Targeting hub genes and pathways of innate immune response in COVID-19: A network biology perspective

Identification of immune-related hub genes and potential molecular mechanisms involved in COVID-19 via integrated bioinformatics analysis

COVID-19, caused by the SARS-CoV-2 virus, poses significant health challenges worldwide, particularly due to severe immune-related complications. Understanding the molecular mechanisms and identifying key immune-related genes (IRGs) involved in COVID-19 pathogenesis is critical for developing effective prevention and treatment strategies. This study employed computational tools to analyze biological data (bioinformatics) and a method for inferring causal relationships based on genetic variations, known as Mendelian randomization (MR), to explore the roles of IRGs in COVID-19. We identified differentially expressed genes (DEGs) from datasets available in the Gene Expression Omnibus (GEO), comparing COVID-19 patients with healthy controls. IRGs were sourced from the ImmPort database. We conducted functional enrichment analysis, pathway analysis, and immune infiltration assessments to determine the biological significance of the identified IRGs. A total of 360 common differential IRGs were identified. Among these genes, CD1C, IL1B, and SLP1 have emerged as key IRGs with potential protective effects against COVID-19. Pathway enrichment analysis revealed that CD1C is involved in terpenoid backbone biosynthesis and Th17 cell differentiation, while IL1B is linked to B-cell receptor signaling and the NF-kappa B signaling pathway. Significant correlations were observed between key genes and various immune cells, suggesting that they influence immune cell modulation in COVID-19. This study provides new insights into the immune mechanisms underlying COVID-19, highlighting the crucial role of IRGs in disease progression. These findings suggest that CD1C and IL1B could be potential therapeutic targets. The integrated bioinformatics and MR analysis approach offers a robust framework for further exploring immune responses in COVID-19 patients, as well as for targeted therapy and vaccine development.

Immune Stimulation with Imiquimod to Best Face SARS-CoV-2 Infection and Prevent Long COVID

Through widespread immunization against SARS-CoV-2 prior to or post-infection, a substantial segment of the global population has acquired both humoral and cellular immunity, and there has been a notable reduction in the incidence of severe and fatal cases linked to this virus and accelerated recovery times for those infected. Nonetheless, a significant demographic, comprising around 20% to 30% of the adult population, remains unimmunized due to diverse factors. Furthermore, alongside those recovered from the infection, there is a subset of the population experiencing persistent symptoms referred to as Long COVID. This condition is more prevalent among individuals with underlying health conditions and immune system impairments. Some Long COVID pathologies stem from direct damage inflicted by the viral infection, whereas others arise from inadequate immune system control over the infection or suboptimal immunoregulation. There are differences in the serum cytokines and miRNA profiles between infected individuals who develop severe COVID-19 or Long COVID and those who control adequately the infection. This review delves into the advantages and constraints associated with employing imiquimod in human subjects to enhance the immune response during SARS-CoV-2 immunization. Restoration of the immune system can modify it towards a profile of non-susceptibility to SARS-CoV-2. An adequate immune system has the potential to curb viral propagation, mitigate symptoms, and ameliorate the severe consequences of the infection.

Genomic analysis of severe COVID-19 considering or not asthma comorbidity: GWAS insights from the BQC19 cohort

BACKGROUND

The severity of COVID-19 is influenced by various factors including the presence of respiratory diseases. Studies have indicated a potential relationship between asthma and COVID-19 severity.

OBJECTIVE

This study aimed to conduct a genome-wide association study (GWAS) to identify genetic and clinical variants associated with the severity of COVID-19, both among patients with and without asthma.

METHODS

We analyzed data from 2131 samples sourced from the Biobanque québécoise de la COVID-19 (BQC19), with 1499 samples from patients who tested positive for COVID-19. Among these, 1110 exhibited mild-to-moderate symptoms, 389 had severe symptoms, and 58 had asthma. We conducted a comparative analysis of clinical data from individuals in these three groups and GWAS using a logistic regression model. Phenotypic data analysis resulted in the refined covariates integrated into logistic models for genetic studies.

RESULTS

Considering a significance threshold of 1 × 10-6, seven genetic variants were associated with severe COVID-19. These variants were located proximal to five genes: sodium voltage-gated channel alpha subunit 1 (SCN10A), desmoplakin (DSP), RP1 axonemal microtubule associated (RP1), IGF like family member 1 (IGFL1), and docking protein 5 (DOK5). The GWAS comparing individuals with severe COVID-19 with asthma to those without asthma revealed four genetic variants in transmembrane protein with EGF like and two follistatin like domains 2 (TMEFF2) and huntingtin interacting protein-1 (HIP1) genes.

CONCLUSION

This study provides significant insights into the genetic profiles of patients with severe forms of the disease, whether accompanied by asthma or not. These findings enhance our comprehension of the genetic factors that affect COVID-19 severity.

KEY MESSAGES

Seven genetic variants were associated with the severe form of COVID-19; Four genetic variants were associated with the severe form of COVID-19 in individuals with comorbid asthma; These findings help define the genetic component of the severe form of COVID-19 in relation to asthma as a comorbidity.

Generic model to unravel the deeper insights of viral infections: an empirical application of evolutionary graph coloring in computational network biology

PURPOSE

Graph coloring approach has emerged as a valuable problem-solving tool for both theoretical and practical aspects across various scientific disciplines, including biology. In this study, we demonstrate the graph coloring's effectiveness in computational network biology, more precisely in analyzing protein-protein interaction (PPI) networks to gain insights about the viral infections and its consequences on human health. Accordingly, we propose a generic model that can highlight important hub proteins of virus-associated disease manifestations, changes in disease-associated biological pathways, potential drug targets and respective drugs. We test our model on SARS-CoV-2 infection, a highly transmissible virus responsible for the COVID-19 pandemic. The pandemic took significant human lives, causing severe respiratory illnesses and exhibiting various symptoms ranging from fever and cough to gastrointestinal, cardiac, renal, neurological, and other manifestations.

METHODS

To investigate the underlying mechanisms of SARS-CoV-2 infection-induced dysregulation of human pathobiology, we construct a two-level PPI network and employed a differential evolution-based graph coloring (DEGCP) algorithm to identify critical hub proteins that might serve as potential targets for resolving the associated issues. Initially, we concentrate on the direct human interactors of SARS-CoV-2 proteins to construct the first-level PPI network and subsequently applied the DEGCP algorithm to identify essential hub proteins within this network. We then build a second-level PPI network by incorporating the next-level human interactors of the first-level hub proteins and use the DEGCP algorithm to predict the second level of hub proteins.

RESULTS

We first identify the potential crucial hub proteins associated with SARS-CoV-2 infection at different levels. Through comprehensive analysis, we then investigate the cellular localization, interactions with other viral families, involvement in biological pathways and processes, functional attributes, gene regulation capabilities as transcription factors, and their associations with disease-associated symptoms of these identified hub proteins. Our findings highlight the significance of these hub proteins and their intricate connections with disease pathophysiology. Furthermore, we predict potential drug targets among the hub proteins and identify specific drugs that hold promise in preventing or treating SARS-CoV-2 infection and its consequences.

CONCLUSION

Our generic model demonstrates the effectiveness of DEGCP algorithm in analyzing biological PPI networks, provides valuable insights into disease biology, and offers a basis for developing novel therapeutic strategies for other viral infections that may cause future pandemic.

Network pharmacology and in vivo evidence of the pharmacological mechanism of geniposide in the treatment of atherosclerosis

BACKGROUND

Atherosclerosis (AS) is a fundamental pathological state in various cardiovascular diseases. Geniposide, which is the main active component of Gardenia jasminides, is effective against AS. However, the underlying molecular mechanisms remain unclear. Here, we sought to elucidate them.

METHODS

The targets of AS and geniposide were collected from online public databases. The potential mechanism of Geniposide in treating AS was predicted by constructing a protein-protein interaction (PPI) network and conducting Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses. Hub proteins and core pathways were verified by molecular docking and in vivo experiments. Moreover, the effect of geniposide on AS was assessed by measuring the atherosclerotic plaque area in the thoracic aorta of mice. ApoE-/- mice were used to establish AS models and randomly divided into different groups. Two different doses of geniposide were administered to the mice. Hematoxylin and eosin (HE) staining was performed to evaluate the effects of geniposide on AS. Oil Red O and Sirius Red staining were used to evaluate plaque stability. The protein expression of key markers involved in the signalling pathways was examined using western blotting and immunofluorescence.

RESULTS

A total of 239 active targets, 3418 AS-related disease targets, and 129 overlapping targets were identified. Hub genes were detected, and molecular docking revealed that geniposide strongly interacted with hub proteins (AKT1, VEGFA, CTNNB1, MMP9, and EGFR). Moreover, 109 signalling pathways, including the Rap1 signalling pathway, were identified using enrichment analysis. The results of in vivo experiments demonstrated that geniposide reduced body weight and blood lipid levels, alleviated the formation of atherosclerotic plaques, enhanced plaque stability, and inhibited inflammation, at least partially, by activating the Rap1/PI3K/Akt signalling pathway in ApoE-/- mice.

CONCLUSION

Geniposide can alleviate AS and enhance the stability of atherosclerotic plaques by regulating the Rap1/PI3K/Akt signalling pathway.

