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May 28, 2013 - Individual Platelet Adhesion Assay: Measuring Platelet Function and Antiplatelet Therapies in Whole Blood via Digital Quantification of...
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Individual Platelet Adhesion Assay: Measuring Platelet Function and Antiplatelet Therapies in Whole Blood via Digital Quantification of Cell Adhesion Ana Lopez-Alonso,† Bincy Jose,‡ Martin Somers,‡ Karl Egan,† David P. Foley,§ Antonio J. Ricco,*,‡ Sofia Ramström,*,†,¶ Lourdes Basabe-Desmonts,*,‡,∥ and Dermot Kenny†,⊥ †

Molecular and Cellular Therapeutics and ⊥Biomedical Diagnostics Institute, Royal College of Surgeons in Ireland, Dublin 2, Ireland Biomedical Diagnostics Institute, Dublin City University, Dublin 9, Ireland § Division of Cardiology, Beaumont Hospital, Dublin 2, Ireland ¶ Department of Clinical and Experimental Medicine, Clinical Chemistry, Linköping University, Linköping, Sweden ∥ CIC microGUNE, Polo Innovación Garaia, 20500 Arrasate-Mondragón, Spain, and IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain ‡

S Supporting Information *

ABSTRACT: Widespread monitoring of platelet function and the effect of antiplatelet drugs will improve outcomes in cardiovascular patients, but platelet function testing is not routine in clinical practice. We report a rapid, accurate methodology to quantify platelet-protein interactions: a microarray of contact-printed 6-μm fibrinogen dots on a transparent substrate binds platelets from whole blood, one platelet per dot. The fractional occupancy of an array of fibrinogen dots after a predefined incubation time quantitatively assays platelet adhesion to the protein matrix. We demonstrate this technique by measurement of platelet adhesion to fibrinogen as a means to quantify the effect of the P2Y12 and αIIbβ3 receptor inhibitors cangrelor and abciximab, respectively, both in vitroby incubating the drug with a freshly drawn blood sampleand in blood from patients treated with antiplatelet agents. The effects of single- and dual-antiplatelet therapy are also assessed. Results from this platelet-binding assay are well correlated with standard techniques including flow cytometry and light transmission aggregometry. This assay technology, readily integrated with microfluidic platforms, is generally applicable to the assay of cellprotein interactions and promises more effective, rapid assay of drug effects in cardiovascular disease patients.

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(POC) aggregometry-based tests, which have the advantage of using whole blood and being simpler to execute than laboratory tests. These include ICHOR-Plateletworks and VerifyNow, neither of which, however, is widely used: the former is highly time dependent, must be completed within 10 min, and does not predict adverse cardiovascular outcomes;10 the latter is the most expensive POC platelet function assay on the market, is not flexible, measures only one antiplatelet drug per cartridge type, and uses a substantial (by POC standards) 2 mL of blood per sample.11 VerifyNow also has been shown to have limited dynamic range, with reduced sensitivity at higher levels of antiplatelet drug induced inhibition.12 The above assays share a key characteristic: they measure platelet aggregation, from which platelet function is inferred. Surprisingly, there are few reports of platelet function assays based on adhesion to specific proteins, despite the fact that

ardiovascular disease is the leading cause of mortality in the developed world,1,2 and acute coronary syndromes (ACS) are the major cause of mortality in this group of disorders.3 Platelets play a major role in ACS: platelet-mediated thrombosis is a significant cause of cardiovascular mortality.4,5 Clinical trials demonstrate that use of antiplatelet drugs including aspirin, P2Y12 inhibitors, and αIIbβ3 inhibitors in the management of patients with ACS6 decrease the risk of thrombosis. Efficacy and patient compliance, however, are far from ideal: often, there is poor response to therapy. Moreover, while these drugs can decrease the risk of thrombosis, their use in combination increases the risk of major, even fatal, bleeding events.7,8 The response to antiplatelet drugs is patient specific, and diagnostic assays of platelet function for personalized monitoring of therapies may minimize adverse events and guide appropriate therapy. The gold-standard technique for platelet function testing, light transmission platelet aggregometry (LTA), infers platelet function by measuring the decrease in optical density as platelets aggregate in solution in response to the addition of platelet aggregation agonists.9 There are also point-of-care © XXXX American Chemical Society

