Insight into molecular mechanisms underlying hepatic dysfunction in severe COVID-19 patients using systems biology

Uncovering the Effect of SARS-CoV-2 on Liver Metabolism via Genome-Scale Metabolic Modeling for Reprogramming and Therapeutic Strategies

Genome-scale metabolic models (GEMs) are promising computational tools that contribute to elucidating host-virus interactions at the system level and developing therapeutic strategies against viral infection. In this study, the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on liver metabolism was investigated using integrated GEMs of human hepatocytes and SARS-CoV-2. They were generated for uninfected and infected hepatocytes using transcriptome data. Reporter metabolite analysis resulted in significant transcriptional changes around several metabolites involved in xenobiotics, drugs, arachidonic acid, and leukotriene metabolisms due to SARS-CoV-2 infection. Flux balance analysis and minimization of metabolic adjustment approaches unraveled possible virus-induced hepatocellular reprogramming in fatty acid, glycerophospholipid, sphingolipid cholesterol, and folate metabolisms, bile acid biosynthesis, and carnitine shuttle among others. Reaction knockout analysis provided critical reactions in glycolysis, oxidative phosphorylation, purine metabolism, and reactive oxygen species detoxification subsystems. Computational analysis also showed that administration of dopamine, glucosamine, D-xylose, cysteine, and (R)-3-hydroxybutanoate contributes to alleviating viral infection. In essence, the reconstructed host-virus GEM helps us understand metabolic programming and develop therapeutic strategies to battle SARS-CoV-2.

Identification of shared biological features in four different lung cell lines infected with SARS-CoV-2 virus through RNA-seq analysis

The COVID-19 pandemic caused by SARS-CoV-2 has resulted in millions of confirmed cases and deaths worldwide. Understanding the biological mechanisms of SARS-CoV-2 infection is crucial for the development of effective therapies. This study conducts differential expression (DE) analysis, pathway analysis, and differential network (DN) analysis on RNA-seq data of four lung cell lines, NHBE, A549, A549.ACE2, and Calu3, to identify their common and unique biological features in response to SARS-CoV-2 infection. DE analysis shows that cell line A549.ACE2 has the highest number of DE genes, while cell line NHBE has the lowest. Among the DE genes identified for the four cell lines, 12 genes are overlapped, associated with various health conditions. The most significant signaling pathways varied among the four cell lines. Only one pathway, "cytokine-cytokine receptor interaction", is found to be significant among all four cell lines and is related to inflammation and immune response. The DN analysis reveals considerable variation in the differential connectivity of the most significant pathway shared among the four lung cell lines. These findings help to elucidate the mechanisms of SARS-CoV-2 infection and potential therapeutic targets.

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

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

Reductionist methodology and the ambiguity of the categories of race and ethnicity in biomedical research: an exploratory study of recent evidence

In this article, we analyse how researchers use the categories of race and ethnicity with reference to genetics and genomics. We show that there is still considerable conceptual "messiness" (despite the wide-ranging and popular debate on the subject) when it comes to the use of ethnoracial categories in genetics and genomics that among other things makes it difficult to properly compare and interpret research using ethnoracial categories, as well as draw conclusions from them. Finally, we briefly reconstruct some of the biases of reductionism to which geneticists (as well as other researchers referring to genetic methods and explanations) are particularly exposed to, and we analyse the problem in the context of the biologization of ethnoracial categories. Our work constitutes a novel, in-depth contribution to the debate about reporting race and ethnicity in biomedical and health research. First, we reconstruct the theoretical background assumptions about racial ontology which researchers implicitly presume in their studies with the aid of a sample of recent papers published in medical journals about COVID-19. Secondly, we use the typology of the biases of reductionism to the problem of biologization of ethnoracial categories with reference to genetics and genomics.

