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COVID-19 is associated with dysregulation of several genes and signaling pathways. Based on the importance of expression profiling in identification of the pathogenesis of COVID-19 and proposing novel therapies for this disorder, we have employed an in silico approach to find differentially expressed genes between COVID-19 patients and healthy controls and their relevance with cellular functions and signaling pathways. We obtained 630 DEmRNAs, including 486 down-regulated DEGs (such as CCL3 and RSAD2) and 144 up-regulated DEGs (such as RHO and IQCA1L), and 15 DElncRNAs, including 9 down-regulated DElncRNAs (such as PELATON and LINC01506) and 6 up-regulated DElncRNAs (such as AJUBA-DT and FALEC). The PPI network of DEGs showed the presence of a number immune-related genes such as those coding for HLA molecules and interferon regulatory factors. Taken together, these results highlight the importance of immune-related genes and pathways in the pathogenesis of COVID-19 and suggest novel targets for treatment of this disorder., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Motivation A patient's disease phenotype can be driven and determined by specific groups of cells whose marker genes are either unknown or can only be detected at late-stage using conventional bulk assays such as RNA-Seq technology. Recent advances in single-cell RNA sequencing (scRNA-seq) enable gene expression profiling in cell-level resolution, and therefore have the potential to identify those cells driving the disease phenotype even while the number of these cells is small. However, most existing methods rely heavily on accurate cell type detection, and the number of available annotated samples is usually too small for training deep learning predictive models. Results Here, we propose the method ScRAT for phenotype prediction using scRNA-seq data. To train ScRAT with a limited number of samples of different phenotypes, such as coronavirus disease (COVID) and non-COVID, ScRAT first applies a mixup module to increase the number of training samples. A multi-head attention mechanism is employed to learn the most informative cells for each phenotype without relying on a given cell type annotation. Using three public COVID datasets, we show that ScRAT outperforms other phenotype prediction methods. The performance edge of ScRAT over its competitors increases as the number of training samples decreases, indicating the efficacy of our sample mixup. Critical cell types detected based on high-attention cells also support novel findings in the original papers and the recent literature. This suggests that ScRAT overcomes the challenge of missing marker genes and limited sample number with great potential revealing novel molecular mechanisms and/or therapies. Availability and implementation The code of our proposed method ScRAT is published at https://github.com/yuzhenmao/ScRAT. [ABSTRACT FROM AUTHOR]

Background: Single-cell (sc) sequencing performs unbiased profiling of individual cells and enables evaluation of less prevalent cellular populations, often missed using bulk sequencing. However, the scale and the complexity of the sc datasets poses a great challenge in its utility and this problem is further exacerbated when working with larger datasets typically generated by consortium efforts. As the scale of single cell datasets continues to increase exponentially, there is an unmet technological need to develop database platforms that can evaluate key biological hypotheses by querying extensive single-cell datasets. Large single-cell datasets like Human Cell Atlas and COVID-19 cell atlas (collection of annotated sc datasets from various human organs) are excellent resources for profiling target genes involved in human diseases and disorders ranging from oncology, auto-immunity, as well as infectious diseases like COVID-19 caused by SARS-CoV-2 virus. SARS-CoV-2 infections have led to a worldwide pandemic with massive loss of lives, infections exceeding 7 million cases. The virus uses ACE2 and TMPRSS2 as key viral entry associated proteins expressed in human cells for infections. Evaluating the expression profile of key genes in large single-cell datasets can facilitate testing for diagnostics, therapeutics, and vaccine targets, as the world struggles to cope with the on-going spread of COVID-19 infections. Main body: In this manuscript we describe REVEAL: SingleCell, which enables storage, retrieval, and rapid query of single-cell datasets inclusive of millions of cells. The array native database described here enables selecting and analyzing cells across multiple studies. Cells can be selected using individual metadata tags, more complex hierarchical ontology filtering, and gene expression threshold ranges, including co-expression of multiple genes. The tags on selected cells can be further evaluated for testing biological hypotheses. One such example includes identifying the most prevalent cell type annotation tag on returned cells. We used REVEAL: SingleCell to evaluate the expression of key SARS-CoV-2 entry associated genes, and queried the current database (2.2 Million cells, 32 projects) to obtain the results in < 60 s. We highlighted cells expressing COVID-19 associated genes are expressed on multiple tissue types, thus in part explains the multi-organ involvement in infected patients observed worldwide during the on-going COVID-19 pandemic. Conclusion: In this paper, we introduce the REVEAL: SingleCell database that addresses immediate needs for SARS-CoV-2 research and has the potential to be used more broadly for many precision medicine applications. We used the REVEAL: SingleCell database as a reference to ask questions relevant to drug development and precision medicine regarding cell type and co-expression for genes that encode proteins necessary for SARS-CoV-2 to enter and reproduce in cells. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is a type of pneumonia caused by the SARS-CoV-2 coronavirus. It can cause acute pulmonary and systemic inflammation, which can lead to death in severely ill patients. This study explores the potential reasons behind severe COVID-19 and its similarities to systemic autoimmune diseases. This study reviewed unbiased high-throughput gene expression datasets, including next-generation and single-cell RNA sequencing. A total of 27 studies and eight meta-analyses were reviewed. The studies indicated that severe COVID-19 is associated with the upregulation of genes involved in pro-inflammatory, interferon, and cytokine/chemokine pathways. Additionally, changes were observed in the proportions of immune cell types in the blood and tissues, along with degenerative alterations in lung epithelial cells. Genomic evidence also supports the association of severe COVID-19 with various inflammatory syndromes, such as neuronal COVID-19, acute respiratory distress syndrome, vascular inflammation, and multisystem inflammatory syndrome. In conclusion, this study suggests that gene expression profiling plays a significant role in elucidating the etiology of severe COVID-19. [ABSTRACT FROM AUTHOR]

