Dynamic changes in human HLA-DRA gene expression and Th cell subsets in sepsis: Indications of immunosuppression and associated outcomes

Predictive value of CD86 for the occurrence of sepsis (Sepsis-3) in patients with infection

This prospective observational study explored the predictive value of CD86 in the early diagnosis of sepsis in the emergency department. The primary endpoint was the factors associated with a diagnosis of sepsis. The secondary endpoint was the factors associated with mortality among patients with sepsis. It enrolled inpatients with infection or high clinical suspicion of infection in the emergency department of a tertiary Hospital between September 2019 and June 2021. The patients were divided into the sepsis and non-sepsis groups according to the Sepsis-3 standard. The non-sepsis group included 56 patients, and the sepsis group included 65 patients (19 of whom ultimately died). The multivariable analysis showed that CD86% (odds ratio [OR] = 1.22, 95% confidence interval [CI]: 1.04-1.44, P = 0.015), platelet count (OR = 0.99, 95%CI: 0.986-0.997, P = 0.001), interleukin-10 (OR = 1.01, 95%CI: 1.004-1.025, P = 0.009), and procalcitonin (OR = 1.17, 95%CI: 1.01-1.37, P = 0.043) were independent risk factors for sepsis, while human leukocyte antigen (HLA%) (OR = 0.96, 05%CI: 0.935-0.995, P = 0.022), respiratory rate (OR = 1.16, 95%CI: 1.03-1.30, P = 0.014), and platelet count (OR = 1.01, 95%CI: 1.002-1.016, P = 0.016) were independent risk factors for death in patients with sepsis. The model for sepsis (CD86%, platelets, interleukin-10, and procalcitonin) and the model for death (HLA%, respiratory rate, and platelets) had an area under the curve (AUC) of 0.870 and 0.843, respectively. CD86% in the first 24 h after admission for acute infection was independently associated with the occurrence of sepsis in the emergency department.

Advances in the Study of Immunosuppressive Mechanisms in Sepsis

Sepsis is a life-threatening disease caused by a systemic infection that triggers a dysregulated immune response. Sepsis is an important cause of death in intensive care units (ICUs), poses a major threat to human health, and is a common cause of death in ICUs worldwide. The pathogenesis of sepsis is intricate and involves a complex interplay of pro- and anti-inflammatory mechanisms that can lead to excessive inflammation, immunosuppression, and potentially long-term immune disorders. Recent evidence highlights the importance of immunosuppression in sepsis. Immunosuppression is recognized as a predisposing factor for increased susceptibility to secondary infections and mortality in patients. Immunosuppression due to sepsis increases a patient's chance of re-infection and increases organ load. In addition, antibiotics, fluid resuscitation, and organ support therapy have limited impact on the prognosis of septic patients. Therapeutic approaches by suppressing excessive inflammation have not achieved the desired results in clinical trials. Research into immunosuppression has brought new hope for the treatment of sepsis, and a number of therapeutic approaches have demonstrated the potential of immunostimulatory therapies. In this article, we will focus on the mechanisms of immunosuppression and markers of immune monitoring in sepsis and describe various targets for immunostimulatory therapy in sepsis.

Identification of Potential Biomarkers of Septic Shock Based on Pathway and Transcriptome Analyses of Immune-Related Genes

Immunoregulation is crucial to septic shock (SS) but has not been clearly explained. Our aim was to explore potential biomarkers for SS by pathway and transcriptional analyses of immune-related genes to improve early detection. GSE57065 and GSE95233 microarray data were used to screen differentially expressed genes (DEGs) in SS. Gene Ontology and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analyses of DEGs were performed, and correlations between immune cell and pathway enrichment scores were analyzed. The predictive value of candidate genes was evaluated by receiver operating characteristic (ROC) curves. GSE66099, GSE4607, and GSE13904 datasets were used for external validation. Blood samples from six patients and six controls were collected for validation by qRT-PCR and western blotting. In total, 550 DEGs in SS were identified; these genes were involved in the immune response, inflammation, and infection. Immune-related pathways and levels of infiltration of CD4 + TCM, CD8 + T cells, and preadipocytes differed between SS cases and controls. Seventeen genes were identified as potential biomarkers of SS (areas under ROC curves >0.9). The downregulation of CD8A, CD247, CD3G, LCK, and HLA-DRA in SS was experimentally confirmed. We identified several immune-related biomarkers in SS that may improve early identification of disease risk.