Role of different types of RNA molecules in the severity prediction of SARS-CoV-2 patients

SARS-CoV-2 pandemic is the current threat of the world with enormous number of deceases. As most of the countries have constraints on resources, particularly for intensive care and oxygen, severity prediction with high accuracy is crucial. This prediction will help the medical society in the selection of patients with the need for these constrained resources. Literature shows that using clinical data in this study is the common trend and molecular data is rarely utilized in this prediction. As molecular data carry more disease related information, in this study, three different types of RNA molecules ( lncRNA, miRNA and mRNA) of SARS-COV-2 patients are used to predict the severity stage and treatment stage of those patients. Using seven different machine learning algorithms along with several feature selection techniques shows that in both phenotypes, feature importance selected features provides the best accuracy along with random forest classifier. Further to this, it shows that in the severity stage prediction miRNA and lncRNA give the best performance, and lncRNA data gives the best in treatment stage prediction. As most of the studies related to molecular data uses mRNA data, this is an interesting finding.

Clinical implications of COVID-19 in patients with metabolic-associated fatty liver disease

People across the world are affected by the "coronavirus disease 2019 (COVID-19)", brought on by the "SARS-CoV type-2 coronavirus". Due to its high incidence in individuals with diabetes, metabolic syndrome, and metabolic-associated fatty liver disease (MAFLD), COVID-19 has gained much attention. The metabolic syndrome's hepatic manifestation, MAFLD, carries a significant risk of type-2-diabetes. The link between the above two conditions has also drawn increasing consideration since MAFLD is intricately linked to the obesity epidemic. Independent of the metabolic syndrome, MAFLD may impact the severity of the viral infections, including COVID-19 or may even be a risk factor. An important question is whether the present COVID-19 pandemic has been fueled by the obesity and MAFLD epidemics. Many liver markers are seen elevated in COVID-19. MAFLD patients with associated comorbid conditions like obesity, cardiovascular disease, renal disease, malignancy, hypertension, and old age are prone to develop severe disease. There is an urgent need for more studies to determine the link between the two conditions and whether it might account for racial differences in the mortality and morbidity rates linked to COVID-19. The role of innate and adaptive immunity alterations in MAFLD patients may influence the severity of COVID-19. This review investigates the implications of COVID-19 on liver injury and disease severity and vice-versa. We also addressed the severity of COVID-19 in patients with prior MAFLD and its potential implications and therapeutic administration in the clinical setting.

Association of COVID-19 with hepatic metabolic dysfunction

The coronavirus disease 2019 (COVID-19) pandemic continues to be a global problem with over 438 million cases reported so far. Although it mostly affects the respiratory system, the involvement of extrapulmonary organs, including the liver, is not uncommon. Since the beginning of the pandemic, metabolic com-orbidities, such as obesity, diabetes, hypertension, and dyslipidemia, have been identified as poor prognostic indicators. Subsequent metabolic and lipidomic studies have identified several metabolic dysfunctions in patients with COVID-19. The metabolic alterations appear to be linked to the course of the disease and inflammatory reaction in the body. The liver is an important organ with high metabolic activity, and a significant proportion of COVID-19 patients have metabolic comorbidities; thus, this factor could play a key role in orchestrating systemic metabolic changes during infection. Evidence suggests that metabolic dysregulation in COVID-19 has both short- and long-term metabolic implications. Furthermore, COVID-19 has adverse associations with metabolic-associated fatty liver disease. Due to the ensuing effects on the renin-angiotensin-aldosterone system and ammonia metabolism, COVID-19 can have significant implications in patients with advanced chronic liver disease. A thorough understanding of COVID-19-associated metabolic dysfunction could lead to the identification of important plasma biomarkers and novel treatment targets. In this review, we discuss the current understanding of metabolic dysfunction in COVID-19, focusing on the liver and exploring the underlying mechanistic pathogenesis and clinical implications.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways

Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.proteomics.wustl.edu/ ). Using those proteins and machine learning approached we created and validated specific prediction models for ventilation (AUC>0.91), death (AUC>0.95) and either outcome (AUC>0.80). These proteins were also enriched in specific biological processes, including immune and cytokine signaling (FDR ≤ 3.72×10 -14 ), Alzheimer's disease (FDR ≤ 5.46×10 -10 ) and coronary artery disease (FDR ≤ 4.64×10 -2 ). Mendelian randomization using pQTL as instrumental variants nominated BCAT2 and GOLM1 as a causal proteins for COVID-19. Causal gene network analyses identified 141 highly connected key proteins, of which 35 have known drug targets with FDA-approved compounds. Our findings provide distinctive prognostic biomarkers for two severe COVID-19 outcomes (ventilation and death), reveal their relationship to Alzheimer's disease and coronary artery disease, and identify potential therapeutic targets for COVID-19 outcomes.

