IL1R2基因的脓毒症

Sepsis is a life-threatening condition characterized by systemic inflammation and organ dysfunction, with a complex and not yet fully elucidated molecular basis. Central to its pathogenesis is a dysregulated immune response. In this study, we performed a comprehensive multi-omics analysis on transcriptomic datasets retrieved from the GEO database, including samples from sepsis patients (n = 23) and healthy controls (n = 27). and identified a pivotal role of Interleukin-1 receptor 2 (IL-1R2) in modulating inflammatory responses in sepsis. Transcriptomic integration revealed activation of critical signaling pathways, including NFκB/NLRP3, associated with sepsis-induced immune dysregulation. We identified a pivotal role of Interleukin-1 receptor 2 (IL-1R2) in modulating inflammatory responses in sepsis, with IL-1R2 showing a 2.1-fold upregulation in septic patients. Transcriptomic integration revealed the activation of 42 significantly enriched signaling pathways, with 26 upregulated and 26 downregulated pathways. Notably, the NFκB/NLRP3 signaling axis emerged as a central hub of immune dysregulation. Gene Ontology (GO) enrichment analysis highlighted “neutrophil activation involved in immune response” as the top biological process. Our findings suggest that IL-1R2 functions as a key immunoregulatory molecule and represents a promising therapeutic target. Moreover, we observed distinct patterns of oxidative stress regulation and immune cell activation, with potential biomarkers correlating with disease severity. These insights not only enhance the molecular understanding of sepsis but also point toward novel precision therapeutic strategies focused on modulating inflammation to improve patient outcomes.

Introduction Interleukin-1 (IL-1), a key inflammatory mediator, plays a critical role in the pathogenesis of sepsis. IL-1 signals through two major receptors, the signaling receptor IL-1R1 and the decoy receptor IL-1R2. However, the cell-type-specific and organ-specific expression dynamics of these receptors during sepsis remain poorly characterized. Methods Using publicly available single-cell RNA sequencing (scRNA-seq) datasets and flow cytometry validation, we systematically analyzed the expression profiles of IL-1R1 and IL-1R2 across multiple organs—including the lung, liver, heart, and small intestine in murine models of cecal ligation and puncture (CLP)-induced sepsis. Results We found that IL-1R1 was predominantly expressed on non-immune cells (lung fibroblasts, liver endothelial cells and heart fibroblasts), and showed increased changes during sepsis. In contrast, IL-1R2 was primarily expressed on neutrophils and monocyte-derived macrophages in healthy conditions, with minimal expression on tissue resident macrophages such as alveolar macrophages and Kupffer cells). Sepsis induced a significant upregulation of IL-1R2 on neutrophils and monocyte-derived macrophages across all organs. However, resident macrophages in the lung, liver and heart maintain low expression during sepsis. Discussion We reveal distinct and compartmentalized expression landscapes for IL-1R1 and IL-1R2 across organs during sepsis. These findings offer a deep understanding of IL-1 receptors biology and shed light on their contributions to immune modulation and tissue-specific responses in sepsis.

Interleukin-1 (IL-1)/IL-1 receptor family consists of activators and inhibitors which play a key role in inflammation, emergency myelopoiesis, and myeloid cell activation. The latter includes the IL-1R2 decoy receptor. To investigate the expression and significance of IL-1R2 in sepsis, we conducted high-dimensional flow cytometry of circulating cells from patients stratified according to the Sequential Sepsis-Related Organ Failure Assessment (SOFA) score. Here we report that the IL-1 decoy receptor is selectively upregulated on the plasma membrane of leukocytes and, in particular, monocytes from septic patients, and downregulated in septic shock. Flow cytometry combined with transcriptomic analysis of publicly available datasets indicated that IL-1R2 is associated with the differentiation of monocytes to a population of circulating monocytic cells with macrophage features (Mono/Mφ). In vitro stimulation of monocytes from healthy donors with Colony Stimulating Factors (CSFs), in particular GM-CSF and Lipopolysaccharides (LPS), induced IL-1R2+ Mono/Mφ, which recapitulated the characteristics of sepsis-associated monocytic cells, including low expression of HLA-DR, high levels of macrophage markers such as MS4A4A and CD63, immune checkpoints, immunosuppressive molecules and selected scavenger receptors. Membrane-associated IL-1R2 and MS4A4A correlated with immunological markers, cytokine storm, and clinical parameters (e.g., SOFA score, creatinine, survival), reflecting the infection severity in hospitalized patients. Thus, in sepsis IL-1R2 is expressed in a subset of circulating monocytes co-expressing mature macrophage and immune dysfunction features with clinical significance.