Identification of immune-related genes and integrated analysis of immune-cell infiltration in melanoma

OBJECTIVE

This study was conducted to screen out immune-related genes in connection with the prognosis of melanoma, construct a prognosis model and explore the relevant mechanisms.

METHODS AND MATERIALS

1973 genes associated with immune system were derived from the Immport database, and RNA-seq data of melanoma and information of patients were searched from the Xena database. Cox univariate analysis, Lasso analysis and Cox multivariate analysis were used to screen out six genes to construct the model. Then the risk scores were estimated for patients based on our constructed prognosis model. Estimate was used to affirm that the model was about immune infiltration, and CIBERSORT was used to screen out immune cells associated with prognosis. TIDE was applied to predict the efficacy of immunotherapy. Finally, GSE65904 and GSE19234 were used to confirm the effectiveness of the model.

RESULTS

ADCYAP1R1, GPI, NTS might cause poor prognosis while IFITM1, KIR2DL4, LIF were more likely conductive to prognosis of melanoma patients and a model of prognosis was constructed on the basis of these six genes. The effectiveness of the model has been proven by the ROC curve, and the miRNAs targeting the screened genes were found out, suggesting that the immune system might impact on the prognosis of melanoma by T cell CD8+, T cell CD4+ memory and NK cells.

CONCLUSIONS

In this study, the screened six genes were associated with the prognosis of melanoma, which was conductive to clinical prognostic prediction and individualized treatment strategy.

First in vitro and in vivo evaluation of recombinant IL-1β protein as a potential immunomodulator against viral infection in fish

IL-1β is an important proinflammatory cytokine with multifaceted modulatory roles in immune responses. In fish, recombinant IL-1β has been employed in the control of bacterial diseases, while the antiviral mechanisms of IL-1β remain largely unknown, and the efficacy of recombinant IL-1β as an immunomodulator to prevent viral diseases is still not determined. This study evaluated the immunomodulatory effects of recombinant grass carp IL-1β against grass carp reovirus (GCRV) in vitro and in vivo. Firstly, the mature form (Ser111-Lys270) of grass carp IL-1β was identified, and its recombinant protein (designated as rgcIL-1β) was prepared through prokaryotic expression. Then, an in vitro evaluation model for rgcIL-1β activity was established in the CIK cells, with the appropriate concentration (600 ng/mL) and effect time (1 h). In vitro, rgcIL-1β could not only induce the production of proinflammatory cytokines such as IL-1β, IL-6, IL-8, and TNF-α but also a series of antiviral factors including IFN-1, IFN-2, IFN-γ, and ISG15. Mechanistically, transcriptome analysis and western blotting confirmed that rgcIL-1β activated multiple transcriptional factors, including NF-κB, IRF1, IRF3, and IRF8, and the signal pathways associated with inflammatory cytokines and antiviral factors expression. Expectedly, rgcIL-1β treatment significantly inhibited GCRV replication in vitro. In vivo administration of rgcIL-1β via intraperitoneal pre-injection significantly aroused an antiviral response to restrict GCRV replication and intense tissue inflammation in grass carp, demonstrating the immunomodulatory effects of rgcIL-1β. More importantly, rgcIL-1β administrated with 10 ng/g and 1 ng/g could improve the survival rate of grass carp during GCRV infection. This study represents the first time to comprehensively reveal the immunomodulatory and antiviral mechanisms of IL-1β in fish and may also pave the way for further developing recombinant IL-1β as an immunotherapy for the prevention and control of fish viral diseases.

A comprehensive SARS-CoV-2 and COVID-19 review, Part 2: host extracellular to systemic effects of SARS-CoV-2 infection

COVID-19, the disease caused by SARS-CoV-2, has caused significant morbidity and mortality worldwide. The betacoronavirus continues to evolve with global health implications as we race to learn more to curb its transmission, evolution, and sequelae. The focus of this review, the second of a three-part series, is on the biological effects of the SARS-CoV-2 virus on post-acute disease in the context of tissue and organ adaptations and damage. We highlight the current knowledge and describe how virological, animal, and clinical studies have shed light on the mechanisms driving the varied clinical diagnoses and observations of COVID-19 patients. Moreover, we describe how investigations into SARS-CoV-2 effects have informed the understanding of viral pathogenesis and provide innovative pathways for future research on the mechanisms of viral diseases.

In silico identification of microRNAs targeting the PPARα/γ: promising therapeutics for SARS-CoV‑2 infection

The SARS-CoV-2 lifecycle is dependent on the host metabolism machinery. It upregulates the PPARα and PPARγ genes in lipid metabolism, which supports the essential viral replication complex including lipid rafts and palmitoylation of viral protein. The use of PPAR ligands in SARS-CoV-2 infection may have positive effects by preventing cytokine storm and the ensuing inflammatory cascade. The inhibition of PPARα and PPARγ genes may alter the metabolism and may disrupt the lifecycle of SARS-CoV-2 and COVID-19 progression. In the present work, we have identified possible miRNAs targeting PPARα and PPARγ in search of modulators of PPARα and PPARγ genes expression. The identified miRNAs could possibly be viewed as new therapeutic targets against COVID-19 infection.

Hsa-miR-1269a up-regulation fosters the malignant progression of esophageal squamous cell carcinoma via targeting FAM46C

Esophageal squamous cell carcinoma (ESCC) is a malignancy of the alimentary tract resulting in death worldwide. The role and underlying mechanism of hsa-miR-1269a in the progression of ESCC remain unclear. In this study, hsa-miR-1269a was screened by differential expression analysis in TCGA, and its target gene FAM46C was predicted. qRT-PCR was conducted to assay the expression of hsa-miR-1269a and FAM46C in ESCC cells. The results showed that hsa-miR-1269a was upregulated in ESCC tissues and cell lines. Hsa-miR-1269a overexpression stimulated the proliferation, migration, and invasion capacities of ESCC cells, and FAM46C overexpression inhibited these phenotypes. Dual-luciferase assay verified that hsa-miR-1269a could target FAM46C. Next, qRT-PCR and western blot demonstrated that hsa-miR-1269a overexpression downregulated FAM46C. Rescue experiments revealed that hsa-miR-1269a accelerated the malignant progression of ESCC through FAM46C down-regulation. These results indicate that the interaction between hsa-miR-1269a and FAM46C plays a regulatory role in driving the malignant progression of ESCC cells, thereby providing a novel molecular mechanism for understanding ESCC.

SARS-CoV-2 airway infection results in the development of somatosensory abnormalities in a hamster model

Although largely confined to the airways, SARS-CoV-2 infection has been associated with sensory abnormalities that manifest in both acute and chronic phenotypes. To gain insight on the molecular basis of these sensory abnormalities, we used the golden hamster model to characterize and compare the effects of infection with SARS-CoV-2 and influenza A virus (IAV) on the sensory nervous system. We detected SARS-CoV-2 transcripts but no infectious material in the cervical and thoracic spinal cord and dorsal root ganglia (DRGs) within the first 24 hours of intranasal virus infection. SARS-CoV-2-infected hamsters exhibited mechanical hypersensitivity that was milder but prolonged compared with that observed in IAV-infected hamsters. RNA sequencing analysis of thoracic DRGs 1 to 4 days after infection suggested perturbations in predominantly neuronal signaling in SARS-CoV-2-infected animals as opposed to type I interferon signaling in IAV-infected animals. Later, 31 days after infection, a neuropathic transcriptome emerged in thoracic DRGs from SARS-CoV-2-infected animals, which coincided with SARS-CoV-2-specific mechanical hypersensitivity. These data revealed potential targets for pain management, including the RNA binding protein ILF3, which was validated in murine pain models. This work elucidates transcriptomic signatures in the DRGs triggered by SARS-CoV-2 that may underlie both short- and long-term sensory abnormalities.

Activation of the Interferon Pathway in Trophoblast Cells Productively Infected with SARS-CoV-2

SARS-CoV-2 infection during pregnancy has been associated with poor maternal and neonatal outcomes and placental defects. The placenta, which acts as a physical and immunological barrier at the maternal-fetal interface, is not established until the end of the first trimester. Therefore, localized viral infection of the trophoblast compartment early in gestation could trigger an inflammatory response resulting in altered placental function and consequent suboptimal conditions for fetal growth and development. In this study, we investigated the effect of SARS-CoV-2 infection in early gestation placentae using placenta-derived human trophoblast stem cells (TSCs), a novel in vitro model, and their extravillous trophoblast (EVT) and syncytiotrophoblast (STB) derivatives. SARS-CoV-2 was able to productively replicate in TSC-derived STB and EVT, but not undifferentiated TSCs, which is consistent with the expression of SARS-CoV-2 entry host factors, ACE2 (angiotensin-converting enzyme 2) and TMPRSS2 (transmembrane cellular serine protease) in these cells. In addition, both TSC-derived EVT and STB infected with SARS-CoV-2 elicited an interferon-mediated innate immune response. Combined, these results suggest that placenta-derived TSCs are a robust in vitro model to investigate the effect of SARS-CoV-2 infection in the trophoblast compartment of the early placenta and that SARS-CoV-2 infection in early gestation activates the innate immune response and inflammation pathways. Therefore, placental development could be adversely affected by early SARS-CoV-2 infection by directly infecting the developing differentiated trophoblast compartment, posing a higher risk for poor pregnancy outcomes.

