Skip to main content
Erschienen in: Annals of Intensive Care 1/2021

Open Access 01.12.2021 | COVID-19 | Research

Platelet activation in critically ill COVID-19 patients

verfasst von: Nader Yatim, Jeremy Boussier, Richard Chocron, Jérôme Hadjadj, Aurélien Philippe, Nicolas Gendron, Laura Barnabei, Bruno Charbit, Tali-Anne Szwebel, Nicolas Carlier, Frédéric Pène, Célia Azoulay, Lina Khider, Tristan Mirault, Jean-Luc Diehl, Coralie L. Guerin, Frédéric Rieux-Laucat, Darragh Duffy, Solen Kernéis, David M. Smadja, Benjamin Terrier

Erschienen in: Annals of Intensive Care | Ausgabe 1/2021

Abstract

Background

Microvascular, arterial and venous thrombotic events have been largely described during severe coronavirus disease 19 (COVID-19). However, mechanisms underlying hemostasis dysregulation remain unclear.

Methods

We explored two independent cross-sectional cohorts to identify soluble markers and gene-expression signatures that discriminated COVID-19 severity and outcomes.

Results

We found that elevated soluble (s)P-selectin at admission was associated with disease severity. Elevated sP-selectin was predictive of intubation and death (ROC AUC = 0.67, p = 0.028 and AUC = 0.74, p = 0.0047, respectively). An optimal cutoff value was predictive of intubation with 66% negative predictive value (NPV) and 61% positive predictive value (PPV), and of death with 90% NPV and 55% PPV. An unbiased gene set enrichment analysis revealed that critically ill patients had increased expression of genes related to platelet activation. Hierarchical clustering identified ITG2AB, GP1BB, PPBP and SELPLG to be upregulated in a grade-dependent manner. ROC curve analysis for the prediction of intubation was significant for SELPLG and PPBP (AUC = 0.8, p = 0.046 for both). An optimal cutoff value for PBPP was predictive of intubation with 100% NPV and 45% PPV, and for SELPLG with 100% NPV and 50% PPV.

Conclusion

We provide evidence that platelets contribute to COVID-19 severity. Plasma sP-selectin level was associated with severity and in-hospital mortality. Transcriptional analysis identified PPBP/CXCL7 and SELPLG as biomarkers for intubation. These findings provide additional evidence for platelet activation in driving critical COVID-19. Specific studies evaluating the performance of these biomarkers are required.

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the coronavirus disease 2019 (COVID-19) pandemic [1]. Severe disease is characterized by an acute respiratory distress syndrome (ARDS), respiratory failure and death in about 1% of cases [2, 3]. Most important risk factors for severe disease include age, overweight, diabetes, hypertension and history of cardiovascular disease [4, 5]. Severe and critical patients were shown to develop arterial and venous thrombotic complications, such as pulmonary embolism, stroke and myocardial infarction [6, 7]. Markers of coagulation activation, in particular increased D-dimer, fibrinogen and von Willebrand factor (vWF) levels were found to be associated with critical illness, whereas only minor changes were noted in prothrombin time and platelet counts [811]. In addition, autopsy series described multiple thrombosis in deceased COVID-19 patients [12, 13]. These findings suggest vascular micro-thrombotic disease as a primary factor for mortality in critically ill COVID-19 [6, 14]. Therefore, some authors supported the systematic use of curative anticoagulation upon admission to intensive care unit (ICU) [15], a strategy that has been reported to decrease mortality in severe COVID-19 [8, 1618].
Mechanisms underlying increased thrombotic events are still unclear but accumulating evidence point to a key role for endothelial and platelet activation [19, 20]. As viral inclusions were described in endothelial cells, it has been hypothesized that endothelial cell injury and activation could drive platelet activation and subsequent coagulopathy [13, 21]. Therefore, dissecting the contribution of platelets to COVID-19 critical illness is key to understand SARS-CoV-2 infection pathogenesis and identify novel therapeutic strategies.
Platelet P-selectin is a key thromboinflammatory molecule involved in platelet activation and function. It has been demonstrated to play a crucial role in primary hemostasis by regulating platelet–leukocyte interactions, fibrin and tissue factor recruitment into platelet aggregates and thrombus formation [22]. Its soluble form, sP-selectin, is released upon platelet and/or endothelial cell activation and measurement of sP-selectin has been proposed as a reliable marker of in vivo platelet activation [23]. Moreover, sP-selectin levels have been shown to correlate with acute lung injury severity score and related death [24].
The aim of our study was to assess, in hospitalized COVID-19 patients, the ability of sP-selectin to predict requirement for mechanical ventilation and in-hospital mortality. Next, using whole-blood transcriptional data, we uncovered a platelet activation transcriptional signature associated with critical illness.

Methods

Cohorts

Two independent cohorts were analyzed for this study. Data used for the analysis of soluble P-selectin’s ability to predict admission to ICU were extracted from a non-interventional study that was conducted at European Georges Pompidou Hospital (Paris, France) and partially described in [25] (Cohort 1). Briefly, Cohort 1 included consecutive patients with SARS-CoV-2 infection. Inclusion criteria were patients over 18 years of age, with a proven SARS-CoV-2 infection, which presented to the emergency department with hospitalization criteria. Patients were then hospitalized into conventional wards or directly to the ICU. For all patients, baseline characteristics (demographic, treatment, clinical, cardiovascular risk factors and body mass index) and biological data were retrieved from the medical records using a standardized data collection. As a control non-COVID-19 septic ICU cohort, we included plasma samples from a previously described pre-pandemic cohort [25, 26].
Cohort 2 [27] was conducted between March 19, 2020 and April 3, 2020 in Cochin Hospital (Paris, France), in the setting of the local RADIPEM biological samples collection derived from samples collected in routine care. Inclusion criteria for COVID-19 inpatients were: age between 18 and 80 years, diagnosis of COVID-19 according to WHO interim guidance and positive SARS-CoV-2 RT-PCR testing on a respiratory sample (nasopharyngeal swab or invasive respiratory sample). Detailed clinical and immunological characterization of the cohort was previously described in [27]. Epidemiological, demographic, clinical, laboratory, treatment, and outcome data were extracted from electronic medical records using a standardized data collection form.
The severity of COVID-19 was classified at the time of inclusion based on the adaptation of the Sixth Revised Trial Version of the Novel Coronavirus Pneumonia Diagnosis and Treatment Guidance and described in [27].

Soluble P-selectin measurement

sP-selectin quantification was performed on Cohort 1. Plasmas were collected on 0.129 M trisodium citrate tubes (9NC BD Vacutainer, Plymouth, UK). Plasma poor platelet was obtained after centrifugation twice at 2500 g for 15 min. PPP was frozen after a second centrifugation at 2500 g for 15 min and stored at − 80 °C until analysis of vascular markers. Soluble P-selectin were quantified in PPP with a Human Magnetic Luminex Assay from R&D systems (Lille, France). Data were assessed with the Bio-Plex 200 using the Bio-Plex Manager 5.0 software (Bio-Rad, Marnes-la-Coquette, France). Normalized concentration (NC) used to calculate receiver operating characteristic (ROC) area under curve (AUC) p values represents sP-selectin concentration in pg/mL normalized to platelet numbers (106/mL).

Gene expression analysis

Detailed methods was previously reported in Hadjadj et al. [27]. Briefly, we analyzed 100 ng (5 μL) of total RNA from each sample using the Nanostring Human Immunology kit v2 according to manufacturer’s instructions. Raw RNA counts were adjusted using five housekeeping genes selected from the 15 candidate control genes provided by Nanostring, following the geNorm method. For gene set enrichment analysis (GSEA), genes were ordered by t-statistic from unpaired t test comparing normalized RNA levels of severe vs critical patients, and then fed to the gene set enrichment algorithm (GSEA version 4.0.3, Broad Institute), along with a pathway data set built from the Nanostring Immunology panel version 2 annotation file. Parameters were set as follows: method, pre ranked gene list; number of permutations, 2000; enrichment statistic, classic; min set size, 5; max set size, 200; and all other parameters as default. Hierarchical clustering of genes belonging to the hemostasis gene set was performed using hclust with default distance matrix. Heatmap displaying genes that are upregulated in a grade-dependent manner was obtained using pheatmap (package pheatmap), with data centered to 0 and scaled to unit variance for each gene. Normalized RNA count (NRC) used to calculate ROC AUC p values represents adjusted RNA count (to housekeeping genes) normalized to platelet numbers (109/L).