This study aimed to identify novel sepsis biomarkers by evaluating serum interleukin-1 receptor type 2 (IL1R2) for its diagnostic and prognostic utility, in light of the limitations of current markers like PCT and CRP. A single-center retrospective analysis was conducted involving 55 sepsis patients and 42 non-sepsis controls. Serum IL1R2 levels, measured via ELISA within 24 h of admission, were compared against clinical data, including SOFA scores, 28-day mortality, and laboratory parameters (PCT, CRP). Diagnostic performance was assessed using ROC curve analysis, while prognostic utility was determined via Kaplan–Meier analysis. A cecal ligation and puncture (CLP) was used to track IL1R2 dynamics over time. Sepsis patients exhibited significantly elevated serum IL1R2 levels compared to controls. IL1R2 demonstrated strong diagnostic power (AUC = 0.908), outperforming PCT and CRP. Furthermore, higher IL1R2 levels correlated with increased SOFA scores and predicted poorer 28-day survival. In the CLP model, serum IL1R2 rose within 4 h post-sepsis, peaked within 24 h, returned to baseline by day 3, and fell below normal by day 7. Serum IL1R2 is a promising biomarker, offering a superior ability to correlate with disease severity and predict 28-day mortality.

Interleukin-1 (IL-1) is a primary cytokine of innate immunity and inflammation. IL-1 belongs to a complex family including ligands with agonist activity, receptor antagonists, and an anti-inflammatory cytokine. The receptors for these ligands, the IL-1 Receptor (IL-1R) family, include signaling receptor complexes, decoy receptors, and negative regulators. Agonists and regulatory molecules co-evolved, suggesting the evolutionary relevance of a tight control of inflammatory responses, which ensures a balance between amplification of innate immunity and uncontrolled inflammation. IL-1 family members interact with innate immunity cells promoting innate immunity, as well as with innate and adaptive lymphoid cells, contributing to their differentiation and functional polarization and plasticity. Here we will review the properties of two key regulatory receptors of the IL-1 system, IL-1R2, the first decoy receptor identified, and IL-1R8, a pleiotropic regulator of different IL-1 family members and co-receptor for IL-37, the anti-inflammatory member of the IL-1 family. Their complex impact in pathology, ranging from infections and inflammatory responses, to cancer and neurologic disorders, as well as clinical implications and potential therapeutic exploitation will be presented.

IL‐1 family members and their signaling receptors are key drivers of inflammation in sterile or infectious conditions, as well as polarization of the innate and adaptive immunity. Deregulated or excessive activation of the IL‐1 system is associated with detrimental inflammatory reactions. Beside signaling receptors, IL‐1‐family receptors comprise decoy or negative regulatory receptors, which regulate cell activation mediated by IL‐1 family ligands. IL‐1‐family negative regulatory receptors, which include IL‐1R8 and IL‐1R2, have peculiar structural features and functions essential to the self‐regulation of the IL‐1 system. IL‐1R8 and IL‐1R2 emerge as regulatory molecules whose function is context‐dependent, spanning from negative regulation of inflammation in infections or conditions of sterile inflammation and cell damage, including cancer‐related inflammation, to skewing of myeloid and lymphoid cells, modulation of anti‐tumor immunity, and immune checkpoint activity. This review reports new insights into the physio‐pathological roles of these two negative regulatory IL‐1 family members, emphasizing their mechanisms of action and potential for innovative therapeutic interventions.

Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS) are severe inflammatory conditions with high morbidity and mortality. Understanding the molecular mechanisms underlying these diseases is crucial for developing effective treatments. To investigate the molecular mechanisms underlying ALI, we established a lipopolysaccharide (LPS)-induced mouse model. Bioinformatics and machine learning techniques were utilized to identify key genes and construct gene co-expression networks. Single-cell RNA sequencing was performed to analyze Il1r2 expression specifically in neutrophils. CellChat and hdWGCNA were employed to explore gene co-expression modules and cell-cell communication networks, respectively. Experimental validations included qRT-PCR for gene expression quantification, and western blotting, immunohistochemistry, and immunofluorescence for protein-level confirmation. Four key genes—Cebpd, Hspa12b, Pim1, and Il1r2—were identified as potential biomarkers and therapeutic targets. Il1r2 was identified as a key regulator of inflammation, predominantly expressed in neutrophils. Immune cell infiltration analysis revealed increased neutrophils, monocytes, and dendritic cells in ALI samples. CellChat and hdWGCNA highlighted the significant role of Il1r2 in neutrophil-macrophage signaling in immune regulation. Furthermore, overexpression of Il1r2 in neutrophils reduced lung inflammation and promoted M2 macrophage polarization in vivo. This indicated that Il1r2 alleviates ALI by modulating the immune response, particularly through interactions with macrophages. Neutrophil-derived Il1r2 plays a critical role in modulating inflammation in ALI by promoting M2 macrophage polarization. These findings suggest that targeting Il1r2 may offer a novel therapeutic approach to control the immune response in ALI and other inflammatory diseases.

Background Septic shock is linked with high mortality and significant long-term morbidity in survivors. However, the specific role of neutrophils in septic shock pathophysiology remains scarce in recent research. Methods Peripheral blood immune cells from healthy donors and patients with septic shock were analyzed using single-cell RNA sequencing and batch RNA sequencing. We measured serum CD121b in both patients and healthy donors. Peripheral immune cells were isolated and exposed to either a CD121b recombinant protein or a CD121b blocking antibody to evaluate the expression of inflammatory factors. Additionally, in a humanized mouse sepsis model, the expression of CD121b in neutrophils across different tissues was assessed following treatment with all-trans retinoic acid (ATRA). Results This study identified a subset of CD10-CD121b+ neutrophils in the peripheral blood of patients with septic shock. These patients exhibited elevated concentrations of soluble CD121b in serum and urine. Furthermore, outcomes revealed that the presence of CD121b+ neutrophils positively correlated with the severity of septic shock. These cells displayed immunosuppressive characteristics; after blocking CD121b, proinflammatory cytokines increased in peripheral immune cells. Additionally, we found that treatment with ATRA down-regulated the expression of CD121b. Conclusions CD121b is closely associated with the progression of septic shock and may serve as a potential predictor indicator of immunosuppression for the condition.

Objective To screen out core genes potentially prognostic for sepsis and construct a competing endogenous RNA (ceRNA) regulatory network. Methods Subjects included in this project were 23 sepsis patients and 10 healthy people. RNA-seq for lncRNA, miRNA and mRNA was performed in the peripheral blood samples. Differentially expressed RNAs (DER) were screened out for further analysis. GO annotation and GSEA functional clustering were performed to view the functional enrichment of DEmRNAs. Core genes of prognostic significance were screened out with the weighted correlation network analysis (WGCNA). Meta-analysis and Survival analysis was devised in different microarray datasets. RT-qPCR was conducted to validate these core genes. A ceRNA network was accordingly constructed according to the correlation analysis and molecular interaction prediction. Results RNA-seq and differential analysis screened out 1,044 DEmRNAs, 66 DEmiRNAs and 155 DElncRNAs. The GO and GSEA analysis revealed that DEmRNAs are mainly involved in inflammatory response, immune regulation, neutrophil activation. WGCNA revealed 4 potential core genes, including CD247, IL-2Rβ, TGF-βR3 and IL-1R2. In vitro cellular experiment showed up-regulated expression of IL-1R2 while down-regulated of CD247, IL-2Rβ, TGF-βR3 in sepsis patients. Correspondingly, a ceRNA regulatory network was build based on the core genes, and multiple lncRNAs and miRNAs were identified to have a potential regulatory role in sepsis. Conclusion This study identified four core genes, including CD247, IL-1R2, IL-2Rβ and TGF-βR3, with potential to be novel biomarkers for the prognosis of sepsis. In the meantime, a ceRNA network was constructed aiming to guide further study on prognostic mechanism in sepsis.