Background: The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown. Methods: Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex. Results: The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients. Conclusions: Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future. [ABSTRACT FROM AUTHOR]

Introduction: COVID-19 typically causes Q7 respiratory disorders, but a high proportion of patients also reports neurological and neuromuscular symptoms during and after SARSCoV-2 infection. Despite a number of studies documenting SARS-CoV-2 infection of various neuronal cell populations, the impact of SARSCoV-2 exposure on motor neuronal cells specifically has not been investigated so far. Methods: Thus, by using human iPSC-derived motor neurons (iPSC-MNs) we assessed: (i) the expression of SARS-CoV-2 main receptors; (ii) iPSC-MN infectability by SARS-CoV-2; and (iii) the effect of SARS-CoV-2 exposure on iPSC-MN transcriptome. Results: Gene expression profiling and immunofluorescence (IF) analysis of the main host cell receptors recognized by SARS-CoV-2 revealed that all of them are expressed in iPSC-MNs, with CD147 and NRP1 being the most represented ones. By analyzing SARS-CoV-2 N1 and N2 gene expression over time, we observed that human iPSC-MNs were productively infected by SARS-CoV-2 in the absence of cytopathic effect. Supernatants collected from SARS-CoV-2-infected iPSC-MNs were able to re-infect VeroE6 cells. Image analyses of SARS-CoV-2 nucleocapsid proteins by IF confirmed iPSC-MN infectability. Furthermore, SARSCoV-2 infection in iPSCMNs significantly altered the expression of genes (IL-6, ANG, S1PR1, BCL2, BAX, Casp8, HLA-A, ERAP1, CD147, MX1) associated with cell survival and metabolism, as well as antiviral and inflammatory response. Discussion: These results suggest for the very first time that SARS-CoV-2 can productively infect human iPSC-derived MNs probably by binding CD147 and NRP1 receptors. Such information will be important to unveil the biological bases of neuromuscular disorders characterizing SARS-CoV-2 infection and the so called long-COVID symptoms. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 variants and seasonal coronaviruses continue to cause disease and coronaviruses in the animal reservoir pose a constant spillover threat. Importantly, understanding of how previous infection may influence future exposures, especially in the context of seasonal coronaviruses and SARS-CoV-2 variants, is still limited. Here we adopted a step-wise experimental approach to examine the primary immune response and subsequent immune recall toward antigenically distinct coronaviruses using male Syrian hamsters. Hamsters were initially inoculated with seasonal coronaviruses (HCoV-NL63, HCoV-229E, or HCoV-OC43), or SARS-CoV-2 pango B lineage virus, then challenged with SARS-CoV-2 pango B lineage virus, or SARS-CoV-2 variants Beta or Omicron. Although infection with seasonal coronaviruses offered little protection against SARS-CoV-2 challenge, HCoV-NL63-infected animals had an increase of the previously elicited HCoV-NL63-specific neutralizing antibodies during challenge with SARS-CoV-2. On the other hand, primary infection with HCoV-OC43 induced distinct T cell gene signatures. Gene expression profiling indicated interferon responses and germinal center reactions to be induced during more similar primary infection-challenge combinations while signatures of increased inflammation as well as suppression of the antiviral response were observed following antigenically distant viral challenges. This work characterizes and analyzes seasonal coronaviruses effect on SARS-CoV-2 secondary infection and the findings are important for pan-coronavirus vaccine design. Here, the authors analysed immune response to two consecutive coronavirus infections and observed that hamsters infected with seasonal coronaviruses were not protected from COVID-19 despite cross-reactive antibodies. Antiviral and germinal center B cell responses were suppressed but not during SARS-CoV-2 variant infections. [ABSTRACT FROM AUTHOR]

