Genes Involved in miRNA Biogenesis Are Not Downregulated in SARS-CoV-2 Infection.

miRNAs, small non-coding RNAs that regulate gene expression, are involved in various pathological processes, including viral infections. Virus infections may interfere with the miRNA pathway through the inhibition of genes involved in miRNA biogenesis. A reduction in the number and the levels of miRNAs expressed in nasopharyngeal swabs of patients with severe COVID-19 was lately observed by us, pointing towards the potential of miRNAs as possible diagnostic or prognostic biomarkers for predicting outcomes among patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. The objective of the present study was to investigate whether SARS-CoV-2 infection influences the expression levels of messenger RNAs (mRNAs) of key genes involved in miRNA biogenesis. mRNA levels of AGO2, DICER1, DGCR8, DROSHA, and Exportin-5 (XPO5) were measured by quantitative reverse-transcription polymerase chain reaction (RT-qPCR) in nasopharyngeal swab specimens from patients with COVID-19 and controls, as well as in cells infected with SARS-CoV-2 in vitro. Our data showed that the mRNA expression levels of AGO2, DICER1, DGCR8, DROSHA, and XPO5 were not significantly different in patients with severe COVID-19 when compared to patients with non-severe COVID-19 and controls. Similarly, the mRNA expression of these genes was not affected by SARS-CoV-2 infection in NHBE and Calu-3 cells. However, in Vero E6 cells, AGO2, DICER1, DGCR8, and XPO5 mRNA levels were slightly upregulated 24 h after infection with SARS-CoV-2. In conclusion, we did not find evidence for downregulation of mRNA levels of miRNA biogenesis genes during SARS-CoV-2 infection, neither ex vivo nor in vitro.

Bioinformatics and system biology approach to identify the influences among COVID-19, ARDS and sepsis.

Background Severe coronavirus disease 2019 (COVID -19) has led to severe pneumonia or acute respiratory distress syndrome (ARDS) worldwide. we have noted that many critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. The molecular mechanisms that underlie COVID-19, ARDS and sepsis are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19, ARDS and sepsis using bioinformatics and a systems biology approach. Methods Three RNA-seq datasets (GSE171110, GSE76293 and GSE137342) from Gene Expression Omnibus (GEO) were employed to detect mutual differentially expressed genes (DEGs) for the patients with the COVID-19, ARDS and sepsis for functional enrichment, pathway analysis, and candidate drugs analysis. Results We obtained 110 common DEGs among COVID-19, ARDS and sepsis. ARG1, FCGR1A, MPO, and TLR5 are the most influential hub genes. The infection and immune-related pathways and functions are the main pathways and molecular functions of these three diseases. FOXC1, YY1, GATA2, FOXL, STAT1 and STAT3 are important TFs for COVID-19. mir-335-5p, miR-335-5p and hsa-mir-26a-5p were associated with COVID-19. Finally, the hub genes retrieved from the DSigDB database indicate multiple drug molecules and drug-targets interaction. Conclusion We performed a functional analysis under ontology terms and pathway analysis and found some common associations among COVID-19, ARDS and sepsis. Transcription factors-genes interaction, protein-drug interactions, and DEGs-miRNAs coregulatory network with common DEGs were also identified on the datasets. We believe that the candidate drugs obtained in this study may contribute to the effective treatment of COVID-19.

Systems genetics identifies miRNA-mediated regulation of host response in COVID-19.

BACKGROUND: Individuals infected with SARS-CoV-2 vary greatly in their disease severity, ranging from asymptomatic infection to severe disease. The regulation of gene expression is an important mechanism in the host immune response and can modulate the outcome of the disease. miRNAs play important roles in post-transcriptional regulation with consequences on downstream molecular and cellular host immune response processes. The nature and magnitude of miRNA perturbations associated with blood phenotypes and intensive care unit (ICU) admission in COVID-19 are poorly understood. RESULTS: We combined multi-omics profiling-genotyping, miRNA and RNA expression, measured at the time of hospital admission soon after the onset of COVID-19 symptoms-with phenotypes from electronic health records to understand how miRNA expression contributes to variation in disease severity in a diverse cohort of 259 unvaccinated patients in Abu Dhabi, United Arab Emirates. We analyzed 62 clinical variables and expression levels of 632 miRNAs measured at admission and identified 97 miRNAs associated with 8 blood phenotypes significantly associated with later ICU admission. Integrative miRNA-mRNA cross-correlation analysis identified multiple miRNA-mRNA-blood endophenotype associations and revealed the effect of miR-143-3p on neutrophil count mediated by the expression of its target gene BCL2. We report 168 significant cis-miRNA expression quantitative trait loci, 57 of which implicate miRNAs associated with either ICU admission or a blood endophenotype. CONCLUSIONS: This systems genetics study has given rise to a genomic picture of the architecture of whole blood miRNAs in unvaccinated COVID-19 patients and pinpoints post-transcriptional regulation as a potential mechanism that impacts blood traits underlying COVID-19 severity. The results also highlight the impact of host genetic regulatory control of miRNA expression in early stages of COVID-19 disease.

