Differential expression of the Nrf2-linked genes in pediatric septic shock

Biological basis of critical illness subclasses: from the bedside to the bench and back again

Critical illness syndromes including sepsis, acute respiratory distress syndrome, and acute kidney injury (AKI) are associated with high in-hospital mortality and long-term adverse health outcomes among survivors. Despite advancements in care, clinical and biological heterogeneity among patients continues to hamper identification of efficacious therapies. Precision medicine offers hope by identifying patient subclasses based on clinical, laboratory, biomarker and 'omic' data and potentially facilitating better alignment of interventions. Within the previous two decades, numerous studies have made strides in identifying gene-expression based endotypes and clinico-biomarker based phenotypes among critically ill patients associated with differential outcomes and responses to treatment. In this state-of-the-art review, we summarize the biological similarities and differences across the various subclassification schemes among critically ill patients. In addition, we highlight current translational gaps, the need for advanced scientific tools, human-relevant disease models, to gain a comprehensive understanding of the molecular mechanisms underlying critical illness subclasses.

Identification of a Ferroptosis-Related Prognostic Signature in Sepsis via Bioinformatics Analyses and Experiment Validation

Ferroptosis is a new type of programmed cell death that is different from apoptosis, cell necrosis, and autophagy, which might be involved in development of sepsis. However, the potential role of ferroptosis-related genes (FRGs) in sepsis remained unclear. We identified 41 ferroptosis-related differential expression genes by weighted correlation network and differential expression analysis. The hub module of 41 ferroptosis-related differential expression genes in the protein-protein interaction network was identified. Next, we estimated diagnostic values of genes in hub modules. TLR4, WIPI1, and GABARAPL2 with high diagnostic value were selected for construction of risk prognostic model. The high risk-scored patients had significantly higher mortality than the patients with low risk scores in discovery dataset. Furthermore, the risk scores of nonsurvivor were higher than those of survivor in validation dataset. It suggested that risk score was significantly correlated to prognosis in sepsis. Then, we constructed a nomogram for improving the clinical applicability of risk signature. Moreover, the risk score was significantly associated with immune infiltration in sepsis. Our comprehensive analysis of FRGs in sepsis demonstrated the potential roles in diagnosis, prognosis, and immune infiltration. This work may benefit in understanding FRGs in sepsis and pave a new path for diagnosis and assessment of prognosis.

A six‑gene support vector machine classifier contributes to the diagnosis of pediatric septic shock

Septic shock is induced by an uncontrolled inflammatory immune response to pathogens and the survival rate of patients with pediatric septic shock (PSS) is particularly low, with a mortality rate of 25‑50%. The present study explored the mechanisms of PSS using four microarray datasets (GSE26378, GSE26440, GSE13904 and GSE4607) that were obtained from the Gene Expression Omnibus database. Based on the MetaDE package, the consistently differentially expressed genes (DEGs) in the four datasets were screened. Using the WGCNA package, the disease‑associated modules and genes were identified. Subsequently, the optimal feature genes were further selected using the caret package. Finally, a support vector machine (SVM) classifier based on the optimal feature genes was built using the e1071 package. Initially, there were 2,699 consistent DEGs across the four datasets. From the 10 significantly stable modules across the datasets, four stable modules (including the magenta, purple, turquoise and yellow modules), in which the consistent DEGs were significantly enriched (P<0.05), were further screened. Subsequently, six optimal feature genes (including cysteine rich transmembrane module containing 1, S100 calcium binding protein A9, solute carrier family 2 member 14, stomatin, uridine phosphorylase 1 and utrophin) were selected from the genes in the four stable modules. Additionally, an effective SVM classifier was constructed based on the six optimal genes. The SVM classifier based on the six optimal genes has the potential to be applied for PSS diagnosis. This may improve the accuracy of early PSS diagnosis and suggest possible molecular targets for interventions.

