Transcriptomic analysis of COVID‑19 lungs and bronchoalveolar lavage fluid samples reveals predominant B cell activation responses to infection

Differential Gene Expression of SARS-CoV-2 Positive Bronchoalveolar Lavages: A Case Series

BACKGROUND

Transcriptomic data on bronchoalveolar lavage (BAL) from COVID-19 patients are currently scarce.

OBJECTIVES

This case series seeks to characterize the intra-alveolar immunopathology of COVID-19.

METHOD

BALs were performed on 14 patients (5 COVID-19, of which 3 mild and 2 largely asymptomatic, 9 controls). Controls included asthma (n = 1), unremarkable BALs (n = 3), infections with respiratory syncytial virus (n = 1), influenza B (n = 1), and infections with other coronaviruses (n = 3). SARS-CoV-2 RNA load was measured by quantitative nucleic acid testing, while the detection of other pathogens was performed by immunofluorescence or multiplex NAT.

RESULTS

Gene expression profiling showed 71 significantly downregulated and 5 upregulated transcripts in SARS-CoV-2-positive lavages versus controls. Downregulated transcripts included genes involved in macrophage development, polarization, and crosstalk (LGALS3, MARCO, ERG2, BTK, RAC1, CD83), and genes involved in chemokine signaling and immunometabolism (NUPR1, CEBPB, CEBPA, PECAM1, CCL18, PPARG, ALOX5, ALOX5AP). Upregulated transcripts featured genes involved in NK-T cell signaling (GZMA, GZMH, GNLY, PRF1, CD3G). Patients with mild COVID-19 showed a significant upregulation of genes involved in blood mononuclear cell/leukocyte function (G0S2, ANXA6, FCGR2B, ADORA3), coagulation (von Willebrand factor [VWF]), interferon response (IFRD1, IL12RB2), and a zinc metalloprotease elevated in asthma (CPA3) compared to asymptomatic cases. In-silico comparison of the 5 COVID-19 BAL cases to a published cohort of lethal COVID-19 showed a significant upregulation of "antigen processing and presentation" and "lysosome" pathways in lethal cases.

CONCLUSIONS

These data underscore the heterogeneity of immune response in COVID-19. Further studies with a larger dataset are required to gain a better understanding of the hallmarks of SARS-CoV-2 immunological response.

Shared 6mer Peptides of Human and Omicron (21K and 21L) at SARS-CoV-2 Mutation Sites

We investigated the short sequences involving Omicron 21K and Omicron 21L variants to reveal any possible molecular mimicry-associated autoimmunity risks and changes in those. We first identified common 6mers of the viral and human protein sequences present for both the mutant (Omicron) and nonmutant (SARS-CoV-2) versions of the same viral sequence and then predicted the binding affinities of those sequences to the HLA supertype representatives. We evaluated change in the potential autoimmunity risk, through comparative assessment of the nonmutant and mutant viral sequences and their similar human peptides with common 6mers and affinities to the same HLA allele. This change is the lost and the new, or de novo, autoimmunity risk, associated with the mutations in the Omicron 21K and Omicron 21L variants. Accordingly, e.g., the affinity of virus-similar sequences of the Ig heavy chain junction regions shifted from the HLA-B*15:01 to the HLA-A*01:01 allele at the mutant sequences. Additionally, peptides of different human proteins sharing 6mers with SARS-CoV-2 proteins at the mutation sites of interest and with affinities to the HLA-B*07:02 allele, such as the respective SARS-CoV-2 sequences, were lost. Among all, any possible molecular mimicry-associated novel risk appeared to be prominent in HLA-A*24:02 and HLA-B*27:05 serotypes upon infection with Omicron 21L. Associated disease, pathway, and tissue expression data supported possible new risks for the HLA-B*27:05 and HLA-A*01:01 serotypes, while the risks for the HLA-B*07:02 serotypes could have been lost or diminished, and those for the HLA-A*03:01 serotypes could have been retained, for the individuals infected with Omicron variants under study. These are likely to affect the complications related to cross-reactions influencing the relevant HLA serotypes upon infection with Omicron 21K and Omicron 21L.