Using bioinformatics and systems biology methods to identify the mechanism of interaction between COVID-19 and nonalcoholic fatty liver disease.

Nonalcoholic fatty liver disease (NAFLD) is considered a risk factor for severe COVID-19, but the mechanism remains unknown. This study used bioinformatics to help define the relationship between these diseases. The GSE147507 (COVID-19), GSE126848 (NAFLD), and GSE63067 (NAFLD-2) datasets were screened using the Gene Expression Omnibus. Common differentially expressed genes were then identified using a Venn diagram. Gene ontology analysis and KEGG pathway enrichment were performed on the differentially expressed genes. A protein-protein interaction network was also constructed using the STRING platform, and key genes were identified using the Cytoscape plugin. GES63067 was selected for validation of the results. Analysis of ferroptosis gene expression during the development of the 2 diseases and prediction of their upstream miRNAs and lncRNAs. In addition, transcription factors (TFs) and miRNAs related to key genes were identified. Effective drugs that act on target genes were found in the DSigDB. The GSE147507 and GSE126848 datasets were crossed to obtain 28 co-regulated genes, 22 gene ontology terms, 3 KEGG pathways, and 10 key genes. NAFLD may affect COVID-19 progression through immune function and inflammatory signaling pathways. CYBB was predicted to be a differential ferroptosis gene associated with 2 diseases, and the CYBB-hsa-miR-196a/b-5p-TUG1 regulatory axis was identified. TF-gene interactions and TF-miRNA coregulatory network were constructed successfully. A total of 10 drugs, (such as Eckol, sulfinpyrazone, and phenylbutazone) were considered as target drugs for Patients with COVID-19 and NAFLD. This study identified key gene and defined molecular mechanisms associated with the progression of COVID-19 and NAFLD. COVID-19 and NAFLD progression may regulate ferroptosis through the CYBB-hsa-miR-196a/b-5p-TUG1 axis. This study provides additional drug options for the treatment of COVID-19 combined with NAFLD disease.

IMC-MDA: Prediction of miRNA-disease association based on induction matrix completion.

To comprehend the etiology and pathogenesis of many illnesses, it is essential to identify disease-associated microRNAs (miRNAs). However, there are a number of challenges with current computational approaches, such as the lack of "negative samples", that is, confirmed irrelevant miRNA-disease pairs, and the poor performance in terms of predicting miRNAs related with "isolated diseases", i.e. illnesses with no known associated miRNAs, which presents the need for novel computational methods. In this study, for the purpose of predicting the connection between disease and miRNA, an inductive matrix completion model was designed, referred to as IMC-MDA. In the model of IMC-MDA, for each miRNA-disease pair, the predicted marks are calculated by combining the known miRNA-disease connection with the integrated disease similarities and miRNA similarities. Based on LOOCV, IMC-MDA had an AUC of 0.8034, which shows better performance than previous methods. Furthermore, experiments have validated the prediction of disease-related miRNAs for three major human diseases: colon cancer, kidney cancer, and lung cancer.

Interaction of Biochemical Processes between Chronic Obstructive Pulmonary Disease (COPD), Pulmonary Arterial Hypertension (PAH), and Coronavirus Disease 2019 (COVID-19).

