Advances in Immune Monitoring Approaches for Sepsis-Induced Immunosuppression

Identification and validation of potential genes for the diagnosis of sepsis by bioinformatics and 2-sample Mendelian randomization study

This integrated study combines bioinformatics, machine learning, and Mendelian randomization (MR) to discover and validate molecular biomarkers for sepsis diagnosis. Methods include differential expression analysis, weighted gene co-expression network analysis (WGCNA) for identifying sepsis-related modules and hub genes, and functional enrichment analyses to explore the roles of hub genes. Machine learning algorithms identify 3 diagnostic genes - CD177, LDHA, and MCEMP1 - consistently highly expressed in sepsis patients. The nomogram model effectively predicts sepsis risk, supported by receiver operator characteristic (ROC) curves. Correlations between diagnostic genes and immune cell infiltration are observed. MR analysis reveals a positive causal relationship between MCEMP1 and sepsis risk. In conclusion, this study presents potential sepsis diagnostic biomarkers, highlighting the genetic association of MCEMP1 with sepsis for insights into early diagnosis.

Protective effects of DcR3-SUMO on lipopolysaccharide-induced inflammatory cells and septic mice

Despite the high mortality rate associated with sepsis, no specific drugs are available. Decoy receptor 3 (DcR3) is now considered a valuable biomarker and therapeutic target for managing inflammatory conditions. DcR3-SUMO, an analog of DcR3, has a simple production process and high yield. However, its precise underlying mechanisms in sepsis remain unclear. This study investigated the protective effects of DcR3-SUMO on lipopolysaccharide (LPS)-induced inflammatory cells and septic mice. We evaluated the effects of DcR3 intervention and overexpression on intracellular inflammatory cytokine levels in vitro. DcR3-SUMO significantly reduced cytokine levels within inflammatory cells, and notably increased DcR3 protein and mRNA levels in LPS-induced septic mice, confirming its anti-inflammatory efficacy. Our in vitro and in vivo results demonstrated comparable anti-inflammatory effects between DcR3-SUMO and native DcR3. DcR3-SUMO protein administration in septic mice notably enhanced tissue morphology, decreased sepsis scores, and elevated survival rates. Furthermore, DcR3-SUMO treatment effectively lowered inflammatory cytokine levels in the serum, liver, and lung tissues, and mitigated the extent of tissue damage. AlphaFold3 structural predictions indicated that DcR3-SUMO, similar to DcR3, effectively interacts with the three pro-apoptotic ligands, namely TL1A, LIGHT, and FasL. Collectively, DcR3-SUMO and DcR3 exhibit comparable anti-inflammatory effects, making DcR3-SUMO a promising therapeutic agent for sepsis.

Dysregulated dendritic cells in sepsis: functional impairment and regulated cell death

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Studies have indicated that immune dysfunction plays a central role in the pathogenesis of sepsis. Dendritic cells (DCs) play a crucial role in the emergence of immune dysfunction in sepsis. The major manifestations of DCs in the septic state are abnormal functions and depletion in numbers, which are linked to higher mortality and vulnerability to secondary infections in sepsis. Apoptosis is the most widely studied pathway of number reduction in DCs. In the past few years, there has been a surge in studies focusing on regulated cell death (RCD). This emerging field encompasses various forms of cell death, such as necroptosis, pyroptosis, ferroptosis, and autophagy-dependent cell death (ADCD). Regulation of DC's RCD can serve as a possible therapeutic focus for the treatment of sepsis. Throughout time, numerous tactics have been devised and effectively implemented to improve abnormal immune response during sepsis progression, including modifying the functions of DCs and inhibiting DC cell death. In this review, we provide an overview of the functional impairment and RCD of DCs in septic states. Also, we highlight recent advances in targeting DCs to regulate host immune response following septic challenge.