Objectives: The purpose of this study was to evaluate available evidence on the association between the human oral microbiota and coronavirus disease 2019 (COVID-19) and summarize relevant data obtained during the pandemic. Methods: We searched EMBASE, PubMed, and the Cochrane Library for human studies published up to October 2022. The main outcomes of the study were the differences in the diversity (a and b) and composition of the oral microbiota at the phylum and genus levels between patients with laboratory-confirmed SARSCoV-2 infection (CPs) and healthy controls (HCs). We used the Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA) database, Protein-protein interaction (PPI) network (STRING) and Gene enrichment analysis (Metascape) to evaluate the expression of dipeptidyl peptidase 4 (DPP4) (which is the cell receptor of SARS CoV-2) in oral tissues and evaluate its correlation with viral genes or changes in the oral microbiota. Results: Out of 706 studies, a meta-analysis of 9 studies revealed a significantly lower alpha diversity (Shannon index) in CPs than in HCs (standardized mean difference (SMD): -0.53, 95% confidence intervals (95% CI): -0.97 to -0.09). Subgroup meta-analysis revealed a significantly lower alpha diversity (Shannon index) in older than younger individuals (SMD: -0.54, 95% CI: -0.86 to -0.23/SMD: -0.52, 95% CI: -1.18 to 0.14). At the genus level, the most significant changes were in Streptococcus and Neisseria, which had abundances that were significantly higher and lower in CPs than in HCs based on data obtained from six out of eleven and five out of eleven studies, respectively. DPP4 mRNA expression in the oral salivary gland was significantly lower in elderly individuals than in young individuals. Spearman correlation analysis showed that DPP4 expression was negatively correlated with the expression of viral genes. Gene enrichment analysis showed that DPP4-associated proteins were mainly enriched in biological processes, such as regulation of receptor-mediated endocytosis of viruses by host cells and bacterial invasion of epithelial cells. Conclusion: The oral microbial composition in COVID-19 patients was significantly different from that in healthy individuals, especially among elderly individuals. DPP4 may be related to viral infection and dysbiosis of the oral microbiome in elderly individuals. [ABSTRACT FROM AUTHOR]

A growing of evidence has showed that patients with osteoarthritis (OA) had a higher coronavirus 2019 (COVID-19) infection rate and a poorer prognosis after infected it. Additionally, scientists have also discovered that COVID-19 infection might cause pathological changes in the musculoskeletal system. However, its mechanism is still not fully elucidated. This study aims to further explore the sharing pathogenesis of patients with both OA and COVID-19 infection and find candidate drugs. Gene expression profiles of OA (GSE51588) and COVID-19 (GSE147507) were obtained from the Gene Expression Omnibus (GEO) database. The common differentially expressed genes (DEGs) for both OA and COVID-19 were identified and several hub genes were extracted from them. Then gene and pathway enrichment analysis of the DEGs were performed; protein–protein interaction (PPI) network, transcription factor (TF)-gene regulatory network, TF-miRNA regulatory network and gene-disease association network were constructed based on the DEGs and hub genes. Finally, we predicted several candidate molecular drugs related to hub genes using DSigDB database. The receiver operating characteristic curve (ROC) was applied to evaluate the accuracy of hub genes in the diagnosis of both OA and COVID-19. In total, 83 overlapping DEGs were identified and selected for subsequent analyses. CXCR4, EGR2, ENO1, FASN, GATA6, HIST1H3H, HIST1H4H, HIST1H4I, HIST1H4K, MTHFD2, PDK1, TUBA4A, TUBB1 and TUBB3 were screened out as hub genes, and some showed preferable values as diagnostic markers for both OA and COVID-19. Several candidate molecular drugs, which are related to the hug genes, were identified. These sharing pathways and hub genes may provide new ideas for further mechanistic studies and guide more individual-based effective treatments for OA patients with COVID-19 infection. [ABSTRACT FROM AUTHOR]

The clinical manifestations of SARS-CoV-2 infection vary widely, from asymptomatic infection to the development of acute respiratory distress syndrome (ARDS) and death. The host response elicited by SARS-CoV-2 plays a key role in determining the clinical outcome. We hypothesized that determining the dynamic whole blood transcriptomic profile of hospitalized adult COVID-19 patients and characterizing the subgroup that develops severe disease and ARDS would broaden our understanding of the heterogeneity in clinical outcomes. We recruited 60 hospitalized patients with RT-PCR-confirmed SARS-CoV-2 infection, among whom 19 developed ARDS. Peripheral blood was collected using PAXGene RNA tubes within 24 h of admission and on day 7. There were 2572 differently expressed genes in patients with ARDS at baseline and 1149 at day 7. We found a dysregulated inflammatory response in COVID-19 ARDS patients, with an increased expression of genes related to pro-inflammatory molecules and neutrophil and macrophage activation at admission, in addition to an immune regulation loss. This led, in turn, to a higher expression of genes related to reactive oxygen species, protein polyubiquitination, and metalloproteinases in the latter stages. Some of the most significant differences in gene expression found between patients with and without ARDS corresponded to long non-coding RNA involved in epigenetic control. [ABSTRACT FROM AUTHOR]

