[Expression Levels and Regulation of Selenoprotein Genes in Patients With Coronavirus Disease 2019].

Objective To investigate the expression levels of selenoprotein genes in the patients with coronavirus disease 2019 (COVID-19) and the possible regulatory mechanisms.Methods The dataset GSE177477 was obtained from the Gene Expression Omnibus,consisting of a symptomatic group (n=11),an asymptomatic group (n=18),and a healthy control group (n=18).The dataset was preprocessed to screen the differentially expressed genes (DEG) related to COVID-19,and gene ontology functional annotation and Kyoto encyclopedia of genes and genomes enrichment analysis were performed for the DEGs.The protein-protein interaction network of DEGs was established,and multivariate Logistic regression was employed to analyze the effects of selenoprotein genes on the presence/absence of symptoms in the patients with COVID-19.Results Compared with the healthy control,the symptomatic COVID-19 patients presented up-regulated expression of GPX1,GPX4,GPX6,DIO2,TXNRD1,SELENOF,SELENOK,SELENOS,SELENOT,and SELENOW and down-regulated expression of TXNRD2 and SELENON (all P<0.05).The asymptomatic patients showcased up-regulated expression of GPX2,SELENOI,SELENOO,SELENOS,SELENOT,and SELENOW and down-regulated expression of SELP (all P<0.05).The results of multivariate Logistic regression analysis showed that the abnormally high expression of GPX1 (OR=0.067,95%CI=0.005-0.904,P=0.042) and SELENON (OR=56.663,95%CI=3.114-856.999,P=0.006) was the risk factor for symptomatic COVID-19,and the abnormally high expression of SELP was a risk factor for asymptomatic COVID-19 (OR=15.000,95%CI=2.537-88.701,P=0.003).Conclusions Selenoprotein genes with differential expression are involved in the regulation of COVID-19 development.The findings provide a new reference for the prevention and treatment of COVID-19.

The association of rs17713054 with Neanderthal origin at 3p21.31 locus with the severity of COVID-19 in Iranian patients.

Since the COVID-19 pandemic, the diversity of clinical manifestations in patients has been a tremendous challenge. It seems that genetic variations, as one of the players, contribute to the variety of symptoms. Genome-wide association studies have demonstrated the influence of certain genomic regions on the disease prognosis. Particularly, a haplotype at 3p21.31 locus, inherited from Neanderthals, showed an association with COVID-19 severity. Despite several studies regarding this haplotype, some key variants are not sufficiently addressed. In the present study, we investigated the association of rs17713054 at 3p21.31 with COVID-19 severity. We analyzed the genotype of 251 Iranian COVID-19 patients (151 patients with asymptomatic to mild form as control and 100 patients with severe to critical symptoms without any comorbidities as case group) using the ARMS-PCR method. Results demonstrated that the A allele confers an almost twofold increased risk for COVID-19 severity (P value = 0.008). The AA genotype also raises the risk by more than 11 times following the recessive model (P value = 0.013). In conclusion, the A allele in rs17713054 was a risk allele in Iranian patients and was independently associated with COVID-19 severity. More studies are beneficial to confirm these findings in other populations and to develop strategies for risk assessment, prevention, and personalized medicine.

NF-κB inhibitor alpha controls SARS-CoV-2 infection in ACE2-overexpressing human airway organoids.

As SARS-CoV-2 continues to spread worldwide, tractable primary airway cell models that recapitulate the cell-intrinsic response to arising viral variants are needed. Here we describe an adult stem cell-derived human airway organoid model overexpressing the ACE2 receptor (ACE2-OE) that supports robust viral replication while maintaining 3D architecture and cellular diversity of the airway epithelium. ACE2-OE organoids were infected with SARS-CoV-2 variants and subjected to single-cell RNA-sequencing. Interferon-lambda was upregulated in cells with low-level infection while the NF-kB inhibitor alpha gene (encoding IkBa) was consistently upregulated in infected cells, and its expression positively correlated with infection levels. Confocal microscopy showed more IkBa expression in infected than bystander cells, but found concurrent nuclear translocation of NF-kB that IkBa usually prevents. Overexpressing a nondegradable IkBa mutant reduced NF-kB translocation and increased viral infection. These data demonstrate the functionality of ACE2-OE organoids in SARS-CoV-2 research and underscore that the strength of the NF-kB feedback loop in infected cells controls viral replication.

Accurate estimation of pathway activity in single cells for clustering and differential analysis.