EFHD2 regulates T cell receptor signaling and modulates T helper cell activation in early sepsis

EFHD2 (EF-hand domain family, member D2) has been identified as a calcium-binding protein with immunomodulatory effects. In this study, we characterized the phenotype of Efhd2-deficient mice in sepsis and examined the biological functions of EFHD2 in peripheral T cell activation and T helper (Th) cell differentiation. Increased levels of EFHD2 expression accompanied peripheral CD4+ T cell activation in the early stages of sepsis. Transcriptomic analysis indicated that immune response activation was impaired in Efhd2-deficient CD4+ T cells. Further, Efhd2-deficient CD4+ T cells isolated from the spleen of septic mice showed impaired T cell receptor (TCR)-induced Th differentiation, especially Th1 and Th17 differentiation. In vitro data also showed that Efhd2-deficient CD4+ T cells exhibit impaired Th1 and Th17 differentiation. In the CD4+ T cells and macrophages co-culture model for antigen presentation, the deficiency of Efhd2 in CD4+ T cells resulted in impaired formation of immunological synapses. In addition, Efhd2-deficient CD4+ T cells exhibited reduced levels of phospho-LCK and phospho-ZAP70, and downstream transcription factors including Nfat, Nfκb and Nur77 following TCR engagement. In summary, EFHD2 may promote TCR-mediated T cell activation subsequent Th1 and Th17 differentiation in the early stages of sepsis by regulating the intensity of TCR complex formation.

Establishment and assessment of mortality risk prediction model in patients with sepsis based on early-stage peripheral lymphocyte subsets

This study is aimed to explore the value of lymphocyte subsets in evaluating the severity and prognosis of sepsis. The counts of lymphocytes, CD3+ T cells, CD4+ T cells, CD8+ T cells, CD19+ B cells, and NK cells significantly decreased between day 1 and day 3 in both the survivor and the non-survivor groups. The peripheral lymphocyte subsets (PLS) at day 1 were not significantly different between the survivor and the non-survivor groups. However, at day 3, the counts of lymphocytes, CD3+ T cells, CD4+ T cells, and NK cells were remarkably lower in the non-survivor group. No significant differences in CD8+ T cells, or CD19+ B cells were observed. The PLS index was independently and significantly associated with the 28-day mortality risk in septic patients (OR: 3.08, 95% CI: 1.18-9.67). Based on these clinical parameters and the PLS index, we developed a nomograph for evaluating the individual mortality risk in sepsis. The area under the curve of prediction with the PLS index was significantly higher than that from the model with only clinical parameters (0.912 vs. 0.817). Our study suggests that the decline of PLS occurred in the early stage of sepsis. The new novel PLS index can be an independent predictor of 28-day mortality in septic patients. The prediction model based on clinical parameters and the PLS index has relatively high predicting ability.

Clinical impact of transient lymphopenia

Transient or persistent immunosuppression is a known risk factor for morbidity and mortality in critically ill patients. Aim of the present study is to evaluate the lymphopenia in patients admitted to the Emergency Unit of AOU Policlinico Umberto I, to investigate its prevalence at admission and the persistence during hospitalization until discharge. Possible correlations were evaluated between lymphopenia, diagnosis of admission, comorbidities and chronic treatments. In this study, 240 patients (142 men; 98 female; mean age 75.1 ± 15.1) were enrolled. Patients were divided into two groups according to the lymphocytes count at hospital admission, namely "Group A" with lymphopenia and "Group B" with values in the normal range. Moreover, the patients in group A were distinguished in relation to the regression or persistence of the lymphopenia assessed at the time of hospital discharge (Group A1: persistence; Group A2: normalization). Prevalence of lymphopenia at admission was 57%; Group A showed higher mean age and percentage of patients over 65 years of age; and none differences were observed regarding gender. Prevalence of lymphopenia at admission was 57%; Group A showed higher mean age and percentage of patients over 65 years of age; no differences were observed regarding gender. All subsets of the lymphocytes (CD4+, CD8+, NK) were equally reduced. Persistent lymphopenia was found in 19% of patients. Lymphopenia should be valued at the time of hospital admission as a factor influencing the prognosis, the management and the treatment of these patients.