Received: April 15, 2013 Accepted: May 28, 2013

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Figure 1. Measuring platelet adhesion to fibrinogen using individual platelet adhesion (iPA) assay. (A) Schematic of the iPA methodology: (i) A 6μm fibrinogen dot array patterned on a glass substrate is made by microcontact printing. (ii) The fibrinogen array is incubated with whole blood, capturing platelets on the fibrinogen dots. Platelets are then inmunostained (green dots) to facilitate their counting. (iii) Two-color fluorescence microscopy images are taken: the red channel (a) shows the protein array and the green channel (b) shows the platelets adhering to the protein dots (iv) Custom software analyzes the two images, representing dots occupied by platelets in green and those remaining empty in red; from the resulting image (c), dot array occupancy (DAO) is quantified. (B) DAO as a function of time for a fibrinogen iPA incubated with whole blood. Error bars represent standard deviations (n = 3).

platelet adhesion is the initiating event in hemostasis and thrombus formation. The few adhesion assays that are available, such as IMPACT-R, have poor accuracy to detect the activity or efficacy of antiplatelet drugs.13 In general, the lack of accurate methods to measure platelet adhesion is compounded by the reliance of many platelet assays upon shear-induced platelet activation to initiate aggregation, a process that obscures the in vivo physiological state of the platelet. The ideal methodology to measure platelet function and the response to antiplatelet drugs would enable quantitative measurement of a physiologically relevant parameter, such as platelet adhesion to specific proteins, closely linked to platelet function and to the status of particular classes of platelet receptors. This assay would be performed directly in whole blood within a short time after a blood draw. We previously reported a method for single-step surface capture of platelets from whole blood using platelet-specific protein patterns immobilized on transparent planar substrates.14 Here, we demonstrate the use of this methodology to enable accurate measurement of platelet adhesion to fibrinogen, enabling quantification of the effects of P2Y12 and αIIbβ3 receptor inhibitors both in vitro (incubation of the drug with a freshly drawn blood sample) and in samples from patients being treated with antiplatelet agents. This new method, individual platelet adhesion (iPA) assay, is surface confined and requires only a fraction of 1 mm2 as an assay area, making it suitable for integration in microfluidic platforms and thereby enabling multiple simultaneous adhesion assays using multiple proteins to target several receptors. The iPA assay methodology has the potential to enable a rapid, accurate POC platform suitable as an adjunct to the administration of multiple

antiplatelet agents; it is extensible to the study and understanding of cell adhesion critical to many different physiological processes.

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EXPERIMENTAL DETAILS In this section we explain the experimental protocols related to the individual platelet adhesion assay and imaging, as well as describing the analysis software of the iPA substrates. A complete description of all the experimental details is included in the Supporting Information. Individual Platelet Adhesion (iPA) Assay. Using a previously described method,14 6-μm-diameter spots of fibrinogen/bovine serum albumin (BSA)-Cy3 (ratio 8:1) were arrayed onto glass slides by microcontact printing. The glass slides were then blocked with 1% BSA (10 mg/mL) by incubation for 1 h at room temperature. Protein arrays were shown to be stable and reproducible for up to 2 weeks when kept at 4 °C in the dark. To measure platelet adhesion, whole blood (1 mL) was added to the protein array and placed in a 35-mm-diameter Petri dish on a “see-saw” rocking platform (Stuart SSL4, Stone, Staffordshire, U.K.), and incubated at 35 oscillations/min for 30 min at room temperature. The glass slides were washed with HEPES buffer (20 mM 4-(2hydroxyethyl)-1-piperazineethanesulfonic acid, 137 mM NaCl, 2.7 mM KCl, 1 mM MgCl2, 5.6 mM glucose, 1 g/L BSA; pH 7.40) and then fixed with 3.7% paraformaldehyde (PFA). The fixing step was done to preserve the structure of the platelets on the substrate after incubation and to enable sample storage and subsequent imaging. This step would not be required if the imaging of the adhering platelets were done in real time or shortly after the incubation. For platelet staining, the glass slides B