Background To identify potential diagnostic and prognostic biomarkers of the early stage of sepsis. Methods The differentially expressed genes (DEGs) between sepsis and control transcriptomes were screened from GSE65682 and GSE134347 datasets. The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) analyses. The diagnostic and prognostic abilities of the markers were evaluated by plotting receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed to further elucidate the molecular mechanisms and immune-related processes. Finally, the potential biomarkers were validated in a septic mouse model by qRT-PCR and western blotting. Results Eleven DEGs were identified between the sepsis and control samples, including YOD1, GADD45A, BCL11B, IL1R2, UGCG, TLR5, S100A12, ITK, HP, CCR7 and C19orf59 (all AUC>0.9). Furthermore, the survival analysis identified YOD1, GADD45A, BCL11B and IL1R2 as the prognostic biomarkers of sepsis. According to GSEA, four DEGs were significantly associated with immune-related processes. In addition, ssGSEA demonstrated a significant difference in the enriched immune cell populations between the sepsis and control groups (all P < 0.05). Moreover, YOD1, GADD45A and IL1R2 were upregulated, and BCL11B was downregulated in the heart, liver, lungs, and kidneys of the septic mice model. Conclusions We identified four potential immune-releated diagnostic and prognostic gene markers for sepsis that offer new insights into its underlying mechanisms.

Sepsis, a life‐threatening condition triggered by dysregulated host response to infection, poses significant global health challenges. Identifying lipopolysaccharide (LPS)‐related biomarkers and underlying mechanisms remains critical, yet underexplored. We integrated bulk microarray datasets and single‐cell RNA‐seq data from the Gene Expression Omnibus to identify LPS‐related genes associated with sepsis. scRNA‐seq was used for cell clustering, annotation, AUCell scoring, and cell‐cell communication analysis. Differentially expressed LRGs were screened from both bulk and single‐cell datasets and intersected. Three machine learning algorithms—least absolute shrinkage and selection operator regression, support vector machine–recursive feature elimination, and extreme gradient boosting—were applied to select robust diagnostic biomarkers. Gene expression was validated via qRT‐PCR. Diagnostic and prognostic models were constructed and validated in independent cohorts. Seven key LRGs were identified. The diagnostic model achieved high AUCs (> 0.89) across validation cohorts, while the prognostic model effectively stratified patients into distinct survival groups. High‐risk groups showed increased myeloid‐derived suppressor cell and macrophage infiltration, activation of inflammatory pathways, and unique intercellular communication networks. scRNA‐seq revealed cell‐type‐specific LRGs expression, particularly in myeloid populations. We established and validated a robust LPS‐related biomarker model that integrates bulk microarray and single‐cell transcriptomics, offering novel diagnostic, prognostic, and therapeutic insights for sepsis.

Sepsis is a condition of high mortality arising from dysregulation of the host immune response. Gene expression studies have identified multiple immune endotypes but gaps remain in our understanding of the underlying biology and heterogeneity. We used single-cell multi-omics to profile 272,993 cells across 48 whole blood samples from 26 sepsis patients (9 with paired convalescent samples), 6 healthy controls and 7 post-surgery patients. We identified immature neutrophil populations specific to sepsis and demonstrated the immunosuppressive nature of sepsis neutrophils in vitro. An IL1R2+ neutrophil state was expanded in a transcriptomic sepsis endotype associated with increased early mortality (sepsis response signature 1, SRS1), together with enrichment of the response to IL-1 pathway in mature neutrophils, marking IL-1 out as a potential target for immunotherapy in SRS1 sepsis patients. We confirmed the expansion of immature neutrophils, specifically IL1R2+ neutrophils, in SRS1 in additional cohorts of patients (n = 906 RNA-sequencing samples, n = 41 CyTOF samples). Neutrophil changes persisted in convalescence, implicating disrupted granulopoiesis. Our findings establish a cellular immunological basis for transcriptomically defined sepsis endotypes and emphasise the relevance of granulopoietic dysfunction in sepsis, identifying opportunities for precision medicine approaches to the condition.

