Predicting the prognosis in patients with sepsis by a pyroptosis-related gene signature

Comprehensive transcriptome profiling in sepsis induced by pyogenic liver abscess

Sepsis is a critical condition characterized by a dysregulated immune response to infection, leading to widespread inflammation, tissue damage, organ failure, and often death. It is a leading cause of morbidity and mortality, particularly in intensive care units, due to its complex pathophysiology involving immune dysregulation, coagulation abnormalities, and metabolic disturbances. Pyogenic liver abscess (PLA) is a significant cause, especially in developing countries where its incidence is rising. PLA, an infectious liver disease, can lead to sepsis, termed sepsis secondary to PLA (SLA). This study aimed to identify key genes and non-coding RNAs involved in the pathogenesis and treatment of SLA. We performed RNA sequencing on peripheral blood samples from healthy individuals, SLA patients, and SLA patients after seven days of therapy. Integrated bioinformatics analysis identified 4549 differentially expressed (DE) mRNAs, 9808 DE lncRNAs, 467 DE circRNAs, and 292 DE miRNAs between SLA patients and healthy controls. Additionally, 3199 mRNAs, 6018 lncRNAs, 161 circRNAs, and 132 miRNAs were differentially expressed between SLA patients before and after seven days of therapy. DE mRNAs in both comparisons were associated with immune responses; DE lncRNAs were linked to the B cell receptor signaling pathway and osteoclast differentiation; DE circRNAs were connected to Chagas disease and the B cell receptor signaling pathway; and DE miRNAs were implicated in the MAPK and estrogen signaling pathways. We constructed lncRNA/circRNA-miRNA-mRNA networks to explore regulatory relationships, validating 16 ceRNAs through RT-PCR. These findings provide new insights into SLA pathogenesis and treatment, potentially guiding the development of novel therapies.

Leveraging diverse cell-death patterns in diagnosis of sepsis by integrating bioinformatics and machine learning

Background

Sepsis is a life-threatening disease causing millions of deaths every year. It has been reported that programmed cell death (PCD) plays a critical role in the development and progression of sepsis, which has the potential to be a diagnosis and prognosis indicator for patient with sepsis.

Methods

Fourteen PCD patterns were analyzed for model construction. Seven transcriptome datasets and a single cell sequencing dataset were collected from the Gene Expression Omnibus database.

Results

A total of 289 PCD-related differentially expressed genes were identified between sepsis patients and healthy individuals. The machine learning algorithm screened three PCD-related genes, NLRC4, TXN and S100A9, as potential biomarkers for sepsis. The area under curve of the diagnostic model reached 100.0% in the training set and 100.0%, 99.9%, 98.9%, 99.5% and 98.6% in five validation sets. Furthermore, we verified the diagnostic genes in sepsis patients from our center via qPCR experiment. Single cell sequencing analysis revealed that NLRC4, TXN and S100A9 were mainly expressed on myeloid/monocytes and dendritic cells. Immune infiltration analysis revealed that multiple immune cells involved in the development of sepsis. Correlation and gene set enrichment analysis (GSEA) analysis revealed that the three biomarkers were significantly associated with immune cells infiltration.

Conclusions

We developed and validated a diagnostic model for sepsis based on three PCD-related genes. Our study might provide potential peripheral blood diagnostic candidate biomarkers for patients with sepsis.

CircIRAK3 Promotes Neutrophil Extracellular Trap Formation by Improving the Stability of ELANE mRNA in Sepsis

Excessive formation of neutrophil extracellular traps (NETs) has been shown to exacerbate inflammatory injury and organ damage in patients with sepsis. Circular RNAs (circRNAs) abnormally expressed in immune cells of sepsis patients, and play an important role in the pathogenesis of dysregulated immune responses. However, the functions of circRNAs in NET formation during sepsis remain unknown. Here, we identified circIRAK3, a novel circRNA that was upregulated in peripheral blood neutrophils of sepsis patients. Combining clinical data, we revealed that elevated circIRAK3 was positively correlated with blood NET levels. Furthermore, knockdown and overexpression in differentiated HL-60 (dHL-60) neutrophil-like cells demonstrated that circIRAK3 promoted NET formation. In addition, we found that circIRAK3 promoted NET formation via positively regulating elastase expression in dHL-60 cells when treated with inflammatory stimuli. Mechanistically, circIRAK3 directly interacted with ELAVL1 to improve ELANE mRNA stability and consequently promote elastase protein expression. In summary, our study reveals that circIRAK3 promotes NET formation in sepsis by increasing ELANE mRNA levels.

