Glycyrrhetinic acid: A potential drug for the treatment of COVID-19 cytokine storm

Li, Huawei; You, Jia; Yang, Xi; Wei, Yuanfeng; Liu, Zheng; Zhao, Yaqin; Huang, Ying; Jin, Zhao; Yi, Cheng

doi:10.1016/j.phymed.2022.154153

Cited by 15 publications

(6 citation statements)

References 43 publications

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“…( 73 ) both found that FOXC1, YY1, GATA2, and FOXL1 are important TFs for COVID-19. Some network pharmacology studies ( 74 , 75 ) also found that PPARG may be a key therapeutic target for COVID-19. In addition, hsa-mir-27a-3p may be related to the malignant biological behavior of glioma cells ( 76 ), and may also be an important molecular feature in esophageal cancer ( 77 ).…”

Section: Discussionmentioning

confidence: 98%

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach

Liu

Gui

et al. 2022

Front. Immunol.

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Corona Virus Disease 2019 (COVID-19), an acute respiratory infectious disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has spread rapidly worldwide, resulting in a pandemic with a high mortality rate. In clinical practice, we have noted that many critically ill or critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. In addition, it has been demonstrated that severe COVID-19 has some pathological similarities with sepsis, such as cytokine storm, hypercoagulable state after blood balance is disrupted and neutrophil dysfunction. Considering the parallels between COVID-19 and non-SARS-CoV-2 induced sepsis (hereafter referred to as sepsis), the aim of this study was to analyze the underlying molecular mechanisms between these two diseases by bioinformatics and a systems biology approach, providing new insights into the pathogenesis of COVID-19 and the development of new treatments. Specifically, the gene expression profiles of COVID-19 and sepsis patients were obtained from the Gene Expression Omnibus (GEO) database and compared to extract common differentially expressed genes (DEGs). Subsequently, common DEGs were used to investigate the genetic links between COVID-19 and sepsis. Based on enrichment analysis of common DEGs, many pathways closely related to inflammatory response were observed, such as Cytokine-cytokine receptor interaction pathway and NF-kappa B signaling pathway. In addition, protein-protein interaction networks and gene regulatory networks of common DEGs were constructed, and the analysis results showed that ITGAM may be a potential key biomarker base on regulatory analysis. Furthermore, a disease diagnostic model and risk prediction nomogram for COVID-19 were constructed using machine learning methods. Finally, potential therapeutic agents, including progesterone and emetine, were screened through drug-protein interaction networks and molecular docking simulations. We hope to provide new strategies for future research and treatment related to COVID-19 by elucidating the pathogenesis and genetic mechanisms between COVID-19 and sepsis.

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Section: Discussionmentioning

confidence: 98%

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach

Liu

Gui

et al. 2022

Front. Immunol.

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“…80 Human cytomegalovirus infection pathways are related to the regulation of inflammation of COVID-19 patients. 81 Also, smokers have a higher tendency to be infected by human cytomegalovirus infection pathway. 82 In the hub-protein interaction, we have validated total of 7 proteins with previous literature named WDR46, C4A, APOE, HLA-C, HLA-DQB1, BCAR1, and NTS.…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Molecular Biomarker Identification Using a Network-Based Bioinformatics Approach That Links COVID-19 With Smoking

Rahman

Amin

Yeasmin

et al. 2023

Bioinform Biol Insights

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The COVID-19 coronavirus, which primarily affects the lungs, is the source of the disease known as SARS-CoV-2. According to “Smoking and COVID-19: a scoping review,” about 32% of smokers had a severe case of COVID-19 pneumonia at their admission time and 15% of non-smokers had this case of COVID-19 pneumonia. We were able to determine which genes were expressed differently in each group by comparing the expression of gene transcriptomic datasets of COVID-19 patients, smokers, and healthy controls. In all, 37 dysregulated genes are common in COVID-19 patients and smokers, according to our analysis. We have applied all important methods namely protein-protein interaction, hub-protein interaction, drug-protein interaction, tf-gene interaction, and gene-MiRNA interaction of bioinformatics to analyze to understand deeply the connection between both smoking and COVID-19 severity. We have also analyzed Pathways and Gene Ontology where 5 significant signaling pathways were validated with previous literature. Also, we verified 7 hub-proteins, and finally, we validated a total of 7 drugs with the previous study.

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“…Currently, monoclonal antibodies against a variety of cytokines and a variety of related signaling pathway modulatory agents have shown potential to control the SARS-CoV-2 cytokine storm, such as tocilizumab for IL-6 ( 140 , 141 ), emapalumab for IFN-γ ( 142 ), canakinumab for IL-1β and anakinra for IL-1R ( 143 ), JAK2/STAT3 inhibitors ( 131 , 144 ), NF-κB pathway regulators ( 145 ), MAPK/NF-κB pathway regulators ( 146 ), the nucleotide-binding and oligomerization domain-like receptor family pyrin domain-containing 3 inflammasome signaling inhibitors ( 147 , 148 ). In addition, immunoglobulin ( 149 ), nanotechnology-based corticosteroid drugs ( 150 ), and traditional Chinese medicine ( 151 – 153 ) are also potential drugs to alleviate cytokine storms.…”

Section: Discussionmentioning

confidence: 99%

Uncovering the information immunology journals transmitted for COVID-19: A bibliometric and visualization analysis

et al. 2022

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BackgroundSince the global epidemic of the coronavirus disease 2019 (COVID-19), a large number of immunological studies related to COVID-19 have been published in various immunology journals. However, the results from these studies were discrete, and no study summarized the important immunological information about COVID-19 released by these immunology journals. This study aimed to comprehensively summarize the knowledge structure and research hotspots of COVID-19 published in major immunology journals through bibliometrics.MethodsPublications on COVID-19 in major immunology journals were obtained from the Web of Science Core Collection. CiteSpace, VOSviewer, and R-bibliometrix were comprehensively used for bibliometric and visual analysis.Results1,331 and 5,000 publications of 10 journals with high impact factors and 10 journals with the most papers were included, respectively. The USA, China, England, and Italy made the most significant contributions to these papers. University College London, National Institute of Allergy and Infectious Diseases, Harvard Medical School, University California San Diego, and University of Pennsylvania played a central role in international cooperation in the immunology research field of COVID-19. Yuen Kwok Yung was the most important author in terms of the number of publications and citations, and the H-index. CLINICAL INFECTIOUS DISEASES and FRONTIERS IN IMMUNOLOGY were the most essential immunology journals. These immunology journals mostly focused on the following topics: “Delta/Omicron variants”, “cytokine storm”, “neutralization/neutralizing antibody”, “T cell”, “BNT162b2”, “mRNA vaccine”, “vaccine effectiveness/safety”, and “long COVID”.ConclusionThis study systematically uncovered a holistic picture of the current research on COVID-19 published in major immunology journals from the perspective of bibliometrics, which will provide a reference for future research in this field.

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Glycyrrhetinic acid: A potential drug for the treatment of COVID-19 cytokine storm

Cited by 15 publications

References 43 publications

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach

Discovering common pathogenetic processes between COVID-19 and sepsis by bioinformatics and system biology approach

Molecular Biomarker Identification Using a Network-Based Bioinformatics Approach That Links COVID-19 With Smoking

Uncovering the information immunology journals transmitted for COVID-19: A bibliometric and visualization analysis

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