Multi-omics characterization of RNA binding proteins reveals disease comorbidities and potential drugs in COVID-19

The COVID-19 has led to a devastating global health crisis, which emphasizes the urgent need to deepen our understanding of the molecular mechanism and identifying potential antiviral drugs. Here, we comprehensively analyzed the transcriptomic and proteomic profiles of 178 COVID-19 patients, ranging from asymptomatic to critically ill. Our analyses found that the RNA binding proteins (RBPs) were likely to be perturbed in infection. Interactome analysis revealed that RBPs interact with virus proteins and the viral interacting RBPs were likely to locate in central regions of human protein-protein interaction network. Functional enrichment analysis revealed that the viral interacting RBPs were likely to be enriched in RNA transport, apoptosis and viral genome replication-related pathways. Based on network proximity analyses of 299 human complex-disease genes and COVID-19-related RBPs in the human interactome, we revealed the significant associations between complex diseases and COVID-19. Network analysis also implicated potential antiviral drugs for treatment of COVID-19. In summary, our integrative characterization of COVID-19 patients may thus help providing evidence regarding pathophysiology and potential therapeutic strategies for COVID-19.

An integrated in-silico Pharmaco-BioInformatics approaches to identify synergistic effects of COVID-19 to HIV patients

BACKGROUND

With high inflammatory states from both COVID-19 and HIV conditions further result in complications. The ongoing confrontation between these two viral infections can be avoided by adopting suitable management measures.

PURPOSE

The aim of this study was to figure out the pharmacological mechanism behind apigenin's role in the synergetic effects of COVID-19 to the progression of HIV patients.

METHOD

We employed computer-aided methods to uncover similar biological targets and signaling pathways associated with COVID-19 and HIV, along with bioinformatics and network pharmacology techniques to assess the synergetic effects of apigenin on COVID-19 to the progression of HIV, as well as pharmacokinetics analysis to examine apigenin's safety in the human body.

RESULT

Stress-responsive, membrane receptor, and induction pathways were mostly involved in gene ontology (GO) pathways, whereas apoptosis and inflammatory pathways were significantly associated in the Kyoto encyclopedia of genes and genomes (KEGG). The top 20 hub genes were detected utilizing the shortest path ranked by degree method and protein-protein interaction (PPI), as well as molecular docking and molecular dynamics simulation were performed, revealing apigenin's strong interaction with hub proteins (MAPK3, RELA, MAPK1, EP300, and AKT1). Moreover, the pharmacokinetic features of apigenin revealed that it is an effective therapeutic agent with minimal adverse effects, for instance, hepatoxicity.

CONCLUSION

Synergetic effects of COVID-19 on the progression of HIV may still be a danger to global public health. Consequently, advanced solutions are required to give valid information regarding apigenin as a suitable therapeutic agent for the management of COVID-19 and HIV synergetic effects. However, the findings have yet to be confirmed in patients, suggesting more in vitro and in vivo studies.

COVID-19 signalome: Potential therapeutic interventions

The COVID-19 pandemic has triggered intensive research and development of drugs and vaccines against SARS-CoV-2 during the last two years. The major success was especially observed with development of vaccines based on viral vectors, nucleic acids and whole viral particles, which have received emergent authorization leading to global mass vaccinations. Although the vaccine programs have made a big impact on COVID-19 spread and severity, emerging novel variants have raised serious concerns about vaccine efficacy. Due to the urgent demand, drug development had originally to rely on repurposing of antiviral drugs developed against other infectious diseases. For both drug and vaccine development the focus has been mainly on SARS-CoV-2 surface proteins and host cell receptors involved in viral attachment and entry. In this review, we expand the spectrum of SARS-CoV-2 targets by investigating the COVID-19 signalome. In addition to the SARS-CoV-2 Spike protein, the envelope, membrane, and nucleoprotein targets have been subjected to research. Moreover, viral proteases have presented the possibility to develop different strategies for the inhibition of SARS-CoV-2 replication and spread. Several signaling pathways involving the renin-angiotensin system, angiotensin-converting enzymes, immune pathways, hypoxia, and calcium signaling have provided attractive alternative targets for more efficient drug development.

Mucosal Gene Expression in Response to SARS-CoV-2 Is Associated with Viral Load

Little is known about the relationships between symptomatic early severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and upper airway mucosal gene expression and immune response. To examine the association of symptomatic SARS-CoV-2 early viral load with upper airway mucosal gene expression, we profiled the host mucosal transcriptome from nasopharyngeal swab samples from 68 adults with symptomatic, mild-to-moderate coronavirus disease 19 (COVID-19). We measured SARS-CoV-2 viral load using reverse transcription-quantitative PCR (RT-qPCR). We then examined the association of SARS-CoV-2 viral load with upper airway mucosal immune response. We detected SARS-CoV-2 in all samples and recovered >80% of the genome from 95% of the samples from symptomatic COVID-19 adults. The respiratory virome was dominated by SARS-CoV-2, with limited codetection of other respiratory viruses, with the human Rhinovirus C being identified in 4 (6%) samples. This limited codetection of other respiratory viral pathogens may be due to the implementation of public health measures, like social distancing and masking practices. We observed a significant positive correlation between SARS-CoV-2 viral load and interferon signaling (OAS2, OAS3, IFIT1, UPS18, ISG15, ISG20, IFITM1, and OASL), chemokine signaling (CXCL10 and CXCL11), and adaptive immune system (IFITM1, CD300E, and SIGLEC1) genes in symptomatic, mild-to-moderate COVID-19 adults, when adjusting for age, sex, and race. Interestingly, the expression levels of most of these genes plateaued at a cycle threshold (C_T) value of ~25. Overall, our data show that the early nasal mucosal immune response to SARS-CoV-2 infection is viral load dependent, potentially modifying COVID-19 outcomes. IMPORTANCE Several prior studies have shown that SARS-CoV-2 viral load can predict the likelihood of disease spread and severity. A higher detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity. However, the relationship between SARS-CoV-2 viral load, airway mucosal gene expression, and immune response remains elusive. We profiled the nasal mucosal transcriptome from nasal samples collected from adults infected with SARS-CoV-2 during spring 2020 with mild-to-moderate symptoms using a comprehensive metatranscriptomics method. We observed a positive correlation between SARS-CoV-2 viral load, interferon signaling, chemokine signaling, and adaptive immune system in adults with COVID-19. Our data suggest that early nasal mucosal immune response to SARS-CoV-2 infection was viral load dependent and may modify COVID-19 outcomes.

Association of CYP24A1 Gene rs6127099 (A > T) Polymorphism with Lower Risk to COVID-19 Infection in Kazakhstan

In December 2019, SARS-CoV-2 was identified in Wuhan, China. Infection by SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), which is characterized by fever, cough, dyspnea, anosmia, and myalgia in many cases. There are discussions about the association of vitamin D levels with COVID-19 severity. However, views are conflicting. The aim of the study was to examine associations of vitamin D metabolism pathway gene polymorphisms with symptomless COVID-19 susceptibility in Kazakhstan. The case-control study examined the association between asymptomatic COVID-19 and vitamin D metabolism pathway gene polymorphisms in 185 participants, who previously reported not having COVID-19, were PCR negative at the moment of data collection, and were not vaccinated. A dominant mutation in rs6127099 (CYP24A1) was found to be protective of asymptomatic COVID-19. Additionally, the G allele of rs731236 TaqI (VDR), dominant mutation in rs10877012 (CYP27B1), recessive rs1544410 BsmI (VDR), and rs7041 (GC) are worth consideration since they were statistically significant in bivariate analysis, although their independent effect was not found in the adjusted multivariate logistic regression model.

Co-expression of fibrotic genes in inflammatory bowel disease; A localized event?

INTRODUCTION

Extracellular matrix turnover, a ubiquitous dynamic biological process, can be diverted to fibrosis. The latter can affect the intestine as a serious complication of Inflammatory Bowel Diseases (IBD) and is resistant to current pharmacological interventions. It embosses the need for out-of-the-box approaches to identify and target molecular mechanisms of fibrosis.

METHODS AND RESULTS

In this study, a novel mRNA sequencing dataset of 22 pairs of intestinal biopsies from the terminal ileum (TI) and the sigmoid of 7 patients with Crohn's disease, 6 with ulcerative colitis and 9 control individuals (CI) served as a validation cohort of a core fibrotic transcriptomic signature (FIBSig), This signature, which was identified in publicly available data (839 samples from patients and healthy individuals) of 5 fibrotic disorders affecting different organs (GI tract, lung, skin, liver, kidney), encompasses 241 genes and the functional pathways which derive from their interactome. These genes were used in further bioinformatics co-expression analyses to elucidate the site-specific molecular background of intestinal fibrosis highlighting their involvement, particularly in the terminal ileum. We also confirmed different transcriptomic profiles of the sigmoid and terminal ileum in our validation cohort. Combining the results of these analyses we highlight 21 core hub genes within a larger single co-expression module, highly enriched in the terminal ileum of CD patients. Further pathway analysis revealed known and novel inflammation-regulated, fibrogenic pathways operating in the TI, such as IL-13 signaling and pyroptosis, respectively.

DISCUSSION

These findings provide a rationale for the increased incidence of fibrosis at the terminal ileum of CD patients and highlight operating pathways in intestinal fibrosis for future evaluation with mechanistic and translational studies.