Statistical analyses

Quantitative variables were compared among groups using Kurskal–Wallis test followed by Dunn’s post-test, while quantitative variables were compared using the χ2 test of independence. Correlations coefficients and p values were assessed using Spearman’s method. ROC AUC p values were determined using Hanley’s method. Optimal thresholds were determined by maximization of Youden’s index. Multivariate logistic regression was performed using death as the dependent variable, and log10(normalized P-selectin), age and sex as independent variables. All analyses were two-sided and a p value smaller than 0.05 was considered statistically significant. Statistical analyses were performed using R v. 3.4.3 (CRAN).

Results

Patient characteristics

Cohort 1 consisted of 60 COVID-19 patients that were admitted to European Georges Pompidou Hospital and included upon admission. Clinical and biological characteristics are previously reported in [28] and described in Table 1. Briefly, median age was 58.5 years (IQR, 49 to 72) and 76.7% were male. Patients were analyzed after a median duration of 6 days (IQR, 4 to 7) after onset of first symptoms. Interval from first symptoms on hospital admission and from first symptoms on blood sampling coincided in most patients. Fever was present in 97% of the patients, and other most common symptoms were cough (83.3%), dyspnea (71.7%), fatigue (70.0%), myalgia (40.0%) and diarrhea (26.7%). Degree of COVID-19 severity was categorized as mild-to-moderate in 35 patients (clinical symptoms associated with dyspnea and requiring a maximum of 3 L/min), severe in 10 patients (respiratory distress requiring more than 3 L/min of oxygen and no other organ failure) and critical in 15 patients (respiratory failure requiring mechanical ventilation). Eleven out of 35 patients with mild-to-moderate disease and 3/10 patients with severe disease experienced clinical worsening and required mechanical ventilation. Thrombotic events were noted in 8 patients (3 mild-to-moderate, 2 severe and 3 critical). We also included and analyzed plasma samples from a previously described pre-pandemic cohort [25, 26] as an ICU control non-COVID-19 septic ICU cohort.
Table 1
Clinical characteristics and laboratory findings of patients from Cohort 1
Characteristics
All patients
Disease severity 
p value
 
N = 60
Mild-to-moderate
Severe
Critical
 
  
N = 35
N = 10
N = 15
 
Age, median (IQR), year
58.50 [49.00, 72.25]
59.00 [47.50, 74.00]
58.00 [47.25, 70.00]
58.00 [54.00, 68.50]
0.98
Male, no. (%)
46 (76.7)
22 (62.9)
10 (100.0)
14 (93.3)
0.011
Median interval from first symptoms
6.0 [4.0, 8.0]
6.0 [3.0, 7.0]
4.0 [4.0, 7.5]
7.0 [6.5, 9.0]
0.063
Coexisting disorder, no. (%)
     
 Any
 
18 (51.4)
5 (50.0)
11 (73.3)
0.18
 COPD
1 (1.7)
0 (0.0)
0 (0.0)
1 (6.7)
0.21
 Diabetes
16 (26.7)
8 (22.9)
3 (30.0)
5 (33.3)
0.72
 Hypertension
27 (45.0)
14 (40.0)
5 (50.0)
8 (53.3)
0.65
 Cardiovascular disease
12 (20.0)
5 (14.2)
3 (30.0)
4 (26.7)
0.26
 Cancer or hemopathy
3 (5.0)
3 (8.6)
0 (0.0)
0 (0.0)
0.32
 Chronic renal disease
8 (13.3)
4 (11.4)
3 (30.0)
1 (6.7)
0.21
 Overweight
39 (65.0)
19 (54.3)
7 (70.0)
13 (86.7)
0.026
Fever on admission
     
 Median temperature (IQR), °C
38.20 [37.70, 38.80]
38.20 [37.80, 38.70]
38.00 [37.60, 38.35]
38.70 [37.40, 39.00]
0.53
Symptoms on admission no. (%)
     
 Fever
58 (96.7 )
34 (97.1 )
9 (90.0)
15 (100)
0.38
 Cough
50 (83.3)
32 (91.4)
7 (70.0)
11 (73.3)
0.14
 Dyspnea
43 (71.7)
21 (60.0)
8 (80.0)
15 (100)
0.046
 Fatigue
42 (70.0)
21 (60.0)
8 (80.0)
15 (100)
0.36
 Myalgia
24 (40.0)
15 (42.9)
4 (40.0)
5 (33.3)
0.87
 Diarrhea
16 (26.7)
10 (28.6)
3 (30.0)
3 (20.0)
0.79
 Median oxygen requirement (IQR, L/min)
3.00 [2.00, 5.00]
2.00 [1.25, 2.00]
4.00 [4.00, 5.00]
MV
Clinical outcomes, no. (%)
     
 Thrombotic event (%)
8 (13.3)
3 (8.6)
2 (20.0)
3 (20.0)
0.44
 Clinical worsening requiring MV (%)
11 (31.4)
3 (30.0)
 Death (%)
17 (28.3)
4 (11.4)
2 (20.0)
11 (73.3)
< 0.001
Laboratory findings on admission
     
 Leukocytes (IQR), × 109/L
5.75 [4.47, 7.77]
5.40 [4.15, 6.85]
6.35 [5.05, 10.92]
7.60 [4.90, 11.90]
0.041
 Neutrophils (IQR), × 109/L
4.36 [3.13, 6.83]
3.74 [2.84, 5.18]
5.43 [3.89, 10.86]
6.99 [3.88, 10.48]
0.015
 Lymphocytes (IQR), × 109/L
0.85 [0.62, 1.15]
0.88 [0.71, 1.10]
0.85 [0.57, 1.25]
0.60 [0.46, 1.05]
0.19
 Monocytes (IQR), × 109/L
0.35 [0.24, 0.49]
0.35 [0.25, 0.48]
0.43 [0.35, 0.59]
0.26 [0.16, 0.53]
0.26
 Platelets (IQR), × 109/L
164 [124, 221]
165 [124, 216]
167 [135, 242]
162 [127.00, 258]
0.79
 CRP (IQR), mg/L
104 [62, 168]
86 [38, 120]
117 [109, 184]
161 [98, 207]
0.005
 Lactate dehydrogenase (IQR), U/L
 
 Fibrinogen (mean (SD)), g/L
5.83 [4.90, 6.50]
5.30 [4.62, 6.30]
6.80 [5.85, 7.38]
6.30 [5.65, 7.00]
0.006
 DDimer (mean (SD)), ng/ml
999 [662, 1724]
789 [537, 1270]
1145 [759, 2142]
1170 [988, 2151]
0.05
 Soluble Pselectine, pg/mL
23663 [18693, 30394]
20556 [17484, 29677]
25239 [21637, 28565]
27041 [24171, 38934]
0.048
Significant values (p < 0.05) are emphasized in bold
Quantitative variables are described as median (interquartile range) and compared using the Kruskal–Wallis test; qualitative variables are described as n (%) and compared using the χ2 test of independence
COPD chronic obstructive pulmonary disease, CRP C-reactive protein, IQR interquartile range, MV mechanical ventilation
Cohort 2 consisted of 50 patients with various degree of COVID-19 severity admitted to Cochin hospital and 18 healthy controls, and was described in [27]. For the purpose of the present study, only patients with whole-blood transcriptional analysis were included, i.e., 32 COVID-19 patients and 13 healthy controls. Characteristics of the patients are described in Table 2. Median age was 56 years (IQR, 51 to 65) and 78% were male, while median age of healthy controls was 59 years (IQR, 41 to 60) and 77% were male. Patients were analyzed after a median duration of 10 days (IQR, 9 to 11) after onset of first symptoms. Interval from first symptoms on hospital admission and from first symptoms on blood sampling coincided in most patients. Fever was present in 100%, and other most common symptoms were dyspnea (100%), fatigue (32%), cough (97%), myalgia (97%) and diarrhea (34%). Degree of COVID-19 severity was categorized as mild-to-moderate in 11 patients (median oxygen requirement 1.5 L/min), severe in 10 patients (median oxygen requirement 5 L/min) and critical in 11 patients. No patients with mild-to-moderate disease required admission to an ICU, while 5 out of 10 patients with severe disease were eventually admitted to the ICU. Thrombotic events were noted in 3 patients (1 severe and 2 critical).
Table 2
Clinical characteristics and laboratory findings of patients from Cohort 2
Characteristics
Healthy controls
All patients
Disease severity
p value
 