The current status of gene expression profilings in COVID‐19 patients

Background

The global pandemic of coronavirus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) has swept through every part of the world. Because of its impact, international efforts have been underway to identify the variants of SARS‐CoV‐2 by genome sequencing and to understand the gene expression changes in COVID‐19 patients compared to healthy donors using RNA sequencing (RNA‐seq) assay. Within the last two and half years since the emergence of SARS‐CoV‐2, a large number of OMICS data of COVID‐19 patients have accumulated. Yet, we are still far from understanding the disease mechanism. Further, many people suffer from long‐term effects of COVID‐19; calling for a more systematic way to data mine the generated OMICS data, especially RNA‐seq data.

Methods

By searching gene expression omnibus (GEO) using the key terms, COVID‐19 and RNA‐seq, 108 GEO entries were identified. Each of these studies was manually examined to categorize the studies into bulk or single‐cell RNA‐seq (scRNA‐seq) followed by an inspection of their original articles.

Results

The currently available RNA‐seq data were generated from various types of patients’ samples, and COVID‐19 related sample materials have been sequenced at the level of RNA, including whole blood, different components of blood [e.g., plasma, peripheral blood mononuclear cells (PBMCs), leukocytes, lymphocytes, monocytes, T cells], nasal swabs, and autopsy samples (e.g., lung, heart, liver, kidney). Of these, RNA‐seq studies using whole blood, PBMCs, nasal swabs and autopsy/biopsy samples were reviewed to highlight the major findings from RNA‐seq data analysis.

Conclusions

Based on the bulk and scRNA‐seq data analysis, severe COVID‐19 patients display shifts in cell populations, especially those of leukocytes and monocytes, possibly leading to cytokine storms and immune silence. These RNA‐seq data form the foundation for further gene expression analysis using samples from individuals suffering from long COVID.

Computational Analysis of Pathogenetic Pathways in Alzheimer’s Disease and Prediction of Potential Therapeutic Drugs

Background. Alzheimer’s disease (AD) is a chronic and progressive neurodegenerative disease which affects more than 50 million patients and represents 60–80% of all cases of dementia. Mutations in the APP gene, mostly affecting the γ-secretase site of cleavage and presenilin mutations, have been identified in inherited forms of AD. Methods. In the present study, we performed a meta-analysis of the transcriptional signatures that characterize two familial AD mutations (APP^V7171F and PSEN1^M146V) in order to characterize the common altered biomolecular pathways affected by these mutations. Next, an anti-signature perturbation analysis was performed using the AD meta-signature and the drug meta-signatures obtained from the L1000 database, using cosine similarity as distance metrics. Results. Overall, the meta-analysis identified 1479 differentially expressed genes (DEGs), 684 downregulated genes, and 795 upregulated genes. Additionally, we found 14 drugs with a significant anti-similarity to the AD signature, with the top five drugs being naftifine, moricizine, ketoconazole, perindopril, and fexofenadine. Conclusions. This study aimed to integrate the transcriptional profiles associated with common familial AD mutations in neurons in order to characterize the pathogenetic mechanisms involved in AD and to find more effective drugs for AD.

Eosinophil-mediated lung inflammation associated with elevated natural killer T cell response in COVID-19 patients

BACKGROUND/AIMS

Coronavirus disease 2019 (COVID-19) is associated with acute respiratory syndrome. The mechanisms underlying the different degrees of pneumonia severity in patients with COVID-19 remain elusive. This study provides evidence that COVID-19 is associated with eosinophil-mediated inflammation.

METHODS

We performed a retrospective case series of three patients with laboratory and radiologically confirmed COVID-19 pneumonia admitted to Chosun University Hospital. Demographic and clinical data on inflammatory cell lung infiltration and cytokine levels in patients with COVID-19 were collected.

RESULTS

Cytological analysis of sputum, tracheal aspirates, and bronchoalveolar lavage fluid (BALF) samples from all three patients revealed massive infiltration of polymorphonuclear cells (PMNs), such as eosinophils and neutrophils. All sputum and BALF specimens contained high levels of eosinophil cationic proteins. The infiltration of PMNs into the lungs, together with elevated levels of natural killer T (NKT) cells in BALF and peripheral blood samples from patients with severe pneumonia in the acute phase was confirmed by flow cytometry.