Chest Computed Tomography Is an Efficient Method for Initial Diagnosis of COVID-19: An Observational Study

Coronavirus disease (COVID-19) is an infectious disease that can lead to pneumonia, pulmonary oedema, acute respiratory distress syndrome, multiple organ and system dysfunction, and death. This study aimed to verify the efficacy of chest computed tomography (CT) for the initial diagnosis of COVID-19. This observational, retrospective, cross-sectional study included 259 individuals who underwent clinical evaluation, blood collection, chest CT, and a reverse transcription polymerase chain reaction (RT-PCR) diagnostic test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during their course of treatment at a reference hospital in Belém, Pará, Brazil between April and June 2020. Inclusion criteria were flu-like symptoms in adults of both sexes. Individuals with an inconclusive COVID-19 molecular test or who had artifacts in the chest CT images were excluded. Parametric data were analyzed using Student-t-test and non-parametric data were analyzed using average test and Fisher exact test. Participants were divided into two groups: Group 1 (COVID-19 positive), n = 211 (124 males, 87 females), 51.8 ± 17.9 years old and Group 2 (COVID-19 negative), n = 48 (22 males, 26 females), 47.6 ± 18.6 years old. Most frequent symptoms were cough [Group 1 n = 199 (94%)/Group 2 n = 46 (95%)], fever [Group 1 n = 154 (72%)/Group 2 n = 28 (58%)], myalgia [Group 1 n = 172 (81%)/Group 2 n = 38 (79%)], dyspnoea [Group 1 n = 169 (80%) / Group 2 n = 37 (77%)], headache [Group 1 n = 163 (77%)/Group 2 n = 32 (66%)], and anosmia [Group 1 n = 154 (73%)/Group 2 n = 29 (60%)]. Group 1 had a higher proportion of ground-glass opacity [Group 1 n = 175 (83%)/Group 2 n = 24 (50%), 0.00], vascular enhancement sign [Group 1 n = 128 (60%)/Group 2 n = 15 (31%), 0.00], septal thickening [Group 1 n = 99 (47%)/Group 2 n = 13 (27%), 0.01], crazy-paving pattern [Group 1 n = 98 (46%) / Group 2 n = 13 (27%), 0.01], consolidations [Group 1 n = 92 (43%)/Group 2 n = 8 (16%), 0.00], and CO-RADS 4 and 5 [Group 1 n = 163 (77.25%)/Group 2 n = 24 (50%), 0.00] categories in chest CT. Chest CT, when available, was found to be an efficient method for the initial diagnosis and better management of individuals with COVID-19.

Downregulation of CYP39A1 Serves as a Novel Biomarker in Hepatocellular Carcinoma with Worse Clinical Outcome

Background

CYP39A1 is a poorly characterized metabolic enzyme that has been investigated in a few tumors. However, the role of CYP39A1 in hepatocellular carcinoma (HCC) has not yet been clarified. In this study, the expression and clinical significance of CYP39A1 in HCC were explored.

Methods

CYP39A1 protein expression was detected in Akt/c-Met-induced HCC mice and 14 paired fresh HCC samples as well as another 159 HCC and matched noncancerous tissues. Meanwhile, the mRNA expression was analyzed by GEO and TCGA analysis and validated in 14 paired fresh HCC tissues. Furthermore, the relationships between CYP39A1 expression and clinicopathologic features as well as prognosis were analyzed. HCC cell growth changes were analyzed by cell viability assays after CYP39A1 overexpression and then validated after CYP39A1 knockout by DepMap database analysis.

