P2Y12 Inhibition Suppresses Proinflammatory Platelet–Monocyte Interactions

Abstract

Background Monocyte–platelet aggregates (MPAs) represent the crossroads between thrombosis and inflammation, and targeting this axis may suppress thromboinflammation. While antiplatelet therapy (APT) reduces platelet–platelet aggregation and thrombosis, its effects on MPA and platelet effector properties on monocytes are uncertain.

Objectives To analyze the effect of platelets on monocyte activation and APT on MPA and platelet-induced monocyte activation.

Methods Agonist-stimulated whole blood was incubated in the presence of P-selectin, PSGL1, PAR1, P2Y₁₂, GP IIb/IIIa, and COX-1 inhibitors and assessed for platelet and monocyte activity via flow cytometry. RNA-Seq of monocytes incubated with platelets was used to identify platelet-induced monocyte transcripts and was validated by RT-qPCR in monocyte-PR co-incubation ± APT.

Results Consistent with a proinflammatory platelet effector role, MPAs were increased in patients with COVID-19. RNA-Seq revealed a thromboinflammatory monocyte transcriptome upon incubation with platelets. Monocytes aggregated to platelets expressed higher CD40 and tissue factor than monocytes without platelets (p < 0.05 for each). Inhibition with P-selectin (85% reduction) and PSGL1 (87% reduction) led to a robust decrease in MPA. P2Y₁₂ and PAR1 inhibition lowered MPA formation (30 and 21% reduction, p < 0.05, respectively) and decreased monocyte CD40 and TF expression, while GP IIb/IIIa and COX1 inhibition had no effect. Pretreatment of platelets with P2Y₁₂ inhibitors reduced the expression of platelet-mediated monocyte transcription of proinflammatory SOCS3 and OSM.

Conclusions Platelets skew monocytes toward a proinflammatory phenotype. Among traditional APTs, P2Y₁₂ inhibition attenuates platelet-induced monocyte activation.

Keywords

aspirin - monocytes - antiplatelet therapy - platelet activation - thromboinflammation

Introduction

Platelets are anuclear megakaryocyte-derived cells that, in addition to their role in primary hemostasis and thrombosis, are crucial intercellular mediators of thromboinflammation.[1] Importantly, activated platelets attach to monocytes, forming monocyte–platelet aggregates (MPAs) via binding of platelet-expressed P-selectin to monocyte P-selectin glycoprotein ligand-1 (PSGL1). Additional interactions involve platelet CD40L and glycoprotein (GP) VI and monocyte CD40 and CD147.[2]

Circulating MPAs are increased in proinflammatory and prothrombotic clinical settings, including hypertension, diabetes, coronary artery disease (CAD), peripheral artery disease (PAD), and stroke.[3] [4] [5] MPAs are proposed to have an important pathogenic mechanism in inflammatory conditions by skewing monocytes toward a proinflammatory, procoagulant state, thereby contributing to disease progression.[6] Based on these observations, targeting MPA by platelet inhibitors offers a promising and interesting therapeutic target in thromboinflammation linked monocyte activation by platelets.

Antiplatelet therapy (APT) is a mainstay therapy in cardiovascular disease (CVD) prevention. Over the past several decades, we have seen clinically effective APT with inhibition of the P2Y₁₂ receptor (clopidogrel, prasugrel, and ticagrelor), GP IIb/IIIa receptor (integrilin, abciximab), protease-activated receptor 1 (PAR1; vorapaxar), and cyclooxygenase-1 (COX-1; aspirin).[7] [8] [9] Despite their well-defined role in suppressing platelet activation, there are limited data regarding the effect of APT on MPA. COX-1 inhibition has been shown not to reduce MPA assessed following 1 week of low-dose aspirin.[10] Among people with diabetes, clopidogrel was associated with lower MPA, and clopidogrel, but not aspirin, reduced MPA in patients with atherosclerosis.[11] [12] The effect of other APT on circulating MPA is unknown, and the impact of APT on platelet-induced monocyte activation is uncertain. More data are needed to better understand the role of MPA in thromboinflammation and its potential as a therapeutic target by platelet inhibitors.

Our study aimed to evaluate the effect of APT on MPA and the platelet effector properties on monocytes. RNA-seq of platelet-treated monocytes revealed a proinflammatory and prothrombotic monocyte transcriptome, characterized by enrichment of pathways associated with inflammation and coagulation. We show that platelets enhance surface expression of inflammatory CD40, tissue factor (TF), and CD11b on monocytes at a functional level. Screening of the standard APT therapies inhibiting COX-1, GP IIb/IIIa, PAR1, and P2Y₁₂ revealed that targeting the P2Y₁₂ receptor attenuates platelet–monocyte proinflammatory interactions. Platelet-mediated upregulation of mRNA proinflammatory transcripts was decreased with inhibitors against P2Y₁₂ and GP IIb/IIIa.

Materials and Methods

Clinical Studies

We leveraged a cohort of coronavirus disease 2019 (COVID-19) patients previously described with well-established platelet hyperactivity.[13] In the current analysis, we investigate monocyte–platelet interactions. Hospitalized patients with COVID-19 (n = 9) and controls (n = 7) were recruited from NYU Langone Health in the spring of 2020.[13] SARS-CoV-2 infection was confirmed by quantitative real-time polymerase chain reaction (RT-qPCR), in accordance with current standards. Patients with systemic lupus erythematosus (SLE) (n = 16) and controls (n = 8) were recruited from the NYU SAMPLE (Specimen and Matched Phenotype Linked Evaluation) biorepository after signing informed consent approved by the NYU School of Medicine Institutional Review Board. All patients and age- and sex-matched donors were recruited under study protocols approved by the NYU Langone Health Institutional Review Board. Each study participant or their legal authorized representative gave written informed consent for study enrollment in accordance with the Declaration of Helsinki.

