Case Report: Molecular autopsy underlie COVID-19-associated sudden, unexplained child mortality.

Herein, we report a child with COVID-19 and seemingly no underlying disease, who died suddenly. The autopsy revealed severe anemia and thrombocytopenia, splenomegaly, hypercytokinemia, and a rare ectopic congenital coronary origin. Immunohistochemical analysis demonstrated that the patient had acute lymphoblastic leukemia of the B-cell precursor phenotype (BCP-ALL). The complex cardiac and hematological abnormalities suggested the presence of an underlying disease; therefore, we performed whole-exome sequencing (WES). WES revealed a leucine-zipper-like transcription regulator 1 (LZTR1) variant, indicating Noonan syndrome (NS). Therefore, we concluded that the patient had underlying NS along with coronary artery malformation and that COVID-19 infection may have triggered the sudden cardiac death due to increased cardiac load caused by high fever and dehydration. In addition, multiple organ failure due to hypercytokinemia probably contributed to the patient's death. This case would be of interest to pathologists and pediatricians because of the limited number of NS patients with LZTR1 variants; the complex combination of an LZTR1 variant, BCP-ALL, and COVID-19; and a rare pattern of the anomalous origin of the coronary artery. Thus, we highlight the significance of molecular autopsy and the application of WES with conventional diagnostic methods.

Cytokine storm-based mechanisms for extrapulmonary manifestations of SARS-CoV-2 infection.

Viral illnesses like SARS-CoV-2 have pathologic effects on nonrespiratory organs in the absence of direct viral infection. We injected mice with cocktails of rodent equivalents of human cytokine storms resulting from SARS-CoV-2/COVID-19 or rhinovirus common cold infection. At low doses, COVID-19 cocktails induced glomerular injury and albuminuria in zinc fingers and homeoboxes 2 (Zhx2) hypomorph and Zhx2+/+ mice to mimic COVID-19-related proteinuria. Common Cold cocktail induced albuminuria selectively in Zhx2 hypomorph mice to model relapse of minimal change disease, which improved after depletion of TNF-α, soluble IL-4Rα, or IL-6. The Zhx2 hypomorph state increased cell membrane to nuclear migration of podocyte ZHX proteins in vivo (both cocktails) and lowered phosphorylated STAT6 activation (COVID-19 cocktail) in vitro. At higher doses, COVID-19 cocktails induced acute heart injury, myocarditis, pericarditis, acute liver injury, acute kidney injury, and high mortality in Zhx2+/+ mice, whereas Zhx2 hypomorph mice were relatively protected, due in part to early, asynchronous activation of STAT5 and STAT6 pathways in these organs. Dual depletion of cytokine combinations of TNF-α with IL-2, IL-13, or IL-4 in Zhx2+/+ mice reduced multiorgan injury and eliminated mortality. Using genome sequencing and CRISPR/Cas9, an insertion upstream of ZHX2 was identified as a cause of the human ZHX2 hypomorph state.

The study of the strength and significance of four biological parameters on the body weight of goose.

Alternative products such as those from high-value protien animals have increased the demand for the production of high-quality chicken meat in past few years. This study examines the impact of two distinct feeding types on goose body-weight, as well as the genetic variation of growth hormone (GH) and pituitary-specific transcription factor (Pit-1) genes in ten goose populations using single nucleotide polymorphism (SNP) markers and PCR-RFLP analysis. Both genes were seen as very important for productivity, especially in light of the COVID-19 and its effect on poultry industry at the time. The findings suggest that employing genetic indicators in these two genes in conjunction with a high-fat diet may be a feasible strategy for goose selection programme aiming to increase marketing body weight, as the high-fat diet outperformed the balanced diet. The study investigates the effect of gender, 2 types of diets, breeds and the genetic variation of the two genes, four SNPs were reported to be found: two at the GH gene exons C123T and C158T, and two at the Pit-1 gene exons G161A and T282G. Certain genotypes were found to have a substantial effect on the marketing body-weight of goose, which varied depending on the tested breeds. However, in terms of gender, males report higher and better performance levels than females. Diet, breeds and genotype interaction, and breeds, gender and genotype interaction were found to have a minor effect on goose body weight. However, diet, breeds, gender, SNP locus, diet and breeds interaction, and breeds and gender interaction were found to have a significant effect on goose body weight, as indicated by the effect size results.