Network-based approach for targeting human kinases commonly associated with amyotrophic lateral sclerosis and cancer

Background

Amyotrophic Lateral Sclerosis (ALS) is a rare progressive and chronic motor neuron degenerative disease for which at present no cure is available. In recent years, multiple genes encode kinases and other causative agents for ALS have been identified. Kinases are enzymes that show pleiotropic nature and regulate different signal transduction processes and pathways. The dysregulation of kinase activity results in dramatic changes in processes and causes many other human diseases including cancers.

Methods

In this study, we have adopted a network-based system biology approach to investigate the kinase-based molecular interplay between ALS and other human disorders. A list of 62 ALS-associated-kinases was first identified and then we identified the disease associated with them by scanning multiple disease-gene interaction databases to understand the link between the ALS-associated kinases and other disorders.

Results

An interaction network with 36 kinases and 381 different disorders associated with them was prepared, which represents the complexity and the comorbidity associated with the kinases. Further, we have identified 5 miRNAs targeting the majority of the kinases in the disease-causing network. The gene ontology and pathways enrichment analysis of those miRNAs were performed to understand their biological and molecular functions along with to identify the important pathways. We also identified 3 drug molecules that can perturb the disease-causing network by drug repurposing.

Conclusion

This network-based study presented hereby contributes to a better knowledge of the molecular underpinning of comorbidities associated with the kinases associated with the ALS disease and provides the potential therapeutic targets to disrupt the highly complex disease-causing network.

Identification of GINS1 as a therapeutic target in the cancer patients infected with COVID-19: a bioinformatics and system biology approach

BACKGROUND

Coronavirus disease 2019 (COVID-19) caused a series of biological changes in cancer patients which have rendered the original treatment ineffective and increased the difficulty of clinical treatment. However, the clinical treatment for cancer patients infected with COVID-19 is currently unavailable. Since bioinformatics is an effective method to understand undiscovered biological functions, pharmacological targets, and therapeutic mechanisms. The aim of this study was to investigate the influence of COVID-19 infection in cancer patients and to search the potential treatments.

METHODS

Firstly, we obtained the COVID-19-associated genes from seven databases and analyzed the cancer pathogenic genes from Gene Expression Omnibus (GEO) databases, respectively. The Cancer/COVID-19-associated genes were shown by Venn analyses. Moreover, we demonstrated the signaling pathways and biological functions of pathogenic genes in Cancer/COVID-19.

RESULTS

We identified that Go-Ichi-Ni-San complex subunit 1 (GINS1) is the potential therapeutic target in Cancer/COVID-19 by GEPIA. The high expression of GINS1 was not only promoting the development of cancers but also affecting their prognosis. Furthermore, eight potential compounds of Cancer/COVID-19 were identified from CMap and molecular docking analysis.

CONCLUSION

We revealed the GINS1 is a potential therapeutic target in cancer patients infected with COVID-19 for the first time, as COVID-19 will be a severe and prolonged pandemic. However, the findings have not been verified actually cancer patients infected with COVID-19, and further studies are needed to demonstrate the functions of GINS1 and the clinical treatment of the compounds.

Systematic identification of the interventional mechanism of Qingfei Xiaoyan Wan (QFXYW) in treatment of the cytokine storm in acute lung injury using transcriptomics-based system pharmacological analyses

CONTEXT

Acute lung injury (ALI) is a complex, severe inflammation disease with high mortality, and there is no specific and effective treatment for ALI. Qingfei Xiaoyan Wan (QFXYW) has been widely used to treat lung-related diseases for centuries.

OBJECTIVE

This study evaluates the potential effects and elucidates the therapeutic mechanism of QFXYW against LPS induced ALI in mice.

MATERIALS AND METHODS

BALB/c Mice in each group were first orally administered medicines (0.9% saline solution for the control group, 0.5 mg/kg Dexamethasone, or 1.3, 2.6, 5.2 g/kg QFXYW), after 4 h, the groups were injected LPS (1.0 mg/kg) to induce ALI, then the same medicines were administered repeatedly. The transcriptomics-based system pharmacological analyses were applied to screen the hub genes, RT-PCR, ELISA, and protein array assay was applied to verify the predicted hub genes and key pathways.

RESULTS

QFXYW significantly decreased the number of leukocytes from (6.34 ± 0.51) × 10⁵/mL to (4.01 ± 0.11) × 10⁵/mL, accompanied by the neutrophil from (1.41 ± 0.19) × 10⁵/mL to (0.77 ± 0.10) × 10⁵/mL in bronchoalveolar lavage fluid (BALF). Based on Degree of node connection (Degree) and BottleNeck (BN), important parameters of network topology, the protein-protein interaction (PPI) network screened hub genes, including IL-6, TNF-α, CCL2, TLR2, CXCL1, and MMP-9. The results of RT-PCR, ELISA, and protein chip assay revealed that QFXYW could effectively inhibit ALI via multiple key targets and the cytokine-cytokine signalling pathway.

CONCLUSIONS

This study showed that QFXYW decreased the number of leukocytes and neutrophils by attenuating inflammatory response, which provides an important basis for the use of QFXYW in the treatment of ALI.

A machine learning approach utilizing DNA methylation as an accurate classifier of COVID-19 disease severity

Since the onset of the COVID-19 pandemic, increasing cases with variable outcomes continue globally because of variants and despite vaccines and therapies. There is a need to identify at-risk individuals early that would benefit from timely medical interventions. DNA methylation provides an opportunity to identify an epigenetic signature of individuals at increased risk. We utilized machine learning to identify DNA methylation signatures of COVID-19 disease from data available through NCBI Gene Expression Omnibus. A training cohort of 460 individuals (164 COVID-19-infected and 296 non-infected) and an external validation dataset of 128 individuals (102 COVID-19-infected and 26 non-COVID-associated pneumonia) were reanalyzed. Data was processed using ChAMP and beta values were logit transformed. The JADBio AutoML platform was leveraged to identify a methylation signature associated with severe COVID-19 disease. We identified a random forest classification model from 4 unique methylation sites with the power to discern individuals with severe COVID-19 disease. The average area under the curve of receiver operator characteristic (AUC-ROC) of the model was 0.933 and the average area under the precision-recall curve (AUC-PRC) was 0.965. When applied to our external validation, this model produced an AUC-ROC of 0.898 and an AUC-PRC of 0.864. These results further our understanding of the utility of DNA methylation in COVID-19 disease pathology and serve as a platform to inform future COVID-19 related studies.

Values of OAS gene family in the expression signature, immune cell infiltration and prognosis of human bladder cancer

BACKGROUND

Bladder cancer (BLCA) is one of the most common genitourinary malignancies in the world, but its pathogenic genes have not been fully identified and the treatment outcomes are still unsatisfactory. Although the members of 2', 5'-oligoadenylate synthetase (OAS) gene family are known involved in some tumorous biological processes, the roles of the OAS gene family in BLCA are still undetermined.

METHODS

By combining vast bioinformatic datasets analyses of BLCA and the experimental verification on clinical BLCA specimen, we identified the expressions and biological functions of OAS gene family members in BLCA with comparison to normal bladder tissues.

RESULTS

The expression levels of OAS gene family members were higher in BLCA than in normal bladder tissues. The expression levels of most OAS genes had correlations with genomic mutation and methylation, and with the infiltration levels of CD4 + T cells, CD8 + T cells, neutrophils, and dendritic cells in the microenvironment of BLCA. In addition, high expressions of OAS1, OAS2, OAS3, and OASL predicted better overall survival in BLCA patients.

CONCLUSIONS

The highly expressed OAS genes in BLCA can reflect immune cells infiltration in the tumor microenvironment and predict the better overall survival of BLCA, and thus may be considered as a signature of BLCA. The study provides new insights into the diagnosis, treatment, and prognosis of BLCA.

Mucosal gene expression in response to SARS-CoV-2 is associated with early viral load

Little is known about the relationships between symptomatic early-time SARS-CoV-2 viral load and upper airway mucosal gene expression and immune response. To examine the association of symptomatic SARS-CoV-2 early viral load with upper airway mucosal gene expression, we profiled the host mucosal transcriptome from nasopharyngeal swab samples from 68 adults with symptomatic, mild-to-moderate COVID-19. We measured SARS-CoV-2 viral load using qRT-PCR. We then examined the association of SARS-CoV-2 viral load with upper airway mucosal immune response. We detected SARS-CoV-2 in all samples and recovered >80% of the genome from 85% of the samples from symptomatic COVID-19 adults. The respiratory virome was dominated by SARS-CoV-2, with limited co-detection of common respiratory viruses i.e., only the human Rhinovirus (HRV) being identified in 6% of the samples. We observed a significant positive correlation between SARS-CoV-2 viral load and interferon signaling (OAS2, OAS3, IFIT1, UPS18, ISG15, ISG20, IFITM1, and OASL), chemokine signaling (CXCL10 and CXCL11), and adaptive immune system (IFITM1, CD300E, and SIGLEC1) genes in symptomatic, mild-to-moderate COVID-19 adults, when adjusted for age, sex and race. Interestingly, the expression levels of most of these genes plateaued at a CT value of ~25. Overall, our data shows that early nasal mucosal immune response to SARS-CoV-2 infection is viral load dependent, which potentially could modify COVID-19 outcomes.

