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

Abstract

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.

Identification of Key Genes Related to Immune Cells in Patients with COVID-19 Via Integrated Bioinformatics-Based Analysis

“…Additionally, these DEGs were mainly enriched in cellular senescence, complement and coagulation cascades, organelle fission, DNA replication, and P53 signaling pathways. Sagulkoo illustrated that upregulated DEGs in COVID-19 were mainly concentrated on cell division, cell cycle, and innate immune signaling pathways, which was consistent with our study (Sagulkoo et al 2022 ). Lucy Kundura discovered that the monocyte of COVID-19 can spontaneously release ROS (reactive oxygen species, ROS) which was able to result in DNA damage and apoptosis in neighboring cells.…”

Identification of key genes related to immune cells in patients with COVID-19 via Integrated Bioinformatics-Based Analysis

“…Additionally, these DEGs were mainly enriched in cellular senescence, complement and coagulation cascades, organelle ssion, DNA replication, and P53 signaling pathways. Pakorn Sagulkoo illustrated that upregulated DEGs in COVID-19 were mainly concentrated in cell division, cell cycle, and innate immune signaling pathways, which was consistent with our study 21 . Lucy Kundura discovered that the monocyte of COVID-19 spontaneously released ROS (reactive oxygen species, ROS) able to result in DNA damage and apoptosis in neighboring cells.…”

Analysis of the potential relationship between COVID-19 and Behcet’s disease using transcriptome data

“…We also found the basis for the association of hsa-mir-124-3p and hsa-let-7b-5p with the developmental process of COVID-19. [48,49] We performed genes-diseases analysis to predict the association between hub genes and related diseases, and we found 284 diseases with significant association with hub genes, and we screened the top 20 diseases as the most significantly associated with hub genes. We constructed genes-diseases networks and found that such as liver carcinoma of cortical development was significantly associated with hub genes.…”

“…We also found the basis for the association of hsa-mir-124-3p and hsa-let-7b-5p with the developmental process of COVID-19. [ 48 , 49 ]…”