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Platelet function and HIV: a case–control study

Satchell, Claudette Sa; Cotter, Aoife Gb; O'Connor, Eileen Fb; Peace, Aaron Jc; Tedesco, Anthony Fc; Clare, Andrewb; Lambert, John Sb; Sheehan, Gerard Jb; Kenny, Dermotc; Mallon, Patrick WGa,b

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doi: 10.1097/QAD.0b013e328336098c
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Increased survival rates as a consequence of longer exposure to HAART have been accompanied by increased cardiovascular disease (CVD) in HIV-infected patients [1]. Dyslipidaemia, inflammation and endothelial dysfunction have all been implicated [2–4]. Several studies have demonstrated that arterial thrombus formation is a major factor in acute vascular events such as myocardial infarction (MI) in the general population [5,6]. Thrombosis in the coronary arteries is mediated by platelets [7], as following rupture of atherosclerotic plaques, platelets adhere and aggregate to form a thrombus [8].

In vitro, platelet aggregation is induced by agonists such as epinephrine, thrombin receptor-activating peptide (TRAP), ADP and collagen. These agonists are used to assess platelet function in many different assays [9]. TRAP, ADP and collagen stimulate platelet aggregation by binding to platelet-surface receptors [protease-activated receptor 1 (PAR-1), P2Y1/P2Y12 and glycoprotein VI (GPVI)/α2β1, respectively], resulting in a series of intracellular changes, including phospholipase-mediated alterations in intracellular calcium and protein phosphorylation [10–15]. Epinephrine stimulates platelet aggregation indirectly by acting on platelet α2-adrenergic receptors to augment the aggregation effect of other platelet agonists. Megakaryocytes, the cells responsible for platelet production, have been shown to express CD4 receptors, and both megakaryocytes and platelets have been shown to express the chemokine (CXC motif) receptor 4 coreceptor on their surface, which renders them susceptible to HIV infection [16,17]. Platelets themselves have been shown to contain HIV particles in vitro, and virus-containing platelets shown to display signs of activation [18]. There is a growing body of evidence that suggests that measuring platelet reactivity may predict cardiovascular events and be important in clinical practice, although platelet function in HIV-infected patients is not well understood [19,20].

Standard assays of platelet function are time-consuming, expensive and labour intensive. More recently developed aggregation-specific platelet function analysers measure platelet aggregation upon exposure to either a narrow range of agonists or a single agonist at a single concentration [21], thus do not reflect the complex biological environment of different disease states. To characterize platelet function in detail in HIV-infected patients, we used a novel platelet assay that characterizes platelet responses to multiple agonists and assesses multiple platelet receptor pathways simultaneously [22]. Our aim was to see whether platelet function in HIV-infected patients was different to HIV-negative controls.


Patients and controls

Twenty adult individuals with documented positive HIV antibody tests (HIVpos) and 20 HIV-negative controls (HIVneg) were enrolled into a single centre, prospective case–control study, with HIVneg controls matched to HIVpos patients for age and sex. Individuals on antiplatelet therapy were excluded. Participants provided written, informed consent, and the study was approved by the Mater Misericordiae University Hospital (MMUH) and Mater Private Hospital Research Ethics Committee.

Clinical and laboratory data collection

Patient demographics, including age, sex, date of birth and country of birth were collected. Detailed medication history, history of CVD (including stroke) and diabetes mellitus, family history of diabetes mellitus or MI, history of current or previous smoking and history of hypertension were recorded.

Clinical assessments included height and weight (from which body mass index (BMI) was estimated), and blood pressure (BP). All participants provided fasting (10 h, water permitted) bloods for full blood count; differential, a chemical profile including urea and electrolytes; liver function tests; corrected calcium; fasting glucose; insulin; total cholesterol; low-density lipoprotein (LDL) cholesterol; high-density lipoprotein (HDL) cholesterol, triglycerides, estimated glomerular filtration rate using the Modification in Diet in Renal Disease study equation [22], lymphocyte subsets and, in the case of HIVpos patients, HIV RNA. High-sensitivity C-reactive protein (hs-CRP) and interleukin-6 were measured on stored plasma by nephelometry and colometric ELISA kit (R&D Systems, Minneapolis, Minnesota, USA), respectively.

