Bioinformatics insights into the genes and pathways on severe COVID-19 pathology in patients with comorbidities

Abdulrahman Mujalli; Kawthar Saad Alghamdi; Khalidah Khalid Nasser; Nuha Al-Rayes; Babajan Banaganapalli; Noor Ahmad Shaik; Ramu Elango

doi:10.3389/fphys.2022.1045469

Bioinformatics insights into the genes and pathways on severe COVID-19 pathology in patients with comorbidities

Front Physiol. 2022 Dec 14:13:1045469. doi: 10.3389/fphys.2022.1045469. eCollection 2022.

Authors

Abdulrahman Mujalli^{1

2

3}, Kawthar Saad Alghamdi^{3

4}, Khalidah Khalid Nasser^{3

5}, Nuha Al-Rayes^{3

5}, Babajan Banaganapalli^{1

3}, Noor Ahmad Shaik^{1

3}, Ramu Elango^{1

3}

Affiliations

¹ Department of Genetic Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
² Department of Laboratory Medicine, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.
³ Princess Al-Jawhara Center of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia.
⁴ Department of Biology, Faculty of Science, University of Hafr Al Batin, Hafar Al-Batin, Saudi Arabia.
⁵ Department of Medical Laboratory Sciences, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Saudi Arabia.

Abstract

Background: Coronavirus disease (COVID-19) infection is known for its severe clinical pathogenesis among individuals with pre-existing comorbidities. However, the molecular basis of this observation remains elusive. Thus, this study aimed to map key genes and pathway alterations in patients with COVID-19 and comorbidities using robust systems biology approaches. Methods: The publicly available genome-wide transcriptomic datasets from 120 COVID-19 patients, 281 patients suffering from different comorbidities (like cardiovascular diseases, atherosclerosis, diabetes, and obesity), and 252 patients with different infectious diseases of the lung (respiratory syncytial virus, influenza, and MERS) were studied using a range of systems biology approaches like differential gene expression, gene ontology (GO), pathway enrichment, functional similarity, mouse phenotypic analysis and drug target identification. Results: By cross-mapping the differentially expressed genes (DEGs) across different datasets, we mapped 274 shared genes to severe symptoms of COVID-19 patients or with comorbidities alone. GO terms and functional pathway analysis highlighted genes in dysregulated pathways of immune response, interleukin signaling, FCGR activation, regulation of cytokines, chemokines secretion, and leukocyte migration. Using network topology parameters, phenotype associations, and functional similarity analysis with ACE2 and TMPRSS2-two key receptors for this virus-we identified 17 genes with high connectivity (CXCL10, IDO1, LEPR, MME, PTAFR, PTGS2, MAOB, PDE4B, PLA2G2A, COL5A1, ICAM1, SERPINE1, ABCB1, IL1R1, ITGAL, NCAM1 and PRKD1) potentially contributing to the clinical severity of COVID-19 infection in patients with comorbidities. These genes are predicted to be tractable and/or with many existing approved inhibitors, modulators, and enzymes as drugs. Conclusion: By systemic implementation of computational methods, this study identified potential candidate genes and pathways likely to confer disease severity in COVID-19 patients with pre-existing comorbidities. Our findings pave the way to develop targeted repurposed therapies in COVID-19 patients.

Keywords: COVID-19; MERS; SARS-CoV-2; cardiovascular diseases; comorbidities; diabetes; obesity; viral infections.