Longitudinal whole blood transcriptomic analysis characterizes neutrophil activation and interferon signaling in moderate and severe COVID-19

Identification of potential biomarkers and drug of ischemic stroke in patients with COVID-19 through machine learning

The relationship between COVID-19 and ischemic stroke (IS) has attracted significant attention, yet the precise mechanism at the gene level remains unclear. This study aims to reveal potential biomarkers and drugs for COVID-19-related IS through bioinformatics methods. We collected two gene expression profiling datasets, GSE16561 and GSE213313, and selected GSE179879 and GSE196822 as validation sets for analysis. Through analysis, we identified 77 differentially expressed genes (DEGs) shared between COVID-19 and IS. Further gene enrichment analysis revealed that these genes are primarily involved in immune regulation. By constructing a protein-protein interaction network, we screened out nine hub genes, including FCGR3A, KLRB1, IL2RB, CD2, IL7R, CCR7, CD3D, GZMK, and ITK. In LASSO regression analysis, we evaluated the ROC curve's area under the curve (AUC) scores of key genes to assess their diagnostic accuracy. Subsequently, we performed random forest (RF), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and neural network construction on hub genes to ensure accurate diagnosis of IS. Finally, by intersecting the results of three algorithms (LASSO regression, random forest, and SVM), CD3D and ITK were identified as the ultimate key genes. Based on this, we predicted potential targeted drug Blinatumomab. These research findings provide clues for a deeper understanding of the biological mechanisms of COVID-19-related IS and offer new insights for exploring novel treatment approaches.

Identification of key regulatory genes in the pathogenesis of COVID-19 and sepsis: An observational study

Patients with severe COVID-19 and those with sepsis have similar clinical manifestations. We used bioinformatics methods to identify the common hub genes in these 2 diseases. Two RNA-seq datasets from the Gene Expression Omnibus were used to identify common differentially expressed genes (DEGs) in COVID-19 and sepsis. These common genes were used for analysis of functional enrichment; pathway analysis; identification of associated transcription factors, metabolites, and miRNAs; and mapping of protein-protein interaction networks. The major hub genes of COVID-19 and sepsis were identified, and validation datasets were used to assess the value of these hub genes using receiver operating characteristic (ROC) curves. Analysis of the 800 common DEGs for COVID-19 and sepsis, as well as common transcription factors, miRNAs, and metabolites, demonstrated that the immune response had a key role in both diseases. DLGAP5, BUB1, CDK1, CCNB1, and BUB1B were the most important common hub genes. Analysis of a validation cohort indicated these 5 genes had significantly higher expression in COVID-19 patients and sepsis patients than in corresponding controls, and the area under the ROC curves ranged from 0.832 to 0.981 for COVID-19 and 0.840 to 0.930 for sepsis. We used bioinformatics tools to identify common DEGs, miRNAs, and transcription factors for COVID-19 and sepsis. The 5 identified hub genes had higher expression in validation cohorts of COVID-19 and sepsis. These genes had good or excellent diagnostic performance based on ROC analysis, and therefore have potential use as novel markers or therapeutic targets.

Immunological Signatures in Blood and Urine in 80 Individuals Hospitalized during the Initial Phase of COVID-19 Pandemic with Quantified Nicotine Exposure

This research analyzes immunological response patterns to SARS-CoV-2 infection in blood and urine in individuals with serum cotinine-confirmed exposure to nicotine. Samples of blood and urine were obtained from a total of 80 patients admitted to hospital within 24 h of admission (tadm), 48 h later (t48h), and 7 days later (t7d) if patients remained hospitalized or at discharge. Serum cotinine above 3.75 ng/mL was deemed as biologically significant exposure to nicotine. Viral load was measured with serum SARS-CoV-2 S-spike protein. Titer of IgG, IgA, and IgM against S- and N-protein assessed specific antiviral responses. Cellular destruction was measured by high mobility group box protein-1 (HMGB-1) serum levels and heat shock protein 60 (Hsp-60). Serum interleukin 6 (IL-6), and ferritin gauged non-specific inflammation. The immunological profile was assessed with O-link. Serum titers of IgA were lower at tadm in smokers vs. nonsmokers (p = 0.0397). IgM at t48h was lower in cotinine-positive individuals (p = 0.0188). IgG did not differ between cotinine-positive and negative individuals. HMGB-1 at admission was elevated in cotinine positive individuals. Patients with positive cotinine did not exhibit increased markers of non-specific inflammation and tissue destruction. The blood immunological profile had distinctive differences at admission (MIC A/B↓), 48 h (CCL19↓, MCP-3↓, CD28↑, CD8↓, IFNγ↓, IL-12↓, GZNB↓, MIC A/B↓) or 7 days (CD28↓) in the cotinine-positive group. The urine immunological profile showed a profile with minimal overlap with blood as the following markers being affected at tadm (CCL20↑, CXCL5↑, CD8↑, IL-12↑, MIC A/B↑, GZNH↑, TNFRS14↑), t48h (CCL20↓, TRAIL↓) and t7d (EGF↑, ADA↑) in patients with a cotinine-positive test. Here, we showed a distinctive immunological profile in hospitalized COVID-19 patients with confirmed exposure to nicotine.