EIF2AK2 protein targeted activation of AIM2-mediated PANoptosis promotes sepsis-induced acute kidney injury

BACKGROUND

Acute kidney injury (AKI) frequently occurs as a complication of sepsis. PANoptosis refers to a type of inflammatory programmed cell death that exhibits key characteristics of apoptosis, necroptosis, and pyroptosis. Here, we evaluated the role of absent in melanoma 2 (AIM2) and eukaryotic translation initiation factor 2 alpha kinase 2 (EIF2AK2) in septic AKI.

METHODS

A septic AKI model was created through cecal ligation and puncture (CLP), while an in vitro model was developed using lipopolysaccharide (LPS)-stimulated HK2 cells. Hematoxylin and eosin (HE), Periodic acid-Schiff (PAS), and TUNEL staining were conducted to assess kidney injury in mice. Levels of serum creatinine (Scr) and blood urea nitrogen (BUN) were detected by kits. Gene expression was detected utilizing RT-qPCR, and Western blot was used to test protein levels. Immunofluorescence was employed to measure EIF2AK2 and AIM2 expression in mouse kidney tissue. Lactate dehydrogenase (LDH) activity assay was conducted to evaluate cytotoxicity. Co-immunoprecipitation (Co-IP) was performed to verify the binding relationship between EIF2AK2 and AIM2.

RESULTS

AIM2 expression was increased in the renal tissue of mice subjected to CLP. Activation of the inflammasome and PANoptosis were observed in the renal tissue of CLP mice. AIM2 depletion attenuated PANoptosis in LPS-treated HK-2 cells. Additionally, EIF2AK2 could directly target AIM2, leading to a positive regulation of AIM2 expression. Notably, EIF2AK2 induced PANoptosis through upregulating AIM2 in HK-2 cells stimulated by LPS.

CONCLUSIONS

Our results revealed the important role of EIF2AK2-induced AIM2 upregulation in the activation of PANoptosis during septic AKI.

IL7R, GZMA and CD8A serve as potential molecular biomarkers for sepsis based on bioinformatics analysis

Purpose

Sepsis is an unusual systemic reaction to what is sometimes an otherwise ordinary infection, and it probably represents a pattern of response by the immune system to injury. However, the relationship between biomarkers and sepsis remains unclear. This study aimed to find potential molecular biomarkers, which could do some help to patients with sepsis.

Methods

The sepsis dataset GSE28750, GSE57065 was downloaded from the GEO database, and ten patients with or without sepsis from our hospital were admitted for RNA-seq and the differentially expressed genes (DEGs) were screened. The Metascape database was used for functional enrichment analysis and was used to found the differential gene list. Protein-protein interaction network was used and further analyzed by using Cytoscape and STRING. Logistic regression and Correlation analysis were used to find the potential molecular biomarkers.

Results

Taking the intersection of the three datasets yielded 287 differential genes. The enrichment results included Neutrophil degranulation, leukocyte activation, immune effectors process, positive regulation of immune response, regulation of leukocyte activation. The top 10 key genes of PPI connectivity were screened using cytoHubba plugin, which were KLRK1, KLRB1, IL7R, GZMA, CD27, PRF1, CD8A, CD2, IL2RB, and GZMB. All of the hub genes are higher expressed in health group of different databases. Logistic regression showed that IL7R, GZMA and CD8A proteins were analyzed and all of them were statistically significant. Correlation analysis showed that there was a statistically significant correlation between IL7R, GZMA and CD8A.

Conclusion

KLRK1, KLRB1, IL7R, GZMA, CD27, PRF1, CD8A, CD2, IL2RB, GZMB are key genes in sepsis, which associated with the development of sepsis. However, IL7R, GZMA and CD8A may serve as the attractively potential molecular biomarkers for sepsis.