Corona Virus Disease 2019 (COVID-19) not only causes respiratory system damage, but also imposes strain on the cardiovascular system. Vascular endothelial cells and cardiomyocytes play an important role in cardiac function. The aberrant expression of genes in vascular endothelial cells and cardiomyocytes can lead to cardiovascular diseases. In this study, we sought to explain the influence of respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on the gene expression levels of vascular endothelial cells and cardiomyocytes. We designed an advanced machine learning-based workflow to analyze the gene expression profile data of vascular endothelial cells and cardiomyocytes from patients with COVID-19 and healthy controls. An incremental feature selection method with a decision tree was used in building efficient classifiers and summarizing quantitative classification genes and rules. Some key genes, such as MALAT1, MT-CO1, and CD36, were extracted, which exert important effects on cardiac function, from the gene expression matrix of 104,182 cardiomyocytes, including 12,007 cells from patients with COVID-19 and 92,175 cells from healthy controls, and 22,438 vascular endothelial cells, including 10,812 cells from patients with COVID-19 and 11,626 cells from healthy controls. The findings reported in this study may provide insights into the effect of COVID-19 on cardiac cells and further explain the pathogenesis of COVID-19, and they may facilitate the identification of potential therapeutic targets. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Although alterations in myeloid cells have been observed in COVID-19, the specific underlying mechanisms are not completely understood. Here, we examine the function of classical CD14+ monocytes in patients with mild and moderate COVID-19 during the acute phase of infection and in healthy individuals. Monocytes from COVID-19 patients display altered expression of cell surface receptors and a dysfunctional metabolic profile that distinguish them from healthy monocytes. Secondary pathogen sensing ex vivo leads to defects in pro-inflammatory cytokine and type-I IFN production in moderate COVID-19 cases, together with defects in glycolysis. COVID-19 monocytes switch their gene expression profile from canonical innate immune to pro-thrombotic signatures and are functionally pro-thrombotic, both at baseline and following ex vivo stimulation with SARS-CoV-2. Transcriptionally, COVID-19 monocytes are characterized by enrichment of pathways involved in hemostasis, immunothrombosis, platelet aggregation and other accessory pathways to platelet activation and clot formation. These results identify a potential mechanism by which monocyte dysfunction may contribute to COVID-19 pathology. Although myeloid cell dysfunction has been observed in COVID-19, the underlying mechanisms remain incompletely understood. Here, the authors demonstrate that monocytes from patients with mild to moderate COVID-19 show a blunted innate immune response and a pro-thrombotic signature following secondary SARS-CoV-2 challenge. [ABSTRACT FROM AUTHOR]

While the seroprevalence of SARS-CoV-2 in healthy people does not differ significantly among age groups, those aged 65 years or older exhibit strikingly higher COVID-19 mortality compared to younger individuals. To further understand differing COVID-19 manifestations in patients of different ages, three age groups of ferrets are infected with SARS-CoV-2. Although SARS-CoV-2 is isolated from all ferrets regardless of age, aged ferrets (≥3 years old) show higher viral loads, longer nasal virus shedding, and more severe lung inflammatory cell infiltration, and clinical symptoms compared to juvenile (≤6 months) and young adult (1–2 years) groups. Furthermore, direct contact ferrets co-housed with the virus-infected aged group shed more virus than direct-contact ferrets co-housed with virus-infected juvenile or young adult ferrets. Transcriptome analysis of aged ferret lungs reveals strong enrichment of gene sets related to type I interferon, activated T cells, and M1 macrophage responses, mimicking the gene expression profile of severe COVID-19 patients. Thus, SARS-CoV-2-infected aged ferrets highly recapitulate COVID-19 patients with severe symptoms and are useful for understanding age-associated infection, transmission, and pathogenesis of SARS-CoV-2. Here, Kim et al. characterize SARS-CoV-2 infection in juvenile, young, and old aged ferrets to provide a further understanding of differences in COVID-19 severity in humans at different ages. Aged ferrets have higher viral loads, shed virus longer, and mimic the transcriptomic profile of severely infected patients. [ABSTRACT FROM AUTHOR]