N = 13
N = 32
Mild-to-moderate
Severe
Critical
 
   
N = 11
N = 10
N = 11
 
Age, median (IQR), year
59.2 (45.2, 60.0)
55.6 (51.2, 64.8)
55.9 (44.7–65.1)
53.5 (48.02–61)
60.2 (54.8–71.65)
0.23
Male, no. (%)
10 (77)
24 (75)
8 (72.7)
9 (90)
7 (63.6)
0.37
Median interval from first symptoms on admission (IQR), days
10 (9–11)
9 (9–11)
10.5 (10–12)
9 (8–11)
0.06
Coexisting disorder, no. (%)
 Any
0 (0)
14 (44)
2 (18)
3 (30)
9 (82)
0.006
 COPD
0 (0)
1 (3)
0 (0)
0 (0)
1 (9)
0.37
 Diabetes
0 (0)
5 (16)
0 (0)
1 (10)
4 (36)
0.053
 Hypertension
0 (0)
10 (31)
2 (18)
2 (20)
6 (55)
0.12
 Cardiovascular disease
0 (0)
3 (9)
0 (0)
0 (0)
3 (27)
0.042
 Cancer or hemopathy
0 (0)
0 (0)
0 (0)
0 (0)
0 (0)
 Chronic renal disease
0 (0)
1 (3)
0 (0)
0 (0)
1 (9)
0.37
 Overweight
0 (0)
2 (6)
1 (9)
1 (10)
0 (0)
0.5
Fever on admission
 Median temperature (IQR), °C
38.9 (38.5–39.4)
38.8 (38.2–39.5)
38.6 (38.5–39.7)
39.0 (38.5–39.4)
Symptoms on admission (%)
 Fever
32 (100)
11 (100)
10 (100)
11 (100)
 
 Dyspnea
32 (100)
11 (100)
10 (100)
11 (100)
 
 Cough
31 (97)
10 (91)
10 (100)
11 (100)
0.37
 Fatigue
31 (97)
10 (91)
10 (100)
11 (100)
0.37
 Myalgia
20 (63)
8 (73)
8 (10)
4 (36)
0.082
 Diarrhea
11 (34)
4 (36)
5 (50)
1 (9)
0.091
Median oxygen requirement (IQR, L/min)
      
Clinical outcomes, no. (%)
      
 Thrombotic events
3 (9)
0 (0)
1 (10)
2 (18)
0.34
 Clinical worsening requiring MV
0 (0)
5 (50)
 Death
5 (15.6)
0 (0)
0 (0)
5 (45.5)
< 0.001
Laboratory findings on admission
 Leukocytes (IQR), × 109/L
6.7 (4.31–8.82)
4.71 (3.78–5.68)
7.78 (6.46–8.43)
9.38 (5.48–10.49)
0.038
 Neutrophils (IQR), x 109/L
5.08 (3.12–7.37)
3.25 (2.07–3.44)
5.81 (4.74–6.36)
7.69 (4.32–9.13)
0.022
 Lymphocytes (IQR), × 109/L
0.84 (0.56–1.13)
1.00 (0.84–1.40)
0.88 (0.57–1.12)
0.65 (0.45–0.84)
0.031
 Monocytes (IQR), × 109/L
0.41 (0.23–0.52)
0.40 (0.26–0.52)
0.42 (0.27–0.51)
0.33 (0.12–1.05)
0.95
 Platelets (IQR), × 109/L
249 (159–298)
166 (112–251)
229 (170–282)
313 (199–352)
0.007
 CRP (IQR), mg/L
0.7 (0.0–0.8)
118 (55–242)
30 (14–76)
169 (136–249)
159 (109–308)
< 0.001
 Lactate dehydrogenase (IQR), U/L
169 (155–224)
424 (346–574)
262 (196–454)
411 (396–623)
504 (426–614)
0.1
Significant values (p < 0.05) are emphasized in bold
Quantitative variables are described as median (interquartile range) and compared using the Kruskal–Wallis test; qualitative variables are described as n (%) and compared using the χ2 test of independence
COPD chronic obstructive pulmonary disease, CRP C-reactive protein, IQR interquartile range, MV mechanical ventilation

Increased plasma sP-selectin on hospital admission is associated with disease severity and in-hospital mortality

We measured plasma sP-selectin in Cohort 1. Increased plasma sP-selectin levels at admission was significantly associated with critical disease (Fig. 1a) in COVID-19 patients, albeit at similar levels compared to non-COVID-19 septic ICU patients (Fig. 1a and [25, 26]). Moreover, sP-selectin levels were positively correlated with inflammatory parameters, i.e., CRP levels (r = 0.30, p = 0.017, Fig. 1b), but not with platelet count (r = 0.1, p = 0.43, Fig. 1c).
We next evaluated the ability of sP-selectin, normalized to platelet counts, to predict intubation (Fig. 1d) or in-hospital mortality (Fig. 1e) using ROC curves. We found that outcomes were significantly associated with higher sP-selectin values (AUC = 0.67, p = 0.028 for intubation and AUC = 0.74, p = 0.0047 for in-hospital mortality). An optimal cutoff value of 150 normalized concentration (pg/mL normalized to 106 platelets/mL) was predictive for intubation with 66% sensitivity, 61% specificity, 66% negative predictive value (NPV) and 61% positive predictive value (PPV), and death with 82% sensitivity, 60% specificity, 90% NPV and 55% PPV. Multivariate logistic regression after adjustment for age and gender confirmed the association of elevated sP-selectin with in-hospital mortality (OR = 72.0 (2.99–3600.00), p = 0.016). Clinical follow-up of COVID-19 patients initially non-critical (moderate and severe patients) also found that higher sP-selectin values were associated with worst clinical outcomes, albeit without reaching significance (AUC = 0.66, p = 0.086 for intubation and AUC = 0.70, p = 0.12 for in-hospital mortality) (Additional file 1: Figure S1). Interestingly, the predictive potential of normalized sP-selectin in non-COVID-19 septic ICU patients from a pre-pandemic cohort was not significantly associated with in-hospital mortality (AUC = 0.54, p = 0.71) (Additional file 2: Figure S2).
Together, these data suggested that sP-selectin is associated with in-hospital mortality in COVID-19 patients and may identify patients at higher risk of critical illness.