CONCLUSION

These results suggest that the lungs of COVID-19 patients can exhibit eosinophil-mediated inflammation, together with an elevated NKT cell response, which is associated with COVID-19 pneumonia.

Modeling SARS-CoV-2 Infection in Mice Using Lentiviral hACE2 Vectors Infers Two Modes of Immune Responses to SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a severe global pandemic. Mice models are essential to investigate infection pathology, antiviral drugs, and vaccine development. However, wild-type mice lack the human angiotensin-converting enzyme 2 (hACE2) that mediates SARS-CoV-2 entry into human cells and consequently are not susceptible to SARS-CoV-2 infection. hACE2 transgenic mice could provide an efficient COVID-19 model, but are not always readily available, and practically restricted to specific strains. Therefore, there is a dearth of additional mouse models for SARS-CoV-2 infection. We applied lentiviral vectors to generate hACE2 expression in interferon receptor knock-out (IFNAR1^−/−) mice. Lenti-hACE2 transduction supported SARS-CoV-2 replication in vivo, simulating mild acute lung disease. Gene expression analysis revealed two modes of immune responses to SARS-CoV-2 infection: one in response to the exposure of mouse lungs to SARS-CoV-2 particles in the absence of productive viral replication, and the second in response to productive SARS-CoV-2 infection. Our results infer that immune response to immunogenic elements on incoming virus or in productively infected cells stimulate diverse immune effectors, even in absence of type I IFN signaling. Our findings should contribute to a better understanding of the immune response triggered by SARS-CoV-2 and to further elucidate COVID-19.

Transcriptional Profiling and Machine Learning Unveil a Concordant Biosignature of Type I Interferon-Inducible Host Response Across Nasal Swab and Pulmonary Tissue for COVID-19 Diagnosis

Background

COVID-19, caused by SARS-CoV-2 virus, is a global pandemic with high mortality and morbidity. Limited diagnostic methods hampered the infection control. Since the direct detection of virus mainly by RT-PCR may cause false-negative outcome, host response-dependent testing may serve as a complementary approach for improving COVID-19 diagnosis.

Objective

Our study discovered a highly-preserved transcriptional profile of Type I interferon (IFN-I)-dependent genes for COVID-19 complementary diagnosis.

Methods

Computational language R-dependent machine learning was adopted for mining highly-conserved transcriptional profile (RNA-sequencing) across heterogeneous samples infected by SARS-CoV-2 and other respiratory infections. The transcriptomics/high-throughput sequencing data were retrieved from NCBI-GEO datasets (GSE32155, GSE147507, GSE150316, GSE162835, GSE163151, GSE171668, GSE182569). Mathematical approaches for homological analysis were as follows: adjusted rand index-related similarity analysis, geometric and multi-dimensional data interpretation, UpsetR, t-distributed Stochastic Neighbor Embedding (t-SNE), and Weighted Gene Co-expression Network Analysis (WGCNA). Besides, Interferome Database was used for predicting the transcriptional factors possessing IFN-I promoter-binding sites to the key IFN-I genes for COVID-19 diagnosis.

Results

In this study, we identified a highly-preserved gene module between SARS-CoV-2 infected nasal swab and postmortem lung tissue regulating IFN-I signaling for COVID-19 complementary diagnosis, in which the following 14 IFN-I-stimulated genes are highly-conserved, including BST2, IFIT1, IFIT2, IFIT3, IFITM1, ISG15, MX1, MX2, OAS1, OAS2, OAS3, OASL, RSAD2, and STAT1. The stratified severity of COVID-19 may also be identified by the transcriptional level of these 14 IFN-I genes.

Conclusion

Using transcriptional and computational analysis on RNA-seq data retrieved from NCBI-GEO, we identified a highly-preserved 14-gene transcriptional profile regulating IFN-I signaling in nasal swab and postmortem lung tissue infected by SARS-CoV-2. Such a conserved biosignature involved in IFN-I-related host response may be leveraged for COVID-19 diagnosis.