Introduction: Molecular diagnostics using RT-PCR has now emerged as the new diagnostic method for clinicians with the dawn of SARS-CoV-2. In India, the popularity and awareness of RT-PCR and particularly the increased availability of testing machines across hospitals has now opened up possibilities of diagnostic tests with RT-PCR. In view of the cytokine storm which is the significant reason for morbidity and mortality of COVID-19 patients, we proposed to test the usefulness of a multiplex RT-PCR test kit that simultaneously measured inflammatory markers namely, IL-6, TNF– α and IL-10 (IFM) all in one tube. The study included a group of patients who were equally allotted to two treatment arms one of which received standard of care along with a food supplement capsule as a natural anti-inflammatory (RECOVEREEZ FORTE™), and the other group received standard of care that included oral Prednisolone tablets in tapered dosage. RECOVEREEZ FORTE™ consists of potent biomolecules from cardamom extract. A natural product with substantial anti-inflammatory action when consumed early at the onset of symptoms is hereby proven by comparing gene expression profile of inflammatory markers with routinely tested inflammatory parameters such as serum IL-6, CRP and LDH. In addition to predicting worse disease outcomes beforehand, RT-PCR assay tests provides an opportunity for identifying therapeutic window aiding in practicing effective treatment strategy for COVID-19. RT-PCR analysis of IFM together being used in a single multiplex kit is being first reported and such a test as a prognosticator for disease progression does seem promising and worthy of clinicians adopting novel testing modalities in clinical practice. Aim of the study: To study the anti-inflammatory response of RECOVEREEZ FORTE™ using RT-PCR based multiplex gene profiling of inflammatory markers in disease prognosis and show its predictability of worsening outcomes and its role in identifying therapeutic window for RECOVEREEZ FORTE™. To show the potentiality of RECOVEREEZ FORTE™ in reducing COVID-19 symptoms and SARS-CoV-2 RT-PCR Ct values of the treatment group. Materials and methods: This was a short study of a 10-day period where the end point was the negativity of COVID-19 on RT-PCR test or the decline in cycle threshold (Ct) values of the test performed on day 10 when compared to day 0. During the course of the study, patients were given standard treatment and an oral dose of 500 mg of RECOVEREEZ FORTE™ thrice daily, or standard of care and oral Prednisolone in tapered dosage (control group). All essential interventions were included in the standard of care as decided by the attending physician. The RT-PCR results of inflammatory markers were compared to routinely tested parameters such as IL-6, CRP and LDH. Time to clinical improvement was in terms of SARS-CoV-2 RT-PCR test negativity or recovery of COVID-19 symptoms. We enrolled 64 patients, of which 32 were allocated to RECOVEREEZ FORTE ™ group and 32 to the control group. Results: The RT-PCR analysis of elevated IFM on day 0 corresponded to above normal protein levels of routinely tested parameters such as serum IL-6, CRP and LDH on day 5. Similarly, elevated IFM on day 5 corresponded to above normal protein levels on day 10. Such an association was equally prevalent in both the control group and RECOVEREEZ FORTE™ group, stipulating that RECOVEREEZ FORTE™ may be used as an alternative to steroids. The obtained results indicate that the RT-PCR assessment predicts worse outcomes 5 days earlier. But, the RT-PCR analysis of elevated IFM on day 0 did not correspond to the above normal protein levels of other parameters on day 10. Hence, indicating that the IFM RT-PCR test cannot predict worse outcomes 10 days earlier. Also, RECOVEREEZ FORTE™ when consumed for a period of 10 days normalized LDH values, compared to the control group. Moreover, IFM RT-PCR test identified a 5-day therapeutic window for RECOVEREEZ FORTE™ against inflammation experienced by patients. In addition to the above findings, the authors also observed that majority of the patients belonging to the treatment group showed recovery from symptoms such as fever, cough, sore throat and breathlessness compared to control group by day 5. 12 (37.5%) out of 32 patients and 6 (18.75%) out of 32 patients belonging to the treatment group and control group, respectively, became SARS-CoV-2 negative by day 5, indicating a probable anti-viral action of RECOVEREEZ FORTE™ against SARS-CoV-2. Conclusion: The IFM RT-PCR test possess 5-day early prediction ability and lacks 10-day prediction ability. Treatment with RECOVEREEZ FORTE™ indicates good anti-inflammatory action which is equivalent to steroids. Intake of RECOVEREEZ FORTE ™ for a period of 5 days depicts persistent anti-inflammatory action, recovery of COVID-19 symptoms and a probable anti-viral action. Moreover, an effective normalization of LDH may be rendered by RECOVEREEZ FORTE™ when consumed for a period of 10 days. [ABSTRACT FROM AUTHOR]

The risk of severe COVID-19 increases with age as older patients are at highest risk. Thus, there is an urgent need to identify how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with blood components during aging. We investigated the whole blood transcriptome from the Genotype-Tissue Expression (GTEx) database to explore differentially expressed genes (DEGs) translated into proteins interacting with viral proteins during aging. From 22 DEGs in aged blood, FASLG, CTSW, CTSE, VCAM1, and BAG3 were associated with immune response, inflammation, cell component and adhesion, and platelet activation/aggregation. Males and females older than 50 years old overexpress FASLG, possibly inducing a hyperinflammatory cascade. The expression of cathepsins (CTSW and CTSE) and the anti-apoptotic co-chaperone molecule BAG3 also increased throughout aging in both genders. By exploring single-cell RNA-sequencing data from peripheral blood of SARS-CoV-2-infected patients, we found FASLG and CTSW expressed in natural killer cells and CD8 + T lymphocytes, whereas BAG3 was expressed mainly in CD4 + T cells, naive T cells, and CD14 + monocytes. In addition, T cell exhaustion was associated with increased expression of CCL4L2 and DUSP4 over blood aging. LAG3, PDCD1, TIGIT, VCAM1, HLA-DRA, and TOX also increased in individuals aged 60–69 years old; conversely, the RGS2 gene decreased with aging. We further identified a distinct gene expression profile associated with type I interferon signaling following blood aging. These results revealed changes in blood molecules potentially related to SARS-CoV-2 infection throughout aging, emphasizing them as therapeutic candidates for aggressive clinical manifestation of COVID-19. Key messages: • Prediction of host-viral interactions in the whole blood transcriptome during aging. • Expression levels of FASLG, CTSW, CTSE, VCAM1, and BAG3 increase in aged blood. • Blood interactome reveals targets involved with immune response, inflammation, and blood clots. • SARS-CoV-2-infected patients with high viral load showed FASLG overexpression. • Gene expression profile associated with T cell exhaustion and type I interferon signaling were affected with blood aging. [ABSTRACT FROM AUTHOR]