Identification of key immune cell-related genes involved in tumorigenesis and prognosis of cervical squamous cell carcinoma

The infiltration of immune cells can significantly affect the prognosis and immune therapy of patients with cervical squamous cell carcinoma (CSCC). This study aimed to explore key immune cell-related genes in the tumorigenesis and prognosis of CSCC. The module significantly related to immunity was screened by weighted gene co-expression network analysis (WGCNA) and ESTIMATE analysis, followed by correlation analysis with clinical traits. Key candidate genes were intersected with the protein-protein interaction (PPI) network genes for immune-related genes. The relationship between immune cell infiltration and key genes was analyzed. Tumor immune dysfunction and exclusion (TIDE) and immunophenoscore (IPS) predicted the response to immunotherapy in CSCC patients. Clinically, quantitative real-time polymerase chain reaction (qRT-PCR) and immunohistochemistry were manipulated for analyzing the changes in mRNA and protein expression of key genes in cancer. Western blot was conducted to assess the correlation between key genes and immune infiltration. The brown module was notably associated with the immune microenvironment of CSCC, from which three immune-related key genes (TYROBP, CCL5, and HLA-DRA) were obtained. High expression of these genes was significantly positively associated with the infiltration abundance of T cells, B cells, and other immune cells. High expression levels of three key genes were confirmed in para-cancer tissue and correlated with the abundance of immune cells. The high-expression group of key genes was more sensitive to immunotherapy. We provide a theoretical basis for searching for potential targets for effective treatment and diagnosis of CSCC and provide new ideas for developing novel immunotherapy strategies.

Identification of featured necroptosis-related genes and imbalanced immune infiltration in sepsis via machine learning

Background: The precise diagnostic and prognostic biological markers were needed in immunotherapy for sepsis. Considering the role of necroptosis and immune cell infiltration in sepsis, differentially expressed necroptosis-related genes (DE-NRGs) were identified, and the relationship between DE-NRGs and the immune microenvironment in sepsis was analyzed.

Methods: Machine learning algorithms were applied for screening hub genes related to necroptosis in the training cohort. CIBERSORT algorithms were employed for immune infiltration landscape analysis. Then, the diagnostic value of these hub genes was verified by the receiver operating characteristic (ROC) curve and nomogram. In addition, consensus clustering was applied to divide the septic patients into different subgroups, and quantitative real-time PCR was used to detect the mRNA levels of the hub genes between septic patients (SP) (n = 30) and healthy controls (HC) (n = 15). Finally, a multivariate prediction model based on heart rate, temperature, white blood count and 4 hub genes was established.

Results: A total of 47 DE-NRGs were identified between SP and HC and 4 hub genes (BACH2, GATA3, LEF1, and BCL2) relevant to necroptosis were screened out via multiple machine learning algorithms. The high diagnostic value of these hub genes was validated by the ROC curve and Nomogram model. Besides, the immune scores, correlation analysis and immune cell infiltrations suggested an immunosuppressive microenvironment in sepsis. Septic patients were divided into 2 clusters based on the expressions of hub genes using consensus clustering, and the immune microenvironment landscapes and immune function between the 2 clusters were significantly different. The mRNA levels of the 4 hub genes significantly decreased in SP as compared with HC. The area under the curve (AUC) was better in the multivariate prediction model than in other indicators.

Conclusion: This study indicated that these necroptosis hub genes might have great potential in prognosis prediction and personalized immunotherapy for sepsis.