Platelet assay

To assess platelet function, we used a novel platelet aggregation assay based on standard light transmission aggregometry as described previously [23,24]. In brief, platelet-rich plasma (PRP) was obtained from 40 ml venous blood (collected in 3.2% sodium citrate without venostasis using a 19 G butterfly needle) by centrifugation at 150g for 10 min. Platelet poor plasma (PPP) was obtained from 1 ml PRP centrifuged at 16 110g for 1 min.

PRP (180 μl) was added to increasing concentrations of four platelet agonists, epinephrine, ADP, collagen (all from Bio/Data Corporation, Horsham, Pennsylvania, USA) and TRAP (donated by the Centre for Synthesis and Chemical Biology, Department of Pharmaceutical and Medicinal Chemistry, Royal College of Surgeons in Ireland), arranged on a 96-well black microtitre plate (PerkinElmer, Waltham, Massachusetts, USA). The final agonist concentrations were epinephrine, 0.0012, 0.0049, 0.0195, 0.078, 0.313, 1.25, 5, 20 μmol/l; TRAP–ADP, 0.156, 0.313, 0.625, 1.25, 2.5, 5, 10, 20 μmol/l and collagen, 2.23, 4.45, 8.9, 17.8, 35.6, 71.3, 143, 190 μg/ml. Positive (PPP in isotonic saline) and negative (PRP in isotonic saline) controls were arranged in quadruplicate on the same plate.

Platelet aggregation was assessed by light absorbance at 572 nm at 3 min intervals over 21 min using a SpectraMax M2 multidetection microplate reader (Molecular Devices, Sunnyvale, California, USA).

Statistical analysis

Percentage aggregation was calculated from absorbance values, using the light absorbance of PPP as a reference for 100% aggregation and absorbance at time zero in the PRP control wells representing 0% aggregation. Mean platelet aggregation was calculated from the mean of the final three time points for each concentration of agonist. Graphs of log concentration of each agonist versus percentage aggregation were plotted for each group (HIVpos and HIVneg) using Graphpad PRISM version 5.0 (Graphpad Software, Inc., La Jolla, California, USA). Probit analyses were used to determine the agonist concentration required to elicit 50% of maximal aggregation (log EC50). log EC50 and percentage platelet aggregation values that were significantly different between the groups were further interrogated using univariate and multivariate analyses to investigate associations between these between-group differences and covariates of interest. Mann–Whitney U tests (for continuous variables) and chi-squared tests (for categorical variables) were used to determine between-group differences in demographic, clinical and laboratory parameters listed previously. In addition, the following parameters were assessed for the HIVpos group: AIDS diagnosis, antiretroviral history, use of protease inhibitors, use of nonnucleoside reverse transcriptase inhibitors, use of zidovudine, tenofovir and abacavir. Spearman correlation was used to investigate factors associated with differences in these platelet aggregation outcomes and the parameters listed above. Covariates with a P value of less than 0.05 in univariate analyses were included in backward stepwise multiple linear regression to determine independent associations with changes in platelet aggregation (P < 0.05). To account for the unavailability of HDL and LDL data for seven participants, multivariate analysis was performed with and without the inclusion of these variables to determine the effect on the model. We did not correct for multiple comparisons. All analyses were performed using SPSS version 15.01 (SPSS Inc., Chicago, Illinois, USA).


HIVpos and HIVneg individuals were well matched for age and sex (Table 1) with the HIVpos patients having higher diastolic BP (DBP), lower HDL cholesterol, lower neutrophil, lymphocyte and platelet counts and lower CD4+ T-cell count compared with HIVneg patients. Sixty percent of the HIVpos patients had undetectable HIV RNA (<50 copies/ml), and 80% of the HIVpos patients were receiving antiretroviral therapy (ART).

Table 1
Table 1:
Baseline demographics and cardiovascular risk factors.

Platelet function

Evaluation of dose–response curves revealed multiple differences in platelet aggregation between the HIVpos and HIVneg groups. Platelet aggregation was decreased in the HIVpos group as compared with the HIVneg group in response to TRAP, ADP and collagen and increased in the HIVpos group as compared with the HIVneg group in response to epinephrine. Examples of the patterns of observed differences in agonist-induced platelet aggregation curves are outlined in Fig. 1.