Mechanisms of Sepsis-Induced Acute Lung Injury and Advancements of Natural Small Molecules in Its Treatment

Sepsis-induced acute lung injury (ALI), characterized by widespread lung dysfunction, is associated with significant morbidity and mortality due to the lack of effective pharmacological treatments available clinically. Small-molecule compounds derived from natural products represent an innovative source and have demonstrated therapeutic potential against sepsis-induced ALI. These natural small molecules may provide a promising alternative treatment option for sepsis-induced ALI. This review aims to summarize the pathogenesis of sepsis and potential therapeutic targets. It assembles critical updates (from 2014 to 2024) on natural small molecules with therapeutic potential against sepsis-induced ALI, detailing their sources, structures, effects, and mechanisms of action.

Specifications of qPCR based epigenetic immune cell quantification

OBJECTIVES

Immune monitoring is an important aspect in diagnostics and clinical trials for patients with compromised immune systems. Flow cytometry is the standard method for immune cell counting but faces limitations. Best practice guidelines are available, but lack of standardization complicates compliance with e.g., in vitro diagnostic regulations. Limited sample availability forces immune monitoring to predominantly use population-based reference intervals. Epigenetic qPCR has evolved as alternative with broad applicability and low logistical demands. Analytical performance specifications (APS) have been defined for qPCR in several regulated fields including testing of genetically modified organisms or vector-shedding.

METHODS

APS were characterized using five epigenetic qPCR-based assays quantifying CD3+, CD4+, CD8+ T, B and NK cells in light of regulatory requirements.

RESULTS

Epigenetic qPCR meets all specifications including bias, variability, linearity, ruggedness and sample stability as suggested by pertinent guidelines and regulations. The assays were subsequently applied to capillary blood from 25 normal donors over a 28-day period. Index of individuality (IoI) and reference change values were determined to evaluate potential diagnostic gains of individual reference intervals. Analysis of the IoI suggests benefits for individual over population-based references. Reference change values (RCVs) show that changes of approx. Fifty percent from prior measurement are suggestive for clinically relevant changes in any of the 5 cell types.

CONCLUSIONS

The demonstrated precision, long-term stability and obtained RCVs render epigenetic cell counting a promising tool for immune monitoring in clinical trials and diagnosis.

Clinical practice of sepsis-induced immunosuppression: Current immunotherapy and future options

Sepsis is a potentially fatal condition characterized by the failure of one or more organs due to a disordered host response to infection. The development of sepsis is closely linked to immune dysfunction. As a result, immunotherapy has gained traction as a promising approach to sepsis treatment, as it holds the potential to reverse immunosuppression and restore immune balance, thereby improving the prognosis of septic patients. However, due to the highly heterogeneous nature of sepsis, it is crucial to carefully select the appropriate patient population for immunotherapy. This review summarizes the current and evolved treatments for sepsis-induced immunosuppression to enhance clinicians' understanding and practical application of immunotherapy in the management of sepsis.

An integrative model with HLA-DR, CD64, and PD-1 for the diagnostic and prognostic evaluation of sepsis

BACKGROUND

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and progressive immunosuppression with high mortality. HLA-DR, CD64, and PD-1 were assumed to be useful biomarkers for sepsis prediction. However, the ability of a combination of these biomarkers has not been clarified.

METHODS

An observational case-control study was conducted that included 30 sepsis patients, 30 critically ill patients without sepsis admitted to the intensive care unit (ICU), and 32 healthy individuals. The levels of HLA-DR, CD64, and PD-1 expression in peripheral blood immune cells and subsets was assayed on Days 1, 3, and 5, and the clinical information of patients was collected. We compared these biomarkers between groups and evaluated the predictive validity of single and combined biomarkers on sepsis mortality.

