Longitudinal profiles of plasma gelsolin, cytokines and antibody expression predict COVID-19 severity and hospitalization outcomes.

Background: Prognostic markers for COVID-19 disease outcome are currently lacking. Plasma gelsolin (pGSN) is an actin-binding protein and an innate immune marker involved in disease pathogenesis and viral infections. Here, we demonstrate the utility of pGSN as a prognostic marker for COVID-19 disease outcome; a test performance that is significantly improved when combined with cytokines and antibodies compared to other conventional markers such as CRP and ferritin. Methods: Blood samples were longitudinally collected from hospitalized COVID-19 patients as well as COVID-19 negative controls and the levels of pGSN in µg/mL, cytokines and anti- SARS-CoV-2 spike protein antibodies assayed. Mean ± SEM values were correlated with clinical parameters to develop a prognostic platform. Results: pGSN levels were significantly reduced in COVID-19 patients compared to healthy individuals. Additionally, pGSN levels combined with plasma IL-6, IP-10 and M-CSF significantly distinguished COVID-19 patients from healthy individuals. While pGSN and anti-spike IgG titers together strongly predict COVID-19 severity and death, the combination of pGSN and IL-6 was a significant predictor of milder disease and favorable outcomes. Conclusion: Taken together, these findings suggest that multi-parameter analysis of pGSN, cytokines and antibodies could predict COVID-19 hospitalization outcomes with greater certainty compared with conventional clinical laboratory markers such as CRP and ferritin. This research will inform and improve clinical management and health system interventions in response to SARS-CoV-2 infection.

Recombinant human plasma gelsolin reverses increased permeability of the blood-brain barrier induced by the spike protein of the SARS-CoV-2 virus.

BACKGROUND: Plasma gelsolin (pGSN) is an important part of the blood actin buffer that prevents negative consequences of possible F-actin deposition in the microcirculation and has various functions during host immune response. Recent reports reveal that severe COVID-19 correlates with reduced levels of pGSN. Therefore, using an in vitro system, we investigated whether pGSN could attenuate increased permeability of the blood-brain barrier (BBB) during its exposure to the portion of the SARS-CoV-2 spike protein containing the receptor binding domain (S1 subunit). MATERIALS AND METHODS: Two- and three-dimensional models of the human BBB were constructed using the human cerebral microvascular endothelial cell line hCMEC/D3 and exposed to physiologically relevant shear stress to mimic perfusion in the central nervous system (CNS). Trans-endothelial electrical resistance (TEER) as well as immunostaining and Western blotting of tight junction (TJ) proteins assessed barrier integrity in the presence of the SARS-CoV-2 spike protein and pGSN. The IncuCyte Live Imaging system evaluated the motility of the endothelial cells. Magnetic bead-based ELISA was used to determine cytokine secretion. Additionally, quantitative real-time PCR (qRT-PCR) revealed gene expression of proteins from signaling pathways that are associated with the immune response. RESULTS: pGSN reversed S1-induced BBB permeability in both 2D and 3D BBB models in the presence of shear stress. BBB models exposed to pGSN also exhibited attenuated pro-inflammatory signaling pathways (PI3K, AKT, MAPK, NF-κB), reduced cytokine secretion (IL-6, IL-8, TNF-α), and increased expression of proteins that form intercellular TJ (ZO-1, occludin, claudin-5). CONCLUSION: Due to its anti-inflammatory and protective effects on the brain endothelium, pGSN has the potential to be an alternative therapeutic target for patients with severe SARS-CoV-2 infection, especially those suffering neurological complications of COVID-19.

Large-Scale Multi-omic Analysis of COVID-19 Severity.

We performed RNA-seq and high-resolution mass spectrometry on 128 blood samples from COVID-19-positive and COVID-19-negative patients with diverse disease severities and outcomes. 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. We mapped 219 molecular features with high significance to COVID-19 status and severity, many of which were involved in complement activation, dysregulated lipid transport, and neutrophil activation. We identified sets of covarying molecules, e.g., protein gelsolin and metabolite citrate or plasmalogens and apolipoproteins, offering pathophysiological insights and therapeutic suggestions. The observed dysregulation of platelet function, blood coagulation, acute phase response, and endotheliopathy further illuminated the unique COVID-19 phenotype. We present 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.