Progress in the study of biomarkers for early prediction of systemic inflammatory response syndrome after percutaneous nephrolithotomy

Urolithiasis is a common and frequent disease in urology. Percutaneous nephrolithotomy (PCNL) is preferred for the treatment of upper urinary tract stones and complicated renal stones >2 cm in diameter, but it has a higher rate of postoperative complications, especially infection, compared with other minimally invasive treatments for urinary stones. Complications associated with infection after percutaneous nephrolithotomy include transient fever, systemic inflammatory response syndrome (SIRS), and sepsis, which is considered one of the most common causes of perioperative death after percutaneous nephrolithotomy. In contrast, SIRS serves as a sentinel for sepsis, so early intervention of SIRS by biomarker identification can reduce the incidence of postoperative sepsis, which in turn reduces the length of stay and hospital costs for patients. In this paper, we summarize traditional inflammatory indicators, novel inflammatory indicators, composite inflammatory indicators and other biomarkers for early identification of systemic inflammatory response syndrome after percutaneous nephrolithotomy.

Use of machine learning-based integration to develop a monocyte differentiation-related signature for improving prognosis in patients with sepsis

BACKGROUND

Although significant advances have been made in intensive care medicine and antibacterial treatment, sepsis is still a common disease with high mortality. The condition of sepsis patients changes rapidly, and each hour of delay in the administration of appropriate antibiotic treatment can lead to a 4-7% increase in fatality. Therefore, early diagnosis and intervention may help improve the prognosis of patients with sepsis.

METHODS

We obtained single-cell sequencing data from 12 patients. This included 14,622 cells from four patients with bacterial infectious sepsis and eight patients with sepsis admitted to the ICU for other various reasons. Monocyte differentiation trajectories were analyzed using the "monocle" software, and differentiation-related genes were identified. Based on the expression of differentiation-related genes, 99 machine-learning combinations of prognostic signatures were obtained, and risk scores were calculated for all patients. The "scissor" software was used to associate high-risk and low-risk patients with individual cells. The "cellchat" software was used to demonstrate the regulatory relationships between high-risk and low-risk cells in a cellular communication network. The diagnostic value and prognostic predictive value of Enah/Vasp-like (EVL) were determined. Clinical validation of the results was performed with 40 samples. The "CBNplot" software based on Bayesian network inference was used to construct EVL regulatory networks.

RESULTS

We systematically analyzed three cell states during monocyte differentiation. The differential analysis identified 166 monocyte differentiation-related genes. Among the 99 machine-learning combinations of prognostic signatures constructed, the Lasso + CoxBoost signature with 17 genes showed the best prognostic prediction performance. The highest percentage of high-risk cells was found in state one. Cell communication analysis demonstrated regulatory networks between high-risk and low-risk cell subpopulations and other immune cells. We then determined the diagnostic and prognostic value of EVL stabilization in multiple external datasets. Experiments with clinical samples demonstrated the accuracy of this analysis. Finally, Bayesian network inference revealed potential network mechanisms of EVL regulation.

CONCLUSIONS

Monocyte differentiation-related prognostic signatures based on the Lasso + CoxBoost combination were able to accurately predict the prognostic status of patients with sepsis. In addition, low EVL expression was associated with poor prognosis in sepsis.

Sepsis-induced immunosuppression: mechanisms, diagnosis and current treatment options

Sepsis is a common complication of combat injuries and trauma, and is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. It is also one of the significant causes of death and increased health care costs in modern intensive care units. The use of antibiotics, fluid resuscitation, and organ support therapy have limited prognostic impact in patients with sepsis. Although its pathophysiology remains elusive, immunosuppression is now recognized as one of the major causes of septic death. Sepsis-induced immunosuppression is resulted from disruption of immune homeostasis. It is characterized by the release of anti-inflammatory cytokines, abnormal death of immune effector cells, hyperproliferation of immune suppressor cells, and expression of immune checkpoints. By targeting immunosuppression, especially with immune checkpoint inhibitors, preclinical studies have demonstrated the reversal of immunocyte dysfunctions and established host resistance. Here, we comprehensively discuss recent findings on the mechanisms, regulation and biomarkers of sepsis-induced immunosuppression and highlight their implications for developing effective strategies to treat patients with septic shock.