Critically ill COVID-19 patients display a platelet activation transcriptional signature

We previously performed a whole-blood immunological transcriptional characterization on 32 patients with laboratory-confirmed COVID-19 displaying various disease severity (cohort 2) [27]. Using an unbiased gene set enrichment analysis comparing different COVID-19 severity grades, we determined a gene signature that specifically discriminated severe from critical illness. GSEA pathway enrichment analysis identified this signature as related to primary hemostasis (Fig. 2a). Hierarchical clustering identified genes that were upregulated in a grade-dependent manner, thereby driving the primary hemostasis signature in critically ill patients (Fig. 2b). These genes included ITG2AB, GP1BB, PPBP and SELPLG (Fig. 3a), which recapitulated multiple steps of platelet activation [29, 30]. Importantly, and similarly to sP-selectin, RNA levels more strongly correlated with CRP level (Fig. 3b) than with platelet counts (Fig. 3c).
We next evaluated the ability of these genes to predict clinical outcome after normalization with platelets. Among patients that did not initially require critical care upon admission (i.e., moderate and severe patients, n = 21), 5 (24%) presented respiratory failure afterwards requiring mechanical ventilation (Table 2). PPBP and SELPLG were found to be the best predictor of clinical worsening (AUC = 0.8, p = 0.048 for both outcomes) (Fig. 4a–c). An optimal cutoff value for PBPP of 5 normalized RNA counts (NRC, normalized to 106 platelets/mL) was predictive of intubation with 100% sensitivity, 63% specificity, 100% NPV and 45% PPV, while a cutoff value of 2.65 NRC for SELPLG was predictive of intubation with 100% sensitivity, 69% specificity, 100% NPV and 50% PPV. Overall, these markers provide excellent negative predictive values, with no patient below the threshold value requiring future mechanical ventilation.

Discussion

Dysregulated hemostasis is emerging as a key factor in COVID-19 pathogenesis and severity. The present study provides new insights into the contribution of platelets to disease severity with the identification of a unique hemostasis signature in critically ill patients. We identified sP-selectin as a soluble marker associated with in-hospital mortality, and elevated SELPLG and PPBP RNA levels as strong negative predictors of mechanical ventilation in hospitalized patients.
Elevated sP-selectin levels promote leukocyte–endothelial and leucocyte–platelet adhesion [31], release of citrullinated histones and neutrophil extracellular traps (NETs) formation [32], promoting formation of platelet–neutrophil or –monocyte aggregates via binding of P-selectin to its ligand PSGL-1 (encoded by SELPLG) expressed on the surface of leukocytes [33]. Accordingly, elevated sP-selectin and increase in platelet–monocyte aggregates and have been recently described in COVID-19 patients [3335], the latter being effectively blocked by platelet P-selectin neutralization [33]. Our study supports these findings and highlights the key role of platelet activation in critical patients.
Importantly, while signatures related to innate immune activation and impaired interferon activity distinguished mild-to-moderate disease from severe and critical disease [27], we show that only a primary hemostasis-related gene signature could further distinguish severe from critical patients (Fig. 2a), especially the specific platelet chemokine-encoding gene PPBP/CXCL7 and SELPLG, encoding for the P-selectin glycoprotein ligand-1 (PSGL-1), which also predicted clinical outcome. Pro-platelet basic protein (PPBP), also known as CXCL7, is the most abundant platelet chemokine [29, 36], expressed within platelets as an inactive precursor and activated after cleavage during thrombus formation by enzymes released by neutrophils. PSGL-1 is expressed by leukocytes, allowing the formation of platelet–leukocyte conjugates and adhesion of leukocytes to activated endothelium through its interaction with P- or E-selectin [29, 37]. PBPP/CXCL7 has been shown to be essential for neutrophil migration into the thrombus [38], and the formation of platelet–neutrophil aggregates and murine models of acute lung injury showed that deletion of PPBP/CXLC7 protected the mice from lung disease [36], as well as blocking platelet activation [39]. Overall, our data support a model, whereby platelet activation induces PPBP/CXCL7 release and P-selectin upregulation followed by neutrophil attraction into sites of injury and the formation of platelet–leucocyte aggregates, precipitating organ injury and failure.
In addition to their role in primary hemostasis, platelets are an integral part of the immune response to pathogens. The functional interdependence and the coordinated activation of both processes, designated as thrombo-inflammation, may drive adverse effects, such as thrombosis, multiple organ failure and death [40]. We support the hypothesis that deregulated primary hemostasis, in association to inflammation, could drive COVID-19 progression into critical disease. Viral infection and sepsis models have been associated with platelet gene expression and functional alterations [41, 42]. Supporting this generalizable thrombo-inflammation model, we found similar elevated sP-selectin in non-COVID septic ICU patients. However, some unique features may characterize SARS-CoV-2-mediated platelet dysregulation. Authors have shown that sP-selectin seemed to be more strongly associated COVID-19-related in-hospital mortality [43, 44]. Frazer et al. [45] found significantly elevated sP-selectin in ICU patients in comparison to non-COVID-19 ICU patients at day 3 post-admission (and not at days 1 and 2), that persisted until day 7. This finding suggests that persistent platelet activation may characterize COVID-19-associated coagulopathy. In addition, Manne et al. showed that platelet gene expression profile was unique in COVID-19 patients in comparison to H1N1 pandemic patients. Altogether, these data demonstrate that COVID-19 critical patients share important similarities with other critical sepsis, but some features may uniquely contribute to platelet activation during SARS-CoV-2 infection.
Prediction of illness trajectories after the onset of symptoms is difficult but remains critical. Clinical and biological factors have been shown to predict poor outcome, including arterial blood gazes values (e.g., hypoxemia, hypercapnia, P/F ratio, lactate), inflammatory markers (e.g., CRP, IL-6), coagulation markers (e.g., VWF, D-dimer) and cellular blood composition (e.g., neutrophil-to-lymphocyte ratio). These factors have led to the development of prognosis scores to predict critical illness [46]. Our findings suggest that markers of dysregulated hemostasis could be evaluated for their predictive prognostic value.
Finally, these findings suggest that a subset of patient may benefit from drugs preventing platelet activation, such as antiplatelet agents or P-selectin inhibitors [47], which have also been proposed in other septic settings [48, 49]. These anti-platelets agents in combination with anti-inflammatory drugs (glucocorticoids, anti-IL-6) could have substantial impact on thrombo-inflammation.
The benefit of anti-platelet agents is, however, challenged by recent findings from Althaus and coll. [50] which proposed that the induction of a procoagulant platelet subpopulation may be a key driver of critical COVID-19. Procoagulant platelets displayed increased P-selectin, integrin αIIb and GPIbα expression on their surface [51], in line with biomarkers (sP-selectin, PPBP, SELPLG) and signature (ITG2AB, GP1BB, PPBP and SELPLG) we identified. However, in this scenario, the benefits of aspirin and P2Y12 inhibitors would be limited; blockade of P2Y1 and P2Y12 does not inhibit procoagulant platelets activation [52] and pretreatment with aspirin has minimal effect on their generation [53]. In contrast, Manne et al. [35] did not find evidence for an increased procoagulant platelet subpopulation, and an additional study concluded that procoagulant platelets may, on the contrary, have a protective effect during SARS-CoV-2-related pneumonia [54]. Therefore, the mechanisms underlying platelets activation, and subsequently, the potential benefit of anti-platelet therapy remain controversial. The REMA-CAP trial is currently investigating the use of aspirin or a P2Y12 inhibitor (clopidogrel, prasugrel, or ticagrelor) [55], and results from the RECOVERY trial on aspirin will soon be unraveled [56]. So far, one retrospective trial suggested a potential benefit of aspirin use on critical care and in-hospital mortality [57].
Our study has some limitations. We used two independent cohorts with a small sample size from two centers. The two cohorts were not homogenous in regard to timing of measurements and severity of patients. In addition, the study was not designed as a longitudinal study, so no sequential measurement was available. Indeed, sP-selectin association with clinical outcome was moderate and serial measurement over time may optimize its outcome prediction performance. Moreover, longitudinal analysis of sP-selectin levels may provide insights on the causal role of platelets activation in driving critical disease. Our transcriptomic analysis was performed on whole-blood RNA, so we cannot evaluate the contribution of each cell population to hemostasis dysregulation. Separate transcriptional profiling of platelets vs other circulating populations and analysis of cell expression phenotypes (P-selectin, phosphatidyl-serine exposure) and evaluation of platelets functions may provide further insights into the contribution of each population to thrombo-inflammation and dissect the mechanisms of platelet–neutrophil or platelet–monocyte aggregates.
Overall, this exploratory study sheds light onto the role of thrombo-inflammation in critical patients. We identified platelet activation markers sP-selectin, SELPLG and PPBP/CXCL7 as potential biomarkers of critical worsening. Additional studies dedicated to evaluate the predictive performance of these biomarkers are required to both validate our findings and optimize their ability to predict progression to critical disease.