RESULTS

The results indicate that PD-1 expression on CD4- CD8- T (PD-1+ CD4- CD8- T) (19.19% ± 10.78% vs. 9.88% ± 1.79%, p = .004) cells and neutrophil CD64 index (nCD64 index) (9.15 ± 5.46 vs. 5.33 ± 2.34, p = .001) of sepsis patients were significantly increased, and HLA-DR expression on monocytes (mHLA-DR+ ) was significantly reduced (13.26% ± 8.06% vs. 30.17% ± 21.42%, p = 2.54 × 10-4 ) compared with nonsepsis critically ill patients on the first day. Importantly, the expression of PD-1+ CD4- CD8- T (OR = 0.622, 95% CI = 0.423-0.916, p = .016) and mHLA-DR+ (OR = 1.146, 95% CI = 1.014-1.295, p = .029) were significantly associated with sepsis mortality. For sepsis diagnosis, the mHLA-DR+ , PD-1+ CD4- CD8- T, and nCD64 index showed the moderate individual performance, and combinations of the three biomarkers achieved greater diagnostic value (AUC = 0.899, 95% CI = 0.792-0.962). When adding PCT into the combined model, the AUC increased to 0.936 (95% CI = 0.840-0.983). For sepsis mortality, combinations of PD-1+ CD4- CD8- T and mHLA-DR+ , have a good ability to predict the prognosis of sepsis patients, with an AUC = 0.921 (95% CI = 0.762-0.987).

CONCLUSION

These findings indicate that the combinations of HLA-DR, CD64, and PD-1 outperformed each of the single indicator in diagnosis and predicting prognosis of sepsis.

Changes in Early T-Cell Subsets and Their Impact on Prognosis in Patients with Sepsis: A Single-Center Retrospective Study

Objective

To analyze the early changes in CD3+, CD4+, and CD8+T-cell subset counts in patients with sepsis and their correlation with prognosis to provide a feasible basis for clinical immunomodulation in sepsis.

Methods

This is a single-center retrospective study. The study enrolled sepsis patients (meeting SEPSIS 3.0 definition) who were admitted to the Department of Intensive Care Unit at the First Hospital of Jilin University from July 5th, 2018 to December 5th, 2019 and were aged 18 years or above. In addition, these patients underwent cellular immune testing (CD3+, CD4+, CD8+ T lymphocyte counts, and CD4+/CD8+ ratio) within 24 hours of ICU admission. Patient's clinical data including age, gender, infection site, APACHE II score, SOFA score, length of ICU stay, mechanical ventilation time, ICU mortality, 28-day mortality, and 3-year survival status were collected. The prognostic indicators and survival of the decreased and nondecreased groups of different subsets of T lymphocyte counts and CD4+/CD8+ ratio were compared.

Results

A total of 206 patients were enrolled, with 76.7% having a decrease in CD3+ T lymphocyte count, 76.7% having a decrease in CD4+ T lymphocyte count, and 63.6% having a decrease in CD8+ T lymphocyte count. Furthermore, 21.8% had a lower CD4+/CD8+ ratio. Analysis showed that the CD3+ T lymphocyte count decreased group had a longer length of ICU stay [11 d (4, 21) vs. 7 d (4, 17), P=0.03], increased percentage of mechanical ventilation (67.5% vs. 51.0%, P=0.04), and extended mechanical ventilation time [144 h (48, 360) vs. 96 h (48, 144), P=0.04] compared to the nondecreased group. The 28-day mortality was higher in the decreased group of CD4+/CD8+ ratio compared to the nondecreased group (33.3% vs. 25.5%, P=0.29); however, the difference did not reach statistical significance. Logistic regression analysis revealed no significant correlation between the decrease in CD4+/CD8+ ratio and 28-day mortality (P=0.11). The 3-year follow-up revealed that the CD4+/CD8+ decreased group had a lower survival rate than the nondecreased group (33.3% vs. 53.4%, P=0.01).

Conclusions

In the early stage of sepsis, most patients showed a decrease in CD3+, CD4+, and CD8+T-cell subsets, as well as in the CD4+/CD8+ ratio. The decrease in CD3+ and CD4+/CD8+ was related to some poor prognosis.

Whole blood transcriptomics identifies subclasses of pediatric septic shock

BACKGROUND

Sepsis is a highly heterogeneous syndrome, which has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.

METHODS

The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.

RESULTS

Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells and less diverse T cell receptor repertoires.