Integrated Bioinformatics Exploration and Preliminary Clinical Verification for the Identification of Crucial Biomarkers in Severe Cases of COVID-19

Background

Coronavirus disease 2019 (COVID-19) is a respiratory infectious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of this study is to identify reliable and accurate biomarkers for the early stratification of disease severity, a crucial aspect that is currently lacking for the impending phases of the next COVID-19 pandemic.

Methods

In this study, we identified important module and hub genes related to clinical severe COVID-19 using differentially expressed genes (DEGs) screening combing weighted gene co-expression network analysis (WGCNA) in dataset GSE213313. We further screened and confirmed these hub genes in another two new independent datasets (GSE172114 and GSE157103). In order to evaluate these key genes' stability and robustness for diagnosing or predicting the progression of illness, we used RT-PCR validation of selected genes in blood samples obtained from hospitalized COVID-19 patients.

Results

A total of 968 and 52 DEGs were identified between COVID-19 patients and normal people, critical and non-critical patients, respectively. Then, using WGCNA, 10 modules were constructed. Among them, the blue module positively associated with clinic disease severity of COVID-19. From overlapped section between DEGs and blue module, 12 intersected common differential genes were obtained. Subsequently, these hub genes were validated in another two new independent datasets as well and 9 genes that overlapped showed a highly correlation with disease severity. Finally, the mRNA expression levels of these hub genes were tested in blood samples from COVID-19 patients. In severe cases, there was increased expression of MCEMP1, ANXA3, CD177, and SCN9A. In particular, MCEMP1 increased with disease severity, which suggested an unfavorable development and a frustrating prognosis.

Conclusion

Using comprehensive bioinformatical analysis and the validation of clinical samples, we identified four major candidate genes, MCEMP1, ANXA3, CD177, and SCN9A, which are essential for diagnosis or development of COVID-19.

Hypoxia and Activation of Neutrophil Degranulation-Related Genes in the Peripheral Blood of COVID-19 Patients

Severe COVID-19 is characterized by systematic hyper-inflammation and subsequent damage to various organs. Therefore, it is critical to trace this cascade of hyper-inflammation. Blood transcriptome has been routinely utilized in the interrogation of host immune response in COVID-19 and other infectious conditions. In this study, consensus gene dysregulation in the blood was obtained from 13 independent transcriptome studies on COVID-19. Among the up-regulated genes, the most prominent functional categories were neutrophil degranulation and cell cycle, which is clearly different from the classical activation of interferon signaling pathway in seasonal flu. As for the potential upstream causal factors of the atypical gene dysregulation, systemic hypoxia was further examined because it is much more widely reported in COVID-19 than that in seasonal flu. It was found that both physiological and pathological hypoxia can induce activation of neutrophil degranulation-related genes in the blood. Furthermore, COVID-19 patients with different requirement for oxygen intervention showed distinctive levels of gene expression related to neutrophil degranulation in the whole blood, which was validated in isolated neutrophils. Thus, activation of neutrophil degranulation-related genes in the blood of COVID-19 could be partially attributed to hypoxia. Interestingly, similar pattern was also observed in H1N1 infection (the cause of Spanish flu) and several other severe respiratory viral infections. As for the molecular mechanism, both HIF-dependent and HIF-independent pathways have been examined. Since the activation of neutrophil degranulation-related genes is highly correlated with disease severity in COVID-19, early detection of hypoxia and active intervention may prevent further activation of neutrophil degranulation-related genes and other harmful downstream hyper-inflammation. This common mechanism is applicable to current and future pandemic as well as the severe form of common respiratory infection.

How Neutrophils Shape the Immune Response: Reassessing Their Multifaceted Role in Health and Disease

Neutrophils are the most abundant of the circulating immune cells and are the first to be recruited to sites of inflammation. Neutrophils are a heterogeneous group of immune cells from which are derived extracellular traps (NETs), reactive oxygen species, cytokines, chemokines, immunomodulatory factors, and alarmins that regulate the recruitment and phenotypes of neutrophils, macrophages, dendritic cells, T cells, and B cells. In addition, cytokine-stimulated neutrophils can express class II major histocompatibility complex and the internal machinery necessary for successful antigen presentation to memory CD4+ T cells. This may be relevant in the context of vaccine memory. Neutrophils thus emerge as orchestrators of immune responses that play a key role in determining the outcome of infections, vaccine efficacy, and chronic diseases like autoimmunity and cancer. This review aims to provide a synthesis of current evidence as regards the role of these functions of neutrophils in homeostasis and disease.