Sepsis is characterized by severe organ failure due to an impaired response to infection. The underlying pathophysiology of sepsis is characterized by concurrent unbalanced hyperinflammatory and immunoparalysis. This study aimed to identify new key biomarkers that could predict outcomes in sepsis patients and explore theirunderlying molecular mechanisms. Bulk transcriptome data (GSE65682, GSE28750, GSE57065, GSE95233) and scRNA-seq data (GSE167363) of sepsis were obtained from the GEO database. Data for MR analysis were sourced from the eQTLGen Consortium and IEU OpenGWAS project. Prognostic biomarkers and potential drug targets for sepsis were identified through univariate Cox regression and MR analysis. The expression of these biomarkers was further validated using scRNA-seq data to investigate the underlying molecular mechanisms. Significantly higher expression of CHIT1 was found at sepsis non-survivor and associated with 28-day mortality of sepsis. scRNA-seq data of septic samples found that CHIT1 mainly expressed in neutrophils, which was also higher in sepsis non-survivors. The CHIT1 + neutrophils expressed higher inflammation related genes of S100A8, S100A9, S100A11, S100A12, IL1R2, IFNGR2, TLR2 and CXCL8 and reduced expression of HLA related genes of HLA-DMA, HLA-DPA1, HLA-DPB1, HLA-DRA, HLA-DRB1 and HLA-DRB5. Moreover, cell-chat analysis also showed that CHIT1 + neutrophils could interact with other immune cell types, including NK cells, erythroid cells, monocytes/macrophages, and DC by the way of ICAM1-(ITGAM + ITGB2) pathway. We identified CHIT1 as new biomarker and potential drug target for sepsis, which may intensify hyperinflammation and immune suppression of neutrophils. Developing immunotherapeutic strategies aimed at targeting CHIT1 would help to enhance sepsis outcomes.

Abstract Peripheral blood samples from 15 septic patients admitted within 24 h and 8 healthy volunteers were used to conduct RNA-seq. Quantitative PCR of THP1 cells was performed to investigate the expression levels of the selected key genes. A total of 1,128 differential genes were identified, 721 of which were upregulated and 407 were downregulated. These genes are mainly involved in neutrophil activation, T cell regulation, immune effector process regulation, cytokine receptor activity, and cytokine binding. The six target genes were ELANE, IL1R2, RAB13, RNASE3, FCGR1A, and TLR5. In the sepsis group, FCGR1A and TLR5 were positively associated with survival compared to ELANE, IL1R2, RAB13, and RNASE3, which were adversely associated with survival. Furthermore, a meta-analysis based on public databases revealed an increased expression of these six target genes in the peripheral blood of patients with sepsis. In addition, we discovered that monocytes primarily express these genes. Using qPCR, we confirmed that these six important genes were highly expressed in lipopolysaccharide-treated THP1 cells. In summary, these findings suggest that ELANE, IL1R2, RAB13, RNASE3, FCGR1A, and TLR5 may influence the prognosis of patients with sepsis and provide novel insights and potential avenues for the treatment of sepsis.

Sepsis is a life-threatening disease induced by a systemic inflammatory response, which leads to organ dysfunction and mortality. In sepsis, the host immune response is depressed and unable to cope with infection; no drug is currently available to treat this. The lungs are frequently the starting point for sepsis. This study aimed to identify potential genes for diagnostics and therapeutic purposes in sepsis by a comprehensive bioinformatics analysis. Our criteria are to unravel sepsis-associated signature genes from gene expression datasets. Differentially expressed genes (DEGs) were identified from samples of sepsis patients using a meta-analysis and then further subjected to functional enrichment and protein‒protein interaction (PPI) network analysis for examining their potential functions. Finally, the expression of the topmost upregulated genes (ARG1, IL1R2, ELANE, MMP9) was quantified by reverse transcriptase-PCR (RT-PCR), and myeloperoxidase (MPO) expression was confirmed by immunohistochemistry (IHC) staining in the lungs of a well-established sepsis mouse model. We found that all the four genes were upregulated in semiquantitative RT-PCR studies; however, MMP9 showed a nonsignificant increase in expression. MPO staining showed strong immunoreactivity in sepsis as compared to the control. This study demonstrates the role of significant and widespread immune activation (IL1R2, MMP9), along with oxidative stress (ARG1) and the recruitment of neutrophils, in sepsis (ELANE, MPO).