Methylomic and transcriptomic characterization of postoperative systemic inflammatory dysregulation

In this study, we define and validate a state of postoperative systemic inflammatory dysregulation (PSID) based on postoperative phenotypic extremes of plasma C-reactive protein concentration following major abdominal surgery. PSID manifested clinically with significantly higher rates of sepsis, complications, longer hospital stays and poorer short, and long-term outcomes. We hypothesized that PSID will be associated with, and potentially predicted by, altered patterns of genome-wide peripheral blood mononuclear cell differential DNA methylation and gene expression. We identified altered DNA methylation and differential gene expression in specific immune and metabolic pathways during PSID. Our findings suggest that dysregulation results in, or from, dramatic changes in differential DNA methylation and highlights potential targets for early detection and treatment. The combination of altered DNA methylation and gene expression suggests that dysregulation is mediated at multiple levels within specific gene sets and hence, nonspecific anti-inflammatory treatments such as corticosteroids alone are unlikely to represent an effective therapeutic strategy.

The Diagnostic Value of Mitochondrial Mass of Peripheral T Lymphocytes in Early Sepsis

Background

Studies have shown that lymphocyte dysfunction can occur during the early stages of sepsis and that cell dysfunction is associated with mitochondrial dysfunction. Therefore, quantifying the mitochondrial function of lymphocytes in patients with sepsis could be valuable for the early diagnosis of sepsis.

Methods

Seventy-nine patients hospitalized from September 2020 to September 2021 with Sepsis-3 were retrospectively analyzed and subsequently compared with those without sepsis.

Results

Univariate analysis showed statistical differences between the data of the two groups regarding age, neutrophil/lymphocyte, procalcitonin (PCT), C-reactive protein, total bilirubin, serum creatinine, type B natriuretic peptide, albumin, prothrombin time, activated partial thromboplastin time, lactic acid, single-cell mitochondrial mass (SCMM)-CD3, SCMM-CD4, SCMM-CD8, and Acute Physiology and Chronic Health Evaluation II score (P < 0.05). Multivariate logistic regression analysis performed on the indicators mentioned above demonstrated a statistical difference in PCT, lactic acid, SCMM-CD4, and SCMM-CD8 levels between the two groups (P < 0.05). The receiver operating characteristic curves of five models were subsequently compared [area under the curve: 0.740 (PCT) vs. 0.933 (SCMM-CD4) vs. 0.881 (SCMM-CD8) vs. 0.961 (PCT + SCMM-CD4) vs. 0.915 (PCT+SCMM-CD8), P < 0.001].

Conclusion

SCMM-CD4 was shown to be a better diagnostic biomarker of early sepsis when compared with the traditional biomarker, PCT. Furthermore, the value of the combination of PCT and SCMM-CD4 in the diagnosis of early sepsis was better than that of SCMM-CD4 alone.

Regulatory T Cells: Angels or Demons in the Pathophysiology of Sepsis?

Sepsis is a syndrome characterized by life-threatening organ dysfunction caused by the dysregulated host response to an infection. Sepsis, especially septic shock and multiple organ dysfunction is a medical emergency associated with high morbidity, high mortality, and prolonged after-effects. Over the past 20 years, regulatory T cells (Tregs) have been a key topic of focus in all stages of sepsis research. Tregs play a controversial role in sepsis based on their heterogeneous characteristics, complex organ/tissue-specific patterns in the host, the multi-dimensional heterogeneous syndrome of sepsis, the different types of pathogenic microbiology, and even different types of laboratory research models and clinical research methods. In the context of sepsis, Tregs may be considered both angels and demons. We propose that the symptoms and signs of sepsis can be attenuated by regulating Tregs. This review summarizes the controversial roles and Treg checkpoints in sepsis.