Inflammation unleashed: The role of pyroptosis in chronic liver diseases

Pyroptosis, a newly identified form of programmed cell death intertwined with inflammatory responses, is facilitated by the Gasdermin family's pore-forming activity, leading to cell lysis and the release of pro-inflammatory cytokines. This process is a double-edged sword in innate immunity, offering protection against pathogens while risking excessive inflammation and tissue damage when dysregulated. Specifically, pyroptosis operates through two distinct signaling pathways, namely the Caspase-1 pathway and the Caspase-4/5/11 pathway. In the context of chronic liver diseases like fibrosis and cirrhosis, inflammation emerges as a central contributing factor to their pathogenesis. The identification of inflammation is characterized by the activation of innate immune cells and the secretion of pro-inflammatory cytokines such as IL-1α, IL-1β, and TNF-α. This review explores the interrelationship between pyroptosis and the inflammasome, a protein complex located in liver cells that recognizes danger signals and initiates Caspase-1 activation, resulting in the secretion of IL-1β and IL-18. The article delves into the influence of the inflammasome and pyroptosis on various liver disorders, with a specific focus on their molecular and pathophysiological mechanisms. Additionally, the potential therapeutic implications of targeting pyroptosis for liver diseases are highlighted for future consideration.

Alpha-1 antitrypsin targeted neutrophil elastase protects against sepsis-induced inflammation and coagulation in mice via inhibiting neutrophil extracellular trap formation

AIMS

Sepsis pathophysiology is complex and identifying effective treatments for sepsis remains challenging. The study aims to identify effective drugs and targets for sepsis through transcriptomic analysis of sepsis patients, repositioning analysis of compounds, and validation by animal models.

MAIN METHODS

GSE185263 obtained from the GEO database that includes gene expression profiles of 44 healthy controls and 348 sepsis patients categorized by severity. Bioinformatic algorithms revealed the molecular, function, and immune characteristics of the sepsis, and constructed sepsis-related protein-protein interaction networks. Subsequently, Random Walk with Restart analysis was applied to identify candidate drugs for sepsis, which were tested in animal models for survival, inflammation, coagulation, and multi-organ damage.

KEY FINDINGS

Our analysis found 1862 genes linked to sepsis development, enriched in functions like neutrophil extracellular trap formation (NETs) and complement/coagulation cascades. With disease progression, immune activation-associated cells were inhibited, while immune suppression-associated cells were activated. Next, the drug repositioning method identified candidate drugs, such as alpha-1 antitrypsin, that may play a therapeutic role by targeting neutrophil elastase (NE) to inhibit NETs. Animal experiments proved that alpha-1 antitrypsin treatment can improve the survival rate, reduce sepsis score, reduce the levels of inflammation markers in serum, and alleviate muti-organ morphological damage in mice with sepsis. The further results showed that α-1 antitrypsin can inhibit the NETs by suppressing the NE for the treatment of sepsis.

SIGNIFICANCE

Alpha-1 antitrypsin acted on the NE to inhibit NETs thereby protecting mice from sepsis-induced inflammation and coagulation.

Identification of qualitative characteristics of immunosuppression in sepsis based on immune-related genes and immune infiltration features

Objective

Sepsis is linked to high morbidity and mortality rates. Consequently, early diagnosis is crucial for proper treatment, reducing hospitalization, and mortality rates. Additionally, over one-fifth of sepsis patients still face a risk of death. Hence, early diagnosis, and effective treatment play pivotal roles in enhancing the prognosis of patients with sepsis.

Method

The study analyzed whole blood data obtained from patients with sepsis and control samples sourced from three datasets (GSE57065, GSE69528, and GSE28750). Commonly dysregulated immune-related genes (IRGs) among these three datasets were identified. The differential characteristics of these common IRGs in the sepsis and control samples were assessed using the REO-based algorithm. Based on these differential characteristics, samples from eight Gene Expression Omnibus (GEO) databases (GSE57065, GSE69528, GSE28750, GSE65682, GSE69063, GSE95233, GSE131761, and GSE154918), along with three ArrayExpress databases (E-MTAB-4421, E-MTAB-4451, and E-MTAB-7581), were categorized and scored. The effectiveness of these differential characteristics in distinguishing sepsis samples from control samples was evaluated using the AUC value derived from the receiver operating characteristic curve (ROC) curve. Furthermore, the expression of IRGs was validated in peripheral blood samples obtained from patients with sepsis through qRT-PCR.