CONCLUSIONS

Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences. Trial Registration This is a secondary analysis of data generated as part of the observational CAF-PINT ancillary of the HALF-PINT study (NCT01565941). Registered March 29, 2012.

Acute respiratory distress syndrome heterogeneity and the septic ARDS subgroup

Acute respiratory distress syndrome (ARDS) is an acute diffuse inflammatory lung injury characterized by the damage of alveolar epithelial cells and pulmonary capillary endothelial cells. It is mainly manifested by non-cardiogenic pulmonary edema, resulting from intrapulmonary and extrapulmonary risk factors. ARDS is often accompanied by immune system disturbance, both locally in the lungs and systemically. As a common heterogeneous disease in critical care medicine, researchers are often faced with the failure of clinical trials. Latent class analysis had been used to compensate for poor outcomes and found that targeted treatment after subgrouping contribute to ARDS therapy. The subphenotype of ARDS caused by sepsis has garnered attention due to its refractory nature and detrimental consequences. Sepsis stands as the most predominant extrapulmonary cause of ARDS, accounting for approximately 32% of ARDS cases. Studies indicate that sepsis-induced ARDS tends to be more severe than ARDS caused by other factors, leading to poorer prognosis and higher mortality rate. This comprehensive review delves into the immunological mechanisms of sepsis-ARDS, the heterogeneity of ARDS and existing research on targeted treatments, aiming to providing mechanism understanding and exploring ideas for accurate treatment of ARDS or sepsis-ARDS.

Protein modification by short-chain fatty acid metabolites in sepsis: a comprehensive review

Sepsis is a major life-threatening syndrome of organ dysfunction caused by a dysregulated host response due to infection. Dysregulated immunometabolism is fundamental to the onset of sepsis. Particularly, short-chain fatty acids (SCFAs) are gut microbes derived metabolites serving to drive the communication between gut microbes and the immune system, thereby exerting a profound influence on the pathophysiology of sepsis. Protein post-translational modifications (PTMs) have emerged as key players in shaping protein function, offering novel insights into the intricate connections between metabolism and phenotype regulation that characterize sepsis. Accumulating evidence from recent studies suggests that SCFAs can mediate various PTM-dependent mechanisms, modulating protein activity and influencing cellular signaling events in sepsis. This comprehensive review discusses the roles of SCFAs metabolism in sepsis associated inflammatory and immunosuppressive disorders while highlights recent advancements in SCFAs-mediated lysine acylation modifications, such as substrate supplement and enzyme regulation, which may provide new pharmacological targets for the treatment of sepsis.

Construction of HBV-HCC prognostic model and immune characteristics based on potential genes mining through protein interaction networks

OBJECTIVE

To search for human protein-coding genes related to hepatocellular carcinoma (HCC) in the context of hepatitis B virus (HBV) infection, and perform prognosis risk assessment.

METHODS

Genes related to HBV-HCC were selected through literature screening and protein-protein interaction (PPI) network database analysis. Prognosis potential genes (PPGs) were identified using Cox regression analysis. Patients were divided into high-risk and low-risk groups based on PPGs, and risk scores were calculated. Kaplan-Meier plots were used to analyze overall survival rates, and the results were predicted based on clinicopathological variables. Association analysis was also conducted with immune infiltration, immune therapy, and drug sensitivity. Experimental verification of the expression of PPGs was done in patient liver cancer tissue and normal liver tissue adjacent to tumors.

RESULTS

The use of a prognosis potential genes risk assessment model can reliably predict the prognosis risk of patients, demonstrating strong predictive ability. Kaplan-Meier analysis showed that the overall survival rate of the low-risk group was significantly higher than that of the high-risk group. There were significant differences between the two subgroups in terms of immune infiltration and IC50 association analysis. Experimental verification revealed that CYP2C19, FLNC, and HNRNPC were highly expressed in liver cancer tissue, while UBE3A was expressed at a lower level.

CONCLUSION

PPGs can be used to predict the prognosis risk of HBV-HCC patients and play an important role in the diagnosis and treatment of liver cancer. They also reveal their potential role in the tumor immune microenvironment, clinical-pathological characteristics, and prognosis.