Fig. 1
Fig. 1:
Patterns of difference in agonist-induced platelet aggregation.

When patterns suggested a horizontal shift in the curve (Fig. 1a), we analysed differences in log EC50. With patterns of vertical shift (Fig. 1b), we compared differences in aggregation at maximal and submaximal concentrations. When mixed patterns were observed (Fig. 1c), we compared both log EC50 and aggregation at maximal and submaximal agonist concentrations.


Platelets from the HIVpos group exposed to epinephrine were more reactive, with a horizontal shift in the curve (Fig. 2a). Significantly, lower mean epinephrine concentration was required to induce 50% platelet aggregation [mean (SD) log EC50 1.9 (1.2) μmol/l for HIVpos versus 3.0 (1.7) μmol/l for HIVneg, P = 0.028]. In univariate analyses, HIV infection, lower CD4 cell percentage, higher CD8+ T-cell count and positive family history of CVD were associated with lower epinephrine log EC50 (all P ≤ 0.05). In multiple regression, HIV infection and a positive family history of CVD remained independently associated with lower epinephrine log EC50 (P = 0.013 and P = 0.001, respectively, r2 = 0.345, Table 2).

Fig. 2
Fig. 2:
Platelet aggregation in response to increasing concentrations of agonists. log EC50, log concentration required to induce 50% maximal aggregation; TRAP, thrombin receptor-activating peptide.
Table 2
Table 2:
Association of agonist-induced platelet aggregation with clinical and laboratory parameters.

Thrombin receptor-activating peptide

Between-group differences with TRAP exposure followed a vertical shift pattern (Fig. 2b). Exposure to TRAP in the HIVpos group induced significantly less platelet aggregation at maximal and submaximal concentrations [mean (SD) percentage aggregation 73% [15] in HIVpos group versus 82% [8] in HIVneg group at 10 μmol/l, P = 0.011 and 78% [9] versus 82% [9] at 20 μmol/l exposure, P = 0.012]. In univariate analyses, HIV infection, lower BMI, lower total and LDL cholesterol, lower neutrophil count, lower CD4+ T-cell count and higher CD8+ cell percentage were associated with reduced TRAP-induced platelet aggregation at 10 μmol/l (all P < 0.05). In multivariate regression, HIV infection remained independently associated with reduced platelet aggregation upon TRAP exposure (P = 0.003, r2 = 0.303, Table 2).


As with TRAP, between-group differences with ADP exposure followed a vertical shift pattern (Fig. 2c). Exposure to submaximal concentrations of ADP also resulted in significantly less platelet aggregation in the HIVpos group (67% [12] versus 75% [9] at 10 μmol/l, P = 0.035, Fig. 2c). In univariate analyses, HIV infection, non-white ethnicity, lower HDL cholesterol, lower platelet count, lower neutrophil count, lower hs-CRP, lower CD4+ T-cell count and higher CD8+ cell percent were associated with reduced ADP-induced platelet aggregation (all P < 0.05). In multivariate regression, non-white ethnicity and lower hs-CRP remained independently associated with reduced ADP-induced platelet aggregation (P = 0.01 and P = 0.046, respectively, r2 = 0.233, Table 2).


The between-group differences with collagen exposure suggested a mixed shift pattern with collagen exposure (Fig. 2d). The greatest between-group differences in platelet aggregation were observed upon exposure to submaximal concentrations of collagen, with significantly less aggregation seen at 71.3 μg/ml in the HIVpos group [mean (SD) aggregation of 17% [25] in the HIVpos group versus 35% [26] in the HIVneg group, P = 0.007) and at 143 μg/ml (HIVpos 62% [18] versus HIVneg 76% [12], P = 0.014). In univariate analyses, older age, non-white ethnicity, higher systolic BP (SBP) and DBP, higher urea, higher creatinine, lower neutrophil count, lower CD4+ T-cell count and lower CD4 cell percentage were associated with less collagen-induced platelet aggregation at 71.3 μg/ml in the HIVpos group (all P = < 0.05). In multivariate analyses, higher DBP and lower neutrophil count remained independently associated with less collagen-induced platelet aggregation (P = 0.003 and P = 0.001, respectively, r2 = 0.362).