Pharmacological disruption of mSWI/SNF complex activity restricts SARS-CoV-2 infection.

Identification of host determinants of coronavirus infection informs mechanisms of viral pathogenesis and can provide new drug targets. Here we demonstrate that mammalian SWItch/Sucrose Non-Fermentable (mSWI/SNF) chromatin remodeling complexes, specifically canonical BRG1/BRM-associated factor (cBAF) complexes, promote severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and represent host-directed therapeutic targets. The catalytic activity of SMARCA4 is required for mSWI/SNF-driven chromatin accessibility at the ACE2 locus, ACE2 expression and virus susceptibility. The transcription factors HNF1A/B interact with and recruit mSWI/SNF complexes to ACE2 enhancers, which contain high HNF1A motif density. Notably, small-molecule mSWI/SNF ATPase inhibitors or degraders abrogate angiotensin-converting enzyme 2 (ACE2) expression and confer resistance to SARS-CoV-2 variants and a remdesivir-resistant virus in three cell lines and three primary human cell types, including airway epithelial cells, by up to 5 logs. These data highlight the role of mSWI/SNF complex activities in conferring SARS-CoV-2 susceptibility and identify a potential class of broad-acting antivirals to combat emerging coronaviruses and drug-resistant variants.

Gene-Nutrient Interactions in Obesity: COBLL1 Genetic Variants Interact with Dietary Fat Intake to Modulate the Incidence of Obesity.

The COBLL1 gene is associated with leptin, a hormone important for appetite and weight maintenance. Dietary fat is a significant factor in obesity. This study aimed to determine the association between COBLL1 gene, dietary fat, and incidence of obesity. Data from the Korean Genome and Epidemiology Study were used, and 3055 Korean adults aged ≥ 40 years were included. Obesity was defined as a body mass index ≥ 25 kg/m2. Patients with obesity at baseline were excluded. The effects of the COBLL1 rs6717858 genotypes and dietary fat on incidence of obesity were evaluated using multivariable Cox proportional hazard models. During an average follow-up period of 9.2 years, 627 obesity cases were documented. In men, the hazard ratio (HR) for obesity was higher in CT, CC carriers (minor allele carriers) in the highest tertile of dietary fat intake than for men with TT carriers in the lowest tertile of dietary fat intake (Model 1: HR: 1.66, 95% confidence interval [CI]: 1.07-2.58; Model 2: HR: 1.63, 95% CI: 1.04-2.56). In women, the HR for obesity was higher in TT carriers in the highest tertile of dietary fat intake than for women with TT carriers in the lowest tertile of dietary fat intake (Model 1: HR: 1.49, 95% CI: 1.08-2.06; Model 2: HR: 1.53, 95% CI: 1.10-2.13). COBLL1 genetic variants and dietary fat intake had different sex-dependent effects in obesity. These results imply that a low-fat diet may protect against the effects of COBLL1 genetic variants on future obesity risk.

Identification of a key glioblastoma candidate gene, FUBP3, based on weighted gene co-expression network analysis.