INTRINSIC/EXTRINSIC APOPTOSIS AND PYROPTOSIS CONTRIBUTE TO THE SELECTIVE DEPLETION OF B CELL SUBSETS IN SEPTIC SHOCK PATIENTS

ABSTRACT

The depletion of peripheral blood B cells is associated with immunosuppression and poor prognosis during sepsis, and selective depletion occurs when B cell subsets are specifically targeted. In this study, we examined the mechanisms underlying the selective depletion of B cell subsets in the immunosuppressive phase of septic shock patients. Thirty-two septic shock patients were recruited as a septic shock group and 10 healthy volunteers as a control group. The expression of Bcl-2, CD95, cleaved caspase-9/8, and activated caspase-3/1 in the B cell subsets were measured by flow cytometry. Another 23 septic shock patients were recruited to test the remission of caspase-3 (Z-DEVD-FMK) and caspase-1 (VX-765) inhibitors on B cell subset depletion in vitro . In septic shock patients, the Bcl-2 levels in immature/transitional (IM) B cells decreased and the levels of cleaved caspase-9 in IM B cells increased; the levels of CD95 in IM, naive, resting memory (RM), and activated memory (AM) B cells and the levels of cleaved caspase-8 in IM, RM, and AM B cells increased; the levels of activated caspase-3 and caspase-1 in IM, RM, and AM B cells increased. Activated caspase-1 levels in IM B cells were higher compared with activated caspase-3 in septic shock patients, whereas the levels of activated caspase-1 in AM B cells were lower compared with activated caspase-3. Moreover, in vitro experiments showed that Z-DEVD-FMK and VX-765 could alleviate the depletion of IM, AM, and RM B cells. The selective reduction of circulating B cell subsets in septic shock patients could be attributed to intrinsic and extrinsic apoptosis as well as pyroptosis.

Whole Blood Transcriptomics Identifies Subclasses of Pediatric Septic Shock

Background

Sepsis is a highly heterogeneous syndrome, that has hindered the development of effective therapies. This has prompted investigators to develop a precision medicine approach aimed at identifying biologically homogenous subgroups of patients with septic shock and critical illnesses. Transcriptomic analysis can identify subclasses derived from differences in underlying pathophysiological processes that may provide the basis for new targeted therapies. The goal of this study was to elucidate pathophysiological pathways and identify pediatric septic shock subclasses based on whole blood RNA expression profiles.

Methods

The subjects were critically ill children with cardiopulmonary failure who were a part of a prospective randomized insulin titration trial to treat hyperglycemia. Genome-wide expression profiling was conducted using RNA-sequencing from whole blood samples obtained from 46 children with septic shock and 52 mechanically ventilated noninfected controls without shock. Patients with septic shock were allocated to subclasses based on hierarchical clustering of gene expression profiles, and we then compared clinical characteristics, plasma inflammatory markers, cell compositions using GEDIT, and immune repertoires using Imrep between the two subclasses.

Results

Patients with septic shock depicted alterations in innate and adaptive immune pathways. Among patients with septic shock, we identified two subtypes based on gene expression patterns. Compared with Subclass 2, Subclass 1 was characterized by upregulation of innate immunity pathways and downregulation of adaptive immunity pathways. Subclass 1 had significantly worse clinical outcomes despite the two classes having similar illness severity on initial clinical presentation. Subclass 1 had elevated levels of plasma inflammatory cytokines and endothelial injury biomarkers and demonstrated decreased percentages of CD4 T cells and B cells, and less diverse T-Cell receptor repertoires.

Conclusions

Two subclasses of pediatric septic shock patients were discovered through genome-wide expression profiling based on whole blood RNA sequencing with major biological and clinical differences.

Trial Registration

This is a secondary analysis of data generated as part of the observational CAF PINT ancillary of the HALF PINT study (NCT01565941). Registered 29 March 2012.