Blood Drawing

Peripheral blood samples were drawn using a 19-gauge needle (BD Vacutainer) without using a tourniquet for all participants. After an initial 2 cc discard, blood was collected into tubes (BD Vacutainer) containing 3.2% (0.105 mol/L) sodium citrate. Blood samples were allowed to rest at room temperature (RT) for 15 minutes postphlebotomy before further processing, as described below.

Platelet Aggregation

Aggregation was measured using a light transmission aggregometry (Helena AggRAM, Beaumont, Texas, United States) at 37°C under stirred conditions, as previously described.[14] Whole blood was centrifuged at 200 g for 10 minutes, followed by 15 minutes of rest to obtain platelet-rich plasma (PRP). PRP was stimulated with different concentrations of U-46619 (Cayman Chemicals; 0.056 µM, 0.56 µM, and 5.6 µM) for 90 seconds. Concentrations were chosen based on preliminary data,[15] and were further validated by analyzing MPA formation. To assess platelet inhibitors, PRP was incubated with ML161 (PAR-1 inhibitor; 10 µM, 50 µM, Cayman Chemicals), AZD1283 (P2Y₁₂ inhibitor; 0.1 µM, 1 µM, 10 µM, Cayman Chemicals), eptifibatide (GP IIb/IIIa inhibitor; 18 µM, Cayman Chemicals), or aspirin (1 mM, Santa Cruz Biotechnology) for 30 minutes at 37°C before being activated with either thrombin (0.5 U/mL, Werfen), ADP (1 µM, Helena), or arachidonic acid (160 µM, Helena) for 90 seconds ([Supplementary Table S1] [online only]).

Flow Cytometry

MPAs were identified in citrate-anticoagulated whole blood. Briefly, whole blood was fixed with 1% formaldehyde (Sigma) 15 minutes after blood collection of patients from clinical studies. Fixed whole blood was stained with 5 µL CD61-FITC (Dako) to identify platelets and 1 µL CD45-VioGreen (Miltenyi Biotec) and 1 µL CD14-PE-Vio 770 (Miltenyi Biotec) to identify monocytes. To assess monocyte activation markers and monocyte subtypes, CD16-APC-Vio770 (Miltenyi Biotec) and either 5 µL CD142-VioBlue (Miltenyi Biotec) and 2 µL CD11b-APC (Miltenyi Biotec), or 1 µL CD40-V450 (BD BioSciences) was added. After lysis of red blood cells, monocytes were identified based on side-scatter properties and positive staining for CD14 and CD45 using a Miltenyi MACSQuant 10 (Miltenyi Biotec).

For MPA identification, monocytes were gated based on their CD45, CD14, and CD16 expression. Gates were established to include monocytes with (CD61 positive, MPA) and without platelets (CD61 negative), and platelet CD61-positive monocytes (MPA) were calculated as a percentage of total gated monocytes. Monocytes were further stratified in classical (CD14⁺⁺ CD16⁻), intermediate (CD14⁺⁺ CD16⁺), and nonclassical (CD14⁽⁺⁾ CD16⁺⁺) monocyte subtypes. Within each monocyte subgroup, platelet CD61-positive monocytes (MPA) were calculated as described above. Leukocytes, neutrophils, and lymphocytes were identified based on forward- and side-scatter properties within the CD45 gate. CD142 (TF) and CD40-positive monocytes were calculated as a percentage of total gated monocytes or monocytes with (CD61 + ) or without platelets (CD61 − ). CD11b was measured as mean fluorescence intensity within the respective monocyte gates.

To assess the effect of different platelet agonists on MPA formation, whole blood was incubated for 30 minutes at RT in the presence of U-46619 (0.56 µM, 56 µM), collagen (20 µg/mL, 2 µg/mL), epinephrine (20 µM, 2 µM), ADP (20 µM, 2 µM; Helena), and PAR4 (200 µM, 20 µM; Helena). To assess the impact of platelet inhibitors on MPA formation, whole blood was incubated for 30 minutes at RT in the presence of AZD1283 (1 µM; Cayman Chemicals), ML161 (50 µM; Cayman Chemicals), eptifibatide (18 µM; Cayman Chemicals), aspirin (1 mM; Cayman Chemicals), anti-human P-selectin antibody (5 µg/mL; BioLegend), or anti-human PSGL1 antibody (5 µg/mL; BioLegend), followed by 30 minutes of activation with U-46619 (0.56 µM), before being fixed and stained with monocyte and platelet markers as described above.

Platelet activation was determined by platelet surface expression of P-selectin and PAC-1 by flow cytometry, as previously described.[10] Briefly, P-selectin expression was determined with a PE-conjugated anti-CD62P antibody (BD Biosciences), and PAC-1 expression was determined with a FITC-conjugated anti-PAC-1 antibody (BD Biosciences). When indicated, lipopolysaccharide (LPS; 10 µg/mL) from Escherichia coli O111:B4 (Sigma) was added, and whole blood samples were incubated at 37°C for 4 hours. Following incubation and activation, samples were fixed and stained for flow analyses as described above.

Generation of Platelet Releasate

Citrate-anticoagulated blood samples were allowed to rest at RT for 15 minutes postphlebotomy. PRP was obtained by centrifuging blood at 200 g for 10 minutes. PRP was added to 1:10 (v/v) ACD-A (tris-sodium citrate [25 g/L], glucose [20 g/L], and citric acid [14 g/L]) and spun at 1,000 g for 10 minutes. The platelet pellet was washed in Tyrode's buffer (137 mM NaCl, 2.8 mM KCl, 1 mM MgCl₂, 12 mM NaHCO₃, 0.4 mM Na₂HPO₄, 5.5 mM glucose, 10 mM HEPES, pH 7.4) and 1 μM PGE₁ (Sigma), before centrifugation at 1,000 g for 10 minutes and resuspension at 500,000/µL in Tyrode's buffer containing 2 mM CaCl₂, and incubation at RT for 30 minutes. Platelet-secreted factors were then collected by isolating the supernatant following centrifugation at 1,000 g for 3 minutes. Platelet supernatants were stored at −80°C before use.