Inferring which and how biological pathways and gene sets change is a key question in many studies that utilize single-cell RNA sequencing. Typically, these questions are addressed by quantifying the enrichment of known gene sets in lists of genes derived from global analysis. Here we offer SiPSiC, a new method to infer pathway activity in every single cell. This allows more sensitive differential analysis and utilization of pathway scores to cluster cells and compute UMAP or other similar projections. We apply our method to COVID-19, lung adenocarcinoma and glioma data sets, and demonstrate its utility. SiPSiC analysis results are consistent with findings reported in previous studies in many cases, but SiPSiC also reveals the differential activity of novel pathways, enabling us to suggest new mechanisms underlying the pathophysiology of these diseases and demonstrating SiPSiC's high accuracy and sensitivity in detecting biological function and traits. In addition, we demonstrate how it can be used to better classify cells based on activity of biological pathways instead of single genes and its ability to overcome patient-specific artifacts.

Coronavirus disease 2019-related myocarditis genes contribute to ECMO prognosis.

BACKGROUND: Acute myocardial injury, cytokine storms, hypoxemia and pathogen-mediated damage were the major causes responsible for mortality induced by coronavirus disease 2019 (COVID-19)-related myocarditis. These need ECMO treatment. We investigated differentially expressed genes (DEGs) in patients with COVID-19-related myocarditis and ECMO prognosis. METHODS: GSE150392 and GSE93101 were analyzed to identify DEGs. A Venn diagram was used to obtain the same transcripts between myocarditis-related and ECMO-related DEGs. Enrichment pathway analysis was performed and hub genes were identified. Pivotal miRNAs, transcription factors, and chemicals with the screened gene interactions were identified. The GSE167028 dataset and single-cell sequencing data were used to validate the screened genes. RESULTS: Using a Venn diagram, 229 overlapping DEGs were identified between myocarditis-related and ECMO-related DEGs, which were mainly involved in T cell activation, contractile actin filament bundle, actomyosin, cyclic nucleotide phosphodiesterase activity, and cytokine-cytokine receptor interaction. 15 hub genes and 15 neighboring DEGs were screened, which were mainly involved in the positive regulation of T cell activation, integrin complex, integrin binding, the PI3K-Akt signaling pathway, and the TNF signaling pathway. Data in GSE167028 and single-cell sequencing data were used to validate the screened genes, and this demonstrated that the screened genes CCL2, APOE, ITGB8, LAMC2, COL6A3 and TNC were mainly expressed in fibroblast cells; IL6, ITGA1, PTK2, ITGB5, IL15, LAMA4, CAV1, SNCA, BDNF, ACTA2, CD70, MYL9, DPP4, ENO2 and VEGFC were expressed in cardiomyocytes; IL6, PTK2, ITGB5, IL15, APOE, JUN, SNCA, CD83, DPP4 and ENO2 were expressed in macrophages; and IL6, ITGA1, PTK2, ITGB5, IL15, VCAM1, LAMA4, CAV1, ACTA2, MYL9, CD83, DPP4, ENO2, VEGFC and IL32 were expressed in vascular endothelial cells. CONCLUSION: The screened hub genes, IL6, ITGA1, PTK2, ITGB3, ITGB5, CCL2, IL15, VCAM1, GZMB, APOE, ITGB8, LAMA4, LAMC2, COL6A3 and TNFRSF9, were validated using GEO dataset and single-cell sequencing data, which may be therapeutic targets patients with myocarditis to prevent MI progression and adverse cardiovascular events.

Single cell multi-omic analysis identifies key genes differentially expressed in innate lymphoid cells from COVID-19 patients.

Introduction: Innate lymphoid cells (ILCs) are enriched at mucosal surfaces where they respond rapidly to environmental stimuli and contribute to both tissue inflammation and healing. Methods: To gain insight into the role of ILCs in the pathology and recovery from COVID-19 infection, we employed a multi-omics approach consisting of Abseq and targeted mRNA sequencing to respectively probe the surface marker expression, transcriptional profile and heterogeneity of ILCs in peripheral blood of patients with COVID-19 compared with healthy controls. Results: We found that the frequency of ILC1 and ILC2 cells was significantly increased in COVID-19 patients. Moreover, all ILC subsets displayed a significantly higher frequency of CD69-expressing cells, indicating a heightened state of activation. ILC2s from COVID-19 patients had the highest number of significantly differentially expressed (DE) genes. The most notable genes DE in COVID-19 vs healthy participants included a) genes associated with responses to virus infections and b) genes that support ILC self-proliferation, activation and homeostasis. In addition, differential gene regulatory network analysis revealed ILC-specific regulons and their interactions driving the differential gene expression in each ILC. Discussion: Overall, this study provides mechanistic insights into the characteristics of ILC subsets activated during COVID-19 infection.

