Thrombopoietin participates in platelet activation in COVID-19 patients
Notice bibliographique
Résumé
BACKGROUND: The pathogenesis of coronavirus disease 2019 (COVID-19) is characterized by enhanced platelet activation and diffuse hemostatic alterations, which may contribute to immunothrombosis/thromboinflammation and subsequent development of target-organ damage. Thrombopoietin (THPO), a growth factor essential to megakariocyte proliferation, is known to prime platelet activation and leukocyte-platelet interaction. In addition, THPO concentrations increase in several critical diseases, such as acute cardiac ischemia and sepsis, thus representing a potential diagnostic and prognostic biomarker. Furthermore, several data suggest that interleukin (IL)-6 is one of the most important inflammatory mediators involved in these phenomena, which led to explore the potential therapeutic role of IL-6 inhibitors. In this prospective cohort study, we aimed to study THPO and IL-6 concentrations in COVID-19 patients at the time of first clinical evaluation in the Emergency Department (ED), and to investigate their potential use as diagnostic and prognostic biomarkers. In addition, we sought to explore the role of THPO contained in plasma samples obtained from COVID-19 patients in priming in vitro platelet activation and leukocyte-platelet interaction. METHODS: We enrolled 66 patients presenting to the ED with symptoms suggestive of COVID-19, including 47 with confirmed COVID-19 and 19 in whom COVID-19 was excluded (Non-COVID-19 patients). As controls, we also recruited 18 healthy subjects. In vitro, we reproduced the effects of increased circulating THPO on platelet function by adding plasma from COVID-19 patients or controls to platelet-rich plasma or whole blood obtained by healthy donors, and we indirectly studied the effect of THPO on platelet activation by blocking its biological activity. FINDINGS: THPO levels were higher in COVID-19 patients than in both Non-COVID-19 patients and healthy subjects. Studying THPO as diagnostic marker for the diagnosis of COVID-19 by receiver-operating-characteristic (ROC) statistics, we found an area under the curve (AUC) of 0.73, with an optimal cut-off value of 42.60 pg/mL. IL-6 was higher in COVID-19 patients than in healthy subjects, but did not differ between COVID-19 and Non-COVID-19 patients. THPO concentrations measured at the time of diagnosis in the ED were also higher in COVID-19 patients subsequently developing a severe disease than in those with mild disease. Evaluating THPO as biomarker for severe COVID-19 using ROC analysis, we found an AUC of 0.71, with an optimal cut-off value of 57.11 pg/mL. IL-6 was also higher in severe than in mild COVID-19 patients, with an AUC for severe COVID-19 of 0.83 and an optimal cut-off value of 23 pg/ml. THPO concentrations correlated with those of IL-6 (r=0.2963; p=0.043), and decreased 24 h after the administration of tocilizumab, an IL-6 receptor blocking antibody, showing that the increase of THPO levels depends on IL-6-stimulated hepatic synthesis. In vitro, plasma obtained from COVID-19 patients, but not from healthy subjects, primed platelet aggregation and leukocyte-platelet binding, and these effects were reduced by inhibiting THPO activity. INTERPRETATION: Increased THPO may be proposed as an early biomarker for the diagnosis of COVID-19 and for the identification of patients at risk of developing critical illness. Elevated THPO may contribute to enhance platelet activation and leukocyte-platelet interaction in COVID-19 patients, thus potentially participating in immunothrombosis/thromboinflammation. FUNDING: This work was supported by Ministero dell'Università e della Ricerca Scientifica e Tecnologica (MURST) ex 60% to GM and EL.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».