Both pulmonary arterial hypertension (PAH) and chronic obstructive pulmonary disease (COPD) are risk factors for coronavirus disease 2019 (COVID-19). Patients with lung injury and altered pulmonary vascular anatomy or function are more susceptible to infections. The purpose of the study is to ascertain whether individuals with COPD or PAH are affected synergistically by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Data sources for the construction of a protein-protein interaction (PPI) network and the identification of differentially expressed genes (DEGs) included three RNA-seq datasets from the GEO database (GSE147507, GSE106986, and GSE15197). Then, relationships between miRNAs, common DEGs, and transcription factor (TF) genes were discovered. Functional analysis using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and other databases, as well as the forecasting of antiviral medications for COPD and PAH patients infected with SARS-CoV-2, were also performed. Eleven common DEGs were found in the three datasets, and their biological functions were primarily enriched in the control of protein modification processes, particularly phosphorylation. Growth factor receptor binding reflects molecular function. KEGG analysis indicated that co-DEGs mainly activate Ras, and PI3K-Akt signaling pathways and act on focal adhesions. NFKB1 interacted with HSA-miR-942 in the TF-miRNA-DEGs synergistic regulatory network. Acetaminophen is considered an effective drug candidate. There are some connections between COPD and PAH and the development of COVID-19. This research could aid in developing COVID-19 vaccines and medication candidates that would work well as COVID-19 therapies.

Establishment and validation of the autophagy-related ceRNA network in irreversible pulpitis.

BACKGROUND: The molecular mechanisms underlying the onset and progression of irreversible pulpitis have been studied for decades. Many studies have indicated a potential correlation between autophagy and this disease. Against the background of the competing endogenous RNA (ceRNA) theory, protein-coding RNA functions are linked with long noncoding RNAs (lncRNAs) and microRNAs (miRNAs). This mechanism has been widely studied in various fields but has rarely been reported in the context of irreversible pulpitis. The hub genes selected under this theory may represent the key to the interaction between autophagy and irreversible pulpitis. RESULTS: Filtering and differential expression analyses of the GSE92681 dataset, which contains data from 7 inflamed and 5 healthy pulp tissue samples, were conducted. The results were intersected with autophagy-related genes (ARGs), and 36 differentially expressed ARGs (DE-ARGs) were identified. Functional enrichment analysis and construction of the protein‒protein interaction (PPI) network of DE-ARGs were performed. Coexpression analysis was conducted between differentially expressed lncRNAs (DElncRNAs) and DE-ARGs, and 151 downregulated and 59 upregulated autophagy-related DElncRNAs (AR-DElncRNAs) were identified. StarBase and multiMiR were then used to predict related microRNAs of AR-DElncRNAs and DE-ARGs, respectively. We established ceRNA networks including 9 hub lncRNAs (HCP5 and AC112496.1 ↑; FENDRR, AC099850.1, ZSWIM8-AS1, DLX6-AS1, LAMTOR5-AS1, TMEM161B-AS1 and AC145207.5 ↓), which were validated by a qRT‒PCR analysis of pulp tissue from patients with irreversible pulpitis. CONCLUSION: We constructed two networks consisting of 9 hub lncRNAs based on the comprehensive identification of autophagy-related ceRNAs. This study may provide novel insights into the interactive relationship between autophagy and irreversible pulpitis and identifies several lncRNAs that may serve as potential biological markers.

Differentially-regulated miRNAs in COVID-19: A systematic review.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is responsible for coronavirus disease of 2019 (COVID-19) that infected more than 760 million people worldwide with over 6.8 million deaths to date. COVID-19 is one of the most challenging diseases of our times due to the nature of its spread, its effect on multiple organs, and an inability to predict disease prognosis, ranging from being completely asymptomatic to death. Upon infection, SARS-CoV-2 alters the host immune response by changing host-transcriptional machinery. MicroRNAs (miRNAs) are regarded as post-transcriptional regulators of gene expression that can be perturbed by invading viruses. Several in vitro and in vivo studies have reported such dysregulation of host miRNA expression upon SARS-CoV-2 infection. Some of this could occur as an anti-viral response of the host to the viral infection. Viruses themselves can counteract that response by mounting their own pro-viral response that facilitates virus infection, an aspect which may cause pathogenesis. Thus, miRNAs could serve as possible disease biomarkers in infected people. In the current review, we have summarised and analysed the existing data about miRNA dysregulation in patients infected with SARS-CoV-2 to determine their concordance between studies, and identified those that could serve as potential biomarkers during infection, disease progression, and death, even in people with other co-morbidities. Having such biomarkers can be vital in not only predicting COVID-19 prognosis, but also the development of novel miRNA-based anti-virals and therapeutics which can become invaluable in case of the emergence of new viral variants with pandemic potential in the future.

Saliva microRNA Profile in Children with and without Severe SARS-CoV-2 Infection.

Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) may impair immune modulating host microRNAs, causing severe disease. Our objectives were to determine the salivary miRNA profile in children with SARS-CoV-2 infection at presentation and compare the expression in those with and without severe outcomes. Children <18 years with SARS-CoV-2 infection evaluated at two hospitals between March 2021 and February 2022 were prospectively enrolled. Severe outcomes included respiratory failure, shock or death. Saliva microRNAs were quantified with RNA sequencing. Data on 197 infected children (severe = 45) were analyzed. Of the known human miRNAs, 1606 (60%) were measured and compared across saliva samples. There were 43 miRNAs with ≥2-fold difference between severe and non-severe cases (adjusted p-value < 0.05). The majority (31/43) were downregulated in severe cases. The largest between-group differences involved miR-4495, miR-296-5p, miR-548ao-3p and miR-1273c. These microRNAs displayed enrichment for 32 gene ontology pathways including viral processing and transforming growth factor beta and Fc-gamma receptor signaling. In conclusion, salivary miRNA levels are perturbed in children with severe COVID-19, with the majority of miRNAs being down regulated. Further studies are required to validate and determine the utility of salivary miRNAs as biomarkers of severe COVID-19.

IFI44 is an immune evasion biomarker for SARS-CoV-2 and Staphylococcus aureus infection in patients with RA.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global pandemic of severe coronavirus disease 2019 (COVID-19). Staphylococcus aureus is one of the most common pathogenic bacteria in humans, rheumatoid arthritis (RA) is among the most prevalent autoimmune conditions. RA is a significant risk factor for SARS-CoV-2 and S. aureus infections, although the mechanism of RA and SARS-CoV-2 infection in conjunction with S. aureus infection has not been elucidated. The purpose of this study is to investigate the biomarkers and disease targets between RA and SARS-CoV-2 and S. aureus infections using bioinformatics analysis, to search for the molecular mechanisms of SARS-CoV-2 and S. aureus immune escape and potential drug targets in the RA population, and to provide new directions for further analysis and targeted development of clinical treatments. Methods: The RA dataset (GSE93272) and the S. aureus bacteremia (SAB) dataset (GSE33341) were used to obtain differentially expressed gene sets, respectively, and the common differentially expressed genes (DEGs) were determined through the intersection. Functional enrichment analysis utilizing GO, KEGG, and ClueGO methods. The PPI network was created utilizing the STRING database, and the top 10 hub genes were identified and further examined for functional enrichment using Metascape and GeneMANIA. The top 10 hub genes were intersected with the SARS-CoV-2 gene pool to identify five hub genes shared by RA, COVID-19, and SAB, and functional enrichment analysis was conducted using Metascape and GeneMANIA. Using the NetworkAnalyst platform, TF-hub gene and miRNA-hub gene networks were built for these five hub genes. The hub gene was verified utilizing GSE17755, GSE55235, and GSE13670, and its effectiveness was assessed utilizing ROC curves. CIBERSORT was applied to examine immune cell infiltration and the link between the hub gene and immune cells. Results: A total of 199 DEGs were extracted from the GSE93272 and GSE33341 datasets. KEGG analysis of enrichment pathways were NLR signaling pathway, cell membrane DNA sensing pathway, oxidative phosphorylation, and viral infection. Positive/negative regulation of the immune system, regulation of the interferon-I (IFN-I; IFN-α/ß) pathway, and associated pathways of the immunological response to viruses were enriched in GO and ClueGO analyses. PPI network and Cytoscape platform identified the top 10 hub genes: RSAD2, IFIT3, GBP1, RTP4, IFI44, OAS1, IFI44L, ISG15, HERC5, and IFIT5. The pathways are mainly enriched in response to viral and bacterial infection, IFN signaling, and 1,25-dihydroxy vitamin D3. IFI44, OAS1, IFI44L, ISG15, and HERC5 are the five hub genes shared by RA, COVID-19, and SAB. The pathways are primarily enriched for response to viral and bacterial infections. The TF-hub gene network and miRNA-hub gene network identified YY1 as a key TF and hsa-mir-1-3p and hsa-mir-146a-5p as two important miRNAs related to IFI44. IFI44 was identified as a hub gene by validating GSE17755, GSE55235, and GSE13670. Immune cell infiltration analysis showed a strong positive correlation between activated dendritic cells and IFI44 expression. Conclusions: IFI144 was discovered as a shared biomarker and disease target for RA, COVID-19, and SAB by this study. IFI44 negatively regulates the IFN signaling pathway to promote viral replication and bacterial proliferation and is an important molecular target for SARS-CoV-2 and S. aureus immune escape in RA. Dendritic cells play an important role in this process. 1,25-Dihydroxy vitamin D3 may be an important therapeutic agent in treating RA with SARS-CoV-2 and S. aureus infections.

miRNAs, from Evolutionary Junk to Possible Prognostic Markers and Therapeutic Targets in COVID-19.