Acknowledgements

We would like to acknowledge all nurses, technicians and physicians involved in all department involved in COVID-19 patients management in APHP.CUP hospitals, for their help in taking care of patients and including them in the study. This study was supported by the Fonds IMMUNOV, for Innovation in Immunopathology. The study was also supported by the Institut National de la Santé et de la Recherche Médicale (INSERM), by a government grant managed by the Agence National de la Recherche as part of the “Investment for the Future” program (ANR-10-IAHU-01), and by grants from the Agence National de la Recherche: ANR-flash Covid19 “AIROCovid” and “CoVarImm”. We also acknowledge funding from the Institut Pasteur for Covid19 research. J.H. is a recipient of an Institut Imagine MD-PhD fellowship program supported by the Fondation Bettencourt Schueller. L.B. is supported by the EUR G.E.N.E. (reference #ANR-17-EURE-0013) program of the Université de Paris IdEx #ANR-18-IDEX-0001 funded by the French Government through its “Investments for the Future” program. We thank AP-HP for promotion of the SARCODO Project. We thank the unit of clinical research URC HEGP CIC-EC1418 (Natacha Nohile, Pauline Jouany and Dr Juliette Djadi-Prat) and Helene Cart-Grandjean from AP-HP for their involvement in SARCODO project. SARCODO project was supported by grants of ANR (Fondation de France) and Appel d'offre AP-HP mécénat crise COVID-19 from GHU APHP.CUP.

Declarations

Both studies conformed to the principles outlined in the Declaration of Helsinki, and received approval by the appropriate Institutional Review Board (CPP2020-04-048/2020-A01048-31/ 20.04.21.49318).