Classification of subtypes and identification of dysregulated genes in sepsis

Background

Sepsis is a clinical syndrome with high mortality. Subtype identification in sepsis is meaningful for improving the diagnosis and treatment of patients. The purpose of this research was to identify subtypes of sepsis using RNA-seq datasets and further explore key genes that were deregulated during the development of sepsis.

Methods

The datasets GSE95233 and GSE13904 were obtained from the Gene Expression Omnibus database. Differential analysis of the gene expression matrix was performed between sepsis patients and healthy controls. Intersection analysis of differentially expressed genes was applied to identify common differentially expressed genes for enrichment analysis and gene set variation analysis. Obvious differential pathways between sepsis patients and healthy controls were identified, as were developmental stages during sepsis. Then, key dysregulated genes were revealed by short time-series analysis and the least absolute shrinkage and selection operator model. In addition, the MCPcounter package was used to assess infiltrating immunocytes. Finally, the dysregulated genes identified were verified using 69 clinical samples.

Results

A total of 898 common differentially expressed genes were obtained, which were chiefly related to increased metabolic responses and decreased immune responses. The two differential pathways (angiogenesis and myc targets v2) were screened on the basis of gene set variation analysis scores. Four subgroups were identified according to median expression of angiogenesis and myc target v2 genes: normal, myc target v2, mixed-quiescent, and angiogenesis. The genes CHPT1, CPEB4, DNAJC3, MAFG, NARF, SNX3, S100A9, S100A12, and METTL9 were recognized as being progressively dysregulated in sepsis. Furthermore, most types of immune cells showed low infiltration in sepsis patients and had a significant correlation with the key genes. Importantly, all nine key genes were highly expressed in sepsis patients.

Conclusion

This study revealed novel insight into sepsis subtypes and identified nine dysregulated genes associated with immune status in the development of sepsis. This study provides potential molecular targets for the diagnosis and treatment of sepsis.

Research Progress of DcR3 in the Diagnosis and Treatment of Sepsis

Decoy receptor 3 (DcR3), a soluble glycosylated protein in the tumor necrosis factor receptor superfamily, plays a role in tumor and inflammatory diseases. Sepsis is a life-threatening organ dysfunction caused by the dysregulation of the response to infection. Currently, no specific drug that can alleviate or even cure sepsis in a comprehensive and multi-level manner has been found. DcR3 is closely related to sepsis and considerably upregulated in the serum of those patients, and its upregulation is positively correlated with the severity of sepsis and can be a potential biomarker for diagnosis. DcR3 alone or in combination with other markers has shown promising results in the early diagnosis of sepsis. Furthermore, DcR3 is a multipotent immunomodulator that can bind FasL, LIGHT, and TL1A through decoy action, and block downstream apoptosis and inflammatory signaling. It also regulates T-cell and macrophage differentiation and modulates immune status through non-decoy action; therefore, DcR3 could be a potential drug for the treatment of sepsis. The application of DcR3 in the treatment of a mouse model of sepsis also achieved good efficacy. Here, we introduce and discuss the progress in, and suggest novel ideas for, research regarding DcR3 in the diagnosis and treatment of sepsis.

Differentiating infection, colonisation, and sterile inflammation in critical illness: the emerging role of host-response profiling

Infection results when a pathogen produces host tissue damage and elicits an immune response. Critically ill patients experience immune activation secondary to both sterile and infectious insults, with overlapping clinical phenotypes and underlying immunological mechanisms. Patients also undergo a shift in microbiota with the emergence of pathogen-dominant microbiomes. Whilst the combination of inflammation and microbial shift has long challenged intensivists in the identification of true infection, the advent of highly sensitive molecular diagnostics has further confounded the diagnostic dilemma as the number of microbial detections increases. Given the key role of the host immune response in the development and definition of infection, profiling the host response offers the potential to help unravel the conundrum of distinguishing colonisation and sterile inflammation from true infection. This narrative review provides an overview of current approaches to distinguishing colonisation from infection using routinely available techniques and proposes matrices to support decision-making in this setting. In searching for new tools to better discriminate these states, the review turns to the understanding of the underlying pathobiology of the host response to infection. It then reviews the techniques available to assess this response in a clinically applicable context. It will cover techniques including profiling of transcriptome, protein expression, and immune functional assays, detailing the current state of knowledge in diagnostics along with the challenges and opportunities. The ultimate infection diagnostic tool will likely combine an assessment of both host immune response and sensitive pathogen detection to improve patient management and facilitate antimicrobial stewardship.

