Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Nain, Zulkar; Barman, Shital Kumar; Sheam, Md. Moinuddin; Syed, Shifath Bin; Samad, Abdus; Quinn, Julian M.W.; Karim, Mohammad Minnatul; Himel, Mahbubul Kabir; Roy, Rajib Kanti; Moni, Mohammad Ali; Biswas, Sudhangshu Kumar

doi:10.1093/bib/bbab197

Cited by 19 publications

(13 citation statements)

References 104 publications

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“…TF NRF1 can also target gene TFAM , which encodes TFAM that regulates the homeostasis of mitochondria. Similarly, previous studies have reported that downregulated SIRT1 and PGC1α were observed in COVID-19 patients [ 109 , 110 , 111 ]. We observed the lower expression level of SIRT1, which could be due to the inhibitory effect of MALAT1 [ 112 ].…”

Section: Resultssupporting

confidence: 74%

Repurposing Multiple-Molecule Drugs for COVID-19-Associated Acute Respiratory Distress Syndrome and Non-Viral Acute Respiratory Distress Syndrome via a Systems Biology Approach and a DNN-DTI Model Based on Five Drug Design Specifications

Ting

Chen

2022

IJMS

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The coronavirus disease 2019 (COVID-19) epidemic is currently raging around the world at a rapid speed. Among COVID-19 patients, SARS-CoV-2-associated acute respiratory distress syndrome (ARDS) is the main contribution to the high ratio of morbidity and mortality. However, clinical manifestations between SARS-CoV-2-associated ARDS and non-SARS-CoV-2-associated ARDS are quite common, and their therapeutic treatments are limited because the intricated pathophysiology having been not fully understood. In this study, to investigate the pathogenic mechanism of SARS-CoV-2-associated ARDS and non-SARS-CoV-2-associated ARDS, first, we constructed a candidate host-pathogen interspecies genome-wide genetic and epigenetic network (HPI-GWGEN) via database mining. With the help of host-pathogen RNA sequencing (RNA-Seq) data, real HPI-GWGEN of COVID-19-associated ARDS and non-viral ARDS were obtained by system modeling, system identification, and Akaike information criterion (AIC) model order selection method to delete the false positives in candidate HPI-GWGEN. For the convenience of mitigation, the principal network projection (PNP) approach is utilized to extract core HPI-GWGEN, and then the corresponding core signaling pathways of COVID-19-associated ARDS and non-viral ARDS are annotated via their core HPI-GWGEN by KEGG pathways. In order to design multiple-molecule drugs of COVID-19-associated ARDS and non-viral ARDS, we identified essential biomarkers as drug targets of pathogenesis by comparing the core signal pathways between COVID-19-associated ARDS and non-viral ARDS. The deep neural network of the drug–target interaction (DNN-DTI) model could be trained by drug–target interaction databases in advance to predict candidate drugs for the identified biomarkers. We further narrowed down these predicted drug candidates to repurpose potential multiple-molecule drugs by the filters of drug design specifications, including regulation ability, sensitivity, excretion, toxicity, and drug-likeness. Taken together, we not only enlighten the etiologic mechanisms under COVID-19-associated ARDS and non-viral ARDS but also provide novel therapeutic options for COVID-19-associated ARDS and non-viral ARDS.

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Section: Resultssupporting

confidence: 74%

Repurposing Multiple-Molecule Drugs for COVID-19-Associated Acute Respiratory Distress Syndrome and Non-Viral Acute Respiratory Distress Syndrome via a Systems Biology Approach and a DNN-DTI Model Based on Five Drug Design Specifications

Ting

Chen

2022

IJMS

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“…Additionally, some of the purple module hub-high traffic genes, such as MAPK1 ( 189 , 374 ), CUL2 ( 210 ), CMTM6 ( 162 ), TXNRD1 ( 375 ), RAB1A ( 376 ), DICER1 ( 377 ), RAB5A ( 209 ), HSP90B1 ( 343 ), MAGT1 ( 378 ), ADAM10 ( 379 , 380 ), SNX2 ( 89 ), OLA1 ( 381 ), SPTLC1 ( 382 ), SH3GLB1 ( 383 ), TIMM10B ( 384 ), and CREB1 ( 385 ) hub-high traffic TF, which are central for information exchange in this module, are potential targets for development of COVID-19 therapeutic strategies. Among these, the mitogen-activated protein kinase 1 ( MAPK1 ) hub-high traffic gene is a potential core target for many anti-COVID-19 therapeutic strategies ( 189 , 374 , 386 – 390 ).…”

Section: Discussionmentioning

confidence: 99%

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

et al. 2021

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BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches.MethodsRNA-Seq data from peripheral blood mononuclear cells (PBMCs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules.ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19’s main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis.ConclusionThis study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic.