In addition, significantly higher concentrations of collagen were required to induce 50% platelet aggregation in the HIVpos group [mean (SD) log EC50 1.92 (1.2) μg/ml in the HIVpos group versus 1.69 (0.6) μg/ml in the HIVneg group, P = 0.035, Fig. 2b). In univariate analysis, HIV infection, older age, non-white ethnicity, higher BMI, higher DBP, higher creatinine, higher alanine aminotransferase, lower neutrophil count and lower CD4+ T-cell count were associated with higher collagen log EC50 (all P = < 0.05). In multiple regression, higher DBP remained independently associated with higher collagen log EC50 (P = 0.008, r2 = 0.265, Table 2).


This is the first study to demonstrate significant differences in platelet function in adult HIV-1-infected patients as compared with HIV-negative controls. In addition, our results show that platelet aggregation correlates with both clinical and laboratory parameters including HIV disease activity. We assayed platelet responses using a range of inducers of platelet aggregation, and a variety of differences were observed. Platelet aggregation was reduced in response to collagen, TRAP and ADP, whereas platelet aggregation was increased in response to epinephrine. In addition, distinct between-group patterns of agonist-induced dose–response curves, namely vertical shift (epinephrine), horizontal shift (TRAP and ADP) and mixed shift (collagen) were observed. Overall, observations of hyper and hypoplatelet reactivity, depending on the platelet agonist tested, suggest multiple potential underlying defects in platelet reactivity, possibly mediated through effects at both receptor and postreceptor levels.

Collagen induced significantly less aggregation in the HIVpos group. The between-group differences in log EC50 point to possible interference with collagen binding to the GPVI receptor. The differences in aggregation at maximal and submaximal agonist exposure suggest that this effect is not overcome at higher agonist concentrations, pointing to additional postreceptor functional differences (Fig. 2d). Collagen-induced platelet aggregation is mediated through GPVI receptor activation, causing a conformational change in the α2β1 receptor on the platelet surface. This converts the α2β1 receptor from a low-affinity state to a high-affinity state through inside-out signalling [25]. Impairment of this mechanism could explain reduced collagen-induced platelet aggregation seen in the HIVpos group, although further research is required to determine exact underlying mechanisms.

Platelets interact with neutrophils in the thromboinflammatory process to form platelet–neutrophil conjugates, contributing to arterial thrombosis [27]. Platelets themselves also secrete neutrophil activators, resulting in amplification of the acute inflammatory response [27]. The association of lower neutrophil counts with reduced collagen-induced platelet aggregation points to either or both of these aforementioned functions being potentially compromised in HIV-infected patients. Of note, epinephrine has been shown to enhance platelet–neutrophil adhesion in whole blood [28]. An upregulated platelet response to epinephrine in HIV-infected patients may help compensate for reduced collagen-induced responses.

TRAP induces platelet aggregation through the PAR-1 receptor, whereas ADP-induced platelet aggregation is mediated through the P2Y12 receptor [29,30]. TRAP further promotes ADP-induced platelet aggregation by mediating the intracellular secretion of ADP from platelet-dense granules [30]. The between-group differences in platelet aggregation were similar for both agonists, with no differences in log EC50, but significantly less percentage platelet aggregation upon exposure to maximal and submaximal concentrations of both TRAP and ADP. These differences suggest underlying defects in postreceptor signalling in response to these agonists in HIV-infected patients, rather than defective binding of the agonists to the PAR-1 and P2Y12 receptors. Lower hs-CRP was independently associated with lower ADP-induced platelet aggregation. This is in keeping with a documented association between increased ADP-induced platelet reactivity and elevated levels of CRP, both of which have been postulated to increase cardiovascular risk [26,31–33].

Activation of epinephrine-specific α2A-adrenergic receptors on the platelet surface also promotes platelet aggregation [34]. In normal individuals, the affinity of platelet α2A-adrenergic receptors for epinephrine is downregulated in vivo and in vitro after initial exposure to epinephrine [35]. Our data suggest platelet hyperresponsiveness with exposure to epinephrine, which supports a scenario in which epinephrine-induced platelet aggregation is upregulated through α2A-adrenergic receptors to compensate for defective PAR-1 and P2Y12 receptor-mediated aggregation (suggested by TRAP and ADP data) and coexisting decreases in collagen-induced platelet aggregation. The independent association of HIV infection with higher epinephrine log EC50 and lower TRAP-induced platelet aggregation suggests that viral infection could be contributing to these differences in platelet aggregation.

