescence signal gained at 125 ng/L sGPVI standard and no standard (Fig. 1A). Additionally, we tested the antibodies for crossreactivity to mouse sGPVI to identify a suitable dilution matrix for recombinant sGPVI (data not shown). Results revealed no cross-reactivity of the antibodies for mouse sGPVI. Therefore, commercially available mouse serum was used as matrix for preparing standard dilutions. A typical calibration curve in 10% mouse serum is shown in Fig. 1B. Recovery of recombinant sGPVI was between 80% and 120% across the range of the dose-response curve from 8 to 500 ng/L (Fig. 1C). Intraassay CVs did not exceed 7%, and interassay CVs did not exceed 14% (Table 2). Values for assay recovery are identical with intraassay imprecision because no certified standard is available.
[FIGURE 1 OMITTED]
The same samples were used for studying analyte stability. For this purpose, we subjected aliquots to 0, 1, 2, 3, or 4 freeze-thaw cycles. For each cycle, samples were frozen in liquid nitrogen and thawed at 37 [degrees]C. Results revealed no effects of the freeze-thaw procedure (Table 3). Variation of the results were close to the determined intraassay imprecision (Tables 2 and 3).
Patients with NSTEMI and STEMI had significantly lower sGPVI concentrations than patients with SAP [8.4 (3.6) [micro]g/L and 8.6 (4.1) [micro]g/L vs 9.8 (4.8) [micro]g/L; P = 0.002] (Fig. 2A), whereas the subgroup anal ysis showed a significantlyincreased surface expression of pGPVI in NSTEMI (n = 276) and STEMI (n = 80) compared with SAP (n = 655) [MFI21.2 (8.1) and 19.8 (6.8) vs 18.5 (7.7); P = 0.002 and P = 0.018] (Fig. 2B). Comparing the itemized ACS groups of NSTEMI and STEMI, neither sGPVI (P = 0.424) nor pGPVI (P = 0.652) showed any significant difference between these groups.
We found a poor, inverse correlation of pGPVI and sGPVI (r =-0.076; P = 0.023) (Fig. 2C). The AUC in ROC analysis was 0.716 and 95% CI 0.6810.751 for sGPVI, distinguishing patients with SAP from those with ACS and was superior (DeLong test: P = 0.044) to the curve of the subgroup analysis for pGPVI (AUC 0.624; 95%CI 0.586-0.662) (Fig. 2D). Applying ROC curves, we determined cutoffvalues for the identification of ACS, which were 8.75 [micro]g/L for sGPVI and 18.6 MFI for pGPVI, respectively. The cutoff value of 8.75 [micro]g/L yielded a diagnostic sensitivity of 72.6% and a diagnostic specificity of 61.4%.
[FIGURE 2 OMITTED]
To test whether sGPVI is influenced by confounders, comparison of the decadic logarithm of GPVI between ACS and SAP was adjusted by possible confounders such as age, sex, cardiovascular risk factors, and medical treatment. Multifactorial analysis of covariance revealed an independent sGPVI concentration between ACS and SAP (P = 0.040).
Compared with troponin I (P = 0.055), sGPVI (P = 0.023) was more negatively and pGPVI (P = 0.028) more positively associated with the development of ACS in the very early stage of disease at hospital admission, according to binarylogistic regression analysis (Table 4).
The major findings of this study are that (a)wewere able to develop a novel bead-based sandwich immunoassay to reliably measure sGPVI and validate the assayin a large group of patients with a symptomatic CAD; (b) area under the ROC curve analysis of sGPVI helped distinguish patients with ACS from those with SAP better than that of pGPVI; (c) surface expression of pGPVI and plasma concentration of sGPVI showed a poor inverse correlation; and (d) sGPVI was more negatively and pGPVI more positively associated with the development of ACS than conventional laboratory markers in the very early stage of the disease.
Although the mechanisms of plaque-mediated arterial thrombosis and their diagnostic and therapeutic implications are understood, some issues need further clarification. Current diagnostic concepts ofestablished biomarkers still focus on a rather late stage of the disease, demonstrating the effects of inflammation, myocardial stretch, and necrosis (17, 18). Thus, preliminary platelet activation is emerging as a promising target. Concentrations of
P-selectin (CD62P) may reflect increased platelet activation and have been shown to have a predictive and prognostic value in acute ischemic events. Unlike pGPVI, this marker was also found in endothelial cells and, as such, suffers from being nonspecific for platelets (1, 19, 20). Therefore, we attempted to validate pGPVI as a potential diagnostic tool for the identification of acute ischemic events such as ACS and ischemic stroke (4, 5, 11). The diagnostic sensitivity and specificity of flow cytometry, however, were rather too low to allow adequate clinical decision-making, necessitating a different technical method by developing a sandwich immunoassay for the determination of plasmatic sGPVI (5).
Based on promising test series and examination of smaller groups of healthy donors, as well as patients with cerebro- or cardiovascular diseases, by us and other groups (8, 9, 12, 13), we created an assay that proved stable and reproducible (Tables 2 and 3; Fig. 1).