Sepsis-Induced Immunosuppression

Sepsis is expected to have a substantial impact on public health and cost as its prevalence increases. Factors contributing to increased prevalence include a progressively aging population, advances in the use of immunomodulatory agents to treat a rising number of diseases, and immune-suppressing therapies in organ transplant recipients and cancer patients. It is now recognized that sepsis is associated with profound and sustained immunosuppression, which has been implicated as a predisposing factor in the increased susceptibility of patients to secondary infections and mortality. In this review, we discuss mechanisms of sepsis-induced immunosuppression and biomarkers that identify a state of impaired immunity. We also highlight immune-enhancing strategies that have been evaluated in patients with sepsis, as well as therapeutics under current investigation. Finally, we describe future challenges and the need for a new treatment paradigm, integrating predictive enrichment with patient factors that may guide the future selection of tailored immunotherapy. Expected final online publication date for the Annual Review of Physiology, Volume 84 is February 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Non-classical monocytes and its potential in diagnosing sepsis post cardiac surgery

BACKGROUND

Sepsis is caused by a dysregulation of immune response to infection that results in very high mortality. Current laboratory tests and clinical criteria are inadequate to diagnose sepsis due to limited sensitivity and specificity. Circulating monocytes are important players in immune homeostasis and their altered HLA-DR expression indicate immune dysregulation. HLA-DR is an MHC Class II cell-surface receptor that can present foreign antigens to helper T cells and mount an inflammatory response. Therefore, we analyzed the variations in HLA-DR expression and the concentration of monocyte subsets for diagnosing post-surgical sepsis.

METHODS

In this double-blinded prospective cohort study, we adopted immunophenotyping and quantification of antigen expression by flowcytometry to detect the changes in circulating monocyte subsets in patients undergoing cardiac surgery. Statistical analysis was performed to identify significant changes and based on the predictive potential of measured variables ROC curve analysis was done. ROC curve permitted the choice of appropriate cut-off values using which a diagnostic protocol was developed.

RESULTS

We observed that the monocyte subset concentrations in circulation varied differently after surgery. There was a significant downregulation of monocytic HLA-DR on both intermediate (p = 0.0477) and non-classical monocytes (p = 0.0333) at 48 h post-surgery. The monocyte subset analysis clearly showed that the patients with reduced pre-surgical non-classical monocyte count (p = 0.0430) coupled with post-surgical down-regulation of HLA-DR expression on the same subset had a higher incidence of developing sepsis after cardiac surgery.

CONCLUSIONS

Here we are reporting for the first time, the significant influence of non-classical monocytes in inducing dysregulated host response and sepsis after cardiac surgery. Using multiple biomarkers associated with this monocyte subset, we established an algorithm for the diagnosis of sepsis at 48 h post cardiac surgery with 100% sensitivity and 69.23% specificity.

PD-1 signaling pathway in sepsis: Does it have a future?

Sepsis is characterized by high mortality and poor prognosis and is one of the leading causes of death among patients in the intensive care unit (ICU). In the past, drugs that block early inflammatory responses have done little to reverse the progression of sepsis. Programmed cell death receptor 1 (PD-1) and its two ligands, programmed cell death receptor ligand 1(PD-L1) and programmed cell death receptor ligand 2 (PD-L2), are negative regulatory factors of the immune response of the body. Recently, the role of the PD-1 signaling pathway in sepsis has been widely studied. Studies showed that the PD-1 signaling pathways are closely related to the mortality and prognosis of sepsis patients. In the immunotherapy of sepsis, whether in animal experiments or clinical trials, anti-PD-1/PD-L1 antibodies have shown good promise. In this review, firstly, we focus on the immunosuppressive mechanism of sepsis and the structure and function of the PD-1 signaling pathway. The variety of the PD-1 signaling pathways in sepsis is introduced. Then, the relationship between the PD-1 signaling pathway and immune cells and organ dysfunction and the regulatory factors of the PD-1 signaling pathway in sepsis is discussed. Finally, the application of the PD-1 signaling pathway in sepsis is specifically emphasized.