BACKGROUND: Glioblastoma multiforme (GBM) is the most common aggressive malignant brain tumor. However, the molecular mechanism of glioblastoma formation is still poorly understood. To identify candidate genes that may be connected to glioma growth and development, weighted gene co-expression network analysis (WGCNA) was performed to construct a gene co-expression network between gene sets and clinical characteristics. We also explored the function of the key candidate gene. METHODS: Two GBM datasets were selected from GEO Datasets. The R language was used to identify differentially expressed genes. WGCNA was performed to construct a gene co-expression network in the GEO glioblastoma samples. A custom Venn diagram website was used to find the intersecting genes. The GEPIA website was applied for survival analysis to determine the significant gene, FUBP3. OS, DSS, and PFI analyses, based on the UCSC Cancer Genomics Browser, were performed to verify the significance of FUBP3. Immunohistochemistry was performed to evaluate the expression of FUBP3 in glioblastoma and adjacent normal tissue. KEGG and GO enrichment analyses were used to reveal possible functions of FUBP3. Microenvironment analysis was used to explore the relationship between FUBP3 and immune infiltration. Immunohistochemistry was performed to verify the results of the microenvironment analysis. RESULTS: GSE70231 and GSE108474 were selected from GEO Datasets, then 715 and 694 differentially expressed genes (DEGs) from GSE70231 and GSE108474, respectively, were identified. We then performed weighted gene co-expression network analysis (WGCNA) and identified the most downregulated gene modules of GSE70231 and GSE108474, and 659 and 3915 module genes from GSE70231 and GSE108474, respectively, were selected. Five intersection genes (FUBP3, DAD1, CLIC1, ABR, and DNM1) were calculated by Venn diagram. FUBP3 was then identified as the only significant gene by survival analysis using the GEPIA website. OS, DSS, and PFI analyses verified the significance of FUBP3. Immunohistochemical analysis revealed FUBP3 expression in GBM and adjacent normal tissue. KEGG and GO analyses uncovered the possible function of FUBP3 in GBM. Tumor microenvironment analysis showed that FUBP3 may be connected to immune infiltration, and immunohistochemistry identified a positive correlation between immune cells (CD4 + T cells, CD8 + T cells, and macrophages) and FUBP3. CONCLUSION: FUBP3 is associated with immune surveillance in GBM, indicating that it has a great impact on GBM development and progression. Therefore, interventions involving FUBP3 and its regulatory pathway may be a new approach for GBM treatment.

Peripheral Blood Genes Crosstalk between COVID-19 and Sepsis.

Severe coronavirus disease 2019 (COVID-19) has led to a rapid increase in death rates all over the world. Sepsis is a life-threatening disease associated with a dysregulated host immune response. It has been shown that COVID-19 shares many similarities with sepsis in many aspects. However, the molecular mechanisms underlying sepsis and COVID-19 are not well understood. The aim of this study was to identify common transcriptional signatures, regulators, and pathways between COVID-19 and sepsis, which may provide a new direction for the treatment of COVID-19 and sepsis. First, COVID-19 blood gene expression profile (GSE179850) data and sepsis blood expression profile (GSE134347) data were obtained from GEO. Then, we intersected the differentially expressed genes (DEG) from these two datasets to obtain common DEGs. Finally, the common DEGs were used for functional enrichment analysis, transcription factor and miRNA prediction, pathway analysis, and candidate drug analysis. A total of 307 common DEGs were identified between the sepsis and COVID-19 datasets. Protein-protein interactions (PPIs) were constructed using the STRING database. Subsequently, hub genes were identified based on PPI networks. In addition, we performed GO functional analysis and KEGG pathway analysis of common DEGs, and found a common association between sepsis and COVID-19. Finally, we identified transcription factor-gene interaction, DEGs-miRNA co-regulatory networks, and protein-drug interaction, respectively. Through ROC analysis, we identified 10 central hub genes as potential biomarkers. In this study, we identified SARS-CoV-2 infection as a high risk factor for sepsis. Our study may provide a potential therapeutic direction for the treatment of COVID-19 patients suffering from sepsis.

Boolean modeling reveals that cyclic attractors in macrophage polarization serve as reservoirs of states to balance external perturbations from the tumor microenvironment.

Cyclic attractors generated from Boolean models may explain the adaptability of a cell in response to a dynamical complex tumor microenvironment. In contrast to this idea, we postulate that cyclic attractors in certain cases could be a systemic mechanism to face the perturbations coming from the environment. To justify our conjecture, we present a dynamic analysis of a highly curated transcriptional regulatory network of macrophages constrained into a cancer microenvironment. We observed that when M1-associated transcription factors (STAT1 or NF-κB) are perturbed and the microenvironment balances to a hyper-inflammation condition, cycle attractors activate genes whose signals counteract this effect implicated in tissue damage. The same behavior happens when the M2-associated transcription factors are disturbed (STAT3 or STAT6); cycle attractors will prevent a hyper-regulation scenario implicated in providing a suitable environment for tumor growth. Therefore, here we propose that cyclic macrophage phenotypes can serve as a reservoir for balancing the phenotypes when a specific phenotype-based transcription factor is perturbed in the regulatory network of macrophages. We consider that cyclic attractors should not be simply ignored, but it is necessary to carefully evaluate their biological importance. In this work, we suggest one conjecture: the cyclic attractors can serve as a reservoir to balance the inflammatory/regulatory response of the network under external perturbations.