HLA-DQA1*01:03 and DQB1*06:01 are risk factors for severe COVID-19 pneumonia.

The clinical spectrum of COVID-19 includes a wide range of manifestations, from mild symptoms to severe pneumonia. HLA system plays a pivotal role in immune responses to infectious diseases. The purpose of our study was to investigate the association between HLA and COVID-19 severity in a Japanese population. The study included 209 Japanese COVID-19 patients aged ≥20 years. Saliva samples were collected and used to determine the HLA genotype by HLA imputation through genome-wide association analyses. The association between HLA genotype and COVID-19 severity was then evaluated. The allele frequency was compared between patients with respiratory failure (severe group: 91 cases) and those without respiratory failure (non-severe group: 118 cases), categorising the data into three time periods: pre-Omicron epidemic period, Omicron epidemic period, and total period of this study (from January 2021 to May 2023). In comparing the severe and non-severe groups, the frequencies of the HLA-DQA1*01:03 (35.1% vs. 10.5%, odds ratio [OR] = 4.57, corrected p [pc] = 0.041) and -DQB1*06:01 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) alleles were significantly higher in the severe group during the pre-Omicron epidemic period. During the Omicron epidemic period, HLA-DQB1*06 (32.4% vs. 7.9%, OR = 5.54, pc = 0.030) was significantly higher in the severe group. During total period of this study, HLA-DQA1*01:03 (30.2% vs. 14.4%, OR = 2.57, corrected pc = 0.0013) and -DQB1*06:01 (44.5% vs. 26.7%, OR = 2.20, pc = 0.013) alleles were significantly higher in the severe group. HLA-DQB1*06:01 and -DQA1*01:03 were in strong linkage disequilibrium with each other (r2 = 0.91) during total period of this study, indicating that these two alleles form a haplotype. The frequency of the HLA-DQA1*01:03-DQB1*06:01 in the severe group was significantly higher than in the non-severe group during pre-Omicron epidemic period (32.4% vs. 7.9%, OR = 5.59, pc = 0.00072), and total period of this study (28.6% vs. 13.1%, OR = 2.63, pc = 0.0013). During Omicron epidemic period, the haplotype did not demonstrate statistical significance, although the odds ratio indicated a value greater 1. Frequencies of the HLA-DQA1*01:03 and -DQB1*06:01 alleles were significantly higher in severe COVID-19 patients, suggesting that these alleles are risk factors for severe COVID-19 pneumonia in the Japanese population.

The study of single nucleotide polymorphism in a promoter region of ACE-2 receptor gene in the samples of Iraqi population with COVID-19.

BACKGROUND: Angiotensin-converting enzyme 2 (ACE2) is an essential receptor on the host cell's cell membrane. It's interesting to note that the entry point receptor ACE2 protein and the severe acute respiratory syndrome (SARS) coronavirus are correlated. This study aimed to determine the influence of the ACE gene genotype and explore the effects of genetic variation in the promotor region of the ACE-2 gene receptor in SARS COV-2 patients. METHODS AND RESULTS: The 225 participants were categorized into two groups (75 infected and 150 control) according to the results of Real Time -polymerase chain reaction (RT-PCR), IgM, and IgG, also included two types of samples were collected for diagnosis hematological and molecular study. The hematological and biochemical parameters showed significant differences between the two studied groups according to D. dimer, ferritin, lactate dehydrogenase (LDH), C-reactive protein (CRP), white blood cells (WBC), lymphocyte, packed cell volume (PCV) (P˂0.0001), also red blood cell (RBC) (P = 0.0034). While the results of hemoglobin (HB) and platelet displayed non-significant differences between the two groups (p value 0.6811 and 0.9201 respectively). In addition, the sequencing result in the promotor of the ACE-2 gene detected novel eight polymorphisms and recorded them in NCBI under no. (ON959139). CONCLUSIONS: The ACE D/D polymorphism associated with increased levels of ACE could represent a genetic risk factor in addition the discovery stems from the prospect that genetic differences could lead to differing responses to COVID-19 therapies.

Spike deep mutational scanning helps predict success of SARS-CoV-2 clades.