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Figure 2. iPA detects the effect of αIIbβ3 inhibition by abciximab. (A) Representative fluorescence images of glass substrates supporting fibrinogen dot arrays (left) and with fluorescently labeled adherent platelets (center). Arrays were incubated for 30 min with whole blood containing increasing concentrations (from top to bottom) of abciximab. DAO is depicted in the right-hand column. (B) Plot of abciximab effect on a healthy, drug-free donor’s blood measured by iPA. Error bars represent standard deviation of the replicates (two samples from the same donor). (C) Comparison of abciximab effect measured by iPA and flow cytometry in five healthy donors. For flow cytometry experiments, whole blood was activated with TRAP and fibrinogen receptor activation was measured by PAC-1 binding. (D) In vivo abciximab effect in three coronary artery disease patients measured by iPA before, immediately after, and 1 day after administration of a bolus of the drug. (E) Representative images showing iPA assay of the abciximab effect in one coronary artery disease patient for the same administration sequence described for panel D.

Imaging and Analysis Software. Automatic quantification of the percentage of platelet-occupied fibrinogen dots was accomplished using a custom-designed computer program developed at the Biomedical Diagnostics Institute (Dublin, Ireland). This software enables protein dot quantification by color coding. Platelet adhesion is calculated as the dot array occupancy (DAO), i.e., the number of green dots (bound platelets) divided by the total number of green and red dots (fibrinogen dots with no platelets bound) multiplied by 100%.

were incubated with a primary mouse antihuman CD41 antibody (1 μg/mL) for 1 h at room temperature. The slides were washed and then incubated with a secondary Alexa Fluor 488-labeled goat antimouse IgG antibody (4 μg/mL) for 20 min at room temperature in the dark. The slides were then rinsed in phosphate-buffered saline and microscope images were captured from each sample. The average coefficient of variance (CV) of platelet adhesion for samples from the same donor was 6.4% (four donors studied). C

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For more details on the imaging protocol and analysis software, please see the Supporting Information.

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RESULTS Individual Platelet Adhesion (iPA) Assay on Freshly Drawn Blood from Healthy Donors. On the basis of our previously reported results on the surface capture of platelets, we chose 6-μm-diameter fibrinogen dot arrays to quantify platelet adhesion (Figure 1): at this diameter, at most one platelet adheres to each dot.14 After mixing the fibrinogen with Cy3-labeled BSA to provide a positive control for protein printing, the 6-μm dots were arrayed on glass slides by microcontact printing14 (Figure 1). The fibrinogen array was then incubated with whole blood with gentle rocking, and washed, and the adhered platelets were fixed and stained with a platelet-specific antibody against CD41. Fluorescence microscopy images of the array, two per field of view, enable visualization of the protein pattern (red dots in Figure 1A) and adherent platelets (green dots in Figure 1A). From each pair of raw single-fluorophore color images, custom software provided a composite image showing the empty and platelet-occupied fibrinogen dots (red and green, respectively) and calculated the dot array occupancy (DAO: the percentage of protein dots in the array covered by platelets). DAO increases with incubation time, plateauing after 30 min (Figure 1B); normal DAO at 30 min incubation, established in blood from 50 healthy donors taking no medication, was 77 ± 16%. Detection of the in Vitro and in Vivo Effects of αIIbβ3 Inhibitors by iPA; Comparison to Flow Cytometry. To assess the suitability of iPA for measurement of platelet adhesion to fibrinogen through αIIbβ3, the platelets’ fibrinogen receptors were specifically blocked to varying extents prior to incubation with dot arrays. To block platelet binding to the fibrinogen receptor, we used abciximab. Figure 2A,B shows that increasing concentrations of abciximab, incubated with whole blood in vitro prior to iPA assay, caused a decrease in the measured DAO. For comparison, the effect of blocking the αIIbβ3 receptor was measured by flow cytometry via binding of PAC-1, a monoclonal antibody against activated αIIbβ3, following stimulation of the platelets in vitro with the thrombin-receptor-activating peptide TRAP-6, which induces fibrinogen binding in platelets. The two methods yielded similar results, namely, a significant decrease of fibrinogen binding with increasing drug concentration (Figure 2C). For example, 2 μg/mL abciximab inhibited PAC-1 binding by 82 ± 17% (n = 5), while the same concentration completely inhibited platelet adhesion to fibrinogen dots (Figure 2C). Next, the use of iPA to detect the in vivo effects of abciximab was evaluated in patients (n = 3) undergoing percutaneous coronary intervention (PCI). Platelet adhesion was measured in whole blood before and after abciximab administration, yielding DAO values of 48, 44, and 44% prior to administration and 1% for all three patients after administration, indicating very effective blockage of the fibrinogen receptor by the drug (Figure 2D,E). Blood samples from two of the three patients were collected again 24 h following PCI, yielding DAOs of 8 and 5%, indicative of only minor recovery of normal platelet function 24 h after bolus administration. Detection of the in Vitro Effect of P2Y12 Inhibitors by iPA. Adenosine 5′-diphosphate (ADP) is an agonist that induces platelet aggregation mainly by activation of their P2Y12 receptors. To determine whether iPA can be used to monitor P2Y12 inhibitors, the effects of one such drug, cangrelor, were

