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Immune Signature Linked to COVID-19 Severity: A SARS-Score for Personalized Medicine.

ABSTRACT: SARS-CoV-2 infection leads to a highly variable clinical evolution, ranging from asymptomatic to severe disease with acute respiratory distress syndrome, requiring intensive care units (ICU) admission. The optimal management of hospitalized patients has become a worldwide concern and identification of immune biomarkers predictive of the clinical outcome for hospitalized patients remains a major challenge. Immunophenotyping and transcriptomic analysis of hospitalized COVID-19 patients at admission allow identifying the two categories of patients. Inflammation, high neutrophil activation, dysfunctional monocytic response and a strongly impaired adaptive immune response was observed in patients who will experience the more severe form of the disease. This observation was validated in an independent cohort of patients. Using in silico analysis on drug signature database, we identify differential therapeutics that specifically correspond to each group of patients. From this signature, we propose a score-the SARS-Score-composed of easily quantifiable biomarkers, to classify hospitalized patients upon arrival to adapt treatment according to their immune profile.

SUBMITTER: Russick J

PROVIDER: S-EPMC8312547 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Using RNA-seq and high-resolution mass spectrometry we performed a comprehensive systems analysis on 128 plasma and leukocyte samples from hospitalized patients with or without COVID-19 (n=102 and 26 respectively) and with differing degrees of disease severity. We generated abundance measurements for over 17,000 transcripts, proteins, metabolites, and lipids and compiled them with clinical data into a curated relational database. This resource offers the unique opportunity to perform systems analysis and cross-ome correlations to both molecules and patient outcomes. In total 219 molecular features were mapped with high significance to COVID-19 status and severity, including those involved in processes such as complement system activation, dysregulated lipid transport, and B cell activation. In one example, we detected a trio of covarying molecules – citrate, plasmenyl-phosphatidylcholines, and gelsolin (GSN) – that offer both pathophysiological insight and potential novel therapeutic targets. Further, our data revealed in some cases, and supported in others, that several biological processes were dysregulated in COVID-19 patients including vessel damage, platelet activation and degranulation, blood coagulation, and acute phase response. For example, we observed that the coagulation-related protein, cellular fibronectin (cFN), was highly increased within COVID-19 patients and provide new evidence that the upregulated proteoform stems from endothelial cells, consistent with endothelial injury as a major activator of the coagulation cascade. The abundance of prothrombin, which is cleaved to form thrombin during clotting, was significantly reduced and correlated with severity and might help to explain the hyper coagulative environment of SARS-CoV-2 infection. From transcriptomic analysis of leukocytes, we concluded that COVID-19 patients with acute respiratory distress syndrome (ARDS) demonstrated a phenotype that overlapped with, but was distinct from, that found in patients with non-COVID-19-ARDS. To aid in the global efforts toward elucidation of disease pathophysiology and therapeutic development, we created a web-based tool with interactive visualizations allowing for easy navigation of this systems-level compendium of biomolecule abundance in relation to COVID-19 status and severity. Finally, we leveraged these multi-omic data to predict COVID-19 patient outcomes with machine learning, which highlighted the predictive power of these expansive molecular measurements beyond the standardized clinical estimate of 10-year survival Charlson score.

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Immune Signature Linked to COVID-19 Severity: A SARS-Score for Personalized Medicine.

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