Mechanisms of Intestinal Barrier Dysfunction in Sepsis

Intestinal barrier dysfunction is thought to contribute to the development of multiple organ dysfunction syndrome in sepsis. Although there are similarities in clinical course following sepsis, there are significant differences in the host response depending on the initiating organism and time course of the disease, and pathways of gut injury vary widely in different preclinical models of sepsis. The purpose of this study was to determine whether the timecourse and mechanisms of intestinal barrier dysfunction are similar in disparate mouse models of sepsis with similar mortalities. FVB/N mice were randomized to receive cecal ligation and puncture (CLP) or sham laparotomy, and permeability was measured to fluoresceinisothiocyanate conjugated-dextran (FD-4) six to 48 h later. Intestinal permeability was elevated following CLP at all timepoints measured, peaking at 6 to 12 h. Tight junction proteins claudin 1, 2, 3, 4, 5, 7, 8, 13, and 15, Junctional Adhesion Molecule-A (JAM-A), occludin, and ZO-1 were than assayed by Western blot, real-time polymerase chain reaction, and immunohistochemistry 12 h after CLP to determine potential mechanisms underlying increases in intestinal permeability. Claudin 2 and JAM-A were increased by sepsis, whereas claudin-5 and occludin were decreased by sepsis. All other tight junction proteins were unchanged. A further timecourse experiment demonstrated that alterations in claudin-2 and occludin were detectable as early as 1 h after the onset of sepsis. Similar experiments were then performed in a different group of mice subjected to Pseudomonas aeruginosa pneumonia. Mice with pneumonia had an increase in intestinal permeability similar in timecourse and magnitude to that seen in CLP. Similar changes in tight junction proteins were seen in both models of sepsis although mice subjected to pneumonia also had a marked decrease in ZO-1 not seen in CLP. These results indicate that two disparate, clinically relevant models of sepsis induce a significant increase in intestinal permeability mediated through a common pathway involving alterations in claudin 2, claudin 5, JAM-A, and occludin although model-specific differences in ZO-1 were also identified.

Differential regulation of innate immune cytokine production through pharmacological activation of Nuclear Factor-Erythroid-2-Related Factor 2 (NRF2) in burn patient immune cells and monocytes

Burn patients suffer from immunological dysfunction for which there are currently no successful interventions. Similar to previous observations, we find that burn shock patients (≥15% Total Burn Surface Area (TBSA) injury) have elevated levels of the innate immune cytokines Interleukin-6 (IL-6) and Monocyte Chemoattractant Protein-1 (MCP-1)/CC-motif Chemokine Ligand 2(CCL2) early after hospital admission (0–48 Hours Post-hospital Admission (HPA). Functional immune assays with patient Peripheral Blood Mononuclear Cells (PBMCs) revealed that burn shock patients (≥15% TBSA) produced elevated levels of MCP-1/CCL2 after innate immune stimulation ex vivo relative to mild burn patients. Interestingly, treatment of patient PBMCs with the Nuclear Factor-Erythroid-2-Related Factor 2 (NRF2) agonist, CDDO-Me(bardoxolone methyl), reduced MCP-1 production but not IL-6 or Interleukin-10 (IL-10) secretion. In enriched monocytes from healthy donors, CDDO-Me(bardoxolone methyl) also reduced LPS-induced MCP1/CCL2 production but did not alter IL-6 or IL-10 secretion. Similar immunomodulatory effects were observed with Compound 7, which activates the NRF2 pathway through a different and non-covalent Mechanism Of Action (MOA). Hence, our findings with CDDO-Me(bardoxolone methyl) and Compound 7 are likely to reflect a generalizable aspect of NRF2 activation. These observed effects were not specific to LPS-induced immune responses, as NRF2 activation also reduced MCP-1/CCL2 production after stimulation with IL-6. Pharmacological NRF2 activation reduced Mcp-1/Ccl2 transcript accumulation without inhibiting either Il-6 or Il-10 transcript levels. Hence, we describe a novel aspect of NRF2 activation that may contribute to the beneficial effects of NRF2 agonists during disease. Our work also demonstrates that the NRF2 pathway is retained and can be modulated to regulate important immunomodulatory functions in burn patient immune cells.