Both bacterial and viral infections can trigger an overwhelming host response, leading to immunopathology and organ dysfunction. Multiple studies have reported dysregulated myeloid cell states in patients with bacterial sepsis or severe SARS-CoV-2 infection. However, their relevance to viral infections other than COVID-19, the factors driving their induction, and their role in tissue injury remain poorly understood. Here, we performed a multi-cohort analysis of single cell and bulk transcriptomic data from 1845 patients across 25 studies. Our meta-analysis revealed a conserved severity-associated gene signature pointing to emergency myelopoiesis (EM) and increased IL1R2 expression in monocytes and neutrophils from patients with bacterial sepsis, COVID-19, and influenza. Analysis of tocilizumab-treated COVID-19 patients showed that IL-6 signaling blockade partially reduces this signature and results in a compensatory increase in G-CSF. To validate the role of these cytokines in vivo, we used a mouse model of influenza infection that recapitulates severity-associated increases in IL1R2+ monocytes and IL1R2hi neutrophils, and demonstrate that combined IL-6 and G-CSF blockade inhibits their production. Our study demonstrates the cooperative role of G-CSF and IL-6 in driving the production of severity-associated IL1R2+ myeloid cells and highlights the link between myeloid dysregulation and tissue injury during severe infection. Multi-cohort analysis of single cell and bulk transcriptional data combined with in vitro and in vivo experiments highlight the role of IL1R2+ myeloid cells on tissue injury during severe infection.

OBJECTIVES To obtain a gene expression signature to distinguish between septic shock and non-septic shock in postoperative patients, since patients with both conditions show similar signs and symptoms. METHODS Differentially expressed genes were selected by microarray analysis in the discovery cohort. These genes were evaluated by quantitative real time polymerase chain reactions in the validation cohort to determine their reliability and predictive capacity by receiver operating characteristic curve analysis. RESULTS Differentially expressed genes selected were IGHG1, IL1R2, LCN2, LTF, MMP8, and OLFM4. The multivariate regression model for gene expression presented an area under the curve value of 0.922. These genes were able to discern between both shock conditions better than other biomarkers used for diagnosis of these conditions, such as procalcitonin (0.589), C-reactive protein (0.705), or neutrophils (0.605). CONCLUSIONS Gene expression patterns provided a robust tool to distinguish septic shock from non-septic shock postsurgical patients and shows the potential to provide an immediate and specific treatment, avoiding the unnecessary use of broad-spectrum antibiotics and the development of antimicrobial resistance, secondary infections and increase health care costs.

Immune cell metabolic reprogramming toward glycolysis is vital for sepsis defense. While interleukin 1 receptor 2 (IL1R2) acts as a decoy receptor for IL1α/β, its potential impact on cell metabolism and death during sepsis remains unclear. This study observed elevated plasma soluble IL1R2 (sIL1R2) levels in septic patients and mice. In pyroptotic macrophages, reduced intracellular IL1R2 expression led to its release extracellularly. Proteomic screening identified enolase 1 (ENO1), a key glycolysis enzyme, as the binding partner of IL1R2 in macrophages. IL1R2 suppresses ENO1 activity to inhibit glycolysis, gasdermin D (GSDMD)‐mediated pyroptosis, and inflammation in macrophages. IL1R2‐deficient mice exhibited heightened susceptibility to sepsis, with increased inflammation, organ injury, and mortality. Notably, ENO1 inhibition reduced inflammation, organ injury, and improved survival rates in septic mice. The study reveals that IL1R2 interacts with ENO1 to inhibit glycolysis‐mediated pyroptosis and inflammation in sepsis, suggesting the IL1R2‐ENO1 interaction as a promising therapeutic target of sepsis.