SARS-CoV-2 variants acquire mutations in the spike protein that promote immune evasion1 and affect other properties that contribute to viral fitness, such as ACE2 receptor binding and cell entry2,3. Knowledge of how mutations affect these spike phenotypes can provide insight into the current and potential future evolution of the virus. Here we use pseudovirus deep mutational scanning4 to measure how more than 9,000 mutations across the full XBB.1.5 and BA.2 spikes affect ACE2 binding, cell entry or escape from human sera. We find that mutations outside the receptor-binding domain (RBD) have meaningfully affected ACE2 binding during SARS-CoV-2 evolution. We also measure how mutations to the XBB.1.5 spike affect neutralization by serum from individuals who recently had SARS-CoV-2 infections. The strongest serum escape mutations are in the RBD at sites 357, 420, 440, 456 and 473; however, the antigenic effects of these mutations vary across individuals. We also identify strong escape mutations outside the RBD; however, many of them decrease ACE2 binding, suggesting they act by modulating RBD conformation. Notably, the growth rates of human SARS-CoV-2 clades can be explained in substantial part by the measured effects of mutations on spike phenotypes, suggesting our data could enable better prediction of viral evolution.

Complete combinatorial mutational enumeration of a protein functional site enables sequence-landscape mapping and identifies highly-mutated variants that retain activity.

Understanding how proteins evolve under selective pressure is a longstanding challenge. The immensity of the search space has limited efforts to systematically evaluate the impact of multiple simultaneous mutations, so mutations have typically been assessed individually. However, epistasis, or the way in which mutations interact, prevents accurate prediction of combinatorial mutations based on measurements of individual mutations. Here, we use artificial intelligence to define the entire functional sequence landscape of a protein binding site in silico, and we call this approach Complete Combinatorial Mutational Enumeration (CCME). By leveraging CCME, we are able to construct a comprehensive map of the evolutionary connectivity within this functional sequence landscape. As a proof of concept, we applied CCME to the ACE2 binding site of the SARS-CoV-2 spike protein receptor binding domain. We selected representative variants from across the functional sequence landscape for testing in the laboratory. We identified variants that retained functionality to bind ACE2 despite changing over 40% of evaluated residue positions, and the variants now escape binding and neutralization by monoclonal antibodies. This work represents a crucial initial stride toward achieving precise predictions of pathogen evolution, opening avenues for proactive mitigation.

SARS-CoV-2 population dynamics in immunocompetent individuals in a closed transmission chain shows genomic diversity over the course of infection.

BACKGROUND: SARS-CoV-2 remains rapidly evolving, and many biologically important genomic substitutions/indels have characterised novel SARS-CoV-2 lineages, which have emerged during successive global waves of the pandemic. Worldwide genomic sequencing has been able to monitor these waves, track transmission clusters, and examine viral evolution in real time to help inform healthcare policy. One school of thought is that an apparent greater than average divergence in an emerging lineage from contemporary variants may require persistent infection, for example in an immunocompromised host. Due to the nature of the COVID-19 pandemic and sampling, there were few studies that examined the evolutionary trajectory of SARS-CoV-2 in healthy individuals. METHODS: We investigated viral evolutionary trends and participant symptomatology within a cluster of 16 SARS-CoV-2 infected, immunocompetent individuals with no co-morbidities in a closed transmission chain. Longitudinal nasopharyngeal swab sampling allowed characterisation of SARS-CoV-2 intra-host variation over time at both the dominant and minor genomic variant levels through Nimagen-Illumina sequencing. RESULTS: A change in viral lineage assignment was observed in individual infections; however, there was only one indel and no evidence of recombination over the period of an acute infection. Minor and dominant genomic modifications varied between participants, with some minor genomic modifications increasing in abundance to become the dominant viral sequence during infection. CONCLUSIONS: Data from this cohort of SARS-CoV-2-infected participants demonstrated that long-term persistent infection in an immunocompromised host was not necessarily a prerequisite for generating a greater than average frequency of amino acid substitutions. Amino acid substitutions at both the dominant and minor genomic sequence level were observed in immunocompetent individuals during infection showing that viral lineage changes can occur generating viral diversity.

SARS-CoV-2 brainstem encephalitis in human inherited DBR1 deficiency.