The positive impact of meditation on human well-being is well documented, yet its molecular mechanisms are incompletely understood. We applied a comprehensive systems biology approach starting with whole-blood gene expression profiling combined with multilevel bioinformatic analyses to characterize the coexpression, transcriptional, and protein-protein interaction networks to identify a meditation-specific core network after an advanced 8-d Inner Engineering retreat program. We found the response to oxidative stress, detoxification, and cell cycle regulation pathways were down-regulated after meditation. Strikingly, 220 genes directly associated with immune response, including 68 genes related to interferon signaling, were up-regulated, with no significant expression changes in the inflammatory genes. This robust meditation-specific immune response network is significantly dysregulated in multiple sclerosis and severe COVID-19 patients. The work provides a foundation for understanding the effect of meditation and suggests that meditation as a behavioral intervention can voluntarily and nonpharmacologically improve the immune response for treating various conditions associated with excessive or persistent inflammation with a dampened immune system profile. [ABSTRACT FROM AUTHOR]

Although initial immunophenotypical studies on peripheral blood and bronchoalveolar lavage samples have provided a glimpse into the immunopathology of COVID-19, analyses of pulmonary draining lymph nodes are currently scarce. 22 lethal COVID-19 cases and 28 controls were enrolled in this study. Pulmonary draining lymph nodes (mediastinal, tracheal, peribronchial) were collected at autopsy. Control lymph nodes were selected from a range of histomorphological sequelae [unremarkable histology, infectious mononucleosis, follicular hyperplasia, non-SARS related HLH, extrafollicular plasmablast activation, non-SARS related diffuse alveolar damage (DAD), pneumonia]. Samples were mounted on a tissue microarray and underwent immunohistochemical staining for a selection of immunological markers and in-situ hybridization for Epstein Barr Virus (EBV) and SARS-CoV-2. Gene expression profiling was performed using the HTG EdgeSeq Immune Response Panel. Characteristic patterns of a dysregulated immune response were detected in COVID-19: 1. An accumulation of extrafollicular plasmablasts with a relative paucity or depletion of germinal centers. 2. Evidence of T-cell dysregulation demonstrated by immunohistochemical paucity of FOXP3+, Tbet+ and LEF1+ positive T-cells and a downregulation of key genes responsible for T-cell crosstalk, maturation and migration as well as a reactivation of herpes viruses in 6 COVID-19 lymph nodes (EBV, HSV). 3. Macrophage activation by a M2-polarized, CD163+ phenotype and increased incidence of hemophagocytic activity. 4. Microvascular dysfunction, evidenced by an upregulation of hemostatic (CD36, PROCR, VWF) and proangiogenic (FLT1, TEK) genes and an increase of fibrin microthrombi and CD105+ microvessels. Taken together, these findings imply widespread dysregulation of both innate and adoptive pathways with concordant microvascular dysfunction in severe COVID-19. [ABSTRACT FROM AUTHOR]

The MHC class I-mediated antigen presentation pathway plays a critical role in antiviral immunity. Here we show that the MHC class I pathway is targeted by SARS-CoV-2. Analysis of the gene expression profile from COVID-19 patients as well as SARS-CoV-2 infected epithelial cell lines reveals that the induction of the MHC class I pathway is inhibited by SARS-CoV-2 infection. We show that NLRC5, an MHC class I transactivator, is suppressed both transcriptionally and functionally by the SARS-CoV-2 ORF6 protein, providing a mechanistic link. SARS-CoV-2 ORF6 hampers type II interferon-mediated STAT1 signaling, resulting in diminished upregulation of NLRC5 and IRF1 gene expression. Moreover, SARS-CoV-2 ORF6 inhibits NLRC5 function via blocking karyopherin complex-dependent nuclear import of NLRC5. Collectively, our study uncovers an immune evasion mechanism of SARS-CoV-2 that targets the function of key MHC class I transcriptional regulators, STAT1-IRF1-NLRC5. The presentation of viral antigens to T cells via the MHC molecules is a critical component of the host response to viral infection. Here the authors suggest SARS-CoV-2 possesses the immune evasion strategy against the MHC class I pathway by targeting key transcriptional regulators. [ABSTRACT FROM AUTHOR]

The global efforts in the past year have led to the discovery of nearly 200 drug repurposing candidates for COVID-19. Gaining more insights into their mechanisms of action could facilitate a better understanding of infection and the development of therapeutics. Leveraging large-scale drug-induced gene expression profiles, we found 36% of the active compounds regulate genes related to cholesterol homeostasis and microtubule cytoskeleton organization. Following bioinformatics analyses revealed that the expression of these genes is associated with COVID-19 patient severity and has predictive power on anti-SARS-CoV-2 efficacy in vitro. Monensin, a top new compound that regulates these genes, was further confirmed as an inhibitor of SARS-CoV-2 replication in Vero-E6 cells. Interestingly, drugs co-targeting cholesterol homeostasis and microtubule cytoskeleton organization processes more likely present a synergistic effect with antivirals. Therefore, potential therapeutics could be centered around combinations of targeting these processes and viral proteins. [ABSTRACT FROM AUTHOR]

