RNA-Seq and high-resolution mass spectrometry on 128 blood samples from COVID-19 positive and negative patients with diverse disease severities and outcomes were performed and published on Cell Systems
Quantified transcripts, proteins, metabolites, and lipids were associated with clinical outcomes in a curated relational database, uniquely enabling systems analysis and cross-ome correlations to molecules and patient prognoses, mapping 219 molecular features with high significance to COVID-19 status and severity, many involved in complement activation, dysregulated lipid transport, and neutrophil activation.
The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype.
Our list of 219 features strongly correlated to COVID-19 status and severity contained multiple transcripts and proteins involved in neutrophil degranulation . An increased expression of multiple genes related to neutrophil function, including PRTN3, LCN2, CD24, BPI, CTSG, DEFA1, DEFA4, MMP8, and MPO were observed. MPO encodes neutrophil myeloperoxidase, a protein instrumental in complexing extracellular DNA for the development of neutrophil extracellular traps (NETs), extracellular aggregates of DNA, histones, toxic proteins, and oxidative enzymes released by neutrophils to control infections, and their overdrive can amplify tissue injury by inflammation and thrombosis. NETs have been associated with the pathogenesis of ARDS and thrombosis, both phenotypes observed in severe COVID-19 patients, and elevated neutrophil counts predict
worse outcomes in COVID-19 patients . Several NETs proteins linked with thrombosis, including calprotectin, ferritin, CRP, and histone H3, were also increased. Thus, data strengthen earlier suggestions that combating dysregulated NETs may present an avenue towards mitigation of disease
severity in COVID-19. For example, dipyridamole, an FDA-approved drug that can inhibit NET formation by activation of adenosine A2A receptors, has recently been shown to improve outcomes of COVID-19 patients with respiratory failure. Similarly, the platelet P2Y12 receptor antagonist ticagrelor has been proposed to attenuate NET formation in COVID-19 and may simultaneously inhibit platelet activation, a process also involved in COVID-19 pathophysiology. Drugs that antagonize the NET–IL1β loop, such as anakinra, are currently being tested.
Numerous proteins involved in the body’s response to blood vessel damage, including AGT, FBLN5, NID1, and SERPINB1, increased in the COVID-19 samples relative to non-COVID-19 group and were especially higher in abundance in more severe patients. Neuropilin-1 (NRP1) is a regulator of the vascular endothelialgrowth factor (VEGF)-induced angiogenesis, and increase in its abundance with COVID-19 severity is of particular relevance given the recent report describing excessive pulmonary intussusceptive angiogenesis at autopsy in COVID-19. In contrast, other vessel damage-associated proteins, such as SERPINA4, significantly decreased in abundance in COVID-19 patients, highlighting the regulatory intricacies of this biological process.
In accord with earlier reports, severe dysregulation of proteins associated with platelet activation and degranulation was observed. Platelet-associated proteins were increased in COVID19 samples vs. non-COVID-19 samples, like serglycin (SRGN) and the von Willebrand Factor (VWF), which has been recently implicated in COVID-19-associated endotheliopathy by the use of an FDA-approved antibody test. VWF is synthesized by endothelial cells as a 2,813 amino acid-long protein that is processed intracellularly to form VWF antigen 2 (VWFAg2) and VWF multimer.
VWFAg2 is released constitutively into circulation, whereas VWF multimer is stored for later release upon stimulation of endothelial cells. To distinguish between these two products, 19 peptides unique to VWFAg2 and 107 peptides unique to VWF were quantified. Abundances of both VWFAg2 and VWF multimer were increased and correlated with COVID-19 severity.
Endothelial cells increase synthesis, package, and release both VWFAg2 and
VWF multimers, particularly in severe COVID-19 cases.
Consistent with the widely reported hypercoagulative phenotype of
COVID-19 patients, all patients exhibited evidence of excessive clotting in vivo as demonstrated by the increased levels of circulating fibrin D-dimer. To further examine the coagulative dysregulation in COVID-19 patients
at molecular level, were deliberately conducted proteomic analyses using plasma. These plasma proteins, working alongside proteins of the vessel wall and platelets, undergo a cascade of regulated proteolytic reactions to
generate thrombin, which converts fibrinogen to fibrin. Were detected significant increases in abundance of fibrinogen alpha (FGA) and beta (FGB) in COVID-19 vs. non-COVID-19 patient plasma. Were also observed decreases in abundance of prothrombin (F2) and thrombin-activation factor XIII (F13A1, F13B) in COVID-19 samples compared to non-COVID,
and these proteins were further decreased in the most severe patients. Significant reductions and correlations with HFD-45 were found for
plasminogen (PLG), kallikrein (KLKB1) and kininogen (KNG1), which function in the intrinsic coagulation cascade leading to generation of thrombin (Schmaier 2016); heparin cofactor 2 (SERPIND1), which
forms an inhibitory complex with thrombin, protein C (PROC), which is
activated by thrombin to activated protein C and protein C inhibitor (SERPINA5). The decreases of abundance of PROC and SERPINA5 with severity assume greater significance when considered alongside the
finding that soluble plasma thrombomodulin (THBD) rivals elevated VWF as a predictor of mortality in COVID-19. THBD is normally tethered to the surface of endothelial cells, where it forms a complex with thrombin that efficiently activates PROC to APC serving to modulate inflammatory response and administration of recombinant APC mutant has been proposed as a therapy to mitigate thrombo-inflammation
which occurs with ARDS and in severe COVID-19 patients-
A web-based tool (covid-omics.app) enabling interactive exploration of our compendium and illustrate its utility through a machine learning approach for prediction of COVID-19 severity.