Inherited deficiency of the RNA lariat-debranching enzyme 1 (DBR1) is a rare etiology of brainstem viral encephalitis. The cellular basis of disease and the range of viral predisposition are unclear. We report inherited DBR1 deficiency in a 14-year-old boy who suffered from isolated SARS-CoV-2 brainstem encephalitis. The patient is homozygous for a previously reported hypomorphic and pathogenic DBR1 variant (I120T). Consistently, DBR1 I120T/I120T fibroblasts from affected individuals from this and another unrelated kindred have similarly low levels of DBR1 protein and high levels of RNA lariats. DBR1 I120T/I120T human pluripotent stem cell (hPSC)-derived hindbrain neurons are highly susceptible to SARS-CoV-2 infection. Exogenous WT DBR1 expression in DBR1 I120T/I120T fibroblasts and hindbrain neurons rescued the RNA lariat accumulation phenotype. Moreover, expression of exogenous RNA lariats, mimicking DBR1 deficiency, increased the susceptibility of WT hindbrain neurons to SARS-CoV-2 infection. Inborn errors of DBR1 impair hindbrain neuron-intrinsic antiviral immunity, predisposing to viral infections of the brainstem, including that by SARS-CoV-2.

In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing.

COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.

Worldwide distribution of genetic factors related to severity of COVID-19 infection.

BACKGROUND: Genome-wide association studies of COVID-19 severity have been carried out mostly on European or East Asian populations with small representation of other world regions. Here we explore the worldwide distribution and linkage disequilibrium (LD) patterns of genetic variants previously associated with COVID-19 severity. METHODS: We followed up the results of a large Spanish genome-wide meta-analysis on 26 populations from the 1000 Genomes Project by calculating allele frequencies and LD scores of the nine most significant SNPs. We also used the entire set of summary statistics to compute polygenic risk scores (PRSs) and carried out comparisons at the population and continental level. RESULTS: We observed the strongest differences among continental regions for the five top SNPs in chromosome 3. European, American, and South Asian populations showed similar LD patterns. Average PRSs in South Asian and American populations were consistently higher than those observed in Europeans. While PRS distributions were similar among South Asians, the American populations showed striking differences among them. CONCLUSIONS: Considering the caveats of PRS transferability across ethnicities, our analysis showed that American populations present the highest genetic risk score, hence potentially higher propensity, for COVID-19 severity. Independent validation is warranted with additional summary statistics and phenotype data.

Impaired metal perception and regulation of associated human foliate papillae tongue transcriptome in long-COVID-19.

Chemosensory impairment is an outstanding symptom of SARS-CoV-2 infections. We hypothesized that measured sensory impairments are accompanied by transcriptomic changes in the foliate papillae area of the tongue. Hospital personnel with known SARS-CoV-2 immunoglobulin G (IgG) status completed questionnaires on sensory perception (n = 158). A subcohort of n = 141 participated in forced choice taste tests, and n = 43 participants consented to donate tongue swabs of the foliate papillae area for whole transcriptome analysis. The study included four groups of participants differing in IgG levels (≥ 10 AU/mL = IgG+; < 10 AU/mL = IgG-) and self-reported sensory impairment (SSI±). IgG+ subjects not detecting metallic taste had higher IgG+ levels than IgG+ participants detecting iron gluconate (p = 0.03). Smell perception was the most impaired biological process in the transcriptome data from IgG+/SSI+ participants subjected to gene ontology enrichment. IgG+/SSI+ subjects demonstrated lower expression levels of 166 olfactory receptors (OR) and 9 taste associated receptors (TAS) of which OR1A2, OR2J2, OR1A1, OR5K1 and OR1G1, as well as TAS2R7 are linked to metallic perception. The question raised by this study is whether odorant receptors on the tongue (i) might play a role in metal sensation, and (ii) are potential targets for virus-initiated sensory impairments, which needs to be investigated in future functional studies.

Identification of Marker Genes in Infectious Diseases from ScRNA-seq Data Using Interpretable Machine Learning.

A common result of infection is an abnormal immune response, which may be detrimental to the host. To control the infection, the immune system might undergo regulation, therefore producing an excess of either pro-inflammatory or anti-inflammatory pathways that can lead to widespread inflammation, tissue damage, and organ failure. A dysregulated immune response can manifest as changes in differentiated immune cell populations and concentrations of circulating biomarkers. To propose an early diagnostic system that enables differentiation and identifies the severity of immune-dysregulated syndromes, we built an artificial intelligence tool that uses input data from single-cell RNA sequencing. In our results, single-cell transcriptomics successfully distinguished between mild and severe sepsis and COVID-19 infections. Moreover, by interpreting the decision patterns of our classification system, we identified that different immune cells upregulating or downregulating the expression of the genes CD3, CD14, CD16, FOSB, S100A12, and TCRɣδ can accurately differentiate between different degrees of infection. Our research has identified genes of significance that effectively distinguish between infections, offering promising prospects as diagnostic markers and providing potential targets for therapeutic intervention.