Results

Among the three training datasets, a total of 84 common dysregulated immune-related genes (IRGs) were identified. Utilizing a within-sample relative expression ordering (REOs)-based algorithm to analyze these common IRGs, differential characteristics were observed in three reverse stable pairs (ELANE-RORA, IL18RAP-CD247, and IL1R1-CD28). In the eight GEO datasets, the expression of ELANE, IL18RAP, and IL1R1 demonstrated significant upregulation, while RORA, CD247, and CD28 expression exhibited notable downregulation during sepsis. These three pairs of immune-related marker genes displayed accuracies of 95.89% and 97.99% in distinguishing sepsis samples among the eight GEO datasets and the three independent ArrayExpress datasets, respectively. The area under the receiver operating characteristic curve ranged from 0.81 to 1.0. Additionally, among these three immune-related marker gene pairs, mRNA expression levels of ELANE and IL1R1 were upregulated, whereas the levels of CD247 and CD28 mRNA were downregulated in blood samples from patients with sepsis compared to normal controls.

Conclusion

These three immune-related marker gene pairs exhibit high predictive performance for blood samples from patients with sepsis. They hold potential as valuable auxiliary clinical blood screening tools for sepsis.

Exploring ncRNA-mediated pathways in sepsis-induced pyroptosis

Sepsis, a potentially fatal illness caused by an improper host response to infection, remains a serious problem in the world of healthcare. In recent years, the role of ncRNA has emerged as a pivotal aspect in the intricate landscape of cellular regulation. The exploration of ncRNA-mediated regulatory networks reveals their profound influence on key molecular pathways orchestrating pyroptotic responses during septic conditions. Through a comprehensive analysis of current literature, we navigate the diverse classes of ncRNAs, including miRNAs, lncRNAs, and circRNAs, elucidating their roles as both facilitators and inhibitors in the modulation of pyroptotic processes. Furthermore, we highlight the potential diagnostic and therapeutic implications of targeting these ncRNAs in the context of sepsis, aiming to cover the method for novel and effective strategies to mitigate the devastating consequences of septic pathogenesis. As we unravel the complexities of this regulatory axis, a deeper understanding of the intricate crosstalk between ncRNAs and pyroptosis emerges, offering promising avenues for advancing our approach to sepsis intervention. The intricate pathophysiology of sepsis is examined in this review, which explores the dynamic interaction between ncRNAs and pyroptosis, a highly regulated kind of programmed cell death.

Analysis of Immune and Prognostic-Related lncRNA PRKCQ-AS1 for Predicting Prognosis and Regulating Effect in Sepsis

Background

Sepsis was a high mortality and great harm systemic inflammatory response syndrome caused by infection. lncRNAs were potential prognostic marker and therapeutic target. Therefore, we expect to screen and analyze lncRNAs with potential prognostic markers in sepsis.

Methods

Transcriptome sequencing and limma was used to screen dysregulated RNAs. Key RNAs were screened by correlation analysis, lncRNA-mRNA co-expression and weighted gene co-expression network analysis. Immune infiltration, gene set enrichment analysis and gene set variation analysis were used to analyze the immune correlation. Kaplan-Meier curve, receiver operator characteristic curve, Cox regression analysis and nomogram were used to analyze the correlation between key RNAs and prognosis. Sepsis model was established by lipopolysaccharide-induced HUVECs injury, and then cell viability and migration ability were detected by cell counting kit-8 and wound healing assay. The levels of apoptosis-related proteins and inflammatory cytokines were detected by RT-qPCR and Western blot. Reactive Oxygen Species and superoxide dismutase were detected by commercial kit.

Results

Fourteen key differentially expressed lncRNAs and 663 key differentially expressed genes were obtained. And these lncRNAs were closely related to immune cells, especially T cell activation, immune response and inflammation. Subsequently, Subsequently, lncRNA PRKCQ-AS1 was identified as the regulator for further investigation in sepsis. RT-qPCR results showed that PRKCQ-AS1 expression was up-regulated in clinical samples and sepsis model cells, which was an independent prognostic factor in sepsis patients. Immune correlation analysis showed that PRKCQ-AS1 was involved in the immune response and inflammatory process of sepsis. Cell function tests confirmed that PRKCQ-AS1 could inhibit sepsis model cells viability and promote cell apoptosis, inflammatory damage and oxidative stress.

Conclusion

We constructed immune-related lncRNA-mRNA regulatory networks in the progression of sepsis and confirmed that PRKCQ-AS1 is an important prognostic factor affecting the progression of sepsis and is involved in immune response.

