MicroRNAs based regulation of cytokine regulating immune expressed genes and their transcription factors in COVID-19

Abstract

Background Coronavirus disease 2019 is characterized by the elevation of a broad spectrum of inflammatory mediators associated with poor disease outcomes. We aimed at an in-silico analysis of regulatory microRNA and their transcription factors (TF) for these inflammatory genes that may help to devise potential therapeutic strategies in the future. Methods The cytokine regulating immune-expressed genes (CRIEG) were sorted from literature and the GEO microarray dataset. Their co-differentially expressed miRNA and transcription factors were predicted from publicly available databases. Enrichment analysis was done through mienturnet, MiEAA, Gene Ontology, and pathways predicted by KEGG and Reactome pathways. Finally, the functional and regulatory features were analyzed and visualized through Cytoscape. Results Sixteen CRIEG were observed to have a significant protein-protein interaction network. The ontological analysis revealed significantly enriched pathways for biological processes, molecular functions, and cellular components. The search performed in the miRNA database yielded ten miRNAs that are significantly involved in regulating these genes and their transcription factors. Conclusion An in-silico representation of a network involving miRNAs, CRIEGs, and TF, which take part in the inflammatory response in COVID-19, has been elucidated. Thus, these regulatory factors may have potentially critical roles in the inflammatory response in COVID-19 and may be explored further to develop targeted therapeutic strategies and mechanistic validation.

Gene Networks of Hyperglycemia, Diabetic Complications, and Human Proteins Targeted by SARS-CoV-2: What Is the Molecular Basis for Comorbidity?

“…The clinical evidence supports the role of some molecules revealed in this work in COVID-19 pathogenesis: ANGPT2 [48,49], CCL2 [50], ICAM1 [52,53], VCAM-1 [52], MIR21 [54], MMP9 [55,56], STAT3 [57], HMGB1 [58,59], SIRT1 [62,63], AGTR1 [66], APOE4 [69,70], ACE [73], CCL11 [86,87], FGF2 [89], TNF [92], PPAR-γ [95], CASP8 [115], IL8 [117], IL6 [118], PRL [119], SP1 [122], TLR4 [123], BDNF [124], CASP1 [125], CASP3 [126,127], IL18 [128], IL10 [129], TGFB1 [130], ANXA2 [131,132], HPSE [162], MAPK1 [163], CDH1 [166], FBN1 [180], GDF15 [182,183], PLAT [195][196][197], RHOA…”

“…On the other hand, prolactin may reduce the hyperinflammatory status in COVID-19 as it has an antiinflammatory activity [119]. The Sp1 transcription factor could be linked with cytokine expression and the inflammatory response in COVID-19 via miR-155-5p [122]. STAT3 hyperactivation is related to the cytokine storm in COVID-19 [57].…”

Helicobacter pylori regulated microRNA map of human gastric cells

“…While RECK and TIMP3 are well‐known matrix‐metalloproteinase inhibitors whose expression is suppressed in multiple cancers, 48,49 KLF4 and LATS2 are reported to be tumor suppressor genes 50,51 . In support of this observation, other experimentally known targets with highest interacting proteins (degree of interaction of at least 24) are associated with transcriptional regulations (ESR1, STAT3, EP300) and oncogenesis (TP53, MYC, EGFR, JUN) 52,53 . Importantly, tumor suppressors such as p53 (targeted by 8 HP‐hDEmiRs), CDH1 (targeted by 3 HP‐hDEmiRs), and APC (targeted by 3 HP‐hDEmiRs), and proto‐oncogenes such as TERT (targeted by 1 HP‐hDEmiRs) and Ras (targeted by 6 HP‐hDEmiRs) are well associated with gastric cancers and are also targeted by the HP‐hDEmiRs 54–56 …”

Bioinformatics and System Biology Approach to Reveal the Interaction Network and the Therapeutic Implications for Non-Small Cell Lung Cancer Patients With COVID-19

“…Various studies have identified miRNAs as key players in the pathogenesis and therapeutics of viral diseases. Moreover, as part of host–pathogen interactions, miRNA can scan target SARS-CoV-2 genes as well as host inflammatory machinery to counter-act the impairing effects of infection ( Ghosh et al, 2009 ; Khokhar et al, 2022 ). The top 10 most significant miRNAs mainly involved in respiratory diseases ( Table 4 ), including NSCLC [hsa-miR-24-3p ( Wei et al, 2021 ), hsa-miR-34a-5p ( Zhou X. et al, 2020 ), hsa-miR-10b-3p ( Liu et al, 2017 ), hsa-miR-20a-5p, and hsa-miR-17-5p ( Leidinger et al, 2016 )], idiopathic pulmonary fibrosis [hsa-miR-524-5p ( Li Q. et al, 2020 ), COVID-19 (hsa-miR-20a-5p, hsa-miR-17-5p ( Li C. et al, 2020 )), and hsa-miR-16-5p ( Kim et al, 2020 )], pneumoconiosis [hsa-let-7a-5p ( Zhang et al, 2018 )], and asthma [(hsa-let-7a-5p ( Huang et al, 2019 )].…”