A multi-tissue study of immune gene expression profiling highlights the key role of the nasal epithelium in COVID-19 severity.

Coronavirus Disease-19 (COVID-19) symptoms range from mild to severe illness; the cause for this differential response to infection remains unknown. Unravelling the immune mechanisms acting at different levels of the colonization process might be key to understand these differences. We carried out a multi-tissue (nasal, buccal and blood; n = 156) gene expression analysis of immune-related genes from patients affected by different COVID-19 severities, and healthy controls through the nCounter technology. Mild and asymptomatic cases showed a powerful innate antiviral response in nasal epithelium, characterized by activation of interferon (IFN) pathway and downstream cascades, successfully controlling the infection at local level. In contrast, weak macrophage/monocyte driven innate antiviral response and lack of IFN signalling activity were present in severe cases. Consequently, oral mucosa from severe patients showed signals of viral activity, cell arresting and viral dissemination to the lower respiratory tract, which ultimately could explain the exacerbated innate immune response and impaired adaptative immune responses observed at systemic level. Results from saliva transcriptome suggest that the buccal cavity might play a key role in SARS-CoV-2 infection and dissemination in patients with worse prognosis. Co-expression network analysis adds further support to these findings, by detecting modules specifically correlated with severity involved in the abovementioned biological routes; this analysis also provides new candidate genes that might be tested as biomarkers in future studies. We also found tissue specific severity-related signatures mainly represented by genes involved in the innate immune system and cytokine/chemokine signalling. Local immune response could be key to determine the course of the systemic response and thus COVID-19 severity. Our findings provide a framework to investigate severity host gene biomarkers and pathways that might be relevant to diagnosis, prognosis, and therapy.

Prediction of the Effects of Variants and Differential Expression of Key Host Genes ACE2, TMPRSS2, and FURIN in SARS-CoV-2 Pathogenesis: An In Silico Approach.

A new strain of the beta coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is solely responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic. Although several studies suggest that the spike protein of this virus interacts with the cell surface receptor, angiotensin-converting enzyme 2 (ACE2), and is subsequently cleaved by TMPRSS2 and FURIN to enter into the host cell, conclusive insight about the interaction pattern of the variants of these proteins is still lacking. Thus, in this study, we analyzed the functional conjugation among the spike protein, ACE2, TMPRSS2, and FURIN in viral pathogenesis as well as the effects of the mutations of the proteins through the implementation of several bioinformatics approaches. Analysis of the intermolecular interactions revealed that T27A (ACE2), G476S (receptor-binding domain [RBD] of the spike protein), C297T (TMPRSS2), and P812S (cleavage site for TMPRSS2) coding variants may render resistance in viral infection, whereas Q493L (RBD), S477I (RBD), P681R (cleavage site for FURIN), and P683W (cleavage site for FURIN) may lead to increase viral infection. Genotype-specific expression analysis predicted several genetic variants of ACE2 (rs2158082, rs2106806, rs4830971, and rs4830972), TMPRSS2 (rs458213, rs468444, rs4290734, and rs6517666), and FURIN (rs78164913 and rs79742014) that significantly alter their normal expression which might affect the viral spread. Furthermore, we also found that ACE2, TMPRSS2, and FURIN proteins are functionally co-related with each other, and several genes are highly co-expressed with them, which might be involved in viral pathogenesis. This study will thus help in future genomics and proteomics studies of SARS-CoV-2 and will provide an opportunity to understand the underlying molecular mechanism during SARS-CoV-2 pathogenesis.

Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients.

BACKGROUND: The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS: In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS: Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS: Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.