Whole blood or ACD-incubated PRP was incubated with platelet inhibitors for APT experiments. Citrate-anticoagulated blood was incubated with either aspirin (1 mM final concentration), AZD1283 (1 µM final concentration), ML161 (50 µM final concentration), eptifibatide (18 µM final concentration), or with Tyrode's buffer containing 2 mM CaCl₂ for 20 minutes, and PRP was obtained from each tube by centrifugation at 200 g for 10 minutes. PRP was added to 1:10 (v/v) ACD-A and 1 μM PGE₁ (Sigma), and was then centrifuged at 1,000 g for 10 minutes and resuspended at 500,000/µL in Tyrode's buffer containing 2 mM CaCl₂, plus addition of platelet inhibitors at the previously specified concentrations, at which point the platelets were incubated at RT for 30 minutes. Platelet-secreted factors were then collected by isolation of the supernatant following centrifugation at 1,000 g for 3 minutes. Platelet supernatants were stored at −80°C before use.

RNA-Seq

Primary human CD14-isolated monocytes cultured in RPMI-1640 medium (ATCC) supplemented with 10% heat-inactivated fetal bovine serum (FBS; Gibco) were treated for 6 hours with platelet releasate generated from seven healthy human controls, or Tyrode's buffer as vehicle control. Total RNA was isolated using TRIzol reagent (Invitrogen) and Direct-zol RNA MiniPrep columns (Zymo Research); RNA quality and quantity were determined with a Bioanalyzer 2100 (Agilent Technologies). Sequencing libraries were barcoded and prepared using the Clontech SMART-Seq HT with Nxt HT kit (Takara Bio, United States), and libraries sequenced single end on an Illumina NovaSeq 6000.

Data Processing (NYU)

FASTQ files from RNA-sequencing were processed using the Seq-N-Slide pipeline.[16] Reads were aligned to the hg38 genome using STAR[17] v2.6.1 and quantified using featureCounts[18] v1.6.3. Read quality was assessed using FASTQC[19] v0.11.7.

Bioinformatic Analyses (NYU)

All downstream analysis was performed in R[20] v3.6.1. Differential expression analysis was performed via DESeq2[21] v1.24. Multiple hypothesis correction was done using the Benjamini–Hochberg method. Volcano plots were created using ggplot2 v3.2.1. GSEA analyses were performed using clusterprofiler (https://www.liebertpub.com/doi/10.1089/omi.2011.0118).

PBMC and Monocyte Isolation

Human monocytes were isolated from buffy coats obtained from the New York Blood Center by density gradient centrifugation followed by positive selection using magnetic CD14 beads (Miltenyi Biotec). Briefly, buffy coats were diluted 1:1 (v:v) with phosphate-buffered saline (PBS; Corning). Ficoll PAQUE (Fisher Scientific) in a canonical tube was gently overlaid with the diluted blood without breaking the surface plane, followed by centrifugation at 2,000 rpm (on a Centrifuge 5810 R, Eppendorf) for 15 minutes without brake. Peripheral blood mononuclear cells (PBMCs) were collected and washed by centrifugation at 1,400 rpm for 12 minutes (with break). The cell pellet was then diluted in RPMI-1640 (ATCC) supplemented with 10% heat-inactivated FBS (Gibco), and cell concentration and viability were checked. Using the CD14 MicroBeads isolation kit (Miltenyi Biotec), monocytes were magnetically labeled with magnetic CD14 beads and collected within a MACS Column (Miltenyi Biotec) in the magnetic field of a MACS Separator. Unlabeled cells passed through the column. Monocytes were then resuspended in freezing media containing 40% RPMI (ATCC), 50% heat-inactivated FBS (Gibco), and 10% DMSO (Miltenyi), and were transferred to cryovials and frozen prior to use. Monocyte cell purity as assessed by flow cytometry measuring CD14 positivity was always above 97%.

Monocyte - Platelet Releasate Coincubation Assays

Frozen human CD14-isolated monocytes were thawed at 37°C and washed with PBS before use. After confirming a cellular viability of higher than 95% using Trypan Blue staining (Invitrogen), monocytes were then cultured in RPMI-1640 medium (ATCC) supplemented with 10% heat-inactivated FBS (Gibco) for 6 hours at 37°C and 5% CO₂ in the presence of platelet releasates treated with platelet inhibitors generated from healthy human donors as described above, or Tyrode's buffer (plus each respective platelet inhibitor) as vehicle control. After incubation, cells were harvested and washed with PBS, and total RNA was isolated using TRIzol reagent (Invitrogen) and Direct-zol RNA MiniPrep columns (Zymo Research). Complementary DNA (cDNA) was synthesized using the iScript cDNA Synthesis Kit (Bio-Rad) for mRNA quantification. RT-qPCR was performed using a QuantStudio 3 (Thermo Fisher). mRNA was normalized to GAPDH as a housekeeping gene. The following primer sequences were used: GAPDH for 5′- GCGAGATCCCTCCAAAATCA-3′ and rev 5′-GACTGGTCATGAGTCCTTC-3′, oncostatin m (OSM) for 5′- TACTGCTCACACAGAGGACGC-3′ and rev 5′-CTATAGCCGCCATGCTCGC-3′, suppressor of cytokine signaling-3 (SOCS3) for 5′-CTGTCGCGGATCAGAAAGGT-3′ and rev 3-GCTCCAAGAGCGAGTACCAG-3′, and SOCS1 for 5′-TTTTCGCCCTTAGCGTGAAGA-3′ and rev 5′-GAGGCAGTCGAAGCTCTCG-3′.