Interestingly, the human C-type lectin-like molecule, C-type lectin-like receptor 2 expressed on the surface of platelets has been recently identified as an HIV-1 attachment factor, which promotes virus capture by platelets, mediates potent platelet aggregation and has the capacity to promote viral dissemination [36–38]. The extent to which this HIV-associated platelet aggregation subverts the haemostatic machinery involved in platelet reactivity is not known, although our results would support a role for HIV infection disrupting normal platelet aggregation. Further research is required to determine whether such a factor could be contributing to the patterns of platelet aggregation seen in response to TRAP, ADP and collagen.

Although this study demonstrates multiple differences in platelet function in HIV-infected patients and offers insights into the complex mechanisms underlying platelet aggregation, it does have limitations. The cross-sectional study design limits our ability to determine definitive cause and effect relationships. Further prospective clinical and in-vitro studies are required to further elucidate underlying mechanisms. In addition, the sample size prevents us from exploring in-depth associations in multivariate analyses or determining the role of specific antiretroviral drugs or classes of antiretroviral drugs on the observed differences in platelet function (although no effect of specific antiretroviral or drug classes was observed in regression analyses). Our data do support findings from a small (n = 5) German study of HIV-infected men on tipranavir-containing HAART that demonstrated decreased ADP and collagen-induced platelet aggregation 4 h after dose of tipranavir. These results were confirmed in vitro in blood from healthy volunteers (n = 6) exposed to increasing concentrations of tipranavir. Although these data fit well with our observations, this study did not directly compare platelet aggregation between HIV-infected patients and healthy controls and measured two agonists at only one concentration [39].

Nevertheless, our research and its findings suggest significant differences in platelet function in HIV-infected patients and underline the need for further prospective studies in vivo of platelet function in HIV. Although a variety of patterns of difference were observed resulting in both enhanced and reduced platelet aggregation in HIV-infected patients depending on the agonist examined, questions remain as to whether this combination of effects would result in an increased overall propensity for thrombosis in HIV-infected patients and whether there is any role for antiplatelet therapy in this setting. In addition, with increasing data supporting a role for ART exposure in inducing CVD events [4,40,41], further research into the effect of ART on platelet function is required to elucidate whether platelet dysfunction plays a role in the increased prevalence of MI observed in HIV-infected patients prescribed certain antiretrovirals.


This study was funded through project grants from Mater College, MMUH, Dublin, Ireland and Science Foundation Ireland (09/RFP/BMT2461). C.S.S is supported through the 2008/2009 Dr Ciaran Barry Scholarship, Clinical Remedial Centre, Clontarf, Dublin, Ireland and the Commission of the European Communities, Research Directorate-General, FP 6 programme, for the EC project ‘European AIDS Treatment Network, NEAT’ (LSHP-CT-2006-037570).

The authors would like to thank the participants in the HIV Cardiac Monitoring Program, MMUH, Dublin and the HIV-negative volunteers; Dr Gerry O' Toole and the Immunology Department at MMUH, Dublin for hs-CRP testing and Dr Janaki Amin and Dr Steve Kerr for statistical advice.

C.S.S. contributed to the study design, the acquisition, analysis and interpretation of data, and drafting of the manuscript. A.G.C., E.F.O′C., A.C, J.S.L. and G.J.S. contributed to the acquisition of data. A.J.P. provided the intellectual property for the platelet assay and interpretation of data. A.F.T. contributed to the analysis and interpretation of data, and revision of the manuscript. D.K. contributed to the interpretation of data and revision of the manuscript. P.W.G.M. contributed to study conception and design, the acquisition and interpretation of data and revision of the manuscript. All authors have seen and approved the final version of the manuscript for publication.

These data were presented previously at 16th Conference on Retroviruses and Opportunistic Infections; 8–11 February 2009; Montreal, Canada; abstract #737.


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antiretroviral therapy; cardiovascular disease; HIV infection; platelet function; platelet reactivity

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