Figure 3. iPA detects the effect of in vitro P2Y12 inhibition. (A) Platelet adhesion to fibrinogen dots at increasing concentrations of ADP (0, 0.02, 0.2, 2, 20 μM). ADP leads to decreased platelet adhesion as platelets become involved in aggregation and are unavailable for surface binding. Error bars represent standard deviations of the replicates (n = 3). (B) Platelet adhesion to fibrinogen dots (as DAO) in 14 healthy donors with no agonists, with 20 μM ADP, and with 20 μM ADP in the presence of 10 μM cangrelor, which effectively abrogates the ADP effect, demonstrating detection of P2Y12 inhibition. Error bars represent standard deviations for the 14 donors.

tested in vitro. Prior to testing of the drug effects, the action of ADP alone was tested by incubation of blood from healthy donors with various ADP concentrations (0.02, 0.2, 2, 20 μM); platelet adhesion to fibrinogen was then measured by iPA. Figure 3A shows the ADP-dose-dependent decrease in DAO: more ADP causes greater platelet aggregation, resulting in lower platelet adhesion because fewer single platelets remain available for surface binding. A 20 μM ADP concentration was chosen for further experiments because it showed the highest decrease in adhesion; it is also a standard concentration used to measure P2Y12 inhibitors by aggregation.15 Figure 3B shows that 20 μM ADP decreases platelet adhesion to a DAO of 17 ± 12% (n = 14). To characterize the effect of P2Y12 inhibitors on platelet adhesion in the presence of ADP, blood samples were preincubated with the P2Y12 antagonist cangrelor (10 μM, 30 min). ADP (20 μM) was then added and blood was incubated on the fibrinogen array. The decrease in platelet adhesion D

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associated with ADP was completely eliminated by 10 μM cangrelor, with a DAO of 78 ± 12% (Figure 3B). Blood cell counts were measured in samples treated with and without ADP and/or cangrelor as previously described. Three healthy donors were recruited and platelet, red blood cell (RBC), and white blood cell (WBC) counts were measured using a hematology analyzer after measurement of platelet adhesion of the same sample by iPA assay. As shown in Table 1, Table 1. iPA-Assayed Adhesion and Blood Cell Counts for ADP/Cangrelor Treatment of Whole Blooda mean ± SD for n=3 buffer 20 μM ADP 20 μM ADP + 10 μM cangrelor

RBC count, 106/μL

WBC count, 103/μL

platelet count, 103/μL

DAO, %

3.5 ± 0.4 3.4 ± 0.5 3.7 ± 0.2

6.5 ± 1 6±1 7.3 ± 2

142 ± 50 7.3 ± 6 120 ± 67

65 ± 19 10 ± 6 44 ± 31

Figure 4. Comparison of in vitro P2Y12 effect of ADP using iPA, LTA, and VerifyNow P2Y12 cartridge. For one healthy donor’s blood, 20 μM ADP-induced P2Y12 “Platelet Reactivity Units” (PRU) measured by VerifyNow, percentage aggregation measured by LTA, and relative change in dot array occupancy (ΔDAO/DAOi) measured by iPA, all as a function of concentration of cangrelor in vitro pretreatment (0, 0.005, 0.01, 0.05, 0.1, 0.5, 1 μM) of blood or platelet-rich plasma (PRP) (see Table S1 in the Supporting Information for raw data on aggregation and DAO). Although the VerifyNow method shows a greater signal swing in the low concentration range, both LTA and IPA have adequate sensitivity in this range to provide a response to small changes in cangrelor concentration. Note also the greater sensitivity (relative slope) of the iPA assay to cangrelor concentrations from 0.1 to 1.0 μM, where the PRU sensitivity is particularly low. Error bars represent standard deviations of replicates.

a

RBC = red blood cell; WBC = white blood cell; DAO = dot array occupancy. Blood cell counts measured using the Sysmex system.