The COVID-19 pandemic has been a public health issue around the world in the last few years. Currently, there is no specific antiviral treatment to fight the disease. Thus, it is essential to highlight possible prognostic predictors that could identify patients with a high risk of developing complications. Within this framework, miRNA biomolecules play a vital role in the genetic regulation of various genes, principally, those related to the pathophysiology of the disease. Here, we review the interaction of host and viral microRNAs with molecular and cellular elements that could potentiate the main pulmonary, cardiac, renal, circulatory, and neuronal complications in COVID-19 patients. miR-26a, miR-29b, miR-21, miR-372, and miR-2392, among others, have been associated with exacerbation of the inflammatory process, increasing the risk of a cytokine storm. In addition, increased expression of miR-15b, -199a, and -491 are related to the prognosis of the disease, and miR-192 and miR-323a were identified as clinical predictors of mortality in patients admitted to the intensive care unit. Finally, we address miR-29, miR-122, miR-155, and miR-200, among others, as possible therapeutic targets. However, more studies are required to confirm these findings.

Exploring Potential Biomarkers and Molecular Mechanisms of Ischemic Cardiomyopathy and COVID-19 Comorbidity Based on Bioinformatics and Systems Biology.

Cardiovascular complications combined with COVID-19 (SARS-CoV-2) lead to a poor prognosis in patients. The common pathogenesis of ischemic cardiomyopathy (ICM) and COVID-19 is still unclear. Here, we explored potential molecular mechanisms and biomarkers for ICM and COVID-19. Common differentially expressed genes (DEGs) of ICM (GSE5406) and COVID-19 (GSE164805) were identified using GEO2R. We performed enrichment and protein-protein interaction analyses and screened key genes. To confirm the diagnostic performance for these hub genes, we used external datasets (GSE116250 and GSE211979) and plotted ROC curves. Transcription factor and microRNA regulatory networks were constructed for the validated hub genes. Finally, drug prediction and molecular docking validation were performed using cMAP. We identified 81 common DEGs, many of which were enriched in terms of their relation to angiogenesis. Three DEGs were identified as key hub genes (HSP90AA1, HSPA9, and SRSF1) in the protein-protein interaction analysis. These hub genes had high diagnostic performance in the four datasets (AUC > 0.7). Mir-16-5p and KLF9 transcription factor co-regulated these hub genes. The drugs vindesine and ON-01910 showed good binding performance to the hub genes. We identified HSP90AA1, HSPA9, and SRSF1 as markers for the co-pathogenesis of ICM and COVID-19, and showed that co-pathogenesis of ICM and COVID-19 may be related to angiogenesis. Vindesine and ON-01910 were predicted as potential therapeutic agents. Our findings will contribute to a deeper understanding of the comorbidity of ICM with COVID-19.

The 3'UTR region of the DNA repair gene PARP-1 May increase the severity of COVID-19 by altering the binding of antiviral miRNAs.

COVID-19 may cause the release of systemic inflammatory cytokines resulting in severe inflammation. PARP-1 has been identified as a nuclear enzyme that is activated by DNA strand breaks. It has been suggested that PARP-1 has a role in the cytokine storm shown as a cause of mortality in COVID-19, and its inhibition may adversely affect the replication of SARS -CoV-2. We aimed to investigate the relationship between PARP-1 gene polymorphisms and the clinical severity of COVID-19. rs8679 TT genotype was found to increase with the COVID-19 disease severity. The 3'UTR polymorphism rs8679 may cause PARP-1 activity as a result of viral replication increase by changing the binding site of antiviral or anti-inflammatory miRNAs. PARP-1 may affect the severity of COVID-19 by cytokine release and maybe a possible treatment target.

Risk factors and actionable molecular signatures in COVID-19-associated lung adenocarcinoma and lung squamous cell carcinoma patients.