On Deep Landscape Exploration of COVID-19 Patients Cells and Severity Markers

COVID-19 is a disease with a spectrum of clinical responses ranging from moderate to critical. To study and control its effects, a large number of researchers are focused on two substantial aims. On the one hand, the discovery of diverse biomarkers to classify and potentially anticipate the disease severity of patients. These biomarkers could serve as a medical criterion to prioritize attention to those patients with higher prone to severe responses. On the other hand, understanding how the immune system orchestrates its responses in this spectrum of disease severities is a fundamental issue required to design new and optimized therapeutic strategies. In this work, using single-cell RNAseq of bronchoalveolar lavage fluid of nine patients with COVID-19 and three healthy controls, we contribute to both aspects. First, we presented computational supervised machine-learning models with high accuracy in classifying the disease severity (moderate and severe) in patients with COVID-19 starting from single-cell data from bronchoalveolar lavage fluid. Second, we identified regulatory mechanisms from the heterogeneous cell populations in the lungs microenvironment that correlated with different clinical responses. Given the results, patients with moderate COVID-19 symptoms showed an activation/inactivation profile for their analyzed cells leading to a sequential and innocuous immune response. In comparison, severe patients might be promoting cytotoxic and pro-inflammatory responses in a systemic fashion involving epithelial and immune cells without the possibility to develop viral clearance and immune memory. Consequently, we present an in-depth landscape analysis of how transcriptional factors and pathways from these heterogeneous populations can regulate their expression to promote or restrain an effective immune response directly linked to the patients prognosis.

Immunopathology and Immunosenescence, the Immunological Key Words of Severe COVID-19. Is There a Role for Stem Cell Transplantation?

The outcomes of Coronavirus disease-2019 (COVID-19) vary depending on the age, health status and sex of an individual, ranging from asymptomatic to lethal. From an immunologic viewpoint, the final severe lung damage observed in COVID-19 should be caused by cytokine storm, driven mainly by interleukin-6 and other pro-inflammatory cytokines. However, which immunopathogenic status precedes this "cytokine storm" and why the male older population is more severely affected, are currently unanswered questions. The aging of the immune system, i.e., immunosenescence, closely associated with a low-grade inflammatory status called "inflammageing," should play a key role. The remodeling of both innate and adaptive immune response observed with aging can partly explain the age gradient in severity and mortality of COVID-19. This review discusses how aging impacts the immune response to the virus, focusing on possible strategies to rejuvenate the immune system with stem cell-based therapies. Indeed, due to immunomodulatory and anti-inflammatory properties, multipotent mesenchymal stem cells (MSCs) are a worth-considering option against COVID-19 adverse outcomes.

Application of omics technology to combat the COVID-19 pandemic

As of August 27, 2021, the ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to over 220 countries, areas, and territories. Thus far, 214,468,601 confirmed cases, including 4,470,969 deaths, have been reported to the World Health Organization. To combat the COVID-19 pandemic, multiomics-based strategies, including genomics, transcriptomics, proteomics, and metabolomics, have been used to study the diagnosis methods, pathogenesis, prognosis, and potential drug targets of COVID-19. In order to help researchers and clinicians to keep up with the knowledge of COVID-19, we summarized the most recent progresses reported in omics-based research papers. This review discusses omics-based approaches for studying COVID-19, summarizing newly emerged SARS-CoV-2 variants as well as potential diagnostic methods, risk factors, and pathological features of COVID-19. This review can help researchers and clinicians gain insight into COVID-19 features, providing direction for future drug development and guidance for clinical treatment, so that patients can receive appropriate treatment as soon as possible to reduce the risk of disease progression.

Therapeutic Potential of Alpha-Lipoic Acid in Viral Infections, including COVID-19

Oxidative stress (OS), resulting from a disrupted balance between reactive oxygen species (ROS) and protective antioxidants, is thought to play an important pathogenetic role in several diseases, including viral infections. Alpha-lipoic acid (LA) is one of the most-studied and used natural compounds, as it is endowed with a well-defined antioxidant and immunomodulatory profile. Owing to these properties, LA has been tested in several chronic immunoinflammatory conditions, such as diabetic neuropathy and metabolic syndrome. In addition, a pharmacological antiviral profile of LA is emerging, that has attracted attention on the possible use of this compound for the cotreatment of several viral infections. Here, we will review the emerging literature on the potential use of LA in viral infections, including COVID-19.