ADP did not affect RBC or WBC count, but there was a significant drop in platelet count in 20 μM ADP-treated samples from (142 ± 50) × 106/mL to (7.3 ± 6.0) × 106/mL (n = 3, Table 1). This effect was inhibited by cangrelor: platelet count in samples treated with 10 μM cangrelor and 20 μM ADP was (119 ± 67) × 106/mL. Monitoring in Vitro P2Y12 Inhibition with iPA: Comparison with LTA and VerifyNow. While not routinely assayed, P2Y12 receptor inhibition can be monitored by indirect platelet function tests, including LTA and the VerifyNow P2Y12 cartridge. To compare iPA with these two commercial assays’ ability to detect P2Y12 inhibition, whole blood samples obtained from the same blood draw from one healthy donor were pretreated with varying concentrations of the P2Y12 antagonist cangrelor (0, 0.005, 0.01, 0.05, 0.1, 0.5, 1 μM) for 30 min and assayed using the three testsLTA, VerifyNow, and iPAin the presence of 20 μM ADP (Figure 4). The change in DAO (ΔDAO = −[DAOADP − DAOi]) and the relative change in DAO (ΔDAO/DAOi) were both calculated. All three assays detected the effect of P2Y12 inhibition. iPA (expressed as ΔDAO/DAOi) correlated well with both LTA (r = 0.898) and the VerifyNow P2Y12 cartridge (r = 0.855). Detecting in Vivo P2Y12 Inhibition with iPA in Coronary Artery Disease Patients: Lack of Aspirin Interference. P2Y12 inhibitors are often administered in addition to aspirin treatment. To determine if aspirin had an effect on the iPA−P2Y12 assay, we measured the effect of P2Y12 inhibitors in patients taking aspirin. We recruited patients with coronary artery disease on dual antiplatelet therapy (aspirin plus the P2Y12 inhibitor clopidogrel, n = 12), patients on single antiplatelet therapy (aspirin, n = 14), and an age-matched control group of drug-free healthy donors (n = 7). The basal platelet DAOs (blood treated only by addition of buffer) for these three groups were not significantly different according to one-way analysis of variance (p = 0.716). Following ADP treatment of their blood samples, the agematched control group had an average DAO of 14 ± 7% while the patients on dual antiplatelet therapy had 39 ± 10% (Figure 5), clearly revealing the effect of P2Y12 inhibition. However, for patients on aspirin alone, platelet adhesion after ADP treatment was 13 ± 5%, statistically identical to the control group; thus,

Figure 5. iPA detection of the effect of P2Y12 inhibition for healthy donors and coronary artery disease patients. DAO with no agonist (n = 33) (white bar) and with 20 μM ADP (gray bars). Healthy donors (n = 7) were age matched with patients on aspirin (n = 14) and patients on aspirin and the P2Y12 inhibitor clopidogrel (n = 12). Error bars represent standard deviations of replicates.

clinical doses of aspirin do not not interfere with the iPA− P2Y12 assay. Monitoring in Vivo P2Y 12 Inhibition with iPA: Comparison with LTA and VerifyNow. The applicability of iPA to monitoring P2Y12 inhibition in patients with coronary artery disease who were on dual antiplatelet therapy (aspirin and P2Y12 inhibitor) was explored. Twenty-three coronary E

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artery disease patients taking aspirin and a P2Y12 inhibitor (clopidogrel or prasugrel) were recruited, and blood samples were tested with iPA, LTA, and the VerifyNow P2Y12 cartridge. To enable comparative studies between different donors, iPA data were normalized to each patient’s own agonist-free adhesion response. The absolute and relative change (decrease) in DAO upon ADP treatment was then calculated for each patient as above. For comparison of the LTA and iPA results (Figure 6A), iPA data were not normally distributed according to the D’Agostino

which was selected to agree with the LTA cutoff and is similarly meant to identify nonresponders (Figure 6B).