Dynamic activity in cis-regulatory elements of leukocytes identifies transcription factor activation and stratifies COVID-19 severity in ICU patients.

Transcription factor programs mediating the immune response to coronavirus disease 2019 (COVID-19) are not fully understood. Capturing active transcription initiation from cis-regulatory elements such as enhancers and promoters by capped small RNA sequencing (csRNA-seq), in contrast to capturing steady-state transcripts by conventional RNA-seq, allows unbiased identification of the underlying transcription factor activity and regulatory pathways. Here, we profile transcription initiation in critically ill COVID-19 patients, identifying transcription factor motifs that correlate with clinical lung injury and disease severity. Unbiased clustering reveals distinct subsets of cis-regulatory elements that delineate the cell type, pathway-specific, and combinatorial transcription factor activity. We find evidence of critical roles of regulatory networks, showing that STAT/BCL6 and E2F/MYB regulatory programs from myeloid cell populations are activated in patients with poor disease outcomes and associated with COVID-19 susceptibility genetic variants. More broadly, we demonstrate how capturing acute, disease-mediated changes in transcription initiation can provide insight into the underlying molecular mechanisms and stratify patient disease severity.

A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates.

Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed significant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage.

Acute respiratory distress syndrome enhances tumor metastasis into lungs: Role of BRD4 in the tumor microenvironment.

Acute respiratory distress syndrome (ARDS) is associated with severe lung inflammation, edema, hypoxia, and high vascular permeability. The COVID-19-associated pandemic ARDS caused by SARS-CoV-2 has created dire global conditions and has been highly contagious. Chronic inflammatory disease enhances cancer cell proliferation, progression, and invasion. We investigated how acute lung inflammation activates the tumor microenvironment and enhances lung metastasis in LPS induced in vitro and in vivo models. Respiratory illness is mainly caused by cytokine storm, which further influences oxidative and nitrosative stress. The LPS-induced inflammatory cytokines made the conditions suitable for the tumor microenvironment in the lungs. In the present study, we observed that LPS induced the cytokine storm and promoted lung inflammation via BRD4, which further caused the nuclear translocation of p65 NF-κB and STAT3. The transcriptional activation additionally triggers the tumor microenvironment and lung metastasis. Thus, BRD4-regulated p65 and STAT3 transcriptional activity in ARDS enhances lung tumor metastasis. Moreover, LPS-induced ARDS might promote the tumor microenvironment and increase cancer metastasis into the lungs. Collectively, BRD4 plays a vital role in inflammation-mediated tumor metastasis and is found to be a diagnostic and molecular target in inflammation-associated cancers.

Down-regulation of KLF2 in lung fibroblasts is linked with COVID-19 immunofibrosis and restored by combined inhibition of NETs, JAK-1/2 and IL-6 signaling.

Kruppel-like factor 2 (KLF2) has been linked with fibrosis and neutrophil-associated thromboinflammation; however, its role in COVID-19 remains elusive. We investigated the effect of disease microenvironment on the fibrotic potential of human lung fibroblasts (LFs) and its association with KLF2 expression. LFs stimulated with plasma from severe COVID-19 patients down-regulated KLF2 expression at mRNA/protein and functional level acquiring a pre-fibrotic phenotype, as indicated by increased CCN2/collagen levels. Pre-incubation with the COMBI-treatment-agents (DNase I and JAKs/IL-6 inhibitors baricitinib/tocilizumab) restored KLF2 levels of LFs to normal abolishing their fibrotic activity. LFs stimulated with plasma from COMBI-treated patients at day-7 expressed lower CCN2 and higher KLF2 levels, compared to plasma prior-to-treatment, an effect not observed in standard-of-care treatment. In line with this, COMBI-treated patients had better outcome than standard-of-care group. These data link fibroblast KLF2 with NETosis and JAK/IL-6 signaling, suggesting the potential of combined therapeutic strategies in immunofibrotic diseases, such as COVID-19.

ZBTB7A promotes virus-host homeostasis during human coronavirus 229E infection.