AUTHOR SUMMARY

Several prior studies have shown that SARS-CoV-2 viral load can predict the likelihood of disease spread and severity. A higher detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity. However, the relationship between SARS-CoV-2 viral load and airway mucosal gene expression and immune response remains elusive. We profiled the nasal mucosal transcriptome from nasal samples collected from adults infected with SARS-CoV-2 during Spring 2020 with mild-to-moderate symptoms using a comprehensive metatranscriptomics method. We observed a positive correlation between SARS-CoV-2 viral load with interferon signaling, chemokine signaling, and adaptive immune system in adults with COVID-19. Our data suggest that early nasal mucosal immune response to SARS-CoV-2 infection was viral load-dependent and may modify COVID-19 outcomes.

SARS-CoV-2 Airway Infection Results in Time-dependent Sensory Abnormalities in a Hamster Model

Despite being largely confined to the airways, SARS-CoV-2 infection has been associated with sensory abnormalities that manifest in both acute and long-lasting phenotypes. To gain insight on the molecular basis of these sensory abnormalities, we used the golden hamster infection model to characterize the effects of SARS-CoV-2 versus Influenza A virus (IAV) infection on the sensory nervous system. Efforts to detect the presence of virus in the cervical/thoracic spinal cord and dorsal root ganglia (DRGs) demonstrated detectable levels of SARS-CoV-2 by quantitative PCR and RNAscope uniquely within the first 24 hours of infection. SARS-CoV-2-infected hamsters demonstrated mechanical hypersensitivity during acute infection; intriguingly, this hypersensitivity was milder, but prolonged when compared to IAV-infected hamsters. RNA sequencing (RNA-seq) of thoracic DRGs from acute infection revealed predominantly neuron-biased signaling perturbations in SARS-CoV-2-infected animals as opposed to type I interferon signaling in tissue derived from IAV-infected animals. RNA-seq of 31dpi thoracic DRGs from SARS-CoV-2-infected animals highlighted a uniquely neuropathic transcriptomic landscape, which was consistent with substantial SARS-CoV-2-specific mechanical hypersensitivity at 28dpi. Ontology analysis of 1, 4, and 30dpi RNA-seq revealed novel targets for pain management, such as ILF3. Meta-analysis of all SARS-CoV-2 RNA-seq timepoints against preclinical pain model datasets highlighted both conserved and unique pro-nociceptive gene expression changes following infection. Overall, this work elucidates novel transcriptomic signatures triggered by SARS-CoV-2 that may underlie both short- and long-term sensory abnormalities while also highlighting several therapeutic targets for alleviation of infection-induced hypersensitivity.

One Sentence Summary

SARS-CoV-2 infection results in an interferon-associated transcriptional response in sensory tissues underlying time-dependent hypersensitivity.

Meta-Data Analysis to Explore the Hub of the Hub-Genes That Influence SARS-CoV-2 Infections Highlighting Their Pathogenetic Processes and Drugs Repurposing

The pandemic of SARS-CoV-2 infections is a severe threat to human life and the world economic condition. Although vaccination has reduced the outspread, but still the situation is not under control because of the instability of RNA sequence patterns of SARS-CoV-2, which requires effective drugs. Several studies have suggested that the SARS-CoV-2 infection causing hub differentially expressed genes (Hub-DEGs). However, we observed that there was not any common hub gene (Hub-DEGs) in our analyses. Therefore, it may be difficult to take a common treatment plan against SARS-CoV-2 infections globally. The goal of this study was to examine if more representative Hub-DEGs from published studies by means of hub of Hub-DEGs (hHub-DEGs) and associated potential candidate drugs. In this study, we reviewed 41 articles on transcriptomic data analysis of SARS-CoV-2 and found 370 unique hub genes or studied genes in total. Then, we selected 14 more representative Hub-DEGs (AKT1, APP, CXCL8, EGFR, IL6, INS, JUN, MAPK1, STAT3, TNF, TP53, UBA52, UBC, VEGFA) as hHub-DEGs by their protein-protein interaction analysis. Their associated biological functional processes, transcriptional, and post-transcriptional regulatory factors. Then we detected hHub-DEGs guided top-ranked nine candidate drug agents (Digoxin, Avermectin, Simeprevir, Nelfinavir Mesylate, Proscillaridin, Linifanib, Withaferin, Amuvatinib, Atazanavir) by molecular docking and cross-validation for treatment of SARS-CoV-2 infections. Therefore, the findings of this study could be useful in formulating a common treatment plan against SARS-CoV-2 infections globally.

The SARS-CoV-2 targeted human RNA binding proteins network biology to investigate COVID-19 associated manifestations

The global coronavirus disease 2019 (COVID-19) pandemic caused by the SARS-CoV-2 virus has had unprecedented social and economic ramifications. Identifying targets for drug repurposing could be an effective means to present new and fast treatments. Furthermore, the risk of morbidity and mortality from COVID-19 goes up when there are coexisting medical conditions, however, the underlying mechanisms remain unclear. In the current study, we have adopted a network-based systems biology approach to investigate the RNA binding proteins (RBPs)-based molecular interplay between COVID-19, various human cancers, and neurological disorders. The network based on RBPs commonly involved in the three disease conditions consisted of nine RBPs connecting 10 different cancer types, 22 brain disorders, and COVID-19 infection, ultimately hinting at the comorbidities and complexity of COVID-19. Further, we underscored five miRNAs with reported antiviral properties that target all of the nine shared RBPs and are thus therapeutically valuable. As a strategy to improve the clinical conditions in comorbidities associated with COVID-19, we propose perturbing the shared RBPs by drug repurposing. The network-based analysis presented hereby contributes to a better knowledge of the molecular underpinnings of the comorbidities associated with COVID-19.

Bioinformatics analysis of potential common pathogenic mechanisms for COVID-19 infection and primary Sjogren’s syndrome

Background

Accumulating evidence has revealed that the prevalence of Coronavirus 2019 (COVID-19) was significantly higher in patients with primary Sjogren’s syndrome (pSS) compared to the general population. However, the mechanism remains incompletely elucidated. This study aimed to further investigate the molecular mechanisms underlying the development of this complication.

Methods

The gene expression profiles of COVID-19 (GSE157103) and pSS (GSE40611) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) for pSS and COVID-19, functional annotation, protein-protein interaction (PPI) network, module construction and hub gene identification were performed. Finally, we constructed transcription factor (TF)-gene regulatory network and TF-miRNA regulatory network for hub genes.

Results

A total of 40 common DEGs were selected for subsequent analyses. Functional analyses showed that cellular components and metabolic pathways collectively participated in the development and progression of pSS and COVID-19. Finally, 12 significant hub genes were identified using the cytoHubba plugin, including CMPK2, TYMS, RRM2, HERC5, IFI44L, IFI44, IFIT2, IFIT1, IFIT3, MX1, CDCA2 and TOP2A, which had preferable values as diagnostic markers for COVID-19 and pSS.

Conclusions

Our study reveals common pathogenesis of pSS and COVID-19. These common pathways and pivotal genes may provide new ideas for further mechanistic studies.

Identification of COVID-19-Specific Immune Markers Using a Machine Learning Method

Notably, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a tight relationship with the immune system. Human resistance to COVID-19 infection comprises two stages. The first stage is immune defense, while the second stage is extensive inflammation. This process is further divided into innate and adaptive immunity during the immune defense phase. These two stages involve various immune cells, including CD4⁺ T cells, CD8⁺ T cells, monocytes, dendritic cells, B cells, and natural killer cells. Various immune cells are involved and make up the complex and unique immune system response to COVID-19, providing characteristics that set it apart from other respiratory infectious diseases. In the present study, we identified cell markers for differentiating COVID-19 from common inflammatory responses, non-COVID-19 severe respiratory diseases, and healthy populations based on single-cell profiling of the gene expression of six immune cell types by using Boruta and mRMR feature selection methods. Some features such as IFI44L in B cells, S100A8 in monocytes, and NCR2 in natural killer cells are involved in the innate immune response of COVID-19. Other features such as ZFP36L2 in CD4⁺ T cells can regulate the inflammatory process of COVID-19. Subsequently, the IFS method was used to determine the best feature subsets and classifiers in the six immune cell types for two classification algorithms. Furthermore, we established the quantitative rules used to distinguish the disease status. The results of this study can provide theoretical support for a more in-depth investigation of COVID-19 pathogenesis and intervention strategies.

Immune features of COVID-19 convalescent individuals revealed by a single-cell RNA sequencing

It remains unclear whether immune responses following natural infection can be sustained or potentially prove critical for long-term immune protection against SARS-CoV-2 reinfection. Here, we systematically mapped the phenotypic landscape of SARS-CoV-2-specific immune responses in peripheral blood samples of convalescent patients with COVID-19 by single-cell RNA sequencing. The relative percentage of the CD8 + effector memory subset was increased in both convalescent moderate and severe cases, but NKT-CD160 and marginal zone B clusters were decreased. Innate immune responses were attenuated reflected by decreased expression of genes involved in interferon-gamma, leukocyte migration and neutrophil mediated immune response in convalescent COVID-19 patients. Functions of T cell were strengthened in convalescent COVID-19 patients by clear endorsement of increased expression of genes involved in biological processes of regulation of T cell activation, differentiation and cell-cell adhesion. In addition, T cell mediated immune responses were enhanced with remarkable clonal expansions of TCR and increased transition of CD4 + effector memory and CD8 + effector-GNLY in severe subjects. B cell immune responses displayed complicated and dualfunctions during convalescence of COVID-19, providing a novel mechanism that B cell activation was observed especially in moderate while humoral immune response was weakened. Interestingly, HLA class I genes displayed downregulation while HLA class II genes upregulation in both T and B cell subsets in convalescent individuals. Our results showed that innate immunity was declined but SARS-CoV-2-specific T cell responses were retained even strengthened whereas complicated and dualfunctions of B cells, including declined humoral immunity were presented at several months following infections.