Background: Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous malignancy with varied outcomes. However, the fundamental mechanisms remain to be fully defined. Aim: We aimed to identify core differentially co-expressed hub genes and perturbed pathways relevant to the pathogenesis and prognosis of DLBCL. Methods: We retrieved the raw gene expression profile and clinical information of GSE12453 from the Gene Expression Omnibus (GEO) database. We used integrated bioinformatics analysis to identify differentially co-expressed genes. The CIBERSORT analysis was also applied to predict tumor-infiltrating immune cells (TIICs) in the GSE12453 dataset. We performed survival and ssGSEA (single-sample Gene Set Enrichment Analysis) (for TIICs) analyses and validated the hub genes using GEPIA2 and an independent GSE31312 dataset. Results: We identified 46 differentially co-expressed hub genes in the GSE12453 dataset. Gene expression levels and survival analysis found 15 differentially co-expressed core hub genes. The core genes prognostic values and expression levels were further validated in the GEPIA2 database and GSE31312 dataset to be reliable (p < 0.01). The core genes’ main KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichments were Ribosome and Coronavirus disease-COVID-19. High expressions of the 15 core hub genes had prognostic value in DLBCL. The core genes showed significant predictive accuracy in distinguishing DLBCL cases from non-tumor controls, with the area under the curve (AUC) ranging from 0.992 to 1.00. Finally, CIBERSORT analysis on GSE12453 revealed immune cells, including activated memory CD4+ T cells and M0, M1, and M2-macrophages as the infiltrates in the DLBCL microenvironment. Conclusion: Our study found differentially co-expressed core hub genes and relevant pathways involved in ribosome and COVID-19 disease that may be potential targets for prognosis and novel therapeutic intervention in DLBCL. [ABSTRACT FROM AUTHOR]

The article describes the case of a 58-year-old male who experienced a mild adult-onset Still's disease (AOSD) flare following second BNT162b2 vaccine. Topics discussed include result of treatment with prednisolone, the patient's diagnosis with AOSD in 2013, and comparison of the patient's antibody response with those from healthy individuals within the first seven days after second BNT162b2 vaccination.

The immunological features that distinguish COVID-19-associated acute respiratory distress syndrome (ARDS) from other causes of ARDS are incompletely understood. Here, we report the results of comparative lower respiratory tract transcriptional profiling of tracheal aspirate from 52 critically ill patients with ARDS from COVID-19 or from other etiologies, as well as controls without ARDS. In contrast to a "cytokine storm," we observe reduced proinflammatory gene expression in COVID-19 ARDS when compared to ARDS due to other causes. COVID-19 ARDS is characterized by a dysregulated host response with increased PTEN signaling and elevated expression of genes with non-canonical roles in inflammation and immunity. In silico analysis of gene expression identifies several candidate drugs that may modulate gene expression in COVID-19 ARDS, including dexamethasone and granulocyte colony stimulating factor. Compared to ARDS due to other types of viral pneumonia, COVID-19 is characterized by impaired interferon-stimulated gene (ISG) expression. The relationship between SARS-CoV-2 viral load and expression of ISGs is decoupled in patients with COVID-19 ARDS when compared to patients with mild COVID-19. In summary, assessment of host gene expression in the lower airways of patients reveals distinct immunological features of COVID-19 ARDS. Here, the authors perform transcriptional profiling on tracheal aspirates of adults requiring mechanical ventilation for SARS-CoV2-induced acute respiratory distress syndrome (ARDS) and identify a dysregulated host response predicted to predicted to be potentially modulated by dexamethasone. [ABSTRACT FROM AUTHOR]

COVID-19, a severe respiratory disease caused by a new type of coronavirus SARS-CoV-2, has been spreading all over the world. Patients infected with SARS-CoV-2 may have no pathogenic symptoms, i.e., presymptomatic patients and asymptomatic patients. Both patients could further spread the virus to other susceptible people, thereby making the control of COVID-19 difficult. The two major challenges for COVID-19 diagnosis at present are as follows: (1) patients could share similar symptoms with other respiratory infections, and (2) patients may not have any symptoms but could still spread the virus. Therefore, new biomarkers at different omics levels are required for the large-scale screening and diagnosis of COVID-19. Although some initial analyses could identify a group of candidate gene biomarkers for COVID-19, the previous work still could not identify biomarkers capable for clinical use in COVID-19, which requires disease-specific diagnosis compared with other multiple infectious diseases. As an extension of the previous study, optimized machine learning models were applied in the present study to identify some specific qualitative host biomarkers associated with COVID-19 infection on the basis of a publicly released transcriptomic dataset, which included healthy controls and patients with bacterial infection, influenza, COVID-19, and other kinds of coronavirus. This dataset was first analysed by Boruta, Max-Relevance and Min-Redundancy feature selection methods one by one, resulting in a feature list. This list was fed into the incremental feature selection method, incorporating one of the classification algorithms to extract essential biomarkers and build efficient classifiers and classification rules. The capacity of these findings to distinguish COVID-19 with other similar respiratory infectious diseases at the transcriptomic level was also validated, which may improve the efficacy and accuracy of COVID-19 diagnosis. [ABSTRACT FROM AUTHOR]