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DISCUSSION The “digital” nature of the individual platelet adhesion assay is conducive to rapid, automated, reproducible, and accurate assessment of platelet−protein interactions that reflect the platelet functional state: like flow cytometry, the iPA assay is a counting process, and the number of protein spots in this assay can be chosen to be large enoughthousands in 1 mm2to provide adhesion statistics representative of the functional activity of an individual’s platelets. The speed and ease of the assay are facilitated by binding of platelets in predefined locations (identified, as in Figure 1, by fluorescent staining), which makes the quantitation process a simple binary assessment of each protein dot as occupied or empty, readily carried out in software. The time-dependent results of the iPA assay for healthy donors (Figure 1) are consistent with the Langmuir model of adsorption (see the Supporting Information for Langmuir-type adhesion curves)more typically used for molecular interactionsin which each of the adsorption sites (here, protein dots) is independent of the others and all have the same energy of interaction with the adsorbing species.17 The kinetics of such a system, which depend nominally upon impact rate, bond formation probability for impact with an open site, and the number of remaining open sites, are simple and well understood. This predictable behavior will facilitate the use of iPA to study and understand the dynamics of a range of cell− protein adhesion processes, particularly in those cases where a protein spot size that binds only a single cell can be determined and where physiologically relevant adhesion does not require cell−cell interactions (although such interactions can be facilitated by use of larger protein spots14). Measuring the adhesion properties of platelets to protein matrices provides a more direct means to detect the effects of drugs that modify platelet function than does measurement of platelet aggregation. PAC-1 binding upon agonist stimulation is a quantitative marker of platelet activation and of the ability of platelets to bind fibrinogen in solution; it is a well-established flow cytometry assay to measure inhibition of fibrinogen binding, but it is quite complex and requires trained personnel. The results of the iPA experiment in which the fibrinogen receptor, αIIbβ3, was blocked are indicative of the potential of iPA to detect the effects of antiplatelet drugs, exemplified by the αIIbβ3 inhibitor abciximab (Figure 2). Beyond direct measurement of the blockage of a given receptor by quantification of platelet adhesion to a protein surface, iPA enables the measurement of the consequences of platelet aggregation, a critical function of platelets. Our results indicate that the induction of platelet aggregation with ADP decreases the number of free single platelets available for binding to the iPA device (Table 1), leading to lower values of DAO (Figure 3). Additionally, Figure 3B shows how inhibition of platelet aggregation with the drug cangrelor (an ADPreceptor inhibitor) gives DAO values analogous to those from nonaggregated samples: it shows simultaneously that platelets are not aggregating and that they are binding normally to fibrinogen; an aggregation assay can say only that they do or do not aggregate. Thus, iPA directly measures platelet function in the form of platelet adhesion to a protein matrix and, at the same time, indirectly measures platelet aggregation. Arguably, this is a more biologically informative combination than

Figure 6. iPA and VerifyNow P2Y12 measurement of in vivo P2Y12 inhibition in coronary artery disease patients compared to LTA results. (A) For iPA assay, relative change in dot array occupancy, −[DAOADP − DAOi]/DAOi, is plotted vs LTA-measured percentage aggregation after 20 μM ADP treatment. The vertical line is the cutoff point for clopidogrel nonresponse by LTA with 20 μM ADP agonist;19 the horizontal line is the equivalent cutoff point for iPA (see text). Data were nonparametric and the Spearman coefficient, r, was −0.73, p < 0.0002, n = 23. (B) For each patient, VerifyNow “Platelet Reactivity Units” (PRU) are plotted vs LTA-measured percentage aggregation after 20 μM ADP treatment. The vertical line is the cutoff point for clopidogrel nonresponse by LTA; the horizontal line is the equivalent cutoff point for VerifyNow. Correlation between PRU and percentage aggregation Pearson coefficient: r = 0.77, p < 0.008, n = 10.

and Pearson omnibus test (as reported by Graph Prism software), so the Spearman correlation test was employed, showing a strong correlation between LTA and iPA results, r = 0.73 for ΔDAO/DAOi compared to LTA (p ≤ 0.0001). Ten of the coronary artery disease patients were also tested using VerifyNow P2Y12 cartridges (Figure 6B), with results that were normally distributed, so the Pearson correlation was employed, yielding a correlation coefficient of r = 0.77, p < 0.008, for VerifyNow P2Y12 and LTA. The cutoff point for VerifyNow to detect P2Y12 inhibitors has been established at 230 PRU,16 F