Results

CYP39A1 protein expression was lower expressed in HCC mouse models, and its mRNA and protein expression were also downregulated in HCC compared with noncancerous liver tissues. Higher CYP39A1 expression was associated with well differentiation. Moreover, survival analysis indicated that lower CYP39A1 expression was associated with poorer overall survival. In addition, HepG2 and SMMC-7721 cell viability were inhibited after CYP39A1 overexpression. Genome-wide CRISPR/Cas9 proliferation screening indicated that knockout of CYP39A1 could promote HCC cell growth. Likewise, p-NF-κB and Nrf2 were suppressed after CYP39A1 overexpression. It is worth mentioning that total bile acid, total bilirubin, and direct bilirubin were significantly increased in the patients with low CYP39A1 expression.

Conclusions

Downregulation of CYP39A1 is associated with HCC carcinogenesis, tumor differentiation, and poor overall survival, suggesting that CYP39A1 may serve as a tumor suppressor gene and novel biomarker for HCC patients.

The Impact of Severe Acute Respiratory Syndrome Coronavirus Type 2 on Children With Liver Diseases: A Joint European Society for Pediatric Gastroenterology, Hepatology and Nutrition and Society of Pediatric Liver Transplantation Position Paper

ABSTRACT

Children are seldom affected by severe forms of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV2) infection; however, the impact of comorbidities in the clinical presentation and outcome of SARS-CoV2 in children is poorly characterized including that of chronic liver disease (CLD) and those taking immunosuppressive medications for autoimmune liver disease or following liver transplantation (LT). Although not the main target organ, a spectrum of liver involvement has been described in children infected with SARS-CoV2 and those presenting with Multisystem Inflammatory Syndrome in Children (MIS-C). The Hepatology Committee of the European Society for Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) and the Society of Pediatric Liver Transplantation (SPLIT) present an evidence-based position paper on liver involvement in children with SARS-CoV2 infection and its impact on those with CLD as well as LT recipients. All children may exhibit acute liver injury from SARS-CoV2 infection, and those with CLD and may experience hepatic decompensation. Preventative and therapeutic measures are discussed.

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

Background

Novel 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.

Methods

In 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 Findings

Emerging 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.

Conclusions

The 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.

Identifying Loci Associated With Bovine Corona Virus Infection and Bovine Respiratory Disease in Dairy and Feedlot Cattle

Bovine coronavirus (BCoV) is associated with respiratory and enteric infections in both dairy and beef cattle worldwide. It is also one of a complex of pathogens associated with bovine respiratory disease (BRD), which affects millions of cattle annually. The objectives of this study were to identify loci and heritability estimates associated with BCoV infection and BRD in dairy calves and feedlot cattle. Dairy calves from California (n = 1,938) and New Mexico (n = 647) and feedlot cattle from Colorado (n = 915) and Washington (n = 934) were tested for the presence of BCoV when classified as BRD cases or controls following the McGuirk scoring system. Two comparisons associated with BCoV were investigated: (1) cattle positive for BCoV (BCoV⁺) were compared to cattle negative for BCoV (BCoV^-) and (2) cattle positive for BCoV and affected with BRD (BCoV⁺BRD⁺) were compared to cattle negative for BCoV and BRD (BCoV^-BRD^-). The Illumina BovineHD BeadChip was used for genotyping, and genome-wide association analyses (GWAA) were performed using EMMAX (efficient mixed-model association eXpedited). The GWAA for BCoV⁺ identified 51 loci (p < 1 × 10^-5; 24 feedlot, 16 dairy, 11 combined) associated with infection with BCoV. Three loci were associated with BCoV⁺ across populations. Heritability estimates for BCoV⁺ were 0.01 for dairy, 0.11 for feedlot cattle, and 0.03 for the combined population. For BCoV⁺BRD⁺, 80 loci (p < 1 × 10^-5; 26 feedlot, 25 dairy, 29 combined) were associated including 14 loci across populations. Heritability estimates for BCoV⁺BRD⁺ were 0.003 for dairy, 0.44 for feedlot cattle, and 0.07 for the combined population. Several positional candidate genes associated with BCoV and BRD in this study have been associated with other coronaviruses and respiratory infections in humans and mice. These results suggest that selection may reduce susceptibility to BCoV infection and BRD in cattle.