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BackgroundCoronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Infected individuals display a wide spectrum of disease severity, as defined by the World Health Organization (WHO). One of the main factors underlying this heterogeneity is the host immune response, with severe COVID-19 often associated with a hyperinflammatory state.AimOur current study aimed to pinpoint the specific genes and pathways underlying differences in the disease spectrum and outcomes observed, through in-depth analyses of whole blood transcriptomics in a large cohort of COVID-19 participants.ResultsAll WHO severity levels were well represented and mild and severe disease displaying distinct gene expression profiles. WHO severity levels 1-4 were grouped as mild disease, and signatures from these participants were different from those with WHO severity levels 6-9 classified as severe disease. Severity level 5 (moderate cases) presented a unique transitional gene signature between severity levels 2-4 (mild/moderate) and 6-9 (severe) and hence might represent the turning point for better or worse disease outcome. Gene expression changes are very distinct when comparing mild/moderate or severe cases to healthy controls. In particular, we demonstrated the hallmark down-regulation of adaptive immune response pathways and activation of neutrophil pathways in severe compared to mild/moderate cases, as well as activation of blood coagulation pathways.ConclusionsOur data revealed discrete gene signatures associated with mild, moderate, and severe COVID-19 identifying valuable candidates for future biomarker discovery.

PurposeRobust biomarkers that predict disease outcomes amongst COVID-19 patients are necessary for both patient triage and resource prioritisation. Numerous candidate biomarkers have been proposed for COVID-19. However, at present, there is no consensus on the best diagnostic approach to predict outcomes in infected patients. Moreover, it is not clear whether such tools would apply to other potentially pandemic pathogens and therefore of use as stockpile for future pandemic preparedness.MethodsWe conducted a multi-cohort observational study to investigate the biology and the prognostic role of interferon alpha-inducible protein 27 (IFI27) in COVID-19 patients.ResultsWe show that IFI27 is expressed in the respiratory tract of COVID-19 patients and elevated IFI27 expression in the lower respiratory tract is associated with the presence of a high viral load. We further demonstrate that the systemic host response, as measured by blood IFI27 expression, is associated with COVID-19 infection. For clinical outcome prediction (e.g., respiratory failure), IFI27 expression displays a high sensitivity (0.95) and specificity (0.83), outperforming other known predictors of COVID-19 outcomes. Furthermore, IFI27 is upregulated in the blood of infected patients in response to other respiratory viruses. For example, in the pandemic H1N1/09 influenza virus infection, IFI27-like genes were highly upregulated in the blood samples of severely infected patients.ConclusionThese data suggest that prognostic biomarkers targeting the family of IFI27 genes could potentially supplement conventional diagnostic tools in future virus pandemics, independent of whether such pandemics are caused by a coronavirus, an influenza virus or another as yet-to-be discovered respiratory virus.

Patients with preexisting metabolic disorders such as diabetes are at a higher risk of developing severe coronavirus disease 2019 (COVID-19). Mitochondrion, the very organelle that controls cellular metabolism, holds the key to understanding disease progression at the cellular level. Our current study aimed to understand how cellular metabolism contributes to COVID-19 outcomes. Metacore pathway enrichment analyses on differentially expressed genes (encoded by both mitochondrial and nuclear deoxyribonucleic acid (DNA)) involved in cellular metabolism, regulation of mitochondrial respiration and organization, and apoptosis, was performed on RNA sequencing (RNASeq) data from blood samples collected from healthy controls and patients with mild/moderate or severe COVID-19. Genes from the enriched pathways were analyzed by network analysis to uncover interactions among them and up- or downstream genes within each pathway. Compared to the mild/moderate COVID-19, the upregulation of a myriad of growth factor and cell cycle signaling pathways, with concomitant downregulation of interferon signaling pathways, were observed in the severe group. Matrix metallopeptidase 9 (MMP9) was found in five of the top 10 upregulated pathways, indicating its potential as therapeutic target against COVID-19. In summary, our data demonstrates aberrant activation of endocrine signaling in severe COVID-19, and its implication in immune and metabolic dysfunction.

Identification of host factors associated with severe influenza infection could provide insights into treatment options. Here, the authors provide transcriptomic analyses of blood from >100 influenza infected patients and show that changes in circulating neutrophils are associated with severe influenza infection.

Sepsis is associated with a dysregulated inflammatory response to infection. Despite the activation of inflammation, an immune suppression is often observed, predisposing patients to secondary infections. Therapies directed at restoration of immunity may be considered but should be guided by the immune status of the patients. In this paper, we described the use of a high-dimensional flow cytometry (HDCyto) panel to assess the immunophenotype of patients with sepsis. We then isolated peripheral blood mononuclear cells (PBMCs) from patients with septic shock and mimicked a secondary infection by stimulating PBMCs for 4 h in vitro with lipopolysaccharide (LPS) with or without prior exposure to either IFN-γ, or LAG-3Ig. We evaluated the response by means of flow cytometry and high-resolution clustering cum differential analysis and compared the results to PBMCs from healthy donors. We observed a heterogeneous immune response in septic patients and identified two major subgroups: one characterized by hypo-responsiveness (Hypo) and another one by hyper-responsiveness (Hyper). Hypo and Hyper groups showed significant differences in the production of cytokines/chemokine and surface human leukocyte antigen-DR (HLA-DR) expression in response to LPS stimulation, which were observed across all cell types. When pre-treated with either interferon gamma (IFN-γ) or lymphocyte-activation gene 3 (LAG)-3 recombinant fusion protein (LAG-3Ig) prior to LPS stimulation, cells from the Hypo group were shown to be more responsive to both immunostimulants than cells from the Hyper group. Our results demonstrate the importance of patient stratification based on their immune status prior to any immune therapies. Once sufficiently scaled, this approach may be useful for prescribing the right immune therapy for the right patient at the right time, the key to the success of any therapy.