Exploring the Role of Different Cell-Death-Related Genes in Sepsis Diagnosis Using a Machine Learning Algorithm

Sepsis, a disease caused by severe infection, has a high mortality rate. At present, there is a lack of reliable algorithmic models for biomarker mining and diagnostic model construction for sepsis. Programmed cell death (PCD) has been shown to play a vital role in disease occurrence and progression, and different PCD-related genes have the potential to be targeted for the treatment of sepsis. In this paper, we analyzed PCD-related genes in sepsis. Implicated PCD processes include apoptosis, necroptosis, ferroptosis, pyroptosis, netotic cell death, entotic cell death, lysosome-dependent cell death, parthanatos, autophagy-dependent cell death, oxeiptosis, and alkaliptosis. We screened for diagnostic-related genes and constructed models for diagnosing sepsis using multiple machine-learning models. In addition, the immune landscape of sepsis was analyzed based on the diagnosis-related genes that were obtained. In this paper, 10 diagnosis-related genes were screened for using machine learning algorithms, and diagnostic models were constructed. The diagnostic model was validated in the internal and external test sets, and the Area Under Curve (AUC) reached 0.7951 in the internal test set and 0.9627 in the external test set. Furthermore, we verified the diagnostic gene via a qPCR experiment. The diagnostic-related genes and diagnostic genes obtained in this paper can be utilized as a reference for clinical sepsis diagnosis. The results of this study can act as a reference for the clinical diagnosis of sepsis and for target discovery for potential therapeutic drugs.

A hypoxia- and lactate metabolism-related gene signature to predict prognosis of sepsis: discovery and validation in independent cohorts

BACKGROUND

High throughput gene expression profiling is a valuable tool in providing insight into the molecular mechanism of human diseases. Hypoxia- and lactate metabolism-related genes (HLMRGs) are fundamentally dysregulated in sepsis and have great predictive potential. Therefore, we attempted to build an HLMRG signature to predict the prognosis of patients with sepsis.

METHODS

Three publicly available transcriptomic profiles of peripheral blood mononuclear cells from patients with sepsis (GSE65682, E-MTAB-4421 and E-MTAB-4451, total n = 850) were included in this study. An HLMRG signature was created by employing Cox regression and least absolute shrinkage and selection operator estimation. The CIBERSORT method was used to analyze the abundances of 22 immune cell subtypes based on transcriptomic data. Metascape was used to investigate pathways related to the HLMRG signature.

RESULTS

We developed a prognostic signature based on five HLMRGs (ERO1L, SIAH2, TGFA, TGFBI, and THBS1). This classifier successfully discriminated patients with disparate 28-day mortality in the discovery cohort (GSE65682, n = 479), and consistent results were observed in the validation cohort (E-MTAB-4421 plus E-MTAB-4451, n = 371). Estimation of immune infiltration revealed significant associations between the risk score and a subset of immune cells. Enrichment analysis revealed that pathways related to antimicrobial immune responses, leukocyte activation, and cell adhesion and migration were significantly associated with the HLMRG signature.

CONCLUSIONS

Identification of a prognostic signature suggests the critical role of hypoxia and lactate metabolism in the pathophysiology of sepsis. The HLMRG signature can be used as an efficient tool for the risk stratification of patients with sepsis.

A novel colchicine-myricetin heterozygous molecule: design, synthesis, and effective evaluations on the pathological models of acute lung injury in vitro and in vivo

Acute lung injury (ALI) is an inflammatory condition and there are no effective treatments. A novel new compound----colchicine-myricetin hybrid (CMyrH) was herein designed and synthesized. To evaluate the activity of CMyrH in ALI, we used a bleomycin (BLM) induced BEAS-2B injury model in vitro and established a well-recognized rat model of BLM-induced lung injury in vivo. The results demonstrated that colchicine-myricetin hybrid protected BEAS-2B cells against BLM-induced cell injury in an increased dose manner, and reduced wet/dry weight ratio, histological scoring, and inflammation cytokines IL-1β, IL-6, IL-18, and TNF-α levels of lung tissue of the rats. Furthermore, we found colchicine-myricetin hybrid inhibited caspase-1, ASC, GSDMD, and NLRP-3 expression in vivo. Meanwhile, we used molecular docking to analyze the binding mode of colchicine-myricetin hybrid and human neutrophil elastase (HNE), it revealed that colchicine-myricetin hybrid showed strong binding affinity toward human neutrophil elastase when compared to its parent molecules. In conclusion, It is suggested that colchicine-myricetin hybrid antagonized acute lung injury by focusing on multi-targets via multi-mechanisms, and might be served as a potential therapeutic agent for acute lung injury.