Weighted Gene Co-Expression Network Analysis Combined with Machine Learning Validation to Identify Key Modules and Hub Genes Associated with SARS-CoV-2 Infection

The coronavirus disease-2019 (COVID-19) pandemic has caused an enormous loss of lives. Various clinical trials of vaccines and drugs are being conducted worldwide; nevertheless, as of today, no effective drug exists for COVID-19. The identification of key genes and pathways in this disease may lead to finding potential drug targets and biomarkers. Here, we applied weighted gene co-expression network analysis and LIME as an explainable artificial intelligence algorithm to comprehensively characterize transcriptional changes in bronchial epithelium cells (primary human lung epithelium (NHBE) and transformed lung alveolar (A549) cells) during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Our study detected a network that significantly correlated to the pathogenicity of COVID-19 infection based on identified hub genes in each cell line separately. The novel hub gene signature that was detected in our study, including PGLYRP4 and HEPHL1, may shed light on the pathogenesis of COVID-19, holding promise for future prognostic and therapeutic approaches. The enrichment analysis of hub genes showed that the most relevant biological process and KEGG pathways were the type I interferon signaling pathway, IL-17 signaling pathway, cytokine-mediated signaling pathway, and defense response to virus categories, all of which play significant roles in restricting viral infection. Moreover, according to the drug-target network, we identified 17 novel FDA-approved candidate drugs, which could potentially be used to treat COVID-19 patients through the regulation of four hub genes of the co-expression network. In conclusion, the aforementioned hub genes might play potential roles in translational medicine and might become promising therapeutic targets. Further in vitro and in vivo experimental studies are needed to evaluate the role of these hub genes in COVID-19.

Efficacy of Different Types of Therapy for COVID-19: A Comprehensive Review

A new coronavirus disease (COVID-19) has already affected millions of people in 213 countries. The possibilities of treatment have been reviewed in recent publications but there are many controversial results and conclusions. An analysis of the studies did not reveal a difference in mortality level between people treated with standard therapy, such as antiviral drugs and dexamethasone, and new antiviral drugs/additional immune therapy. However, most studies describe clinical improvement and a decrease in mortality among patients with severe and critical conditions, with the early initiation of additional immune therapy. Possible new targets based on viral life cycles were considered. Unfortunately, the data analysis on the efficacy of different medicine and therapy regimens among patients with COVID-19, showed little success in decreasing the mortality rate in all treatment methods. Some efficacy has been shown with an immunosuppressive therapy in small patient samples, but when a larger number of patients were analyzed the data did not differ significantly from the control groups.

COVID-19-associated diarrhea

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) recently emerged as a highly virulent respiratory pathogen that is known as the causative agent of coronavirus disease 2019 (COVID-19). Diarrhea is a common early symptom in a significant proportion of patients with SARS-CoV-2 infection. SARS-CoV-2 can infect and replicate in esophageal cells and enterocytes, leading to direct damage to the intestinal epithelium. The infection decreases the level of angiotensin-converting enzyme 2 receptors, thereby altering the composition of the gut microbiota. SARS-CoV-2 elicits a cytokine storm, which contributes to gastrointestinal inflammation. The direct cytopathic effects of SARS-CoV-2, gut dysbiosis, and aberrant immune response result in increased intestinal permeability, which may exacerbate existing symptoms and worsen the prognosis. By exploring the elements of pathogenesis, several therapeutic options have emerged for the treatment of COVID-19 patients, such as biologics and biotherapeutic agents. However, the presence of SARS-CoV-2 in the feces may facilitate the spread of COVID-19 through fecal-oral transmission and contaminate the environment. Thus gastrointestinal SARS-CoV-2 infection has important epidemiological significance. The development of new therapeutic and preventive options is necessary to treat and restrict the spread of this severe and widespread infection more effectively. Therefore, we summarize the key elements involved in the pathogenesis and the epidemiology of COVID-19-associated diarrhea.