Protein Assays

Interleukin (IL)-6 and IL-8 concentrations in the supernatant of monocytes treated with platelet releasates were measured by a LEGENDplex bead-based immunoassay (BioLegend) and Oncostatin M concentrations were measured by an Oncostatin M ELISA kit (Abcam) according to the manufacturer's instructions.

Statistical Analysis

The Shapiro–Wilk test was used to test for normal distribution. Parametric continuous variables were compared with a paired t-test, or with a one-sample t-test, and the Mann–Whitney test was used for nonparametric variables. Two-sided p-values <0.05 were considered statistically significant. Statistical analyses were performed with GraphPad and R version 3.6.1. Unless otherwise specified, figures are presented as box-and-whisker plots with 25th and 75th percentiles and median.

Results

Monocyte–Platelet Aggregates Are Increased in Patients with COVID-19

To investigate the phenotype of circulating monocytes bound to platelets, we analyzed whole blood samples from COVID-19 patients and controls ([Supplementary Table S2] [online only]).[13] Consistent with a hyperreactive platelet phenotype,[13] [22] [23] MPAs (CD45⁺CD14⁺CD61⁺) were increased in patients with COVID-19 versus controls ([Fig. 1A, B]). When stratified into monocyte subtypes (classical [CD14⁺⁺ CD16⁻], intermediate [CD14⁺⁺ CD16⁺], and nonclassical [CD14⁽⁺⁾ CD16⁺⁺]), MPAs were higher in all monocyte subtypes in COVID-19 versus controls ([Fig. 1C, D]). The intermediate monocyte subtype appears to bind platelets preferentially in COVID-19 patients and controls ([Fig. 1D]). We next investigated if platelets alter the phenotype of monocytes. Relative to platelet-free monocytes (CD61⁻), monocytes aggregated to platelets (CD61⁺) had increased expression of TF and CD11b irrespective of disease state ([Fig. 1E, F]). A similar phenotype was found in subjects with Systemic Lupus Erythematosus (SLE). Consistently, MPAs were higher in SLE ([Supplementary Fig. 1A] [online only]) and attachment of platelets on monocytes was associated with higher monocyte expression of inflammatory markers ([Supplementary Fig. 1B], [C] [online only]). In summary, our findings indicate that proinflammatory platelets alter the phenotype of circulating monocytes.

Fig. 1 Elevated monocyte–platelet aggregates in patients with COVID-19. (A) Flow-gating strategy used for detection of monocyte–platelet aggregates (MPAs) in whole blood. After lysis of red blood cells, monocytes were identified based on side-scatter properties and positive staining for CD14 within CD45-positive cells (upper flow plot). MPAs (CD45⁺ CD14⁺ CD61⁺, MPA) were then detected by CD61-positivity (lower flow plot) and calculated as percentage (%) of all gated monocytes. (B) MPAs in COVID-19 patients (red bar) and in controls (blue bar). p-Values determined by unpaired t-test. (C) CD45⁺ gated monocytes were stratified based on expression of CD14 and CD16 in classical (CD14⁺⁺ CD16⁻), intermediate (CD14⁺⁺ CD16⁺), and nonclassical (CD14⁽⁺⁾ CD16⁺⁺) monocyte subtypes. Shown is an exemplary flow plot of a clinical sample. (D) Percentage of CD61+ monocytes (MPA) of all monocytes within each (classical, intermediate, and nonclassical) subtype in COVID-19 patients and in controls. p-Values determined by unpaired t-tests. (E) Percentages of tissue factor (TF)-positive monocytes and (F) MFI of CD11b expression on CD61− and CD61+ monocytes in COVID-19 patients and healthy controls based on the gating strategy depicted in (A). p-Values within patient and control groups determined by paired t-tests and between groups by unpaired t-test. All data presented as *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. MFI, mean fluorescence intensity.

Platelets Induce a Proinflammatory Transcriptome in Monocytes

To assess the pathways by which platelets mediate their proinflammatory effects, we next investigated the effect of platelets on the monocyte transcriptome. Incubation of human primary monocytes with platelet releasate resulted in a significant change to the monocyte transcriptome, with 1,775 differentially expressed transcripts (adjp < 0.05; 909 upregulated and 866 downregulated; [Fig. 2A]). Among the most upregulated genes were genes encoding for proinflammatory chemokines (CCL20), cytokines (IL1β), and coagulation factors (F3). Genes encoding for ligands involved in apoptosis (TNFSF10) and phagocytosis (CD36), and proteins involved in viral infections (IFIT2) were significantly downregulated. Gene Set Enrichment Analysis (GSEA) of platelet-releasate-treated monocytes revealed altered pathways associated with tumor necrosis factor (TNF) signaling, inflammatory responses, and coagulation ([Fig. 2B, C]). Transcripts related to IL6 signaling, a pathway we previously reported to be upregulated in myeloid cells by platelets,[24] OSM and SOCS3, were significantly upregulated (p < 0.0001, [Fig. 2A, D]). Both OSM and SOCS3 are important mediators in the pathogenesis of CVD.[24] [25] [26] Importantly, upregulation of mRNA transcripts for IL6, IL8, and OSM was reflected by elevated antigen expression in the supernatant of PR-treated monocytes ([Supplementary Figs. S2] and [S9A] [online only]).