In ROC analysis, the sGPVI assay showed an improved AUC compared with the flow-cytometric results of pGPVI (P = 0.044). Moreover, sGPVI (P = 0.023) was more negatively and pGPVI (P = 0.028) more positively associated with the development of ACS than other conventional laboratory markers such as troponin I (P = 0.055) in the very early stage of disease at hospital admission, according to binary logistic regression analysis.
Intriguingly, we found a poor, inverse correlation of an increased surface expression of pGPVI and lower plasma concentrations of sGPVI in patients with ACS. It is well known that pGPVI shows constitutive expression (1). On the one hand, activated platelets show enhanced surface expression of collagen receptor pGPVI in ACS as determined by flow cytometry, in accordance with previous findings (4, 5). On the other hand, platelet activation induces matrix metalloproteinase-dependent pGPVI cleavage, which is followed by an ectodomain shedding of sGPVI (21, 22). This shedding is regulated by at least 3 different types of platelet-expressed proteinases/sheddases (23). Because pGPVI is the key to both types of responses, platelet aggregation and phosphatidylserine expression, loss of pGPVI-mediated phosphatidylserine exposure may result in reduced prothrombinase activity (24). Thus, pGPVI cleavage may protect from thrombosis, and released sGPVI may act as an inhibitor of atherothrombosis (22). Several studies have shown that sGPVI may inhibit platelet adhesion and aggregation to the injured vessel wall in the murine model, and with that may substantially attenuate atheroprogression and endothelial dysfunction (15, 25, 26). These antithrombotic effects of sGPVI described earlier referred to experiments with the dimeric, recombinant form of sGPVI instead of the metalloproteinase-induced shedding of sGPVI, however, a difference that should be taken into consideration. Therefore, it could be speculated that plasma sGPVI binds to sites of vascular injury where collagen is exposed and with that consumed or removed from circulation in patients with ACS, whereas patients with SAP do not present with any substantial plaque rupture.
The pathophysiological mechanism of recombinant sGPVI has been targeted for vascular lesion--directed antiplatelet treatment without systemic effects on circulating platelets in humans. In contrast to the previous idea to apply anti-GPVI antibodies, which has been critically compromised by a prolonged bleeding time (in particular, with a concomitant administration of aspirin (27)), administration of sGPVI may offer an alternative, safer therapeutic pathway. To date, a cooperative study has performed studies on this therapeutic principle and accomplished a phase I study that examined safety and pharmacokinetic and -dynamic profiles of an sGPVI called Revacept[R] in healthy volunteers in a single-center, open-label, dose-escalating study with 5 doses (28). Furthermore, a specially designed bifunctional protein of sGPVI may catch progenitor cells to induce reendothelialization of vascular lesions (29).
Although we performed an adjustment for possible confounders, a limitation of this study is that patients had not been examined for genetic polymorphisms and GPVI-related clinical defects (30, 31). However, as Arthur et al. (31) have criticallyobserved, although the study by Ollikainen et al. (30) found that C-allele carriers were associated with coronary thrombosis, there has been no differentiation between homozygotes and heterozygotes, and only1.4% presented a homozygote genotype (30, 31). Therefore, the relevance and frequency of innate issues of GPVI remain low.
Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.
Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the Disclosures of Potential Conflict of Interest form. Potential conflicts of interest:
Employment or Leadership: T. Joos, Director Strategic Alliances, EDI GmbH part-time position.
Consultant or Advisory Role: T. Joos, Luminex Inc. and Rules Based Medicine Inc.
Stock Ownership: T. Joos, Luminex Inc.
Honoraria: T. Geisler, the Medicines Company.
Research Funding: B. Bigalke, program of Applied Clinical Research (AKF) of the University of Tubingen (no. 231-0-0) and grant of the German Cardiac Society (DGK) "molecular imaging of atherosclerotic plaques"; E. Nagel, Philips Healthcare and Bayer Schering Pharma; M. Gawaz, Deutsche Forschungsgemeinschaft (MA2186/ 3-1&GK794) and Sonderforschungsbereich/Transregio19 "Inflammatorische Kardiomyopathie-Molekulare Pathogenese und Therapie" (DFG:Li849/3-1;SFB:SFB-TR19-B8N). Expert Testimony: None declared.
Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, or preparation or approval of manuscript.
Acknowledgments: We thank Christina Flaum, Franka Marz, and Ariadne Seither for expert technical assistance.
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Boris Bigalke, [1,2] * Oliver Potz,  Elisabeth Kremmer,  Tobias Geisler,  Peter Seizer,  Valentina O. Puntmann,  Alkystis Phinikaridou,  Amedeo Chiribiri,  Eike Nage [l,2] Rene M. Botnar,  Thomas Joos,  and Meinrad Gawaz 
 Medizinische Klinik, Klinik fur Kardiologie und Kreislauferkrankungen, Eberhard Karls-Universitat Tubingen, Germany;  Division of Imaging Sciences, School of Medicine, King's College London, The Rayne Institute, London, UK;  Biochemistry Department, NMI--Natural and Medical Sciences Institute at the University of Tubingen, Reutlingen, Germany;  Institute for Molecular Immunology, Helmholtz Zentrum Munchen, Munich, Germany;  Cardiovascular Section, Department of Experimental Medicine, Division of Investigative Sciences, Imperial College London, London, UK.