Competing interests

None of the authors has a relevant competing interest.
Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creativecommons.​org/​licenses/​by/​4.​0/​.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Literatur
1.
Zurück zum Zitat Smadja DM, Mentzer SJ, Fontenay M, Laffan MA, Ackermann M, Helms J, Jonigk D, Chocron R, Pier GB, Gendron N, Pons S, Diehl JL, Margadant C, Guerin C, Huijbers EJM, Philippe A, Chapuis N, Nowak-Sliwinska P, Karagiannidis C, Sanchez O, Kümpers P, Skurnik D, Randi AM, Griffioen AW. COVID-19 is a systemic vascular hemopathy: insight for mechanistic and clinical aspects. Angiogenesis. 2021;28:1–34. https://doi.org/10.1007/s10456-021-09805-6.CrossRef Smadja DM, Mentzer SJ, Fontenay M, Laffan MA, Ackermann M, Helms J, Jonigk D, Chocron R, Pier GB, Gendron N, Pons S, Diehl JL, Margadant C, Guerin C, Huijbers EJM, Philippe A, Chapuis N, Nowak-Sliwinska P, Karagiannidis C, Sanchez O, Kümpers P, Skurnik D, Randi AM, Griffioen AW. COVID-19 is a systemic vascular hemopathy: insight for mechanistic and clinical aspects. Angiogenesis. 2021;28:1–34. https://​doi.​org/​10.​1007/​s10456-021-09805-6.CrossRef
2.
Zurück zum Zitat Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506.PubMedPubMedCentralCrossRef Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395:497–506.PubMedPubMedCentralCrossRef
3.
Zurück zum Zitat Salje H, Kiem CT, Lefrancq N, Courtejoie N, Bosetti P, Paireau J, et al. Estimating the burden of SARS-CoV-2 in France. Science. 2020;369:208–11.PubMedPubMedCentralCrossRef Salje H, Kiem CT, Lefrancq N, Courtejoie N, Bosetti P, Paireau J, et al. Estimating the burden of SARS-CoV-2 in France. Science. 2020;369:208–11.PubMedPubMedCentralCrossRef
4.
Zurück zum Zitat Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061.PubMedPubMedCentralCrossRef Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323:1061.PubMedPubMedCentralCrossRef
5.
Zurück zum Zitat Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584:430–6.PubMedPubMedCentralCrossRef Williamson EJ, Walker AJ, Bhaskaran K, Bacon S, Bates C, Morton CE, et al. Factors associated with COVID-19-related death using OpenSAFELY. Nature. 2020;584:430–6.PubMedPubMedCentralCrossRef
6.
Zurück zum Zitat Julien P, Julien G, Morgan C, Erika P, Thibault D, Fanny L, et al. Pulmonary embolism in patients with COVID-19. Circulation. 2020;142:184–6.CrossRef Julien P, Julien G, Morgan C, Erika P, Thibault D, Fanny L, et al. Pulmonary embolism in patients with COVID-19. Circulation. 2020;142:184–6.CrossRef
8.
Zurück zum Zitat Tang N, Bai H, Chen X, Gong J, Li D, Sun Z. Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost. 2020;18:1094–9.PubMedCrossRef Tang N, Bai H, Chen X, Gong J, Li D, Sun Z. Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thromb Haemost. 2020;18:1094–9.PubMedCrossRef
9.
Zurück zum Zitat Panigada M, Bottino N, Tagliabue P, Grasselli G, Novembrino C, Chantarangkul V, et al. Hypercoagulability of COVID-19 patients in intensive care unit: a report of thromboelastography findings and other parameters of hemostasis. J Thromb Haemost. 2020;18:1738–42.PubMedCrossRef Panigada M, Bottino N, Tagliabue P, Grasselli G, Novembrino C, Chantarangkul V, et al. Hypercoagulability of COVID-19 patients in intensive care unit: a report of thromboelastography findings and other parameters of hemostasis. J Thromb Haemost. 2020;18:1738–42.PubMedCrossRef
10.
Zurück zum Zitat Philippe A, Gendron N, Bory O, Beauvais A, Mirault T, Planquette B, Sanchez O, Diehl JL, Chocron R, Smadja DM. Von Willebrand factor collagen-binding capacity predicts in-hospital mortality in COVID-19 patients: insight from VWF/ADAMTS13 ratio imbalance. Angiogenesis. 2021;11:1–5. https://doi.org/10.1007/s10456-021-09789-3.CrossRef Philippe A, Gendron N, Bory O, Beauvais A, Mirault T, Planquette B, Sanchez O, Diehl JL, Chocron R, Smadja DM. Von Willebrand factor collagen-binding capacity predicts in-hospital mortality in COVID-19 patients: insight from VWF/ADAMTS13 ratio imbalance. Angiogenesis. 2021;11:1–5. https://​doi.​org/​10.​1007/​s10456-021-09789-3.CrossRef
11.
Zurück zum Zitat Smadja DM, Guerin CL, Chocron R, Yatim N, Boussier J, Gendron N, Khider L, Hadjadj J, Goudot G, Debuc B, Juvin P, Hauw-Berlemont C, Augy JL, Peron N, Messas E, Planquette B, Sanchez O, Charbit B, Gaussem P, Duffy D, Terrier B, Mirault T, Diehl JL. Angiopoietin-2 as a marker of endothelial activation is a good predictor factor for intensive care unit admission of COVID-19 patients. Angiogenesis. 2020;23(4):611–20. https://doi.org/10.1007/s10456-020-09730-0CrossRefPubMed Smadja DM, Guerin CL, Chocron R, Yatim N, Boussier J, Gendron N, Khider L, Hadjadj J, Goudot G, Debuc B, Juvin P, Hauw-Berlemont C, Augy JL, Peron N, Messas E, Planquette B, Sanchez O, Charbit B, Gaussem P, Duffy D, Terrier B, Mirault T, Diehl JL. Angiopoietin-2 as a marker of endothelial activation is a good predictor factor for intensive care unit admission of COVID-19 patients. Angiogenesis. 2020;23(4):611–20. https://​doi.​org/​10.​1007/​s10456-020-09730-0CrossRefPubMed
12.
Zurück zum Zitat Carsana L, Sonzogni A, Nasr A, Rossi RS, Pellegrinelli A, Zerbi P, et al. Pulmonary post-mortem findings in a series of COVID-19 cases from northern Italy: a two-centre descriptive study. Lancet Infect Dis. 2020;20:1135–40.PubMedPubMedCentralCrossRef Carsana L, Sonzogni A, Nasr A, Rossi RS, Pellegrinelli A, Zerbi P, et al. Pulmonary post-mortem findings in a series of COVID-19 cases from northern Italy: a two-centre descriptive study. Lancet Infect Dis. 2020;20:1135–40.PubMedPubMedCentralCrossRef
13.
Zurück zum Zitat Ackermann M, Verleden SE, Kuehnel M, Haverich A, Welte T, Laenger F, et al. Pulmonary vascular endothelialitis, thrombosis, and angiogenesis in COVID-19. N Engl J Med. 2020;383:120–8.PubMedPubMedCentralCrossRef Ackermann M, Verleden SE, Kuehnel M, Haverich A, Welte T, Laenger F, et al. Pulmonary vascular endothelialitis, thrombosis, and angiogenesis in COVID-19. N Engl J Med. 2020;383:120–8.PubMedPubMedCentralCrossRef
14.
Zurück zum Zitat Diehl J-L, Peron N, Chocron R, Debuc B, Guerot E, Hauw-Berlemont C, et al. Respiratory mechanics and gas exchanges in the early course of COVID-19 ARDS: a hypothesis-generating study. Ann Intensive Care. 2020;10:95.PubMedPubMedCentralCrossRef Diehl J-L, Peron N, Chocron R, Debuc B, Guerot E, Hauw-Berlemont C, et al. Respiratory mechanics and gas exchanges in the early course of COVID-19 ARDS: a hypothesis-generating study. Ann Intensive Care. 2020;10:95.PubMedPubMedCentralCrossRef
15.
Zurück zum Zitat Thachil J, Tang N, Gando S, Falanga A, Cattaneo M, Levi M, et al. ISTH interim guidance on recognition and management of coagulopathy in COVID-19. J Thromb Haemost. 2020;18:1023–6.PubMedCrossRef Thachil J, Tang N, Gando S, Falanga A, Cattaneo M, Levi M, et al. ISTH interim guidance on recognition and management of coagulopathy in COVID-19. J Thromb Haemost. 2020;18:1023–6.PubMedCrossRef
17.
Zurück zum Zitat Helms J, Tacquard C, Severac F, Leonard-Lorant I, Ohana M, Delabranche X, et al. High risk of thrombosis in patients with severe SARS-CoV-2 infection: a multicenter prospective cohort study. Intensive Care Med. 2020;46:1089–98.PubMedCrossRefPubMedCentral Helms J, Tacquard C, Severac F, Leonard-Lorant I, Ohana M, Delabranche X, et al. High risk of thrombosis in patients with severe SARS-CoV-2 infection: a multicenter prospective cohort study. Intensive Care Med. 2020;46:1089–98.PubMedCrossRefPubMedCentral
18.
Zurück zum Zitat Helms J, Severac F, Merdji H, Schenck M, Clere-Jehl R, Baldacini M, et al. Higher anticoagulation targets and risk of thrombotic events in severe COVID-19 patients: bi-center cohort study. Ann Intensive Care. 2021;11:14.PubMedPubMedCentralCrossRef Helms J, Severac F, Merdji H, Schenck M, Clere-Jehl R, Baldacini M, et al. Higher anticoagulation targets and risk of thrombotic events in severe COVID-19 patients: bi-center cohort study. Ann Intensive Care. 2021;11:14.PubMedPubMedCentralCrossRef
19.
Zurück zum Zitat Khider L, Gendron N, Goudot G, Chocron R, Hauw-Berlemont C, Cheng C, et al. Curative anticoagulation prevents endothelial lesion in COVID-19 patients. J Thromb Haemost. 2020;18:2391–9.PubMedCrossRef Khider L, Gendron N, Goudot G, Chocron R, Hauw-Berlemont C, Cheng C, et al. Curative anticoagulation prevents endothelial lesion in COVID-19 patients. J Thromb Haemost. 2020;18:2391–9.PubMedCrossRef
20.
Zurück zum Zitat Pons S, Fodil S, Azoulay E, Zafrani L. The vascular endothelium: the cornerstone of organ dysfunction in severe SARS-CoV-2 infection. Crit Care. 2020;24:353.PubMedPubMedCentralCrossRef Pons S, Fodil S, Azoulay E, Zafrani L. The vascular endothelium: the cornerstone of organ dysfunction in severe SARS-CoV-2 infection. Crit Care. 2020;24:353.PubMedPubMedCentralCrossRef
21.
Zurück zum Zitat Varga Z, Flammer AJ, Steiger P, Haberecker M, Andermatt R, Zinkernagel AS, et al. Endothelial cell infection and endotheliitis in COVID-19. Lancet. 2020;395:1417–8.PubMedPubMedCentralCrossRef Varga Z, Flammer AJ, Steiger P, Haberecker M, Andermatt R, Zinkernagel AS, et al. Endothelial cell infection and endotheliitis in COVID-19. Lancet. 2020;395:1417–8.PubMedPubMedCentralCrossRef
22.
Zurück zum Zitat Lisman T. Platelet-neutrophil interactions as drivers of inflammatory and thrombotic disease. Cell Tissue Res. 2018;371:567–76.PubMedCrossRef Lisman T. Platelet-neutrophil interactions as drivers of inflammatory and thrombotic disease. Cell Tissue Res. 2018;371:567–76.PubMedCrossRef
23.
Zurück zum Zitat Latrémouille C, Carpentier A, Leprince P, Roussel J-C, Cholley B, Boissier E, et al. A bioprosthetic total artificial heart for end-stage heart failure: results from a pilot study. J Heart Lung Transplant. 2018;37:33–7.PubMedCrossRef Latrémouille C, Carpentier A, Leprince P, Roussel J-C, Cholley B, Boissier E, et al. A bioprosthetic total artificial heart for end-stage heart failure: results from a pilot study. J Heart Lung Transplant. 2018;37:33–7.PubMedCrossRef
24.
Zurück zum Zitat Sakamaki F, Ishizaka A, Handa M, Fujishima S, Urano T, Sayama K, et al. Soluble form of P-selectin in plasma is elevated in acute lung injury. Am J Respir Crit Care Med. 1995;151:1821–6.PubMedCrossRef Sakamaki F, Ishizaka A, Handa M, Fujishima S, Urano T, Sayama K, et al. Soluble form of P-selectin in plasma is elevated in acute lung injury. Am J Respir Crit Care Med. 1995;151:1821–6.PubMedCrossRef
25.
Zurück zum Zitat Smadja DM, Guerin CL, Chocron R, Yatim N, Boussier J, Gendron N, et al. Angiopoietin-2 as a marker of endothelial activation is a good predictor factor for intensive care unit admission of COVID-19 patients. Angiogenesis. 2020;23:611–20.PubMedCrossRef Smadja DM, Guerin CL, Chocron R, Yatim N, Boussier J, Gendron N, et al. Angiopoietin-2 as a marker of endothelial activation is a good predictor factor for intensive care unit admission of COVID-19 patients. Angiogenesis. 2020;23:611–20.PubMedCrossRef
26.
Zurück zum Zitat Borgel D, Clauser S, Bornstain C, Bièche I, Bissery A, Remones V, et al. Elevated growth-arrest-specific protein 6 plasma levels in patients with severe sepsis. Crit Care Med. 2006;34:219–22.PubMedCrossRef Borgel D, Clauser S, Bornstain C, Bièche I, Bissery A, Remones V, et al. Elevated growth-arrest-specific protein 6 plasma levels in patients with severe sepsis. Crit Care Med. 2006;34:219–22.PubMedCrossRef