Fig. 2 Platelet releasates induce upregulation of inflammatory transcripts in human monocytes. CD14+ selected monocytes from healthy human donors were incubated for 6 hours with platelet releasates from healthy donors. Monocytes were then washed, lysed, and RNA was isolated. (A) Volcano plots of differentially expressed monocyte transcripts (adjp < 0.05, |log₂FoldChange| > 0.6) between monocytes that were treated with platelet releasates from healthy donors (red) and untreated monocytes (petrol). (B) Bar chart depicting upregulated (red bars, right side) and downregulated (petrol bars, left side) pathways based on normalized enrichment score (NES) in monocytes treated with healthy platelet releasates compared to nontreated monocytes (adjp < 0.05). (C) Enrichment plots of three of the most upregulated pathways in monocytes treated with platelet releasates compared to Tyrode's controls, obtained by gene set enrichment analysis of differentially expressed genes. Relative gene positions in the ranked list of genes are indicated by straight lines under the graph. Depicted are enrichment plots for TNF-α signaling, inflammatory response, and coagulation. (D) Bar plot (mean ± SEM) of normalized expression counts of proinflammatory and proatherogenic transcripts oncostatin M, SOCS3, IL6, CCL20, IL1b, and IL8 in human monocytes treated with platelet releasates from healthy donors (red bars) compared to monocytes treated with Tyrode's control (blue bars). Reported false-discovery rate (FDR)-adjusted p-values output from DESeq2 (*p < 0.05, ****p < 0.0001). SEM, standard error of the mean; TNF-α, tumor necrosis factor-α.

Collectively, these data support a key role for platelets and platelet-derived mediators in enhancing a proinflammatory and prothrombotic monocyte transcriptome.

Targeting P-Selectin, P2Y₁₂, and PAR1 Suppresses MPA Formation

To test whether APT can influence the proinflammatory effect of platelets, we next investigated the effect of platelet-targeted therapies on MPA and platelet-mediated monocyte activation. To simulate platelet activation and MPA formation as a model for thromboinflammation, we treated whole blood with different platelet agonists, including U-46619, collagen, epinephrine, ADP, and PAR-4-activating peptide ([Supplementary Fig. S3A] [online only]). Consistent with Zhou et al,[15] treatment with U-46619 (0.56 μM) induced robust MPA formation ([Fig. 3A]). Targeting the platelet:monocyte axis with anti-P-selectin and anti-PSGL1 resulted in a significant 85 and 87% decrease in MPA, respectively (p < 0.001; [Fig. 3B]).

Fig. 3 Platelet inhibitors interfere with U-46619-induced increase in MPA. All experiments were performed in citrate-anticoagulated whole blood. Monocyte–platelet aggregates (MPA; %) were assessed by quantification of CD61+ event of CD45 + CD14 + CD16+ monocytes by flow cytometry. (A) MPA formation following stimulation for 30 minutes with U-46619 in a final concentration of 0.56 µM (red bar) compared to a nonstimulated control. p-Values determined by unpaired t-test. (B) Whole blood was incubated with platelet inhibitors anti-P-selectin (0.5 µg/mL), anti-PSGL1 (0.5 µg/mL), or (C) PAR1 inhibitor (ML161, 50 µM), P2Y₁₂ inhibitor (AZD 1283, 1 µM), GP IIb/IIIa inhibitor (eptifibatide, 18 µM), or aspirin (COX-1, 1 mM) for 30 minutes, followed by U-46619 stimulation (0.56 µM) for 30 minutes. MPA formation of U-46619-stimulated whole blood that had been pretreated with different platelet inhibitors was compared to MPA formation of stimulated controls set as 100% (as shown as a dashed line). p-Values determined by one-sample t-tests. All data presented as *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001.

To assess the impact of traditional APT, we pretreated blood with inhibitors of PAR1, P2Y₁₂, COX-1, and GP IIb/IIIa ([Supplementary Fig. S3B–D], [Supplementary Table S1] [online only]).[24] [27] [28] P2Y₁₂ and PAR1 inhibition significantly suppressed MPA formation by 30 and 21%, respectively (p < 0.01 for each comparison, [Fig. 3C]), with MPA reductions consistent across monocyte subtypes ([Supplementary Fig. S4A], [B] [online only]).

Next, we investigated the effect of activated platelets on the formation of leukocyte-PA (LPA) neutrophil-PA (NPA), and lymphocyte-PA (LyPA). Stimulation with U-46619 increased LPA and NPA but did not affect LyPA ([Supplementary Fig. 5A], [D], [G] [online only]). Consistent with our MPA data, blocking P-selectin and PSGL1, or P2Y₁₂, and PAR1 inhibition significantly impaired LPA and NPA formation ([Supplementary Fig. 5B], [C], [E], [F], [H], [I] [online only]).

Activated platelets are characterized by increased surface expression of P-selectin (α-granule release) and PAC-1 (activated GP IIb/IIIa). As expected, stimulation of whole blood with U-46619 increased platelet expression of P-selectin and PAC-1 ([Supplementary Fig. S5A, D] [online only]). While P-selectin inhibition decreased P-selectin expression on platelets, no effect was seen on PAC-1 expression ([Supplementary Fig. S6B], [E] [online only]). Among traditional platelet inhibitors, only targeting P2Y₁₂ decreased both platelet α-granule release and activated GP IIb/IIIa signaling, which is a key receptor for fibrinogen-mediated platelet–platelet aggregation ([Supplementary Fig. S6C], [F] [online only]).

P-Selectin, P2Y₁₂, and PAR1 Inhibition Suppresses Platelet-Mediated Monocyte Proinflammatory Expression

Platelet P-selectin triggers rapid surface TF expression in monocytes[29]; however, it is unknown whether this occurs in all monocytes or monocyte subsets. Consistent with previous reports,[29] we find significant upregulation of TF following platelet agonist stimulation of whole blood ([Fig. 4A]), which can be suppressed by blocking P-selectin and PSGL1 ([Fig. 4B]). Notably, we found that only monocytes bound to platelets had increased TF expression ([Fig. 4C]). Among platelet inhibitors, PAR1 and P2Y₁₂ inhibition significantly decreased monocyte TF expression, while there was no effect following inhibition of GP IIb/IIIa or COX-1 ([Fig. 4D]). The effect was restricted to monocytes attached to platelets (CD61+ monocytes) ([Fig. 4E]) and did not affect monocytes without adherent platelets (CD61− monocytes.) ([Fig. 4F]).