* Address correspondence to this author at: Medizinische Klinik III, EberhardKarls-Universitat Tubingen, Otfried-Muller-Str. 10, D-72076 Tubingen, Ger many. Fax +49-7071-295749; e-mail email@example.com.
Received November 5, 2010; accepted March 24, 2011.
Previously published online at DOI: 10.1373/clinchem.2010.158527
 Nonstandard abbreviations: ACS, acute coronary syndrome; pGPVI, platelet collagen receptor glycoprotein VI; SAP, stable angina pectoris; ECG, electrocardiogram; sGPVI, soluble GPVI; CAD, coronary artery disease; NSTEMI, non-STelevation myocardial infarction; STEMI, ST-elevation MI; CRP, C-reactive protein; mAb, monoclonal antibody; MFI, mean fluorescence intensity; AUC, area under the curve; S/N, signal-to-noise ratio.
Table 1. Patient characteristics and medical treatment at hospital admission. (a) All ACS SAP n 2438 1067 1371 Mean age, years (SD) 67.4 (11.2) 67.6 (11) 67.3 (11.4) Sex Female 687 (28.2) 277 (26) 410 (29.9) Male 1751 (71.8) 790 (74) 961 (70.1) Cardiovascular risk factors Arterial hypertension 1921 (78.8) 822 (77) 1099 (80.2) Hyperlipidemia 1705 (69.9) 770 (72.2) 935 (68.2) Diabetes 781 (32) 325 (30.5) 456(33.3) Family history of 469 (19.2) 196 (18.4) 273 (19.9) CAD Smoking 998 (40.9) 448 (42) 550 (40.1) Coronary artery disease One vessel 783 (32.1) 366 (34.3) 417 (30.4) Two vessels 802 (32.9) 303 (28.4) 499 (36.4) Three vessels 853 (35) 398 (37.3) 455 (33.2) Left ventricular ejection fraction Normal 1287 (52.8) 565 (53) 722 (52.7) Slightly reduced 552 (22.7) 239 (22.4) 313(22.8) Moderate 323 (13.2) 132 (12.4) 191 (13.9) Low 276 (11.3) 131 (12.2) 145 (10.6) Medication ACE inhibitors 1372 (56.3) 654 (61.3) 718(52.4) Angiotensin receptor 284 (11.7) 114(10.7) 170 (12.4) blockers Beta blockers 1609 (66) 687 (64.4) 922 (67.3) Statins 1299 (53.3) 596 (55.9) 703 (51.3) Aspirin 1270 (52.1) 545 (51.1) 725 (52.9) Clopidogrel 215(8.8) 62 (5.8) 153(11.2) Vitamin K antagonist 236 (9.7) 97 (9.1) 139(10.1) (a) Data are n (%) unless noted otherwise. Table 2. Assay imprecision.a Intraassay variability Interassay variability (n = 5) (n = 5) Expected value sGPVI, SD, CV, % sGPVI, SD, CV, % ng/L ng/L ng/L ng/L 500 ng/L 438 4 1 462 51 11 125 ng/L 108 3 3 118 16 14 31 ng/L 34 2 7 34 5 14 (a) Intra- and interassay precision was determined by assaying 3 samples containing high, medium, and low amounts of recombinant sGPVI spiked into 2% GPVI-depleted human plasma, frozen, and stored at -20 [degrees]C. Samples were measured independently 5 times in 5 replicates. Table 3. Analyte stability after 4 freeze-thaw cycles. (a) Expected sGPVI, SD, CV, value ng/L ng/L % 500 ng/L 516 43 8 125 ng/L 118 7 6 31 ng/L 33 2 6 (a) Analyte stability was determined from assaying 3 samples containing high, medium, and low amounts of recombinant sGPVI after 0, 1, 2, 3, or 4 freeze-thaw cycles. Table 4. Associations of sGPVI and pGPVI with development of ACS. P Odds 95% CI ratio sGPVI, [micro]g/L 0.023 0.959 0.925-0.994 pGPVI, MFI 0.028 1.083 1.008-1.163 Troponin I, [micro]g/L 0.055 1.075 0.998-1.158 Creatine kinase, U/L 0.377 1.001 0.999-1.002 CRP, X10 mg/L 0.586 1.063 0.853-1.324
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|Title Annotation:||Proteomics and Protein Markers|
|Author:||Bigalke, Boris; Potz, Oliver; Kremmer, Elisabeth; Geisler, Tobias; Seizer, Peter; Puntmann, Valentin|
|Date:||Jun 1, 2011|
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