Monitoring immunomodulation in patients with sepsis

Introduction: This review aims to summarize current progress of the last ten years in the development of biomarkers used for classifying the immune response of the septic host and for monitoring the efficacy of the applied adjunctive immunotherapy.Areas covered: An extensive search of the literature was performed. In this review the authors discuss available biomarkers of host immune response in sepsis toward two directions; immunosuppression and hyperinflammation. Ferritin, sCD163, sIL-2 ra, and IL-18 may help in the diagnosis of macrophage activation syndrome (MAS) complicating sepsis whereas lymphopenia, decreased HLA-DR expression on monocytes, overexpression of Programmed cell death protein-1 (PD-1)/Programmed death-ligand 1 (PD-L1) and IL-10 are indicators of sepsis-induced immunosuppression. Novel approaches in the classification of immune state in sepsis include Myeloid-Derived Suppressor Cells (MDSC) and specific endotypes, defined by gene expression and molecular techniques.Expert opinion: HLA-DR and ferritin are the most commonly used biomarkers to monitor immunomodulation in clinical practice whereas developing specific sepsis endotypes is the future target. New immunotherapy trials in sepsis need to incorporate biomarkers for a personalized treatment.

T-Bet Expression Mediated by the mTOR Pathway Influences CD4+ T Cell Count in Mice With Lethal Candida Sepsis

The sustained high morbidity and mortality of Candida sepsis are mainly caused by compromise of host immunity. Clinically, it is often manifested as a significant decrease in CD4+ T cell count, although the mechanism is unclear. We established a lethal mice Candida sepsis model and used Murine Sepsis Score to group mice with different disease severity to establish the influence of T-bet expression on CD4+ T cell count in Candida sepsis. We found that CD4+ T cell count decreased in Candida-infected compared to uninfected mice, and the degree of decrease increased with aggravation of sepsis. Expression of T-bet similarly decreased with worsening of sepsis, but it was significantly enhanced in candidiasis in comparison of naïve state. To clarify its possible mechanism, we measured the activity of mammalian target of rapamycin (mTOR), which is a key regulator of T-bet expression. The mTOR pathway was activated after infection and its activity increased with progression of sepsis. We used mice with T-cell-specific knockout of mTOR or tuberous sclerosis complex (TSC)1 to further inhibit or strengthen the mTOR signaling pathway. We found that mTOR deletion mice had a higher CD4+ T cell count by regulating T-bet expression, and the result in TSC1 deletion mice was reversed. These results demonstrate that T-bet expression mediated by the mTOR pathway influences the CD4+ T cell count in mice with Candida sepsis.

Dynamic LTR retrotransposon transcriptome landscape in septic shock patients

BACKGROUND

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. Numerous studies have explored the complex and dynamic transcriptome modulations observed in sepsis patients, but a large fraction of the transcriptome remains unexplored. This fraction could provide information to better understand sepsis pathophysiology. Multiple levels of interaction between human endogenous retroviruses (HERV) and the immune response have led us to hypothesize that sepsis is associated with HERV transcription and that HERVs may contribute to a signature among septic patients allowing stratification and personalized management.

METHODS

We used a high-density microarray and RT-qPCR to evaluate the HERV and Mammalian Apparent Long Terminal Repeat retrotransposons (MaLR) transcriptome in a pilot study that included 20 selected septic shock patients, stratified on mHLA-DR expression, with samples collected on day 1 and day 3 after inclusion. We validated the results in an unselected, independent cohort that included 100 septic shock patients on day 3 after inclusion. We compared septic shock patients, according to their immune status, to describe the transcriptional HERV/MaLR and conventional gene expression. For differential expression analyses, moderated t tests were performed and Wilcoxon signed-rank tests were used to analyze RT-qPCR results.

RESULTS

We showed that 6.9% of the HERV/MaLR repertoire was transcribed in the whole blood, and septic shock was associated with an early modulation of a few thousand of these loci, in comparison to healthy volunteers. We provided evidence that a subset of HERV/MaLR and conventional genes were differentially expressed in septic shock patients, according to their immune status, using monocyte HLA-DR (mHLA-DR) expression as a proxy. A group of 193 differentially expressed HERV/MaLR probesets, tested in an independent septic shock cohort, identified two groups of patients with different immune status and severity features.

CONCLUSION

We demonstrated that a large, unexplored part of our genome, which codes for HERV/MaLR, may be linked to the host immune response. The identified set of HERV/MaLR probesets should be evaluated on a large scale to assess the relevance of these loci in the stratification of septic shock patients. This may help to address the heterogeneity of these patients.