Reduced frequency of T helper 17 and T helper 1 cells and their association with critical coronavirus disease 2019

There is very little knowledge about the immune responses, particularly cellular immunity to coronavirus disease 2019 (COVID-19). The main objective of this study was to evaluate the frequency of T helper (Th) cell subtypes, including Th1, Th17, and Treg cells, in moderate-to-severe and critical COVID-19 patients compared to healthy controls. Twenty-nine moderate-to-severe and 13 critical patients confirmed for COVID-19, and 15 healthy subjects were included in this study. Interferon-γ (IFN-γ)-producing Th1 and interleukin-17A-producing Th17 and Treg cells in peripheral blood were measured with flow cytometry. The frequency of Th1 and Th17 was significantly decreased in critical patients compared to healthy subjects (aMD: -2.76 and - 2.34) and moderate-to-severe patients (aMD: -1.89 and - 1.89), respectively (p < 0.05). Differences were not significant between moderate-to-severe patients and healthy subjects for both Th1 (p = 0.358) and Th17 (p = 0.535), respectively. In contrast, significant difference was not observed between study subjects regarding the frequency of Treg cells. Patients with critical COVID-19 had a markedly lower Th1/Treg and Th17/Treg ratios compared with the controls and moderate-to-severe cases. Our study showed a dysregulated balance of Th1 and Th17 cells and its relation to the severity of COVID-19.

Demystifying Excess Immune Response in COVID-19 to Reposition an Orphan Drug for Down-Regulation of NF-κB: A Systematic Review

The immunological findings from autopsies, biopsies, and various studies in COVID-19 patients show that the major cause of morbidity and mortality in COVID-19 is excess immune response resulting in hyper-inflammation. With the objective to review various mechanisms of excess immune response in adult COVID-19 patients, Pubmed was searched for free full articles not related to therapeutics or co-morbid sub-groups, published in English until 27.10.2020, irrespective of type of article, country, or region. Joanna Briggs Institute's design-specific checklists were used to assess the risk of bias. Out of 122 records screened for eligibility, 42 articles were included in the final review. The review found that eventually, most mechanisms result in cytokine excess and up-regulation of Nuclear Factor-κB (NF-κB) signaling as a common pathway of excess immune response. Molecules blocking NF-κB or targeting downstream effectors like Tumour Necrosis Factor α (TNFα) are either undergoing clinical trials or lack specificity and cause unwanted side effects. Neutralization of upstream histamine by histamine-conjugated normal human immunoglobulin has been demonstrated to inhibit the nuclear translocation of NF-κB, thereby preventing the release of pro-inflammatory cytokines Interleukin (IL) 1β, TNF-α, and IL-6 and IL-10 in a safer manner. The authors recommend repositioning it in COVID-19.

SARS-CoV-2 early infection signature identified potential key infection mechanisms and drug targets

Background

The ongoing COVID-19 outbreak has caused devastating mortality and posed a significant threat to public health worldwide. Despite the severity of this illness and 2.3 million worldwide deaths, the disease mechanism is mostly unknown. Previous studies that characterized differential gene expression due to SARS-CoV-2 infection lacked robust validation. Although vaccines are  now available, effective treatment options are still out of reach.

Results

To characterize the transcriptional activity of SARS-CoV-2 infection, a gene signature consisting of 25 genes was generated using a publicly available RNA-Sequencing (RNA-Seq) dataset of cultured cells infected with SARS-CoV-2. The signature estimated infection level accurately in bronchoalveolar lavage fluid (BALF) cells and peripheral blood mononuclear cells (PBMCs) from healthy and infected patients (mean 0.001 vs. 0.958; P < 0.0001). These signature genes were investigated in their ability to distinguish the severity of SARS-CoV-2 infection in a single-cell RNA-Sequencing dataset. TNFAIP3, PPP1R15A, NFKBIA, and IFIT2 had shown bimodal gene expression in various immune cells from severely infected patients compared to healthy or moderate infection cases. Finally, this signature was assessed using the publicly available ConnectivityMap database to identify potential disease mechanisms and drug repurposing candidates. Pharmacological classes of tricyclic antidepressants, SRC-inhibitors, HDAC inhibitors, MEK inhibitors, and drugs such as atorvastatin, ibuprofen, and ketoconazole showed strong negative associations (connectivity score < − 90), highlighting the need for further evaluation of these candidates for their efficacy in treating SARS-CoV-2 infection.

Conclusions

Thus, using the 25-gene SARS-CoV-2 infection signature, the SARS-CoV-2 infection status was captured in BALF cells, PBMCs and postmortem lung biopsies. In addition, candidate SARS-CoV-2 therapies with known safety profiles were identified. The signature genes could potentially also be used to characterize the COVID-19 disease severity in patients’ expression profiles of BALF cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07433-4.