Fig. 4 Platelet inhibitors interfere with U-46619-induced increase in monocyte tissue factor. (A) Percentages of tissue factor (TF)-positive monocytes in whole blood following 30 minutes of stimulation with U-46619 (0.56 µM) compared to nonstimulated whole blood. p-Value determined by paired t-test. (B) Percentages of TF-positive monocytes of all monocytes in U-46619-stimulated whole blood pretreated with anti-P-selectin (0.5 µg/mL) and anti-PSGL1 (0.5 µg/mL) compared to U-46619-stimulated whole blood set as 100% (as marked by a dashed line). p-Values determined by one-sample t-tests. (C) Percentage of TF-positive monocytes of monocytes without platelets (CD61- mon) and of monocytes attached to platelets (CD61+ mon) in nonstimulated (blue bars) and U-46619-stimulated (red bars) whole blood. p-Values determined by paired t-tests. (D) Percentages of TF-positive monocytes of all monocytes, (E) of monocytes attached to platelets (CD61+ monocytes), and (F) of monocytes without platelets (CD61− monocytes) in U-46619-stimulated whole blood in the presence of platelet inhibitors targeting PAR1, P2Y₁₂, GP IIb/IIIa, and COX-1. Amounts of TF-positive monocytes were compared to TF-positive monocytes in U-46619-stimulated whole blood set as 100% (marked as a dashed line). p-Values determined by one-sample t-tests. (G) Whole blood was incubated with lipopolysaccharide (LPS; 10 µg/mL, red bar) or a vehicle (blue bar) for 4 hours at 37°C. Percentages of TF-positive monocytes and (H) of MPA in controls and in LPS-stimulated whole blood. p-Values determined by paired t-tests. All data presented as *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. LPS, lipopolysaccharide; MPA, monocyte–platelet aggregate.

Conversely, we found that stimulation of monocytes, in the absence of platelet activation, leads to platelet-independent expression of monocyte TF ([Fig. 4G]). LPS treatment of blood increased monocyte TF expression in the absence of MPA formation ([Fig. 4H]). Consistent with no change in MPA formation under LPS, there was no increase in platelet activation markers ([Supplementary Fig. S7A], [B] [online only]).

CD40 is a co-stimulatory molecule expressed on proinflammatory monocytes.[30] Monocyte CD40 expression is, in part, regulated by TNF-α signaling,[31] the top upregulated pathway identified in our RNA-seq ([Fig. 2B]). Therefore, we assessed if monocyte CD40 expression is regulated by platelet exposure and the impact of APT. Similar to TF, U-46619 increased monocyte CD40 expression ([Fig. 5A]), which was suppressed via blocking of P-selectin and PSGL1 ([Fig. 5B]). MPA had significantly higher CD40 expression than monocytes without platelets ([Fig. 5C]). Again, among traditional platelet inhibitors, targeting either PAR1 or P2Y₁₂ reduced monocyte CD40 expression ([Fig. 5D]), which could be attributed to monocytes attached to platelets (CD61+ monocytes) ([Fig. 5E, F]). Like TF, platelet-independent monocyte CD40 expression could be induced by LPS ([Fig. 5G]) and did not depend on MPA formation ([Fig. 4H]). However, in contrast to TF and CD40, increased monocyte CD11b expression following U-46619 stimulation—albeit platelet-dependent ([Supplementary Fig. S8A], [C] [online only])—was not altered by platelet inhibitors ([Supplementary Fig. S8B], [D–F] [online only]).

Fig. 5 Platelet inhibitors interfere with U-46619-induced increase in monocyte CD40. (A) Percentages of CD40-positive monocytes in whole blood following 30 minutes of stimulation with U-46619 (0.56 µM). p-Value determined by paired t-test. (B) Percentages of CD40-positive monocytes in U-46619-stimulated whole blood pretreated with anti-P-selectin (0.5 µg/mL) and anti-PSGL1 (0.5 µg/mL) compared to U-46619-stimulated whole blood set as 100% (as marked by a dashed line). p-Values determined by one-sample t-tests. (C) Percentage of CD40-positive monocytes of monocytes without platelets (CD61 − ) and of monocytes attached to platelets (CD61 + ) in nonstimulated (blue bars) and U-46619-stimulated (red bars) whole blood. p-Values determined by paired t-tests. (D) Percentages of CD40-positive monocytes of all monocytes, (E) of monocytes attached to platelets (CD61+ monocytes), and (F) of monocytes without platelets (CD61− monocytes) in U-46619-stimulated whole blood in the presence of platelet inhibitors targeting PAR1, P2Y₁₂, GP IIb/IIIa, and COX-1 compared to CD40-positive monocytes in U-46619-stimulated whole blood set as 100% (marked as a dashed line). p-Values determined by one-sample t-tests. (G) Percentages of CD40-positive monocytes in nonstimulated (blue bar) versus LPS-stimulated (red bar) whole blood (following incubation with 10 µg/mL LPS for 4 hours at 37°C. p-Values determined by paired t-test. All data presented as ^{^} p < 0.1, *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001. LPS, lipopolysaccharide.

Our data demonstrate that P-selectin–PSGL1-mediated platelet monocyte interaction rapidly shifts monocytes toward a proinflammatory phenotype. A decrease in monocyte activation markers TF and CD40 by traditional platelet inhibitors tracks with their ability to target platelet P-selectin expression.