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without requiring the formation of light-scattering aggregates. Small aggregates involving as few as two or three platelets could indicate undesirable residual platelet reactivity, not fully eliminated by clopidogrel, that will be measured by iPA but may not affect light transmittance in the aggregation of PRP measured by LTA. Of course, any change in platelet reactivity that is in any way modulated by the presence of red blood cells will not be detected by LTA either, due to its reliance upon PRP, but will be detectable by iPA. Our results suggest that iPA may find clopidogrel nonresponders missed by LTAabout 17% of the time for the small cohort of patients we studied. Figure 6B shows complete correlation between LTA and VerifyNow, with both techniques being based on the change of light transmittance upon formation of platelet aggregates of any size.

measuring aggregation directly and inferring platelet binding to proteins, because iPA can be carried out simultaneously on multiple proteins to achieve a degree of specificity unavailable from generic aggregation. In any case, aggregation assays are well developed and iPA offers a complementary assessment of specifically selected platelet−protein interactions. Figure 4 compares the use of iPA to measure P2Y12 inhibition to measurement with light transmission aggregometry and the aggregation-based VerifyNow system. While there is good correlation (see Results) among the three assays when assaying the in vitro effect of cangrelor on a blood sample from a healthy donor, iPA displays a broader measurement range than either of the other assays: Figure 4 shows that iPA results track cangrelor concentrations over which LTA and VerifyNow are essentially unresponsive (saturated), namely, from 0.1 to 1.0 μM. Specifically, iPA DAO in samples with 0.1, 0.5, and 1.0 μM cangrelor was 26 ± 3, 33 ± 0.5, and 43 ± 3%, respectively (Figure 4). These data correlate with previous reports showing that VerifyNow does not detect differences in platelet inhibition at high levels of P2Y12 inhibition.12 The fact that iPA does not suffer this limitation is reasonably explained by the use of 6-μm protein dots, which measure any significant decrease in the number of single platelets available to bind without requiring a particular aggregation threshold to be surpassed as VerifyNow and LTA do. Additionally, we find that iPA assay of P2Y12 inhibitors’ in vivo effect is unaffected by aspirin, a drug very commonly administered to cardiovascular patients (Figure 5), often in conjunction with P2Y12 inhibitors. A main purpose of platelet function testing is to determine if a patient is responsive to the administered antiplatelet therapy.18 Despite being often cited as the gold standard for measurement of platelet function, LTA in fact only enables inference of platelet function from changes in their tendency to form many-platelet aggregates. In previous studies, patients on clopidogrel with an aggregation value higher than 64% by LTA following blood sample treatment with 20 μM ADP have been defined to be nonresponsive to antiplatelet therapy.19 On the basis of the LTA cutoff point, 48% of the patients in our cohort of 23 would be considered nonresponsive to clopidogrel therapy because addition of ADP results in comparatively high aggregation. These same 11 patients can also be identified as nonresponsive to clopidogrel therapy by iPA by defining a relative change in DAO (ΔDAO/DAOi) of 0.6 as the cutoff point. This choice means that 35% of the patients (see Figure 6A) are identified in common by LTA and iPA as responsive: they have appropriately diminished ADP-induced aggregation by LTA, and the relative change upon adding ADP in the number of platelets available for binding to protein spots is small enough by iPA to indicate clopidogrel efficacy. Interestingly, however, Figure 6A shows that the choice of ΔDAO/DAOi = 0.6 as cutoff point results in four of 23 patients (17% of them) who are classified as responders by LTA but appear to be nonresponders when measured by iPA. This discrepancy can be explained by the difference in what the two techniques measure: for these four patients, LTA indicates that the addition of ADP to their PRP samples does not provide the higher level of aggregation typically associated with lack of response to clopidogrel, but iPA indicates their whole blood has a change in availability of single platelets upon adding ADP that is typical of nonresponders. In other words, iPA appears to be more sensitive, because DAO levels measure decreases in the availability of single platelets for surface protein binding