The cellular fate after infection with human coronaviruses (HCoVs) is typically death. Previous data suggest, however, that the transcriptional state of an individual cell may sometimes allow additional outcomes of infection. Here, to probe the range of interactions a permissive cell type can have with a HCoV, we perform a CRISPR activation screen with HCoV-229E. The screen identified the transcription factor ZBTB7A, which strongly promotes cell survival after infection. Rather than suppressing viral infection, ZBTB7A upregulation allows the virus to induce a persistent infection and homeostatic state with the cell. We also find that control of oxidative stress is a primary driver of cellular survival during HCoV-229E infection. These data illustrate that, in addition to the nature of the infecting virus and the type of cell that it encounters, the cellular gene expression profile prior to infection can affect the eventual fate.

Bioinformatics and systems-biology analysis to determine the effects of Coronavirus disease 2019 on patients with allergic asthma.

Background: The coronavirus disease (COVID-19) pandemic has posed a significant challenge for global health systems. Increasing evidence shows that asthma phenotypes and comorbidities are major risk factors for COVID-19 symptom severity. However, the molecular mechanisms underlying the association between COVID-19 and asthma are poorly understood. Therefore, we conducted bioinformatics and systems biology analysis to identify common pathways and molecular biomarkers in patients with COVID-19 and asthma, as well as potential molecular mechanisms and candidate drugs for treating patients with both COVID-19 and asthma. Methods: Two sets of differentially expressed genes (DEGs) from the GSE171110 and GSE143192 datasets were intersected to identify common hub genes, shared pathways, and candidate drugs. In addition, murine models were utilized to explore the expression levels and associations of the hub genes in asthma and lung inflammation/injury. Results: We discovered 157 common DEGs between the asthma and COVID-19 datasets. A protein-protein-interaction network was built using various combinatorial statistical approaches and bioinformatics tools, which revealed several hub genes and critical modules. Six of the hub genes were markedly elevated in murine asthmatic lungs and were positively associated with IL-5, IL-13 and MUC5AC, which are the key mediators of allergic asthma. Gene Ontology and pathway analysis revealed common associations between asthma and COVID-19 progression. Finally, we identified transcription factor-gene interactions, DEG-microRNA coregulatory networks, and potential drug and chemical-compound interactions using the hub genes. Conclusion: We identified the top 15 hub genes that can be used as novel biomarkers of COVID-19 and asthma and discovered several promising candidate drugs that might be helpful for treating patients with COVID-19 and asthma.

CORN-Condition Orientated Regulatory Networks: bridging conditions to gene networks.

A transcriptional regulatory network (TRN) is a collection of transcription regulators with their associated downstream genes, which is highly condition-specific. Understanding how cell states can be programmed through small molecules/drugs or conditions by modulating the whole gene expression system granted us the potential to amend abnormal cells and cure diseases. Condition Orientated Regulatory Networks (CORN, https://qinlab.sysu.edu.cn/home) is a library of condition (small molecule/drug treatments and gene knockdowns)-based transcriptional regulatory sub-networks (TRSNs) that come with an online TRSN matching tool. It allows users to browse condition-associated TRSNs or match those TRSNs by inputting transcriptomic changes of interest. CORN utilizes transcriptomic changes data after specific conditional treatment in cells, and in vivo transcription factor (TF) binding data in cells, by combining TF binding information and calculations of significant expression alterations of TFs and genes after the conditional treatments, TRNs under the effect of different conditions were constructed. In short, CORN associated 1805 different types of specific conditions (small molecule/drug treatments and gene knockdowns) to 9553 TRSNs in 25 human cell lines, involving 204TFs. By linking and curating specific conditions to responsive TRNs, the scientific community can now perceive how TRNs are altered and controlled by conditions alone in an organized manner for the first time. This study demonstrated with examples that CORN can aid the understanding of molecular pathology, pharmacology and drug repositioning, and screened drugs with high potential for cancer and coronavirus disease 2019 (COVID-19) treatments.

ELF5 is a potential respiratory epithelial cell-specific risk gene for severe COVID-19.