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin–angiotensin–aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies. Here, using clinical samples and autopsy tissues, the authors combine fast-colorimetric test (LAMP) for SARS-CoV-2 infection and large-scale shotgun metatranscriptomics for host, viral, and microbial profiling and provide a map of the viral genetic features of the New York City outbreak and associate specific host responses and gene expression perturbations with SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) has been characterized by lymphopenia as well as a proinflammatory cytokine storm, which are responsible for the poor prognosis and multiorgan defects. The transcription factor nuclear factor-κB (NF-κB) modulates the functions of the immune cells and alters the gene expression profile of different cytokines in response to various pathogenic stimuli, while many proinflammatory factors have been known to induce NF-κB signalling cascade. Besides, NF-κB has been known to potentiate the production of reactive oxygen species (ROS) leading to apoptosis in various tissues in many diseases and viral infections. Though the reports on the involvement of the NF-κB signalling pathway in COVID-19 are limited, the therapeutic benefits of NF-κB inhibitors including dexamethasone, a synthetic form of glucocorticoid, have increasingly been realized. Considering the fact, the abnormal activation of the NF-κB resulting from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection might be associated with the pathogenic profile of immune cells, cytokine storm and multiorgan defects. Thus, the pharmacological inactivation of the NF-κB signalling pathway can strongly represent a potential therapeutic target to treat the symptomatology of COVID-19. This article signifies pharmacological blockade of the phosphorylation of inhibitor of nuclear factor kappa B kinase subunit beta (IKKβ), a key downstream effector of NF-κB signalling, for a therapeutic consideration to attenuate COVID-19. [ABSTRACT FROM AUTHOR]

Type 2 transmembrane serine protease (TMPRSS2) is a new member of the serine proteases, and studies have shown that TMPRSS2 plays a role in the occurrence of prostate malignancies and is closely related to the occurrence of the coronavirus disease 2019 (COVID-19). However, the role of TMPRSS2 in prostatic adenocarcinoma (PRAD) remains largely unclear. To better explore its function in PRAD, we examined the expression level of TMPRSS2 in the GEO, tumor immune assessment resource (TIMER), as well as Oncomine databases and studied the association between TMPRSS2 and overall survival (OS) rates in the UALCAN and gene expression profiling interactive analysis (GEPIA) databases. In addition, we studied the correlation of the level of immune infiltration and markers of immune cell type in the TIMER database, analyzed the prognosis based on the expression level of TMPRSS2 in the related immune cell subsets, and determined the methylation profile of TMPRSS2 promoter by UALCAN database. Subsequently, we conducted a survival analysis and gene ontology (GO) pathway analysis in the TISID database and detected the expression of TMPRSS2 in the Human Protein Atlas (HPA) database. We also studied the protein-protein interaction (PPI) network of TMPRSS2 in the GENEMANIA database. Additionally, we used the microarray GSE56677 and GSE52920 to illustrate changes in TMPRSS2 expression in vivo and in vitro after severe acute respiratory syndrome-coronavirus (SARS-COV) infection, finding that expression of TMPRSS2 decreased after SARS-COV infection in vitro. The function of TMPRSS2 in the dataset was further verified by gene set enrichment analysis (GSEA). In conclusion, the expression of TMPRSS2 is significantly increased in PRAD, elevated TMPRSS2 is associated with immune infiltration, and prognosis is positively correlated. In addition, tumor tissue from COVID-19 patients with PRAD may be more susceptible to infection with SARS-COV-2, which may render the prognosis gets worse. [ABSTRACT FROM AUTHOR]

Previous studies reported that Angiotensin converting enzyme 2 (ACE2) is the main cell receptor of SARS-CoV and SARS-CoV-2. It plays a key role in the access of the virus into the cell to produce the final infection. In the present study we investigated in silico the basic mechanism of ACE2 in the lung and provided evidences for new potentially effective drugs for Covid-19. Specifically, we used the gene expression profiles from public datasets including The Cancer Genome Atlas, Gene Expression Omnibus and Genotype-Tissue Expression, Gene Ontology and pathway enrichment analysis to investigate the main functions of ACE2-correlated genes. We constructed a protein-protein interaction network containing the genes co-expressed with ACE2. Finally, we focused on the genes in the network that are already associated with known drugs and evaluated their role for a potential treatment of Covid-19. Our results demonstrate that the genes correlated with ACE2 are mainly enriched in the sterol biosynthetic process, Aryldialkylphosphatase activity, adenosylhomocysteinase activity, trialkylsulfonium hydrolase activity, acetate-CoA and CoA ligase activity. We identified a network of 193 genes, 222 interactions and 36 potential drugs that could have a crucial role. Among possible interesting drugs for Covid-19 treatment, we found Nimesulide, Fluticasone Propionate, Thiabendazole, Photofrin, Didanosine and Flutamide. [ABSTRACT FROM AUTHOR]