XGBoost-Based Feature Learning Method for Mining COVID-19 Novel Diagnostic Markers

In December 2019, an outbreak of novel coronavirus pneumonia spread over Wuhan, Hubei Province, China, which then developed into a significant global health public event, giving rise to substantial economic losses. We downloaded throat swab expression profiling data of COVID-19 positive and negative patients from the Gene Expression Omnibus (GEO) database to mine novel diagnostic biomarkers. XGBoost was used to construct the model and select feature genes. Subsequently, we constructed COVID-19 classifiers such as MARS, KNN, SVM, MIL, and RF using machine learning methods. We selected the KNN classifier with the optimal MCC value from these classifiers using the IFS method to identify 24 feature genes. Finally, we used principal component analysis to classify the samples and found that the 24 feature genes could effectively be used to classify COVID-19-positive and negative patients. Additionally, we analyzed the possible biological functions and signaling pathways in which the 24 feature genes were involved by GO and KEGG enrichment analyses. The results demonstrated that these feature genes were primarily enriched in biological functions such as viral transcription and viral gene expression and pathways such as Coronavirus disease-COVID-19. In summary, the 24 feature genes we identified were highly effective in classifying COVID-19 positive and negative patients, which could serve as novel markers for COVID-19.

Immune-Related Protein Interaction Network in Severe COVID-19 Patients toward the Identification of Key Proteins and Drug Repurposing

Coronavirus disease 2019 (COVID-19) is still an active global public health issue. Although vaccines and therapeutic options are available, some patients experience severe conditions and need critical care support. Hence, identifying key genes or proteins involved in immune-related severe COVID-19 is necessary to find or develop the targeted therapies. This study proposed a novel construction of an immune-related protein interaction network (IPIN) in severe cases with the use of a network diffusion technique on a human interactome network and transcriptomic data. Enrichment analysis revealed that the IPIN was mainly associated with antiviral, innate immune, apoptosis, cell division, and cell cycle regulation signaling pathways. Twenty-three proteins were identified as key proteins to find associated drugs. Finally, poly (I:C), mitomycin C, decitabine, gemcitabine, hydroxyurea, tamoxifen, and curcumin were the potential drugs interacting with the key proteins to heal severe COVID-19. In conclusion, IPIN can be a good representative network for the immune system that integrates the protein interaction network and transcriptomic data. Thus, the key proteins and target drugs in IPIN help to find a new treatment with the use of existing drugs to treat the disease apart from vaccination and conventional antiviral therapy.

Transcriptome Meta-Analysis Associated Targeting Hub Genes and Pathways of Drought and Salt Stress Responses in Cotton (Gossypium hirsutum): A Network Biology Approach

Abiotic stress tolerance is an intricate feature controlled through several genes and networks in the plant system. In abiotic stress, salt, and drought are well known to limit cotton productivity. Transcriptomics meta-analysis has arisen as a robust method to unravel the stress-responsive molecular network in crops. In order to understand drought and salt stress tolerance mechanisms, a meta-analysis of transcriptome studies is crucial. To confront these issues, here, we have given details of genes and networks associated with significant differential expression in response to salt and drought stress. The key regulatory hub genes of drought and salt stress conditions have notable associations with functional drought and salt stress-responsive (DSSR) genes. In the network study, nodulation signaling pathways 2 (NSP2), Dehydration-responsive element1 D (DRE1D), ethylene response factor (ERF61), cycling DOF factor 1 (CDF1), and tubby like protein 3 (TLP3) genes in drought and tubby like protein 1 (TLP1), thaumatin-like proteins (TLP), ethylene-responsive transcription factor ERF109 (EF109), ETS-Related transcription Factor (ELF4), and Arabidopsis thaliana homeodomain leucine-zipper gene (ATHB7) genes in salt showed the significant putative functions and pathways related to providing tolerance against drought and salt stress conditions along with the significant expression values. These outcomes provide potential candidate genes for further in-depth functional studies in cotton, which could be useful for the selection of an improved genotype of Gossypium hirsutum against drought and salt stress conditions.

Causal Association and Shared Genetics Between Asthma and COVID-19

Objectives

Recent studies suggest that asthma may have a protective effect on COVID-19.We aimed to investigate the causality between asthma and two COVID-19 outcomes and explore the mechanisms underlining this connection.

Methods

Summary results of GWAS were used for the analyses, including asthma (88,486 cases and 447,859 controls), COVID-19 hospitalization (6,406 hospitalized COVID-19 cases and 902,088 controls), and COVID-19 infection (14,134 COVID-19 cases and 1,284,876 controls). The Mendelian randomization (MR) analysis was performed to evaluate the causal effects of asthma on the two COVID-19 outcomes. A cross-trait meta-analysis was conducted to analyze genetic variants within two loci shared by COVID-19 hospitalization and asthma.

Results

Asthma is associated with decreased risk both for COVID-19 hospitalization (odds ratio (OR): 0.70, 95% confidence interval (CI): 0.70-0.99) and for COVID-19 infection (OR: 0.83, 95%CI: 0.51-0.95). Asthma and COVID-19 share two genome-wide significant genes, including ABO at the 9q34.2 region and OAS2 at the 12q24.13 region. The meta-analysis revealed that ABO and ATXN2 contain variants with pleiotropic effects on both COVID-19 and asthma.

Conclusion

In conclusion, our results suggest that genetic liability to asthma is associated with decreased susceptibility to SARS-CoV-2 and to severe COVID-19 disease, which may be due to the protective effects of ongoing inflammation and, possibly, related compensatory responses against COVID-19 in its early stage.

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the most severe global pandemic due to its high pathogenicity and death rate starting from the end of 2019. Though there are some vaccines available against SAER-CoV-2 infections, we are worried about their effectiveness, due to its unstable sequence patterns. Therefore, beside vaccines, globally effective supporting drugs are also required for the treatment against SARS-CoV-2 infection. To explore commonly effective repurposable drugs for the treatment against different variants of coronavirus infections, in this article, an attempt was made to explore host genomic biomarkers guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches. At first, we identified 138 differentially expressed genes (DEGs) between SARS-CoV-1 infected and control samples by analyzing high throughput gene-expression profiles to select drug target key receptors. Then we identified top-ranked 11 key DEGs (SMAD4, GSK3B, SIRT1, ATM, RIPK1, PRKACB, MED17, CCT2, BIRC3, ETS1 and TXN) as hub genes (HubGs) by protein-protein interaction (PPI) network analysis of DEGs highlighting their functions, pathways, regulators and linkage with other disease risks that may influence SARS-CoV-1 infections. The DEGs-set enrichment analysis significantly detected some crucial biological processes (immune response, regulation of angiogenesis, apoptotic process, cytokine production and programmed cell death, response to hypoxia and oxidative stress), molecular functions (transcription factor binding and oxidoreductase activity) and pathways (transcriptional mis-regulation in cancer, pathways in cancer, chemokine signaling pathway) that are associated with SARS-CoV-1 infections as well as SARS-CoV-2 infections by involving HubGs. The gene regulatory network (GRN) analysis detected some transcription factors (FOXC1, GATA2, YY1, FOXL1, TP53 and SRF) and micro-RNAs (hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-106b-5p, hsa-mir-34a-5p and hsa-mir-19b-3p) as the key transcriptional and post- transcriptional regulators of HubGs, respectively. We also detected some chemicals (Valproic Acid, Cyclosporine, Copper Sulfate and arsenic trioxide) that may regulates HubGs. The disease-HubGs interaction analysis showed that our predicted HubGs are also associated with several other diseases including different types of lung diseases. Then we considered 11 HubGs mediated proteins and their regulatory 6 key TFs proteins as the drug target proteins (receptors) and performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 anti-viral drugs out of 3410. We found Rapamycin, Tacrolimus, Torin-2, Radotinib, Danoprevir, Ivermectin and Daclatasvir as the top-ranked 7 candidate-drugs with respect to our proposed target proteins for the treatment against SARS-CoV-1 infections. Then, we validated these 7 candidate-drugs against the already published top-ranked 11 target proteins associated with SARS-CoV-2 infections by molecular docking simulation and found their significant binding affinity scores with our proposed candidate-drugs. Finally, we validated all of our findings by the literature review. Therefore, the proposed candidate-drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections with comorbidities, since the proposed HubGs are also associated with several comorbidities.

Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing

The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.

Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome

The molecular mechanisms underlying the pathogenesis of COVID-19 have not been fully discovered. This study aims to decipher potentially hidden parts of the pathogenesis of COVID-19, potential novel drug targets, and identify potential drug candidates. Two gene expression profiles were analyzed, and overlapping differentially expressed genes (DEGs) were selected for which top enriched transcription factors and kinases were identified, and pathway analysis was performed. Protein-protein interaction (PPI) of DEGs was constructed, hub genes were identified, and module analysis was also performed. DGIdb database was used to identify drugs for the potential targets (hub genes and the most enriched transcription factors and kinases for DEGs). A drug-potential target network was constructed, and drugs were ranked according to the degree. L1000FDW was used to identify drugs that can reverse transcriptional profiles of COVID-19. We identified drugs currently in clinical trials, others predicted by different methods, and novel potential drug candidates Entrectinib, Omeprazole, and Exemestane for combating COVID-19. Besides the well-known pathogenic pathways, it was found that axon guidance is a potential pathogenic pathway. Sema7A, which may exacerbate hypercytokinemia, is considered a potential novel drug target. Another potential novel pathway is related to TINF2 overexpression, which may induce potential telomere dysfunction and damage DNA that may exacerbate lung fibrosis. This study identified new potential insights regarding COVID-19 pathogenesis and treatment, which might help us improve our understanding of the mechanisms of COVID-19.

HeberNasvac, a Therapeutic Vaccine for Chronic Hepatitis B, Stimulates Local and Systemic Markers of Innate Immunity: Potential Use in SARS-CoV-2 Postexposure Prophylaxis

Introduction

More than 180 million people have been infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and more than 4 million coronavirus disease-2019 (COVID-19) patients have died in 1.5 years of the pandemic. A novel therapeutic vaccine (NASVAC) has shown to be safe and to have immunomodulating and antiviral properties against chronic hepatitis B (CHB).

Materials and methods

A phase I/II, open-label controlled and randomized clinical trial of NASVAC as a postexposure prophylaxis treatment was designed with the primary aim of assessing the local and systemic immunomodulatory effect of NASVAC in a cohort of suspected and SARS-CoV-2 risk-contact patients. A total of 46 patients, of both sexes, 60 years or older, presenting with symptoms of COVID-19 were enrolled in the study. Patients received NASVAC (100 μg per Ag per dose) via intranasal at days 1, 7, and 14 and sublingual, daily for 14 days.

Results and discussion

The present study detected an increased expression of toll-like receptors (TLR)-related genes in nasopharyngeal tonsils, a relevant property considering these are surrogate markers of SARS protection in the mice model of lethal infection. The HLA-class II increased their expression in peripheral blood mononuclear cell's (PBMC's) monocytes and lymphocytes, which is an attractive property taking into account the functional impairment of innate immune cells from the periphery of COVID-19-infected subjects. NASVAC was safe and well tolerated by the patients with acute respiratory infections and evidenced a preliminary reduction in the number of days with symptoms that needs to be confirmed in larger studies.

Conclusions

Our data justify the use of NASVAC as preemptive therapy or pre-/postexposure prophylaxis of SARS-CoV-2 and acute respiratory infections in general. The use of NASVAC or their active principles has potential as immunomodulatory prophylactic therapies in other antiviral settings like dengue as well as in malignancies like hepatocellular carcinoma where these markers have shown relation to disease progression.

How to cite this article

Fleites YA, Aguiar J, Cinza Z, et al. HeberNasvac, a Therapeutic Vaccine for Chronic Hepatitis B, Stimulates Local and Systemic Markers of Innate Immunity: Potential Use in SARS-CoV-2 Postexposure Prophylaxis. Euroasian J Hepato-Gastroenterol 2021;11(2):59–70.

Insights into the SARS-CoV-2-Mediated Alteration in the Stress Granule Protein Regulatory Networks in Humans

The rapidly and constantly evolving coronavirus, SARS-CoV-2, imposes a great threat to human health causing severe lung disease and significant mortality. Cytoplasmic stress granules (SGs) exert anti-viral activities due to their involvement in translation inhibition and innate immune signaling. SARS-CoV-2 sequesters important SG nucleator proteins and impairs SG formation, thus evading the host response for efficient viral replication. However, the significance of SGs in COVID-19 infection remains elusive. In this study, we utilize a protein-protein interaction network approach to systematically dissect the crosstalk of human post-translational regulatory networks governed by SG proteins due to SARS-CoV-2 infection. We uncovered that 116 human SG proteins directly interact with SARS-CoV-2 proteins and are involved in 430 different brain disorders including COVID-19. Further, we performed gene set enrichment analysis to identify the drugs against three important key SG proteins (DYNC1H1, DCTN1, and LMNA) and also looked for potential microRNAs (miRNAs) targeting these proteins. We identified bexarotene as a potential drug molecule and miRNAs, hsa-miR-615-3p, hsa-miR-221-3p, and hsa-miR-124-3p as potential candidates for the treatment of COVID-19 and associated manifestations.

Drug repurposing for coronavirus (SARS-CoV-2) based on gene co-expression network analysis

Severe acute respiratory syndrome (SARS) is a highly contagious viral respiratory illness. This illness is spurred on by a coronavirus known as SARS-associated coronavirus (SARS-CoV). SARS was first detected in Asia in late February 2003. The genome of this virus is very similar to the SARS-CoV-2. Therefore, the study of SARS-CoV disease and the identification of effective drugs to treat this disease can be new clues for the treatment of SARS-Cov-2. This study aimed to discover novel potential drugs for SARS-CoV disease in order to treating SARS-Cov-2 disease based on a novel systems biology approach. To this end, gene co-expression network analysis was applied. First, the gene co-expression network was reconstructed for 1441 genes, and then two gene modules were discovered as significant modules. Next, a list of miRNAs and transcription factors that target gene co-expression modules' genes were gathered from the valid databases, and two sub-networks formed of transcription factors and miRNAs were established. Afterward, the list of the drugs targeting obtained sub-networks' genes was retrieved from the DGIDb database, and two drug-gene and drug-TF interaction networks were reconstructed. Finally, after conducting different network analyses, we proposed five drugs, including FLUOROURACIL, CISPLATIN, SIROLIMUS, CYCLOPHOSPHAMIDE, and METHYLDOPA, as candidate drugs for SARS-CoV-2 coronavirus treatment. Moreover, ten miRNAs including miR-193b, miR-192, miR-215, miR-34a, miR-16, miR-16, miR-92a, miR-30a, miR-7, and miR-26b were found to be significant miRNAs in treating SARS-CoV-2 coronavirus.

Genomics-guided targeting of stress granule proteins G3BP1/2 to inhibit SARS-CoV-2 propagation

SARS-CoV-2 nucleocapsid (N) protein undergoes RNA-induced phase separation (LLPS) and sequesters the host key stress granule (SG) proteins, Ras-GTPase-activating protein SH3-domain-binding protein 1 and 2 (G3BP1 and G3BP2) to inhibit SG formation. This will allow viral packaging and propagation in host cells. Based on a genomic-guided meta-analysis, here we identify upstream regulatory elements modulating the expression of G3BP1 and G3BP2 (collectively called G3BP1/2). Using this strategy, we have identified FOXA1, YY1, SYK, E2F-1, and TGFBR2 as activators and SIN3A, SRF, and AKT-1 as repressors of G3BP1/2 genes. Panels of the activators and repressors were then used to identify drugs that change their gene expression signatures. Two drugs, imatinib, and decitabine have been identified as putative modulators of G3BP1/2 genes and their regulators, suggesting their role as COVID-19 mitigation agents. Molecular docking analysis suggests that both drugs bind to G3BP1/2 with a much higher affinity than the SARS-CoV-2 N protein. This study reports imatinib and decitabine as candidate drugs against N protein and G3BP1/2 protein.

Review on oxidative stress relation on COVID-19: Biomolecular and bioanalytical approach

COVID-19 disease has put life of people in stress worldwide from many aspects. Since the virus has mutated in absolutely short period of time the challenge to find a suitable vaccine has become harder. Infection to COVID-19, especially at severe life threatening states is highly dependent on the strength of the host immune system. This system is partially dependent on the balance between oxidative stress and antioxidant. Besides, this virus still has unknown mechanism of action companied by a probable commune period. From another hand, some reactive oxygen species (ROS) levels can be helpful on the state determination of the disease. Thus it could be possible to use modern bioanalytical techniques for their detection and determination, which could indicate the disease state at the golden time window since they have the potential to show whether specific DNA, RNA, enzymes and proteins are affected. This also could be used as a preclude study or a reliable pathway to define the best optimized time of cure beside effective medical actions. Herein, some ROS and their relation with SARS-CoV-2 virus have been considered. In addition, modern bioelectroanalytical techniques on this approach from quantitative and qualitative points of view have been reviewed.

Association of Asthma and Rhinitis with Epigenetics of Coronavirus Related Genes

Introduction:

Susceptibility factors for coronavirus disease 2019 (COVID-19) include sex and medical conditions such as asthma and rhinitis. DNA methylation (DNAm) is associated with asthma, rhinitis, and several viruses. We examined associations of asthma/rhinitis with DNAm at CpGs located on coronavirus related genes, and if these associations were sex-specific.

Methods:

In total, n = 242 subjects aged 26 years from the Isle of Wight Birth Cohort were included in the study. Linear regressions were used to examine sex specific and non-specific associations of DNAm at CpGs on coronavirus related genes with asthma/rhinitis status. Associations of DNAm with gene expression in blood were assessed for functional relevance of identified CpGs.

Results:

Statistically significant interaction effects of asthma or rhinitis with sex were identified at 40 CpGs for asthma and 27 CpGs for rhinitis. At 21 CpGs, DNAm was associated with asthma, and at 45 CpGs with rhinitis, regardless of sex. Assessment of functional relevance of the identified CpGs indicated a potential of epigenetic regulatory functionality on gene activity at 14 CpGs for asthma and 17 CpGs for rhinitis, and of those 6 CpGs for asthma and 7 CpGs for rhinitis were likely to be sex-specific.