Despite two years of intense global research activity, host genetic factors that predispose to a poorer prognosis of COVID-19 infection remain poorly understood. Here, we prioritise eight robust (e.g., ELF5) or suggestive but unreported (e.g., RAB2A) candidate protein mediators of COVID-19 outcomes by integrating results from the COVID-19 Host Genetics Initiative with population-based plasma proteomics using statistical colocalisation. The transcription factor ELF5 (ELF5) shows robust and directionally consistent associations across different outcome definitions, including a >4-fold higher risk (odds ratio: 4.88; 95%-CI: 2.47-9.63; p-value < 5.0 × 10-6) for severe COVID-19 per 1 s.d. higher genetically predicted plasma ELF5. We show that ELF5 is specifically expressed in epithelial cells of the respiratory system, such as secretory and alveolar type 2 cells, using single-cell RNA sequencing and immunohistochemistry. These cells are also likely targets of SARS-CoV-2 by colocalisation with key host factors, including ACE2 and TMPRSS2. In summary, large-scale human genetic studies together with gene expression at single-cell resolution highlight ELF5 as a risk gene for severe COVID-19, supporting a role of epithelial cells of the respiratory system in the adverse host response to SARS-CoV-2.

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.

Host genetic loci LZTFL1 and CCL2 associated with SARS-CoV-2 infection and severity of COVID-19.

OBJECTIVES: Host genetic factors contribute to the variable severity of COVID-19. We examined genetic variants from genome-wide association studies and candidate gene association studies in a cohort of patients with COVID-19 and investigated the role of early SARS-CoV-2 strains in COVID-19 severity. METHODS: This case-control study included 123 COVID-19 cases (hospitalized or ambulatory) and healthy controls from the state of Baden-Wuerttemberg, Germany. We genotyped 30 single nucleotide polymorphisms, using a custom-designed panel. Cases were also compared with the 1000 genomes project. Polygenic risk scores were constructed. SARS-CoV-2 genomes from 26 patients with COVID-19 were sequenced and compared between ambulatory and hospitalized cases, and phylogeny was reconstructed. RESULTS: Eight variants reached nominal significance and two were significantly associated with at least one of the phenotypes "susceptibility to infection", "hospitalization", or "severity": rs73064425 in LZTFL1 (hospitalization and severity, P <0.001) and rs1024611 near CCL2 (susceptibility, including 1000 genomes project, P = 0.001). The polygenic risk score could predict hospitalization. Most (23/26, 89%) of the SARS-CoV-2 genomes were classified as B.1 lineage. No associations of SARS-CoV-2 mutations or lineages with severity were observed. CONCLUSION: These host genetic markers provide insights into pathogenesis and enable risk classification. Variants which reached nominal significance should be included in larger studies.

Exploring the potential mechanism of emetine against coronavirus disease 2019 combined with lung adenocarcinoma: bioinformatics and molecular simulation analyses.

BACKGROUND: Patients with lung adenocarcinoma (LUAD) may be more predisposed to coronavirus disease 2019 (COVID-19) and have a poorer prognosis. Currently, there is still a lack of effective anti-LUAD/COVID-19 drugs. Thus, this study aimed to screen for an effective anti-LUAD/COVID-19 drug and explore the potential mechanisms. METHODS: Firstly, we performed differentially expressed gene (DEG) analysis on LUAD transcriptome profiling data in The Cancer Genome Atlas (TCGA), where intersections with COVID-19-related genes were screened out. Then, we conducted Cox proportional hazards analyses on these LUAD/COVID-19 DEGs to construct a risk score. Next, LUAD/COVID-19 DEGs were uploaded on Connectivity Map to obtain drugs for anti-LUAD/COVID-19. Finally, we used network pharmacology, molecular docking, and molecular dynamics (MD) simulation to explore the drug's therapeutic targets and potential mechanisms for anti-LUAD/COVID-19. RESULTS: We identified 230 LUAD/COVID-19 DEGs and constructed a risk score containing 7 genes (BTK, CCL20, FURIN, LDHA, TRPA1, ZIC5, and SDK1) that could classify LUAD patients into two risk groups. Then, we screened emetine as an effective drug for anti-LUAD/COVID-19. Network pharmacology analyses identified 6 potential targets (IL6, DPP4, MIF, PRF1, SERPING1, and SLC6A4) for emetine in anti-LUAD/COVID-19. Molecular docking and MD simulation analyses showed that emetine exhibited excellent binding capacities to DDP4 and the main protease (Mpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). CONCLUSIONS: This study found that emetine may inhibit the entry and replication of SARS-CoV-2 and enhance tumor immunity by bounding to DDP4 and Mpro.

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.