Summary Objectives IL-1α/β and TNF are closely linked to the pathology of severe COVID-19 and sepsis. The soluble forms of their receptors, functioning as decoy receptors, exhibit inhibitory effects. However, little is known about their regulation in severe bacterial and viral infections, which we aimed to investigate in this study. Methods The circulating soluble receptors of TNF (sTNFR1 and sTNFR2) and IL-1α/β (sIL-1R1, sIL-1R2) were evaluated in the plasma of patients with COVID-19, severe bacterial infections, and sepsis and compared with healthy controls. Additionally, IL1R1, IL1R2, TNFRSF1A, and TNFRSF1B expression was evaluated at the single cell level in PBMCs derived from COVID-19 or sepsis patients. Results Plasma concentrations of sIL-1R1, sTNFR1, and sTNFR2 were significantly higher in COVID-19 patients compared to healthy subjects. Notably, sIL-1R1 levels were particularly elevated in ICU COVID-19 patients, and transcriptome analysis indicated heightened IL1R1 expression in PBMCs from severe COVID-19 patients. In severe bacterial infections, only sTNFR1 and sTNFR2 exhibited increased levels compared to healthy controls. Sepsis patients had decreased sIL-1R1 plasma concentrations but elevated sIL-1R2, sTNFR1, and sTNFR2 levels compared to healthy individuals, reflecting the heightened expression due to the increased numbers of monocytes present in sepsis. Finally, elevated concentrations of sIL-1R2, sTNFR1, and sTNFR2 were moderately associated with reduced 28-day survival in sepsis patients. Conclusion Our study reveals distinct regulation of plasma concentrations of soluble IL-1 receptors in COVID-19 and sepsis. Moreover, soluble TNF receptors 1 and 2 consistently rise in all conditions and show a positive correlation with disease severity in sepsis.

… Our data show that in the mouse, neutrophils mainly express the decoy receptor IL-1R2 … Elevated levels of soluble IL-1R2 are also found in vivo in the circulation of sepsis patients [9…

BackgroundAcute respiratory distress syndrome (ARDS) is a disease associated with a high mortality rate. The initial phase is characterized by induction of inflammatory cytokines and chemokines and influx of circulating inflammatory cells, including macrophages which play a pivotal role in the innate and adaptive immune responses to injury. Growing evidence points to phenotypic heterogeneity and plasticity between various macrophage activation states.MethodsIn this study, gene expression in alveolar macrophages and circulating leukocytes from healthy control subjects and patients with ARDS was assessed by mRNA microarray analysis.ResultsBoth alveolar macrophages and circulating leukocytes demonstrated up-regulation of genes encoding chemotactic factors, antimicrobial peptides, chemokine receptors, and matrix metalloproteinases. Two genes, the pro-inflammatory S100A12 and the anti-inflammatory IL-1 decoy receptor IL-1R2 were significantly induced in both cell populations in ARDS patients, which was confirmed by protein quantification. Although S100A12 levels did not correlate with disease severity, there was a significant association between early plasma levels of IL-1R2 and APACHE III scores at presentation. Moreover, higher levels of IL-1R2 in plasma were observed in non-survivors as compared to survivors at later stages of ARDS.ConclusionsThese results suggest a hybrid state of alveolar macrophage activation in ARDS, with features of both alternative activation and immune tolerance/deactivation.. Furthermore, we have identified a novel plasma biomarker candidate in ARDS that correlates with the severity of systemic illness and mortality.

Given the limited data describing the phenotype for type 2 interleukin -1 receptor (Il1r2-/-) in mouse strains and based on the decoy role of the gene product (IL-1R2), we hypothesized that IL-1R2 may have a unique but similar inhibitory role to IL-1R antagonist (IL-1Ra) in vivo. Despite the anti-inflammatory function of IL-1R2, its role in disease in vivo remains unclear. Therefore, we designed and implemented a knock-out construct template for a mouse embryonic stem (ES) cell line that can be used to easily make knockout mice. Bacterial artificial chromosome (BAC) clone of Il1r2 from mouse strain AB2.2 and ES cells from same strain were obtained and a long chain PCR was performed to isolate homologous arms containing homologous segments (8kb and 2kb). Short segments were cloned out for use as probe sequences and a construct with deletion in exon 3 was made so it can be removed in vivo. The NeoR in cloning vector was then flanked with loxP elements. The two homologous arms were successfully amplified with a truncation in exon 3 of the gene and the wild type cloning plasmid (p1049) was serially modified with loxP elements. One of the successfully transformed plasmid DNA was used as the starting material for the ligation of the subsequent loxP-PacI linker. This plasmid (p1049XL) was amplified in E. coli DH5α cells and DNA extracted. The loxP-PacI linker was successfully ligated into the plasmid and transformed clones screened with MspI and compared to the virtual digest of the theoretical plasmid containing the insert and subsequently sequenced. This study has provided the basic ingredients for making an Il1r2-deficient mouse in order to adequately characterize the phenotype. By assembling the complete knock out construct from templates already provided in this study for the knock out in embryonic stem cells, Il1r2-deficient mice could be made.