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“…Expression profile observed in COVID-19 samples (GSE147507) has similar DEGs as seen with other diseases and comorbidities such as liver cirrhosis, influenza, and colonic neoplasms. These DEGs are also positively regulated in respiratory diseases, arthritis, psoriasis, glioblastoma, Crohn’s disease, ulcerative colitis, colorectal cancer, skin diseases, pneumonia, keratosis, lupus erythematosus, esophageal cancer ( Nain et al., 2021 ). Single-cell transcriptome analyses of colon mucosae of normal, colorectal adenoma (CRA), and colorectal cancer (CRC) patients have shown increased expression of SARS-CoV2 entry-related genes such as ACE2, CD147 (Basigin), TMPRSS2, Cathepsin B (CATB), Cathepsin L (CATL), and Furin.…”

Section: Host Gene Expressions In Liver and Gi Tissue Of Sars-cov2-infected Patientsmentioning

confidence: 99%

Host Response to SARS-CoV2 and Emerging Variants in Pre-Existing Liver and Gastrointestinal Diseases

Nayak

Lal

Kumar

et al. 2021

Front. Cell. Infect. Microbiol.

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BackgroundNovel coronavirus SARS-CoV2 is evolving continuously with emergence of several variants of increasing transmission capabilities and pandemic potential. Generation of variants occurs through accumulation of mutations due to the RNA nature of viral genome, which is further enhanced by variable selection pressures of this ongoing pandemic. COVID-19 presentations of SARS-CoV2 are mainly pulmonary manifestations with or without mild gastrointestinal (GI) and hepatic symptoms. However, the virus has evolved beyond pulmonary manifestations to multisystem disorder due to systemic inflammation and cytokine storm. Definitive cause of acute or late onset of inflammation, infection in various organs, and host response to emerging variants lacks clarity and needs elucidation. Several studies have reported underlying diseases including diabetes, hypertension, obesity, cardio- and cerebrovascular disorders, and immunocompromised conditions as significant risk factors for severe form of COVID-19. Pre-existing liver and GI diseases are also highly predominant in the population, which can alter COVID-19 outcome due to altered immune status and host response. We aim to review the emerging variants of SARS-CoV2 and host response in patients with pre-existing liver and GI diseases.MethodsIn this review, we have elucidated the emergence and characteristic features of new SARS-CoV2 variants, mechanisms of infection and host immune response, GI and hepatic manifestation with radiologic features of COVID-19, and outcomes in pre-existing liver and GI diseases.Key FindingsEmerging variants of concern (VOC) have shown increased transmissibility and virulence with severe COVID-19 presentation and mortality. There is a drastic swift of variants from the first wave to the next wave of infections with predominated major VOC including alpha (B.1.1.7, UK), beta (B.1.351, South Africa), gamma (B.1.1.28.1, Brazil), and delta (B1.1.617, India) variants. The mutations in the spike protein of VOC are implicated for increased receptor binding (N501Y, P681R) and immune escape (L452R, E484K/Q, T478K/R) to host response. Pre-existing liver and GI diseases not only have altered tissue expression and distribution of viral entry ACE2 receptor but also host protease TMPRSS2, which is required for both spike protein binding and cleavage to initiate infection. Altered immune status due to pre-existing conditions results in delayed virus clearance or prolonged viremia. Even though GI and hepatic manifestations of SARS-CoV2 are less severe, the detection of virus in patient’s stool indicates GI tropism, replication, and shedding from the GI tract. COVID-19-induced liver injury, acute hepatic decompensation, and incidences of acute-on-chronic liver failure may change the disease outcomes.ConclusionsThe changes in the spike protein of emerging variants, immunomodulation by viral proteins, and altered expression of host viral entry receptor in pre-existing diseases are the key determinants of host response to SARS-CoV2 and its disease outcome.

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Transcriptomic studies revealed pathophysiological impact of COVID-19 to predominant health conditions

Cited by 19 publications

References 104 publications

Repurposing Multiple-Molecule Drugs for COVID-19-Associated Acute Respiratory Distress Syndrome and Non-Viral Acute Respiratory Distress Syndrome via a Systems Biology Approach and a DNN-DTI Model Based on Five Drug Design Specifications

Repurposing Multiple-Molecule Drugs for COVID-19-Associated Acute Respiratory Distress Syndrome and Non-Viral Acute Respiratory Distress Syndrome via a Systems Biology Approach and a DNN-DTI Model Based on Five Drug Design Specifications

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

Host Response to SARS-CoV2 and Emerging Variants in Pre-Existing Liver and Gastrointestinal Diseases

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