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Hasankhani A, Bahrami A, Sheybani N, et al. Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic. Front Immunol. 2021;12:789317doi: 10.3389/fimmu.2021.789317.
Hasankhani, A., Bahrami, A., Sheybani, N., Aria, B., Hemati, B., Fatehi, F., Ghaem Maghami Farahani, H., Javanmard, G., Rezaee, M., Kastelic, J. P., & Barkema, H. W. (2021). Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic. Frontiers in immunology, 12789317. https://doi.org/10.3389/fimmu.2021.789317
Hasankhani, Aliakbar, et al. "Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic." Frontiers in immunology vol. 12 (2021): 789317. doi: https://doi.org/10.3389/fimmu.2021.789317
Hasankhani A, Bahrami A, Sheybani N, Aria B, Hemati B, Fatehi F, Ghaem Maghami Farahani H, Javanmard G, Rezaee M, Kastelic JP, Barkema HW. Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic. Front Immunol. 2021 Dec 15;12:789317. doi: 10.3389/fimmu.2021.789317. eCollection 2021. PMID: 34975885; PMCID: PMC8714803.
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Front Immunol. 2021 Dec 15;12:789317. doi: 10.3389/fimmu.2021.789317. eCollection 2021.

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic.

Frontiers in immunology

Aliakbar Hasankhani, Abolfazl Bahrami, Negin Sheybani, Behzad Aria, Behzad Hemati, Farhang Fatehi, Hamid Ghaem Maghami Farahani, Ghazaleh Javanmard, Mahsa Rezaee, John P Kastelic, Herman W Barkema

Affiliations

  1. Department of Animal Science, College of Agriculture and Natural Resources, University of Tehran, Karaj, Iran.
  2. Biomedical Center for Systems Biology Science Munich, Ludwig-Maximilians-University, Munich, Germany.
  3. Department of Animal and Poultry Science, College of Aburaihan, University of Tehran, Tehran, Iran.
  4. Department of Physical Education and Sports Science, School of Psychology and Educational Sciences, Yazd University, Yazd, Iran.
  5. Biotechnology Research Center, Karaj Branch, Islamic Azad University, Karaj, Iran.
  6. Department of Medical Mycology, School of Medical Science, Tarbiat Modares University, Tehran, Iran.
  7. Department of Production Animal Health, Faculty of Veterinary Medicine, University of Calgary, Calgary, AB, Canada.

PMID: 34975885 PMCID: PMC8714803 DOI: 10.3389/fimmu.2021.789317

Abstract

BACKGROUND: The recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.

METHODS: RNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.

RESULTS: Based on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including

CONCLUSION: This study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

Copyright © 2021 Hasankhani, Bahrami, Sheybani, Aria, Hemati, Fatehi, Ghaem Maghami Farahani, Javanmard, Rezaee, Kastelic and Barkema.

Keywords: COVID-19 pandemic; WGCNA; hub-high traffic genes; immunopathogenesis; systems biology; systems immunology; therapeutic targets in infectious diseases

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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