Purpose Sepsis is a serious life-threatening condition characterised by multi-organ failure due to a disturbed immune response caused by severe infection. The pathogenesis of sepsis is unclear. The aim of this article is to identify potential diagnostic and prognostic biomarkers of sepsis to improve the survival of patients with sepsis. Methods We downloaded 7 datasets from Gene Expression Omnibus database and screened the immune-related differential genes (IRDEGs). The related functions of IRDEGs were analyzed through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). CIBERSORT was used to evaluate the infiltration of the immune cells, and Pearson algorithm of R software was used to calculate the correlation between the immune cell content and gene expression to screen the genes most related to immune cells in sepsis group, which were intersected with IRDEGs to obtain common genes. Key genes were identified from common genes based on the area under the receiver operating characteristic curve (AUC) greater than 0.8 in the 6 datasets. We then analyzed the predictive value of key genes in sepsis survival. Finally, we verified the expression of key genes in patients with sepsis by PCR analysis. Results A total of 164 IRDEGs were obtained, which were associated mainly with inflammatory and immunometabolic responses. Ten key genes (IL1R2, LTB4R, S100A11, S100A12, SORT1, RASGRP1, CD3G, CD40LG, CD8A and PPP3CC) were identified with high diagnostic efficacy. Logistic regression analysis revealed that six of the key genes (LTB4R, S100A11, SORT1, RASGRP1, CD3G and CD8A) may affect the survival prognosis of sepsis. PCR analysis confirmed that the expression of seven key genes (IL1R2, S100A12, RASGRP1, CD3G, CD40LG, CD8A and PPP3CC) was consistent with microarray outcome. Conclusion This study explored the immune and metabolic response mechanisms associated with sepsis, and identified ten potential diagnostic and six prognostic genes.

… The transcriptome library was constructed using the VAHTS Universal V5 RNA-seq Library … the immunoregulatory role of IL1R2 in vitro, we established a cellular infection model using …

Abstract Purpose RNA-seq sequencing and bioinformatics methods were combined to identify differentially expressed genes,and Investigated new biomarkers for sepsis diagnosis and treatment. Methods Blood samples from 30 patients with sepsis, 10 normal volunteers, and 15 patients with systemic inflammatory response syndrome (systemic inflammatory response group) were collected in the Affiliated Hospital of Southwest Medical University for RNA-seq sequencing(TRN:ChiCTR1900021261,Date:2019.02.04).After differentiating the data, the Venn plot intersection, GO enrichment analysis, and protein interaction analysis were performed.Using the public dataset, a survival curve was constructed for the differential genes. The expression of different groups was verified as statistically significant, and then the ROC curve was constructed with sequencing data.Finally, with the help of single-cell transcriptome sequencing, the localization cell line of the core gene was identified. Results Comparing with the normal group, sepsis serum samples were screened for 365 differentially expressed genes: 85 were downregulated and 280 were upregulated. Compared with the systemic inflammatory response group, in the serum samples of patients with sepsis, 484 differential genes were identified.By intersection, 98 differentially expressed genes were identified, of which 184 were down-regulated and 300 were up-regulated. Among these differential genes GO function is enriched in specific granules, tertiary granules and specific granule cavities. CEBPE, IL1R2, CYSTM1, S100A9, FCER1A, MCEMP1, NELL2, SERPINB10 were found in the center of the protein interaction network analysis.Based on RNA-sequencing data, CEBPE was highly expressed in the sepsis group and NELL2 was low in the group.The survival curve showed that the lower the CEBPE expression in patients with sepsis, the higher the NELL2 expression and the higher the survival rate. Based on the ROC curves, CEBPE had an AUC of 0.920 (normal), 0.882 (systemic inflammatory response group), while NELL2 had an AUC of 0.960(normal), 0.844 (systemic inflammatory response group).In single-cell sequencing, CEBPE was mainly found in macrophage cells and NELL2 was found in T cells. Conclusion CEBPE expression in macrophages is positively correlated with sepsis mortality. NELL2 expression in T cell lines is positively correlated with survival rates in sepsis patients.Both have good diagnostic value, or they can be used as new research targets.