27.
Zurück zum Zitat Borgel D, Bornstain C, Reitsma PH, Lerolle N, Gandrille S, Dali-Ali F, et al. A Comparative study of the protein C pathway in septic and nonseptic patients with organ failure. Am J Respir Crit Care Med. 2007;176:878–85.PubMedCrossRef Borgel D, Bornstain C, Reitsma PH, Lerolle N, Gandrille S, Dali-Ali F, et al. A Comparative study of the protein C pathway in septic and nonseptic patients with organ failure. Am J Respir Crit Care Med. 2007;176:878–85.PubMedCrossRef
28.
Zurück zum Zitat Hadjadj J, Yatim N, Barnabei L, Corneau A, Boussier J, Smith N, et al. Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients. Science. 2020;369:718–24.PubMedPubMedCentralCrossRef Hadjadj J, Yatim N, Barnabei L, Corneau A, Boussier J, Smith N, et al. Impaired type I interferon activity and inflammatory responses in severe COVID-19 patients. Science. 2020;369:718–24.PubMedPubMedCentralCrossRef
29.
Zurück zum Zitat Rayes J, Bourne JH, Brill A, Watson SP. The dual role of platelet-innate immune cell interactions in thrombo-inflammation. Res Pract Thromb Haemost. 2020;4:23–35.PubMedCrossRef Rayes J, Bourne JH, Brill A, Watson SP. The dual role of platelet-innate immune cell interactions in thrombo-inflammation. Res Pract Thromb Haemost. 2020;4:23–35.PubMedCrossRef
30.
Zurück zum Zitat Periayah MH, Halim AS, Mat Saad AZ. Mechanism action of platelets and crucial blood coagulation pathways in hemostasis. Int J Hematol-Oncol Stem Cell Res. 2017;11:319–27.PubMedPubMedCentral Periayah MH, Halim AS, Mat Saad AZ. Mechanism action of platelets and crucial blood coagulation pathways in hemostasis. Int J Hematol-Oncol Stem Cell Res. 2017;11:319–27.PubMedPubMedCentral
31.
Zurück zum Zitat Woollard KJ, Andreas S, Harris EE, Eisenhardt SU, Jackson SP, Karlheinz P, et al. Pathophysiological levels of soluble P-selectin mediate adhesion of leukocytes to the endothelium through Mac-1 activation. Circ Res. 2008;103:1128–38.PubMedCrossRef Woollard KJ, Andreas S, Harris EE, Eisenhardt SU, Jackson SP, Karlheinz P, et al. Pathophysiological levels of soluble P-selectin mediate adhesion of leukocytes to the endothelium through Mac-1 activation. Circ Res. 2008;103:1128–38.PubMedCrossRef
32.
Zurück zum Zitat Panicker SR, Mehta-D’souza P, Zhang N, Klopocki AG, Shao B, McEver RP. Circulating soluble P-selectin must dimerize to promote inflammation and coagulation in mice. Blood. 2017;130:181–91.PubMedPubMedCentralCrossRef Panicker SR, Mehta-D’souza P, Zhang N, Klopocki AG, Shao B, McEver RP. Circulating soluble P-selectin must dimerize to promote inflammation and coagulation in mice. Blood. 2017;130:181–91.PubMedPubMedCentralCrossRef
33.
Zurück zum Zitat Hottz ED, Azevedo-Quintanilha IG, Palhinha L, Teixeira L, Barreto EA, Pão CRR, et al. Platelet activation and platelet-monocyte aggregate formation trigger tissue factor expression in patients with severe COVID-19. Blood. 2020;136:1330–41.PubMedCrossRef Hottz ED, Azevedo-Quintanilha IG, Palhinha L, Teixeira L, Barreto EA, Pão CRR, et al. Platelet activation and platelet-monocyte aggregate formation trigger tissue factor expression in patients with severe COVID-19. Blood. 2020;136:1330–41.PubMedCrossRef
34.
Zurück zum Zitat Goshua G, Pine AB, Meizlish ML, Chang C-H, Zhang H, Bahel P, et al. Endotheliopathy in COVID-19-associated coagulopathy: evidence from a single-centre, cross-sectional study. Lancet Haematol. 2020;7:e575–82.PubMedPubMedCentralCrossRef Goshua G, Pine AB, Meizlish ML, Chang C-H, Zhang H, Bahel P, et al. Endotheliopathy in COVID-19-associated coagulopathy: evidence from a single-centre, cross-sectional study. Lancet Haematol. 2020;7:e575–82.PubMedPubMedCentralCrossRef
35.
Zurück zum Zitat Manne BK, Denorme F, Middleton EA, Portier I, Rowley JW, Stubben C, et al. Platelet gene expression and function in patients with COVID-19. Blood. 2020;136:1317–29.PubMedCrossRef Manne BK, Denorme F, Middleton EA, Portier I, Rowley JW, Stubben C, et al. Platelet gene expression and function in patients with COVID-19. Blood. 2020;136:1317–29.PubMedCrossRef
36.
Zurück zum Zitat Bdeir K, Gollomp K, Stasiak M, Mei J, Papiewska-Pajak I, Zhao G, et al. Platelet-specific chemokines contribute to the pathogenesis of acute lung injury. Am J Respir Cell Mol Biol. 2017;56:261–70.PubMedPubMedCentralCrossRef Bdeir K, Gollomp K, Stasiak M, Mei J, Papiewska-Pajak I, Zhao G, et al. Platelet-specific chemokines contribute to the pathogenesis of acute lung injury. Am J Respir Cell Mol Biol. 2017;56:261–70.PubMedPubMedCentralCrossRef
37.
Zurück zum Zitat Furie B, Furie BC. Role of platelet P-selectin and microparticle PSGL-1 in thrombus formation. Trends Mol Med. 2004;10:171–8.PubMedCrossRef Furie B, Furie BC. Role of platelet P-selectin and microparticle PSGL-1 in thrombus formation. Trends Mol Med. 2004;10:171–8.PubMedCrossRef
39.
Zurück zum Zitat Zarbock A, Polanowska-Grabowska RK, Ley K. Platelet-neutrophil-interactions: linking hemostasis and inflammation. Blood Rev. 2007;21:99–111.PubMedCrossRef Zarbock A, Polanowska-Grabowska RK, Ley K. Platelet-neutrophil-interactions: linking hemostasis and inflammation. Blood Rev. 2007;21:99–111.PubMedCrossRef
41.
Zurück zum Zitat Campbell RA, Schwertz H, Hottz ED, Rowley JW, Manne BK, Washington AV, et al. Human megakaryocytes possess intrinsic antiviral immunity through regulated induction of IFITM3. Blood. 2019;133:2013–26.PubMedPubMedCentralCrossRef Campbell RA, Schwertz H, Hottz ED, Rowley JW, Manne BK, Washington AV, et al. Human megakaryocytes possess intrinsic antiviral immunity through regulated induction of IFITM3. Blood. 2019;133:2013–26.PubMedPubMedCentralCrossRef
42.
43.
Zurück zum Zitat Barrett TJ, Lee AH, Xia Y, Lin LH, Black M, Cotzia P, et al. Platelet and vascular biomarkers associate with thrombosis and death in coronavirus disease. Circ Res. 2020;127:945–7.PubMedPubMedCentralCrossRef Barrett TJ, Lee AH, Xia Y, Lin LH, Black M, Cotzia P, et al. Platelet and vascular biomarkers associate with thrombosis and death in coronavirus disease. Circ Res. 2020;127:945–7.PubMedPubMedCentralCrossRef
44.
Zurück zum Zitat Vassiliou AG, Keskinidou C, Jahaj E, Gallos P, Dimopoulou I, Kotanidou A, et al. ICU admission levels of endothelial biomarkers as predictors of mortality in critically ill COVID-19 patients. Cells. 2021;10:186.PubMedPubMedCentralCrossRef Vassiliou AG, Keskinidou C, Jahaj E, Gallos P, Dimopoulou I, Kotanidou A, et al. ICU admission levels of endothelial biomarkers as predictors of mortality in critically ill COVID-19 patients. Cells. 2021;10:186.PubMedPubMedCentralCrossRef
45.
Zurück zum Zitat Fraser DD, Patterson EK, Slessarev M, Gill SE, Martin C, Daley M, et al. Endothelial injury and glycocalyx degradation in critically ill coronavirus disease 2019 patients: implications for microvascular platelet aggregation. Crit Care Explor. 2020;2: e0194.PubMedPubMedCentralCrossRef Fraser DD, Patterson EK, Slessarev M, Gill SE, Martin C, Daley M, et al. Endothelial injury and glycocalyx degradation in critically ill coronavirus disease 2019 patients: implications for microvascular platelet aggregation. Crit Care Explor. 2020;2: e0194.PubMedPubMedCentralCrossRef
46.
Zurück zum Zitat Liang W, Liang H, Ou L, Chen B, Chen A, Li C, et al. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med. 2020;180:1081.PubMedCrossRef Liang W, Liang H, Ou L, Chen B, Chen A, Li C, et al. Development and validation of a clinical risk score to predict the occurrence of critical illness in hospitalized patients with COVID-19. JAMA Intern Med. 2020;180:1081.PubMedCrossRef
47.
Zurück zum Zitat Neri T, Nieri D, Celi A. P-selectin blockade in COVID-19-related ARDS. Am J Physiol-Lung Cell Mol Physiol. 2020;318:237–8.CrossRef Neri T, Nieri D, Celi A. P-selectin blockade in COVID-19-related ARDS. Am J Physiol-Lung Cell Mol Physiol. 2020;318:237–8.CrossRef
48.
Zurück zum Zitat Ouyang Y, Wang Y, Liu B, Ma X, Ding R. Effects of antiplatelet therapy on the mortality rate of patients with sepsis: a meta-analysis. J Crit Care. 2019;50:162–8.PubMedCrossRef Ouyang Y, Wang Y, Liu B, Ma X, Ding R. Effects of antiplatelet therapy on the mortality rate of patients with sepsis: a meta-analysis. J Crit Care. 2019;50:162–8.PubMedCrossRef
50.
Zurück zum Zitat Althaus K, Marini I, Zlamal J, Pelzl L, Singh A, Häberle H, et al. Antibody-induced procoagulant platelets in severe COVID-19 infection. Blood. 2021;137:1061–71.PubMedPubMedCentralCrossRef Althaus K, Marini I, Zlamal J, Pelzl L, Singh A, Häberle H, et al. Antibody-induced procoagulant platelets in severe COVID-19 infection. Blood. 2021;137:1061–71.PubMedPubMedCentralCrossRef
51.
52.
Zurück zum Zitat Agbani EO, Williams CM, Hers I, Poole AW. Membrane ballooning in aggregated platelets is synchronised and mediates a surge in microvesiculation. Sci Rep. 2017;7:2770.PubMedPubMedCentralCrossRef Agbani EO, Williams CM, Hers I, Poole AW. Membrane ballooning in aggregated platelets is synchronised and mediates a surge in microvesiculation. Sci Rep. 2017;7:2770.PubMedPubMedCentralCrossRef
53.
Zurück zum Zitat Hua VM, Abeynaike L, Glaros E, Campbell H, Pasalic L, Hogg PJ, et al. Necrotic platelets provide a procoagulant surface during thrombosis. Blood. 2015;126:2852–62.PubMedPubMedCentralCrossRef Hua VM, Abeynaike L, Glaros E, Campbell H, Pasalic L, Hogg PJ, et al. Necrotic platelets provide a procoagulant surface during thrombosis. Blood. 2015;126:2852–62.PubMedPubMedCentralCrossRef
54.
Zurück zum Zitat Denorme F, Manne BK, Portier I, Petrey AC, Middleton EA, Kile BT, et al. COVID-19 patients exhibit reduced procoagulant platelet responses. J Thromb Haemost. 2020;18:3067–73.PubMedPubMedCentralCrossRef Denorme F, Manne BK, Portier I, Petrey AC, Middleton EA, Kile BT, et al. COVID-19 patients exhibit reduced procoagulant platelet responses. J Thromb Haemost. 2020;18:3067–73.PubMedPubMedCentralCrossRef
57.
Zurück zum Zitat Chow JH, Khanna AK, Kethireddy S, Yamane D, Levine A, Jackson AM, et al. Aspirin use is associated with decreased mechanical ventilation, intensive care unit admission, and in-hospital mortality in hospitalized patients with coronavirus disease 2019. Anesth Analg. 2021;132:930–41.PubMedCrossRef Chow JH, Khanna AK, Kethireddy S, Yamane D, Levine A, Jackson AM, et al. Aspirin use is associated with decreased mechanical ventilation, intensive care unit admission, and in-hospital mortality in hospitalized patients with coronavirus disease 2019. Anesth Analg. 2021;132:930–41.PubMedCrossRef
Metadaten
Titel
Platelet activation in critically ill COVID-19 patients
verfasst von
Nader Yatim
Jeremy Boussier
Richard Chocron
Jérôme Hadjadj
Aurélien Philippe
Nicolas Gendron
Laura Barnabei
Bruno Charbit
Tali-Anne Szwebel
Nicolas Carlier
Frédéric Pène
Célia Azoulay
Lina Khider
Tristan Mirault
Jean-Luc Diehl
Coralie L. Guerin
Frédéric Rieux-Laucat
Darragh Duffy
Solen Kernéis
David M. Smadja
Benjamin Terrier
Publikationsdatum
01.12.2021
Verlag
Springer International Publishing
Schlagwort
COVID-19
Erschienen in
Annals of Intensive Care / Ausgabe 1/2021
Elektronische ISSN: 2110-5820
DOI
https://doi.org/10.1186/s13613-021-00899-1