Deciphering Abnormal Platelet Subpopulations in COVID-19, Sepsis and Systemic Lupus Erythematosus through Machine Learning and Single-Cell Transcriptomics.

This study focuses on understanding the transcriptional heterogeneity of activated platelets and its impact on diseases such as sepsis, COVID-19, and systemic lupus erythematosus (SLE). Recognizing the limited knowledge in this area, our research aims to dissect the complex transcriptional profiles of activated platelets to aid in developing targeted therapies for abnormal and pathogenic platelet subtypes. We analyzed single-cell transcriptional profiles from 47,977 platelets derived from 413 samples of patients with these diseases, utilizing Deep Neural Network (DNN) and eXtreme Gradient Boosting (XGB) to distinguish transcriptomic signatures predictive of fatal or survival outcomes. Our approach included source data annotations and platelet markers, along with SingleR and Seurat for comprehensive profiling. Additionally, we employed Uniform Manifold Approximation and Projection (UMAP) for effective dimensionality reduction and visualization, aiding in the identification of various platelet subtypes and their relation to disease severity and patient outcomes. Our results highlighted distinct platelet subpopulations that correlate with disease severity, revealing that changes in platelet transcription patterns can intensify endotheliopathy, increasing the risk of coagulation in fatal cases. Moreover, these changes may impact lymphocyte function, indicating a more extensive role for platelets in inflammatory and immune responses. This study identifies crucial biomarkers of platelet heterogeneity in serious health conditions, paving the way for innovative therapeutic approaches targeting platelet activation, which could improve patient outcomes in diseases characterized by altered platelet function.

Modulatory Roles of AHR, FFAR2, FXR, and TGR5 Gene Expression in Metabolic-Associated Fatty Liver Disease and COVID-19 Outcomes.

Metabolic-associated fatty liver disease (MAFLD) is a risk factor for severe COVID-19. This study explores the potential influence of gut hormone receptor and immune response gene expression on COVID-19 outcomes in MAFLD patients. METHODS: We investigated gene expression levels of AHR, FFAR2, FXR, and TGR5 in patients with MAFLD and COVID-19 compared to controls. We examined associations between gene expression and clinical outcomes. RESULTS: COVID-19 patients displayed altered AHR expression, potentially impacting immune response and recovery. Downregulated AHR in patients with MAFLD correlated with increased coagulation parameters. Elevated FFAR2 expression in patients with MAFLD was linked to specific immune cell populations and hospital stay duration. A significantly lower FXR expression was observed in both MAFLD and severe COVID-19. CONCLUSION: Our findings suggest potential modulatory roles for AHR, FFAR2, and FXR in COVID-19 and MAFLD.

SARS-CoV-2 Selectively Induces the Expression of Unproductive Splicing Isoforms of Interferon, Class I MHC, and Splicing Machinery Genes.

RNA processing is a highly conserved mechanism that serves as a pivotal regulator of gene expression. Alternative processing generates transcripts that can still be translated but lead to potentially nonfunctional proteins. A plethora of respiratory viruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), strategically manipulate the host's RNA processing machinery to circumvent antiviral responses. We integrated publicly available omics datasets to systematically analyze isoform-level expression and delineate the nascent peptide landscape of SARS-CoV-2-infected human cells. Our findings explore a suggested but uncharacterized mechanism, whereby SARS-CoV-2 infection induces the predominant expression of unproductive splicing isoforms in key IFN signaling, interferon-stimulated (ISGs), class I MHC, and splicing machinery genes, including IRF7, HLA-B, and HNRNPH1. In stark contrast, cytokine and chemokine genes, such as IL6 and TNF, predominantly express productive (protein-coding) splicing isoforms in response to SARS-CoV-2 infection. We postulate that SARS-CoV-2 employs an unreported tactic of exploiting the host splicing machinery to bolster viral replication and subvert the immune response by selectively upregulating unproductive splicing isoforms from antigen presentation and antiviral response genes. Our study sheds new light on the molecular interplay between SARS-CoV-2 and the host immune system, offering a foundation for the development of novel therapeutic strategies to combat COVID-19.