Comprehensive Meta-Analysis of COVID-19 Global Metabolomics Datasets

The novel coronavirus SARS-CoV-2 has spread across the world since 2019, causing a global pandemic. The pathogenesis of the viral infection and the associated clinical presentations depend primarily on host factors such as age and immunity, rather than the viral load or its genetic variations. A growing number of omics studies have been conducted to characterize the host immune and metabolic responses underlying the disease progression. Meta-analyses of these datasets have great potential to identify robust molecular signatures to inform clinical care and to facilitate therapeutics development. In this study, we performed a comprehensive meta-analysis of publicly available global metabolomics datasets obtained from three countries (United States, China and Brazil). To overcome high heterogeneity inherent in these datasets, we have (a) implemented a computational pipeline to perform consistent raw spectra processing; (b) conducted meta-analyses at pathway levels instead of individual feature levels; and (c) performed visual data mining on consistent patterns of change between disease severities for individual studies. Our analyses have yielded several key metabolic signatures characterizing disease progression and clinical outcomes. Their biological interpretations were discussed within the context of the current literature. To the best of our knowledge, this is the first comprehensive meta-analysis of global metabolomics datasets of COVID-19.

Targeting pivotal inflammatory pathways in COVID-19: A mechanistic review

As an emerging global health crisis, coronavirus disease 2019 (COVID-19) has been labeled a worldwide pandemic. Growing evidence is revealing further pathophysiological mechanisms of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Amongst these dysregulated pathways inflammation seems to play a more critical role toward COVID-19 complications. In the present study, precise inflammatory pathways triggered by SARS-CoV-2, along with potential therapeutic candidates have been discussed. Prevailing evidence has indicated a close correlation of inflammatory cascades with severity, pathological progression, and organ damages in COVID-19 patients. From the mechanistic point of view, interleukin-6, interleukin-1β receptor, interferon-gamma, tumor necrosis factor-alpha receptor, toll-like receptor, receptor tyrosine kinases, growth factor receptor, Janus kinase/signal transducers and transcription pathway, mammalian target of rapamycin, cytokine storm and macrophage activation have shown to play critical roles in COVID-19 complications. So, there is an urgent need to provide novel mechanistic-based anti-inflammatory agents. This review highlights inflammatory signaling pathways of SARS-CoV-2. Several therapeutic targets and treatment strategies have also been provided in an attempt to tackle COVID-19 complications.

SARS-CoV-2 Infection-Induced Promoter Hypomethylation as an Epigenetic Modulator of Heat Shock Protein A1L (HSPA1L) Gene

Numerous researches have focused on the genetic variations affecting SARS-CoV-2 infection, whereas the epigenetic effects are inadequately described. In this report, for the first time, we have identified potential candidate genes that might be regulated via SARS-CoV-2 induced DNA methylation changes in COVID-19 infection. At first, in silico transcriptomic data of COVID-19 lung autopsies were used to identify the top differentially expressed genes containing CpG Islands in their promoter region. Similar gene regulations were also observed in an in vitro model of SARS-CoV-2 infected lung epithelial cells (NHBE and A549). SARS-CoV-2 infection significantly decreased the levels of DNA methyltransferases (DNMT1, DNMT3A, and DNMT3B) in lung epithelial cells. Out of 14 candidate genes identified, the expression of 12 genes was upregulated suggesting promoter hypomethylation, while only two genes were downregulated suggesting promoter hypermethylation in COVID-19. Among those 12 upregulated genes, only HSPA1L and ULBP2 were found to be upregulated in AZA-treated lung epithelial cells and immune cells, suggesting their epigenetic regulation. To confirm the hypomethylation of these two genes during SARS-CoV-2 infection, their promoter methylation and mRNA expression levels were determined in the genomic DNA/RNA obtained from whole blood samples of asymptomatic, severe COVID-19 patients and equally matched healthy controls. The methylation level of HSPA1L was significantly decreased and the mRNA expression was increased in both asymptomatic and severe COVID-19 blood samples suggesting its epigenetic regulation by SARS-CoV-2 infection. Functionally, HSPA1L is known to facilitate host viral replication and has been proposed as a potential target for antiviral prophylaxis and treatment.