Conclusion:

Subjects with asthma/rhinitis may have altered susceptibility to COVID-19 due to changes in their DNAm associated with these conditions. Sex specificity on association of asthma/rhinitis with DNAm at certain CpGs, and on the association of DNAm at asthma/rhinitis-linked CpGs with gene expression have the potential to explain the reported sex-specificity in COVID-19 morbidity and mortality.

Identification of Novel COVID-19 Biomarkers by Multiple Feature Selection Strategies

Coronavirus disease 2019 (COVID-19) arising from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in a global pandemic since its first report in December 2019. So far, SARS-CoV-2 nucleic acid detection has been deemed as the golden standard of COVID-19 diagnosis. However, this detection method often leads to false negatives, thus triggering missed COVID-19 diagnosis. Therefore, it is urgent to find new biomarkers to increase the accuracy of COVID-19 diagnosis. To explore new biomarkers of COVID-19 in this study, expression profiles were firstly accessed from the GEO database. On this basis, 500 feature genes were screened by the minimum-redundancy maximum-relevancy (mRMR) feature selection method. Afterwards, the incremental feature selection (IFS) method was used to choose a classifier with the best performance from different feature gene-based support vector machine (SVM) classifiers. The corresponding 66 feature genes were set as the optimal feature genes. Lastly, the optimal feature genes were subjected to GO functional enrichment analysis, principal component analysis (PCA), and protein-protein interaction (PPI) network analysis. All in all, it was posited that the 66 feature genes could effectively classify positive and negative COVID-19 and work as new biomarkers of the disease.

Targeting cathepsins: A potential link between COVID-19 and associated neurological manifestations

Many studies have shown that the lysosomal cathepsins, especially cathepsins B/L (CTSB/L) are required for SARS-CoV-2 entry into host cells. Lysosomal proteases, cathepsins are indispensable for normal health and are involved in several brain disorders occurring at different development age periods. On the other hand, it has been well known that COVID-19 infection is largely associated with several neurological disorders. Taken together these findings and given the high levels of expression of CTSB/L in the brain, we here proposed a reasonable hypothesis about the involvement of CTSB/L in the neurological manifestations linked to COVID-19. Pharmacological inhibitions of the CTSB/L could be a potential therapeutic target to block the virus entry as well as to mitigate the brain disorders. To this end, we utilized the network-based drug repurposing analyses to identify the possible drugs that can target CTSB/L. This study identifies the molecules like cyclosporine, phenytoin, and paclitaxel as potential drugs with binding ability to the CTSB/L. Further, we have performed molecular docking and all-atom molecular dynamics (MD) simulations to investigate the stability of CTSL-drug complexes. The results showed strong and stable binding of drugs with CTSL.

Genomics-guided identification of potential modulators of SARS-CoV-2 entry proteases, TMPRSS2 and Cathepsins B/L

SARS-CoV-2 requires serine protease, transmembrane serine protease 2 (TMPRSS2), and cysteine proteases, cathepsins B, L (CTSB/L) for entry into host cells. These host proteases activate the spike protein and enable SARS-CoV-2 entry. We herein performed genomic-guided gene set enrichment analysis (GSEA) to identify upstream regulatory elements altering the expression of TMPRSS2 and CTSB/L. Further, medicinal compounds were identified based on their effects on gene expression signatures of the modulators of TMPRSS2 and CTSB/L genes. Using this strategy, estradiol and retinoic acid have been identified as putative SARS-CoV-2 alleviation agents. Next, we analyzed drug-gene and gene-gene interaction networks using 809 human targets of SARS-CoV-2 proteins. The network results indicate that estradiol interacts with 370 (45%) and retinoic acid interacts with 251 (31%) human proteins. Interestingly, a combination of estradiol and retinoic acid interacts with 461 (56%) of human proteins, indicating the therapeutic benefits of drug combination therapy. Finally, molecular docking analysis suggests that both the drugs bind to TMPRSS2 and CTSL with the nanomolar to low micromolar affinity. The results suggest that these drugs can simultaneously target both the entry pathways of SARS-CoV-2 and thus can be considered as a potential treatment option for COVID-19.

Toll-like receptor 3 (TLR3) regulation mechanisms and roles in antiviral innate immune responses

Toll-like receptor 3 (TLR3) is a member of the TLR family, mediating the transcriptional induction of type I interferons (IFNs), proinflammatory cytokines, and chemokines, thereby collectively establishing an antiviral host response. Studies have shown that unlike other TLR family members, TLR3 is the only RNA sensor that is utterly dependent on the Toll-interleukin-1 receptor (TIR)‍-domain-containing adaptor-inducing IFN-‍β (TRIF). However, the details of how the TLR3-TRIF signaling pathway works in an antiviral response and how it is regulated are unclear. In this review, we focus on recent advances in understanding the antiviral mechanism of the TRIF pathway and describe the essential characteristics of TLR3 and its antiviral effects. Advancing our understanding of TLR3 may contribute to disease diagnosis and could foster the development of novel treatments for viral diseases.

Autophagy and Mitophagy-Related Pathways at the Crossroads of Genetic Pathways Involved in Familial Sarcoidosis and Host-Pathogen Interactions Induced by Coronaviruses

Sarcoidosis is a multisystem disease characterized by the development and accumulation of granulomas, the hallmark of an inflammatory process induced by environmental and/or infectious and or genetic factors. This auto-inflammatory disease mainly affects the lungs, the gateway to environmental aggressions and viral infections. We have shown previously that genetic predisposition to sarcoidosis occurring in familial cases is related to a large spectrum of pathogenic variants with, however, a clustering around mTOR (mammalian Target Of Rapamycin)-related pathways and autophagy regulation. The context of the COVID-19 pandemic led us to evaluate whether such genetic defects may increase the risk of a severe course of SARS-CoV2 infection in patients with sarcoidosis. We extended a whole exome screening to 13 families predisposed to sarcoidosis and crossed the genes sharing mutations with the list of genes involved in the SARS-CoV2 host-pathogen protein-protein interactome. A similar analysis protocol was applied to a series of 100 healthy individuals. Using ENRICH.R, a comprehensive gene set enrichment web server, we identified the functional pathways represented in the set of genes carrying deleterious mutations and confirmed the overrepresentation of autophagy- and mitophagy-related functions in familial cases of sarcoidosis. The same protocol was applied to the set of genes common to sarcoidosis and the SARS-CoV2-host interactome and found a significant enrichment of genes related to mitochondrial factors involved in autophagy, mitophagy, and RIG-I-like (Retinoic Acid Inducible Gene 1) Receptor antiviral response signaling. From these results, we discuss the hypothesis according to which sarcoidosis is a model for studying genetic abnormalities associated with host response to viral infections as a consequence of defects in autophagy and mitophagy processes.

Methylation of Host Genes Associated with Coronavirus Infection from Birth to 26 Years

DNA methylation (DNAm) patterns over time at 1146 CpGs on coronavirus-related genes were assessed to understand whether the varying differences in susceptibility, symptoms, and the outcomes of the SARS-CoV-2 infection in children and young adults could be explained through epigenetic alterations in a host cell’s transcriptional apparatus to coronaviruses. DNAm data from the Isle of Wight birth cohort (IOWBC) at birth, 10, 18, and 26 years of age were included. Linear mixed models with repeated measurements stratified by sex were used to examine temporal patterns, and cluster analysis was performed to identify CpGs following similar patterns. CpGs on autosomes and sex chromosomes were analyzed separately. The association of identified CpGs and expression of their genes were evaluated. Pathway enrichment analyses of the genes was conducted at FDR = 0.05. DNAm at 635 of the 1146 CpGs on autosomes showed statistically significant time effects (FDR = 0.05). The 635 CpGs were classified into five clusters with each representing a unique temporal pattern of DNAm. Of the 29 CpGs on sex chromosomes, DNAm at seven CpGs in males and eight CpGs in females showed time effects (FDR = 0.05). Sex-specific and non-specific associations of DNAm with gene expression were found at 24 and 93 CpGs, respectively. Genes which mapped the 643 CpGs represent 460 biological processes. We suggest that the observed variability in DNAm with advancing age may partially explain differing susceptibility, disease severity, and mortality of coronavirus infections among different age groups.

Artificial intelligence-driven drug repurposing and structural biology for SARS-CoV-2

It has been said that COVID-19 is a generational challenge in many ways. But, at the same time, it becomes a catalyst for collective action, innovation, and discovery. Realizing the full potential of artificial intelligence (AI) for structure determination of unknown proteins and drug discovery are some of these innovations. Potential applications of AI include predicting the structure of the infectious proteins, identifying drugs that may be effective in targeting these proteins, and proposing new chemical compounds for further testing as potential drugs. AI and machine learning (ML) allow for rapid drug development including repurposing existing drugs. Algorithms were used to search for novel or approved antiviral drugs capable of inhibiting SARS-CoV-2. This paper presents a survey of AI and ML methods being used in various biochemistry of SARS-CoV-2, from structure to drug development, in the fight against the deadly COVID-19 pandemic. It is envisioned that this study will provide AI/ML researchers and the wider community an overview of the current status of AI applications particularly in structural biology, drug repurposing, and development, and motivate researchers in harnessing AI potentials in the fight against COVID-19.