The understanding of the immunopathology in COVID-19 infection

Overreactive macrophages in SARS-CoV-2 infection: The effects of ACEI

Among various factors influencing the course of SARS-CoV-2 infection in humans, macrophage overactivation is considered the main cause of the cytokine storm that leads to severe complications of COVID-19. Moreover, the increased expression of angiotensin converting enzyme 2 (ACE2), an obligatory entry receptor of the coronavirus, caused by treatment with ACE inhibitors (ACEI) lowered overall confidence in the safety of these drugs. However, analysis of the course of coronavirus infection in patients treated with ACEI does not support these concerns. Instead, the beneficial effect of ACEI on macrophages has increasingly been emphasized. This includes their anti-inflammatory activation and the consequent reduction in the risk of severe disease and life-threatening complications. Herein, we summarize the current knowledge and understanding of the dual role of macrophages in SARS-CoV-2 infection, with a special focus on the postulated mechanisms underlying the beneficial effects of macrophage targeting by ACEI. These seem to involve the stimulation of macrophage angiotensin II type 2 and Mas receptors by angiotensin 1-7, intensively produced due to the up-regulation of ACE2 expression on macrophages, as well as the direct inhibition of macrophage hyper-responsiveness by ACEI. The impact of ACEI on macrophages may also lead to the activation of an effective antiviral response due to the increased expression of ACE2.

Difference in mortality rates in hospitalized COVID-19 patients identified by cytokine profile clustering using a machine learning approach: An outcome prediction alternative

COVID-19 is a disease caused by the novel Coronavirus SARS-CoV-2 causing an acute respiratory disease that can eventually lead to severe acute respiratory syndrome (SARS). An exacerbated inflammatory response is characteristic of SARS-CoV-2 infection, which leads to a cytokine release syndrome also known as cytokine storm associated with the severity of the disease. Considering the importance of this event in the immunopathology of COVID-19, this study analyses cytokine levels of hospitalized patients to identify cytokine profiles associated with severity and mortality. Using a machine learning approach, 3 clusters of COVID-19 hospitalized patients were created based on their cytokine profile. Significant differences in the mortality rate were found among the clusters, associated to different CXCL10/IL-38 ratio. The balance of a CXCL10 induced inflammation with an appropriate immune regulation mediated by the anti-inflammatory cytokine IL-38 appears to generate the adequate immune context to overrule SARS-CoV-2 infection without creating a harmful inflammatory reaction. This study supports the concept that analyzing a single cytokine is insufficient to determine the outcome of a complex disease such as COVID-19, and different strategies incorporating bioinformatic analyses considering a broader immune profile represent a more robust alternative to predict the outcome of hospitalized patients with SARS-CoV-2 infection.

Multi-Level Biological Network Analysis and Drug Repurposing Based on Leukocyte Transcriptomics in Severe COVID-19: In Silico Systems Biology to Precision Medicine

The coronavirus disease 2019 (COVID-19) pandemic causes many morbidity and mortality cases. Despite several developed vaccines and antiviral therapies, some patients experience severe conditions that need intensive care units (ICU); therefore, precision medicine is necessary to predict and treat these patients using novel biomarkers and targeted drugs. In this study, we proposed a multi-level biological network analysis framework to identify key genes via protein–protein interaction (PPI) network analysis as well as survival analysis based on differentially expressed genes (DEGs) in leukocyte transcriptomic profiles, discover novel biomarkers using microRNAs (miRNA) from regulatory network analysis, and provide candidate drugs targeting the key genes using drug–gene interaction network and structural analysis. The results show that upregulated DEGs were mainly enriched in cell division, cell cycle, and innate immune signaling pathways. Downregulated DEGs were primarily concentrated in the cellular response to stress, lysosome, glycosaminoglycan catabolic process, and mature B cell differentiation. Regulatory network analysis revealed that hsa-miR-6792-5p, hsa-let-7b-5p, hsa-miR-34a-5p, hsa-miR-92a-3p, and hsa-miR-146a-5p were predicted biomarkers. CDC25A, GUSB, MYBL2, and SDAD1 were identified as key genes in severe COVID-19. In addition, drug repurposing from drug–gene and drug–protein database searching and molecular docking showed that camptothecin and doxorubicin were candidate drugs interacting with the key genes. In conclusion, multi-level systems biology analysis plays an important role in precision medicine by finding novel biomarkers and targeted drugs based on key gene identification.

Circulating B10 regulatory cells are decreased in severe and critical COVID-19

The contribution of B cells in COVID‐19 pathogenesis, beyond the production of specific antibodies against SARS‐CoV‐2, is still not well understood. Since one of their most relevant functional roles includes their immune‐suppressive mechanisms, we decided to evaluate one of the most recognized human B regulatory subpopulations: the IL‐10⁺ B10 cells, during COVID‐19 onset. After stimulation of PBMCs for IL‐10 induction, we employed multiparametric flow cytometry to determine B10 frequencies in severe and critical COVID‐19 patients and then correlated those with clinical and laboratory parameters. Compared with healthy individuals, we detected a significant reduction in the B10 subset in both patient groups, which correlates with some inflammatory parameters that define the disease severity. This evidence suggests an aberrant role of B10 cells in immune responses against SARS‐CoV‐2 that needs to be further explained.

Low Levels of Granulocytic Myeloid-Derived Suppressor Cells May Be a Good Marker of Survival in the Follow-Up of Patients With Severe COVID-19

Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes a disease (coronavirus disease 2019, COVID-19) that may develop into a systemic disease with immunosuppression and death in its severe form. Myeloid-derived suppressive cells (MDSCs) are inhibitory cells that contribute to immunosuppression in patients with cancer and infection. Increased levels of MDSCs have been found in COVID-19 patients, although their role in the pathogenesis of severe COVID-19 has not been clarified. For this reason, we raised the question whether MDSCs could be useful in the follow-up of patients with severe COVID-19 in the intensive care unit (ICU). Thus, we monitored the immunological cells, including MDSCs, in 80 patients admitted into the ICU. After 1, 2, and 3 weeks, we examined for a possible association with mortality (40 patients). Although the basal levels of circulating MDSCs did not discriminate between the two groups of patients, the last measurement before the endpoint (death or ICU discharge) showed that patients discharged alive from the ICU had lower levels of granulocytic MDSCs (G-MDSCs), higher levels of activated lymphocytes, and lower levels of exhausted lymphocytes compared with patients who had a bad evolution (death). In conclusion, a steady increase of G-MDSCs during the follow-up of patients with severe COVID-19 was found in those who eventually died.