The molecular mechanism of the pathological impact of COVID-19 in lung cancer patients remains poorly understood to date. In this study, we used differential gene expression pattern analysis to try to figure out the possible disease mechanism of COVID-19 and its associated risk factors in patients with the two most common types of non-small-cell lung cancer, namely, lung adenocarcinoma and lung squamous cell carcinoma. We also used network-based approaches to identify potential diagnostic and molecular targets for COVID-19-infected lung cancer patients. Our study showed that lung cancer and COVID-19 patients share 36 genes that are expressed differently and in common. Most of these genes are expressed in lung tissues and are mostly involved in the pathogenesis of different respiratory tract diseases. Additionally, we also found that COVID-19 may affect the expression of several cancer-associated genes in lung cancer patients, such as the oncogenes JUN, TNC, and POU2AF1. Moreover, our findings suggest that COVID-19 may predispose lung cancer patients to other diseases like acute liver failure and respiratory distress syndrome. Additionally, our findings, in concert with published literature, suggest that molecular signatures, such as hsa-mir-93-5p, CCNB2, IRF1, CD163, and different immune cell-based approaches could help both diagnose and treat this group of patients. Altogether, the scientific findings of this study will help formulate appropriate management measures and guide the development of diagnostic and therapeutic measures for COVID-19-infected lung cancer patients.

Systematic review of overlapping microRNA patterns in COVID-19 and idiopathic pulmonary fibrosis.

BACKGROUND: Pulmonary fibrosis is an emerging complication of SARS-CoV-2 infection. In this study, we speculate that patients with COVID-19 and idiopathic pulmonary fibrosis (IPF) may share aberrant expressed microRNAs (miRNAs) associated to the progression of lung fibrosis. OBJECTIVE: To identify miRNAs presenting similar alteration in COVID-19 and IPF, and describe their impact on fibrogenesis. METHODS: A systematic review of the literature published between 2010 and January 2022 (PROSPERO, CRD42022341016) was conducted using the key words (COVID-19 OR SARS-CoV-2) AND (microRNA OR miRNA) or (idiopathic pulmonary fibrosis OR IPF) AND (microRNA OR miRNA) in Title/Abstract. RESULTS: Of the 1988 references considered, 70 original articles were appropriate for data extraction: 27 studies focused on miRNAs in COVID-19, and 43 on miRNAs in IPF. 34 miRNAs were overlapping in COVID-19 and IPF, 7 miRNAs presenting an upregulation (miR-19a-3p, miR-200c-3p, miR-21-5p, miR-145-5p, miR-199a-5p, miR-23b and miR-424) and 9 miRNAs a downregulation (miR-17-5p, miR-20a-5p, miR-92a-3p, miR-141-3p, miR-16-5p, miR-142-5p, miR-486-5p, miR-708-3p and miR-150-5p). CONCLUSION: Several studies reported elevated levels of profibrotic miRNAs in COVID-19 context. In addition, the balance of antifibrotic miRNAs responsible of the modulation of fibrotic processes is impaired in COVID-19. This evidence suggests that the deregulation of fibrotic-related miRNAs participates in the development of fibrotic lesions in the lung of post-COVID-19 patients.

Identification of biomarkers, pathways, and potential therapeutic targets for heart failure using next-generation sequencing data and bioinformatics analysis.

BACKGROUND: Heart failure (HF) is the most common cardiovascular diseases and the leading cause of cardiovascular diseases related deaths. Increasing molecular targets have been discovered for HF prognosis and therapy. However, there is still an urgent need to identify novel biomarkers. Therefore, we evaluated biomarkers that might aid the diagnosis and treatment of HF. METHODS: We searched next-generation sequencing (NGS) dataset (GSE161472) and identified differentially expressed genes (DEGs) by comparing 47 HF samples and 37 normal control samples using limma in R package. Gene ontology (GO) and pathway enrichment analyses of the DEGs were performed using the g: Profiler database. The protein-protein interaction (PPI) network was plotted with Human Integrated Protein-Protein Interaction rEference (HiPPIE) and visualized using Cytoscape. Module analysis of the PPI network was done using PEWCC1. Then, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed by Cytoscape software. Finally, we performed receiver operating characteristic (ROC) curve analysis to predict the diagnostic effectiveness of the hub genes. RESULTS: A total of 930 DEGs, 464 upregulated genes and 466 downregulated genes, were identified in HF. GO and REACTOME pathway enrichment results showed that DEGs mainly enriched in localization, small molecule metabolic process, SARS-CoV infections, and the citric acid tricarboxylic acid (TCA) cycle and respiratory electron transport. After combining the results of the PPI network miRNA-hub gene regulatory network and TF-hub gene regulatory network, 10 hub genes were selected, including heat shock protein 90 alpha family class A member 1 (HSP90AA1), arrestin beta 2 (ARRB2), myosin heavy chain 9 (MYH9), heat shock protein 90 alpha family class B member 1 (HSP90AB1), filamin A (FLNA), epidermal growth factor receptor (EGFR), phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), cullin 4A (CUL4A), YEATS domain containing 4 (YEATS4), and lysine acetyltransferase 2B (KAT2B). CONCLUSIONS: This discovery-driven study might be useful to provide a novel insight into the diagnosis and treatment of HF. However, more experiments are needed in the future to investigate the functional roles of these genes in HF.