Host transcriptomic profiling of COVID-19 patients with mild, moderate, and severe clinical outcomes

Characterizing key molecular and cellular pathways involved in COVID-19 is essential for disease prognosis and management. We perform shotgun transcriptome sequencing of human RNA obtained from nasopharyngeal swabs of patients with COVID-19, and identify a molecular signature associated with disease severity. Specifically, we identify globally dysregulated immune related pathways, such as cytokine-cytokine receptor signaling, complement and coagulation cascades, JAK-STAT, and TGF- β signaling pathways in all, though to a higher extent in patients with severe symptoms. The excessive release of cytokines and chemokines such as CCL2, CCL22, CXCL9 and CXCL12 and certain interferons and interleukins related genes like IFIH1, IFI44, IFIT1 and IL10 were significantly higher in patients with severe clinical presentation compared to mild and moderate presentations. Differential gene expression analysis identified a small set of regulatory genes that might act as strong predictors of patient outcome. Our data suggest that rapid transcriptome analysis of nasopharyngeal swabs can be a powerful approach to quantify host molecular response and may provide valuable insights into COVID-19 pathophysiology.

Integrative transcriptomics analysis of lung epithelial cells and identification of repurposable drug candidates for COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease, more commonly COVID-19 has emerged as a world health pandemic. There are couples of treatment methods for COVID-19, however, well-established drugs and vaccines are urgently needed to treat the COVID-19. The new drug discovery is a tremendous challenge; repurposing of existing drugs could shorten the time and expense compared with de novo drug development. In this study, we aimed to decode molecular signatures and pathways of the host cells in response to SARS-CoV-2 and the rapid identification of repurposable drugs using bioinformatics and network biology strategies. We have analyzed available transcriptomic RNA-seq COVID-19 data to identify differentially expressed genes (DEGs). We detected 177 DEGs specific for COVID-19 where 122 were upregulated and 55 were downregulated compared to control (FDR<0.05 and logFC ≥ 1). The DEGs were significantly involved in the immune and inflammatory response. The pathway analysis revealed the DEGs were found in influenza A, measles, cytokine signaling in the immune system, interleukin-4, interleukin -13, interleukin -17 signaling, and TNF signaling pathways. Protein-protein interaction analysis showed 10 hub genes (BIRC3, ICAM1, IRAK2, MAP3K8, S100A8, SOCS3, STAT5A, TNF, TNFAIP3, TNIP1). The regulatory network analysis showed significant transcription factors (TFs) that target DEGs, namely FOXC1, GATA2, YY1, FOXL1, NFKB1. Finally, drug repositioning analysis was performed with these 10 hub genes and showed that in silico validated three drugs with molecular docking. The transcriptomics signatures, molecular pathways, and regulatory biomolecules shed light on candidate biomarkers and drug targets which have potential roles to manage COVID-19. ICAM1 and TNFAIP3 were the key hubs that have demonstrated good binding affinities with repurposed drug candidates. Dabrafenib, radicicol, and AT-7519 were the top-scored repurposed drugs that showed efficient docking results when they tested with hub genes. The identified drugs should be further evaluated in molecular level wet-lab experiments in prior to clinical studies in the treatment of COVID-19.

Emerging Neurological and Psychobiological Aspects of COVID-19 Infection

The SARS-CoV-2 virus, first reported in December 2019 in China, is the causative agent of the current COVID-19 pandemic that, at the time of writing (1 November 2020) has infected almost 43 million people and caused the death of more than 1 million people. The spectrum of clinical manifestations observed during COVID-19 infection varies from asymptomatic to critical life-threatening clinical conditions. Emerging evidence shows that COVID-19 affects far more organs than just the respiratory system, including the heart, kidneys, blood vessels, liver, as well as the central nervous system (CNS) and the peripheral nervous system (PNS). It is also becoming clear that the neurological and psychological disturbances that occur during the acute phase of the infection may persist well beyond the recovery. The aim of this review is to propel further this emerging and relevant field of research related to the pathophysiology of neurological manifestation of COVID-19 infection (Neuro-COVID). We will summarize the PNS and CNS symptoms experienced by people with COVID-19 both during infection and in the recovery phase. Diagnostic and pharmacological findings in this field of study are strongly warranted to address the neurological and psychological symptoms of COVID-19.