Platelet Inhibitors Attenuate Monocyte Inflammatory Transcripts

As acute platelet–monocyte interactions mediate rapid alterations to monocyte cell surface receptor expression, we next aimed to understand the chronic outcome of platelet–monocyte interactions on the background of traditional antiplatelet drugs. To investigate this, we incubated monocytes with platelet releasates generated in the presence of PAR1, P2Y₁₂, COX-1, and GP IIb/IIIa inhibitors ([Fig. 6A]). Both OSM and SOCS3 were significantly upregulated by platelets in our monocyte RNA-Seq datasets (OSM; log2FC 4.02, adjP 2.38 × 10⁻³⁸ and SOCS3; log2FC 2.9, adjP 1.15 × 10⁻⁹) ([Fig. 2A], [D]). Confirming our findings, platelet releasates generated from whole blood in the absence of platelet inhibitors resulted a significant increase in SOCS3 and OSM ([Fig. 6B], [D]). Incubation of platelet releasates generated in the presence of APT found that antagonism of both P2Y₁₂ and GP IIb/IIIa reduced monocyte SOCS3 (25 and 32% reduction, p < 0.05, respectively) and OSM expression (30 and 22% reduction, p < 0.05, respectively) ([Fig. 6C], [E]). Importantly, similar to our mRNA findings, expression of Oncostatin M antigen was increased in the supernatant of monocytes treated with PR, while P2Y₁₂ inhibition attenuated this effect ([Supplementary Fig. S9A], [B] [online only]).

Fig. 6 Monocyte OSM and SOCS3 expression induced by platelets treated with different types of platelet inhibitors. (A) Platelet releasates (PRs) were generated from whole blood samples incubated for 30 minutes with platelet inhibitors (50 µM ML161, 1 µM AZD1283, 18 µM eptifibatide, or 1 mM aspirin) before platelet-rich plasma was generated by centrifugation. Platelets were then transferred to Tyrode's buffer supplemented with Ca²⁺ and PRs were collected following high-speed centrifugation of platelet resuspension. For monocyte–PR incubation assays, CD14+ selected human monocytes were incubated with PRs for 6 hours. Monocytes were then lysed and RNA was collected for RT-qPCR analyses. (B) Monocyte mRNA expression of SOCS3 and (D) OSM compared to nontreated monocytes. Expression of SOCS3 (C) and OSM (E) following exposure of CD14-isolated human monocytes to PRs generated in the presence of PAR1 inhibitor ML161 (50 µM), P2Y₁₂ inhibitor AZD1283 (1 µM), COX-1 inhibitor aspirin (1 mM), and GP IIb/IIIa inhibitor eptifibatide (18 µM) for 6 hours (right panels). Data expressed relative to PR-treated cells in the absence of platelet inhibitors (n = 7 unique releasate donors; *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001 by a paired t-test). PRP, platelet-rich plasma; WB, whole blood.

Our data support a potent effector role for platelets on monocytes. Among traditional platelet inhibitors, targeting platelet receptor P2Y₁₂ was an effective strategy in interfering with platelet-induced proinflammatory and proatherogenic changes in the monocyte phenotype and transcriptome.

Discussion

This study performed a comprehensive analysis of activated platelets' effect on monocytes on both transcriptional and translational levels. By leveraging from clinical conditions associated with enhanced platelet activity and thrombotic risk, we clearly demonstrate a proinflammatory platelet-associated effect on monocytes. Our findings are strengthened by in vitro studies with and without platelet aggregates. We add novel data on the effect of APT on the platelet-induced proinflammatory monocytes. Importantly, we demonstrate a beneficial role in targeting platelet P2Y₁₂, resulting in lower MPA and hence dampening the detrimental effect of proinflammatory platelets on monocytes.

An increase in circulating MPA has been linked to proinflammatory conditions.[32] [33] Consistently, MPAs were elevated in both of our clinical cohorts (COVID-19 and SLE), and they exhibited elevated expression of monocyte activation markers including TF and CD11b.[34] [35] [36] Our finding that both markers were significantly higher on the monocytes attached to platelets in COVID-19 and SLE patients than in healthy controls underlines the proinflammatory modulatory platelet role on the monocyte phenotype.

Importantly, the increase of MPA in other patient populations such as those with CVDs, including chronic atherosclerosis and myocardial infarction (MI),[2] [10] [37] [38] [39] is indicative of similarities in the pathophysiology of inflammatory diseases with enhanced risk of prothrombotic complications.

Consistent with others,[15] thromboxane analog U-46619 potently induced MPA and was therefore used as a model for platelet activation in thromboinflammation. Targeting P-selectin or monocyte PSGL1 resulted in the most prominent decrease in platelet-induced MPA in whole blood in vitro, underlining the critical involvement of these receptors for monocyte platelet interaction. Accordingly, targeting the P-selectin–PSGL1-axis offers therapeutic potential in preventing (athero)thrombosis, as demonstrated by various preclinical studies.[40] [41]

PSGL1 and P-selectin inhibitors target the final path of platelet activation. In contrast, AZD1283 and PAR1 inhibit G-protein coupled receptors (GPCRs) upstream of P-selectin expression. Blocking one of these receptors—the ADP receptor P2Y₁₂ by AZD1283—decreased MPA in whole blood in response to U-46619 stimulation ex vivo. In line with this, platelet aggregation and α-granule release in response to U-46619 were prevented when P2Y₁₂ was blocked in human samples in prior studies.[42] [43] Also, inhibition of PAR1 by ML161 was also effective in attenuating MPA, however, to a reduced degree. In contrast, MPA did not change in the presence of the COX-1 inhibitor aspirin and even increased under eptifibatide-mediated inhibition of GP IIb/IIIa. Both platelet inhibitors interfere with targets not directly involved with or only downstream of GPCR signaling. Our findings underline that blocking GPCR signaling—in addition to blocking the P-selectin–PSGL1 axis—not only prevents platelet activation but also interferes with platelet-mediated upregulation of proinflammatory monocyte surface markers.