Identification of Common Dysregulated Genes in COVID-19 and Hypersensitivity Pneumonitis: A Systems Biology and Machine Learning Approach.

A comprehensive knowledge on systems biology of severe acute respiratory syndrome coronavirus 2 is crucial for differential diagnosis of COVID-19. Interestingly, the radiological and pathological features of COVID-19 mimic that of hypersensitivity pneumonitis (HP), another pulmonary fibrotic phenotype. This motivated us to explore the overlapping pathophysiology of COVID-19 and HP, if any, and using a systems biology approach. Two datasets were obtained from the Gene Expression Omnibus database (GSE147507 and GSE150910) and common differentially expressed genes (DEGs) for both diseases identified. Fourteen common DEGs, significantly altered in both diseases, were found to be implicated in complement activation and growth factor activity. A total of five microRNAs (hsa-miR-1-3p, hsa-miR-20a-5p, hsa-miR-107, hsa-miR-16-5p, and hsa-miR-34b-5p) and five transcription factors (KLF6, ZBTB7A, ELF1, NFIL3, and ZBT33) exhibited highest interaction with these common genes. Next, C3, CFB, MMP-9, and IL1A were identified as common hub genes for both COVID-19 and HP. Finally, these top-ranked genes (hub genes) were evaluated using random forest classifier to discriminate between the disease and control group (coronavirus disease 2019 [COVID-19] vs. controls, and HP vs. controls). This supervised machine learning approach demonstrated 100% and 87.6% accuracy in differentiating COVID-19 from controls, and HP from controls, respectively. These findings provide new molecular leads that inform COVID-19 and HP diagnostics and therapeutics research and innovation.

Mapping CircRNA-miRNA-mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection.

Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fully explored as yet. The current study aimed to holistically map the regulatory networks driven by SARS-CoV-2 related circRNAs, miRNAs and mRNAs to uncover plausible interactions and interplay amongst them in order to explore possible therapeutic options in SARS-CoV-2 infection. Patient datasets were analyzed systematically in a unified approach to explore circRNA, miRNA, and mRNA expression profiles. CircRNA-miRNA-mRNA network was constructed based on cytokine storm related circRNAs forming a total of 165 circRNA-miRNA-mRNA pairs. This study implies the potential regulatory role of the obtained circRNA-miRNA-mRNA network and proposes that two differentially expressed circRNAs hsa_circ_0080942 and hsa_circ_0080135 might serve as a potential theranostic agents for SARS-CoV-2 infection. Collectively, the results shed light on the functional role of circRNAs as ceRNAs to sponge miRNA and regulate mRNA expression during SARS-CoV-2 infection.

SARS-CoV-2 Mutations Lead to a Decrease in the Number of Tissue-Specific MicroRNA-Binding Regions in the Lung.

RNA interference in vertebrates acts as an antiviral mechanism only in undifferentiated embryonic stem cells and is mediated by microRNAs. In somatic cells, host microRNAs also bind to the genomes of RNA viruses, regulating their translation and replication. It has been shown that viral (+)RNA can evolve under the influence of host cell miRNAs. In more than two years of the pandemic, the SARS-CoV-2 virus has mutated significantly. It is quite possible that some mutations could be retained in the virus genome under the influence of miRNAs produced by alveolar cells. We demonstrated that microRNAs in human lung tissue exert evolutionary pressure on the SARS-CoV-2 genome. Moreover, a significant number of sites of host microRNA binding with the virus genome are located in the NSP3-NSP5 region responsible for autoproteolysis of viral polypeptides.