Weitere Artikel der Ausgabe 1/2021

Annals of Intensive Care 1/2021 Zur Ausgabe

Akuter Schwindel: Wann lohnt sich eine MRT?

28.04.2024 Schwindel Nachrichten

Akuter Schwindel stellt oft eine diagnostische Herausforderung dar. Wie nützlich dabei eine MRT ist, hat eine Studie aus Finnland untersucht. Immerhin einer von sechs Patienten wurde mit akutem ischämischem Schlaganfall diagnostiziert.

Bei schweren Reaktionen auf Insektenstiche empfiehlt sich eine spezifische Immuntherapie

Insektenstiche sind bei Erwachsenen die häufigsten Auslöser einer Anaphylaxie. Einen wirksamen Schutz vor schweren anaphylaktischen Reaktionen bietet die allergenspezifische Immuntherapie. Jedoch kommt sie noch viel zu selten zum Einsatz.

Hinter dieser Appendizitis steckte ein Erreger

23.04.2024 Appendizitis Nachrichten

Schmerzen im Unterbauch, aber sonst nicht viel, was auf eine Appendizitis hindeutete: Ein junger Mann hatte Glück, dass trotzdem eine Laparoskopie mit Appendektomie durchgeführt und der Wurmfortsatz histologisch untersucht wurde.

Ärztliche Empathie hilft gegen Rückenschmerzen

23.04.2024 Leitsymptom Rückenschmerzen Nachrichten

Personen mit chronischen Rückenschmerzen, die von einfühlsamen Ärzten und Ärztinnen betreut werden, berichten über weniger Beschwerden und eine bessere Lebensqualität.

Update AINS

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.