Activated platelets induced rapid and potent monocyte TF expression. This was most likely mediated by surface exposure of preformed cellular TF protein and required the platelet–monocyte P-selectin–PSGL1 interaction.[29] [44] In addition, soluble P-selectin has been shown to induce monocyte de novo TF protein synthesis over several hours and might have contributed to our RNA-Seq findings.[33]

In a recent study by Hottz et al, platelets from COVID-19 patients co-cultured with healthy monocytes induced MPA and monocyte TF expression. Similar to our findings, both were prevented in the presence of a P-selectin inhibitor. In their study, only the GP IIb/IIIa inhibitor abciximab but not clopidogrel prevented COVID-19 platelets from inducing monocyte TF, and none of them affected MPA ex vivo.[45] In contrast to eptifibatide, abciximab also targets leukocyte-expressed α_mβ₂.[46] Also, the lack of effect under clopidogrel ex vivo in this study might be due to it being a prodrug that needs to be metabolized to become active.[29] [45]

Importantly, procoagulant monocyte TF initiates the extrinsic pathway of the coagulation cascade, resulting in thrombin generation.[47] Based on previous studies,[48] [49] [50] we hypothesize that platelet–monocyte interaction is capable of initiating TF-driven coagulation activation, and thereby contributes to thromboinflammation.

While induction of monocyte CD40 surface expression has predominantly been linked to CD40 gene transcription,[31] we did not find elevated CD40 mRNA expression in our RNA-Seq dataset of monocytes treated for 6 hours with platelet releasates SOCS3, which was one of the most robust upregulated genes that inhibits expression of CD40.[51] This negative feedback regulation may explain why CD40 expression was higher on the surface of monocytes attached to platelets after 30 minutes of U-46619 stimulation of whole blood but CD40 mRNA was not upregulated in monocytes treated with platelet releasates for 6 hours. Alternatively, the short period in which monocytes upregulated CD40 is indicative of platelet P-selectin monocyte PSGL1-mediated surface expression of preformed CD40 and not necessarily affected by protein transcription. We did not see a decrease in monocyte CD11b in the presence of platelet inhibitors. Monocyte CD11b is a ligand for platelet GP Ibα which is involved in the early steps of platelet activation upstream of platelet degranulation.[52] All platelet inhibitors used in our study target signaling pathways downstream of GP Ibα, which might explain their lack of effect on CD11b expression in our analyses.

While our CD14-isolated monocytes comprised a high purity of >97%, preliminary studies indicated that a small proportion of isolated monocytes were platelet-positive (<10%, data not shown). This may affect the presented RNA-seq analyses; however, given that platelets express very low quantities of RNA relative to monocytes, it is unlikely to be a significant contributor.

Supporting the concept of platelet–monocyte mediated immunothrombosis, pathways connected to inflammation and atherosclerosis were upregulated in monocytes treated with platelet releasates.[2] [53]

Importantly, monocyte mRNA transcripts coding for crucial mediators in atherosclerosis, including SOCS3 and OSM, were highly elevated. Oncostatin M belongs to the IL-6 family of cytokines, is increased in patients with CAD, and contributes to plaque rupture in atherosclerosis.[25] [26] [54] We recently demonstrated a mechanistic role for platelet-induced upregulation of SOCS3 in macrophages, resulting in enhanced proinflammatory myeloid effector functions in a hypercholesteremic mouse model and suggesting a link between platelets and SOCS3-mediated macrophage activation in clinical cohorts of patients with MI and PAD.[24]

Intriguingly, platelet release factor-induced upregulation of monocyte SOCS3 and OSM was decreased under AZD1283 and eptifibatide. Platelet releasates contain active substances released from α and dense granules during high-speed platelet centrifugation and carry platelet-derived extracellular vesicles (PEVs). Evidence shows that PEVs adhere to monocytes, thereby contributing to immunothrombosis in CVD.[55] Interestingly, PEVs were elevated in patients 6 months after acute MI.[56] Integrin GP IIb/IIIa activation is essential for PEV release, and inhibitors against P2Y₁₂ and GP IIb/IIIa have decreased PEV formation.[56] [57] Supporting this, both AZD1283 and eptifibatide decreased platelet expression of activated GP IIb/IIIa (PAC-1) in our study. These findings indicate that release of PEV might have contributed to the upregulation of proatherosclerotic SOCS3 and OSM in monocytes exposed to platelet releasates.

Interestingly, platelet activation was also associated with elevated levels of neutrophil–platelet aggregates, supporting a role for other immune cells in platelet-mediated thromboinflammation. A decrease in platelet–neutrophil interaction under APT underlines its therapeutic potential to target platelet-induced immune responses beyond monocyte activation.

In conclusion, we show that activated platelets affect the monocyte phenotype and transcriptome by both direct platelet–monocyte interaction and by platelet-released mediators. Platelet P2Y12 inhibition was the most potent APT strategy to prevent MPA, platelet-induced surface expression of monocyte activation markers, and upregulation of proinflammatory SOCS3 and OSM in monocytes.

Conflict of Interest/Disclosures

Dr. J.B. is PI for the NIH-funded ACTIV4a trial investigating P2Y12 inhibitors in patients hospitalized with COVID-19. C.C.R., M.A.S., T.T.W., M.C., K.M., T.S., H.B., and T.J.B. declare that they have no conflict of interest.

Author Contributions

The study was conceived by C.C.R., T.J.B., and J.S.B. Experiments were performed by C.C.R., M.A.S., T.T.W., K.M., T.S., and H.E.B. Data analysis, interpretation, and visualization were conducted by C.C.R., M.C., T.J.B., and J.S.B. The first version of the manuscript was drafted by C.C.R. and critically revised and edited by T.J.B. and J.S.B. All co-authors reviewed and edited the manuscript.

^* These authors contributed equally.

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Publikationsverlauf

Eingereicht: 09. Mai 2022

Angenommen: 23. September 2022

Artikel online veröffentlicht:
11. Januar 2023