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SUMMARY AND CONCLUSIONS We have developed an improved whole-blood platelet adhesion assay, iPA, that reliably and specifically detects antiplatelet drug effects from in vivo drug therapy using digital counting of surface-adhered individual platelets. Unlike other measures of platelet (re)activity such as light transmission aggregometry and the VerifyNow assay, iPA directly measures platelet function targeted at specific receptors by assaying the binding of statistically meaningful numbers of a given patient’s individual platelets to printed spots of one or more chosen protein matrices. This method has the potential to personalize and improve the efficacy of antiplatelet therapy. In this paper, we focused on assays based upon binding of platelets to 6-μm fibrinogen spots. Analyzing both whole blood from healthy donors to which therapeutic agents were added in vitro and whole blood drawn from cohorts of patients under treatment with various antiplatelet agents, we showed the following: (1) the kinetics of binding platelets to the protein spots of the iPA array are Langmuirian, indicative of independence of adsorption sites and an impact-rate-limited binding process; (2) measurement by iPA of inhibition of the clinically important platelet receptor αIIbβ3 by the drug abciximab is well correlated with flow cytometry, but without the added steps flow cytometry requires, namely, binding PAC1 to the platelets following their activation by TRAP-6; (3) patients undergoing percutaneous cardiac intervention can be effectively monitored for the consequences of abciximab, the antiplatelet effect of which is still largely present some 24 h after administration, a fact that may be important in managing postoperative bleeding and guiding therapy; (4) the effect of P2Y12 inhibitors, e.g., cangrelor, on platelet reactivity can be assayed by adding ADP to whole blood samples and then analyzing the change in number of (nonaggregated) single platelets via iPA, yielding results that are both independent of the patient’s use of aspirin and well correlated with LTA and VerifyNow assays; (5) due to its direct measurement of the availability of single platelets in whole blood, the ADP-enabled iPA assay of P2Y12 inhibition may uncover a meaningful number of antiplatelet drug nonresponders who are not similarly identified using LTA. iPA, a whole-blood assay performed on a transparent flat substrate, requires only a fraction of 1 mm2, making it easily integrable in a microfluidic device that would use a small volume of blood for simultaneous measurements of multiple receptor/protein combinations under controlled shear conditions, an extremely important parameter in platelet function. The methodology presented here to digitally quantify cell G

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D.; Trenk, D.; Van Werkum, J. W.; Paganelli, F.; Price, M. J.; Waksman, R.; Gurbel, P. A.; Working Group on High On-Treatment Platelet Reactivity. J. Am. Coll. Cardiol. 2010, 56, 919. (16) Brar, S. S.; ten Berg, J.; Marcucci, R.; Price, M. J.; Valgimigli, M.; Kim, H. S.; Patti, G.; Breet, N. J.; DiSciascio, G.; Cuisset, T.; Dangas, G. J. Am. Coll. Cardiol. 2011, 58, 1945. (17) Langmuir, I. J. Am. Chem. Soc. 1916, 38, 2221. (18) Collet, J.-P.; Cuisset, T.; Range, G.; Cayla, G.; Elhadad, S.; Pouillot, C.; Henry, P.; Motreff, P.; Carrie, D.; Boueri, Z.; Belle, L.; Van Belle, E.; Rousseau, H.; Aubry, P.; Monsegu, J.; Sabouret, P.; O’Connor, S. A.; Abtan, J.; Kerneis, M.; Saint-Etienne, C.; Barthelemy, O.; Beygui, F.; Silvain, J.; Vicaut, E.; Montalescot, G. N. Engl. J. Med. 2012, 367, 2100. (19) Breet, N. J.; van Werkum, J. W.; Bouman, H. J.; Kelder, J. C.; Ruven, H. J.; Bal, E. T.; Deneer, V. H.; Harmsze, A. M.; van der Heyden, J. A.; Rensing, B. J.; Suttorp, M. J.; Hackeng, C. M.; ten Berg, J. M. JAMA, J. Am. Med. Assoc. 2010, 303, 754.

adhesion and cell−protein interactions should prove applicable to a wide range of cell adhesion processes and systems.

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ASSOCIATED CONTENT

* Supporting Information S

Additional information as noted in the text. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected] (L.B.-D.). E-mail: Antonio. [email protected] (A.J.R.). Email: sofi[email protected] (S.R.). Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS We thank Prof. Luke P. Lee of the University of California, Berkeley, and Prof. David Williams from the University of Auckland for helpful discussions and insights in the initial stages of this work. The material reported in this paper is based upon works supported by the Science Foundation Ireland (SFI) under Grant 10/CE/B1821 and the National Biophotonics Imaging Platform Ireland (NBIP).

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REFERENCES

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dx.doi.org/10.1021/ac401076s | Anal. Chem. XXXX, XXX, XXX−XXX