Upregulation of cAMP prevents antibody-mediated thrombus formation in COVID-19.
Jan ZlamalKarina AlthausHisham JaffalHelene A HaeberleLisann PelzlAnurag SinghAndreas WitzemannKaroline WeichMichael BitzerNisar MalekSiri GoepelHans BösmüllerMeinrad GawazValbona MirakajPeter RosenbergerTamam BakchoulPublished in: Blood advances (2021)
Thromboembolic events are frequently reported in patients infected with the SARS-CoV-2 virus. The exact mechanisms of COVID-19 associated hypercoagulopathy, however, remain elusive. Recently, we observed that platelets (PLTs) from patients with severe COVID-19 infection express high levels of procoagulant markers, which were found to be associated with increased risk for thrombosis. In the current study, we investigated the time course as well as the mechanisms leading to procoagulant PLTs in COVID-19. Our study demonstrates the presence of PLT-reactive IgG antibodies that induce marked changes in PLTs in terms of increased inner-mitochondrial-transmembrane potential (Δψ) depolarization, phosphatidylserine (PS) externalization and P-selectin expression. The IgG-induced procoagulant PLTs and increased thrombus formation was mediated by ligation of PLT Fc gamma RIIA (FcγRIIA). In addition, PLTs´ contents of calcium and cyclic-adenosine-monophosphate (cAMP) were identified to play central role in antibody-induced procoagulant PLT formation. Most importantly, antibody-induced procoagulant events as well as increased thrombus formation in severe COVID-19 were inhibited by Iloprost a clinically approved therapeutic agent that increases the intracellular cAMP levels in PLTs. Our data indicate that upregulation of cAMP could be a potential therapeutic target to prevent antibody-mediated coagulopathy in COVID-19 disease.
Keyphrases
- sars cov
- coronavirus disease
- respiratory syndrome coronavirus
- poor prognosis
- diabetic rats
- high glucose
- binding protein
- drug induced
- oxidative stress
- protein kinase
- cell proliferation
- signaling pathway
- newly diagnosed
- risk assessment
- prognostic factors
- ejection fraction
- long non coding rna
- deep learning
- mass spectrometry
- artificial intelligence
- data analysis
- patient reported