Single-cell transcriptome profiling of sepsis identifies HLA-DRlowS100Ahigh monocytes with immunosuppressive function

BACKGROUND

Sustained yet intractable immunosuppression is commonly observed in septic patients, resulting in aggravated clinical outcomes. However, due to the substantial heterogeneity within septic patients, precise indicators in deciphering clinical trajectories and immunological alterations for septic patients remain largely lacking.

METHODS

We adopted cross-species, single-cell RNA sequencing (scRNA-seq) analysis based on two published datasets containing circulating immune cell profile of septic patients as well as immune cell atlas of murine model of sepsis. Flow cytometry, laser scanning confocal microscopy (LSCM) imaging and Western blotting were applied to identify the presence of S100A9⁺ monocytes at protein level. To interrogate the immunosuppressive function of this subset, splenic monocytes isolated from septic wild-type or S100a9^-/- mice were co-cultured with naïve CD4⁺ T cells, followed by proliferative assay. Pharmacological inhibition of S100A9 was implemented using Paquinimod via oral gavage.

RESULTS

ScRNA-seq analysis of human sepsis revealed substantial heterogeneity in monocyte compartments following the onset of sepsis, for which distinct monocyte subsets were enriched in disparate subclusters of septic patients. We identified a unique monocyte subset characterized by high expression of S100A family genes and low expression of human leukocyte antigen DR (HLA-DR), which were prominently enriched in septic patients and might exert immunosuppressive function. By combining single-cell transcriptomics of murine model of sepsis with in vivo experiments, we uncovered a similar subtype of monocyte significantly associated with late sepsis and immunocompromised status of septic mice, corresponding to HLA-DR^lowS100A^high monocytes in human sepsis. Moreover, we found that S100A9⁺ monocytes exhibited profound immunosuppressive function on CD4⁺ T cell immune response and blockade of S100A9 using Paquinimod could partially reverse sepsis-induced immunosuppression.

CONCLUSIONS

This study identifies HLA-DR^lowS100A^high monocytes correlated with immunosuppressive state upon septic challenge, inhibition of which can markedly mitigate sepsis-induced immune depression, thereby providing a novel therapeutic strategy for the management of sepsis.

Targeting the Granulocytic Defense against A. fumigatus in Healthy Volunteers and Septic Patients

Neutrophil granulocytes (NGs) are among the key players in the defense against Aspergillus fumigatus (A. fumigatus). To better elucidate a pathophysiological understanding of their role and functions, we applied a human cell model using NGs from healthy participants and septic patients to evaluate their inhibitory effects on the growth of A. fumigatus ex vivo. Conidia of A. fumigatus (ATCC^® 204305) were co-incubated with NGs from healthy volunteers or septic patients for 16 h. A. fumigatus growth was measured by XTT assays with a plate reader. The inhibitory effect of NGs on 18 healthy volunteers revealed great heterogeneity. Additionally, growth inhibition was significantly stronger in the afternoon than the morning, due to potentially different cortisol levels. It is particularly interesting that the inhibitory effect of NGs was reduced in patients with sepsis compared to healthy controls. In addition, the magnitude of the NG-driven defense against A. fumigatus was highly variable among healthy volunteers. Moreover, daytime and corresponding cortisol levels also seem to have a strong influence. Most interestingly, preliminary experiments with NGs from septic patients point to a strongly diminished granulocytic defense against Aspergillus spp.

Regulatory role of the programmed cell death 1 signaling pathway in sepsis induced immunosuppression

Sepsis is a multiple organ dysfunction syndrome caused by the host's immune response to infection, with extremely high incidence and mortality. Immunosuppression is an essential pathophysiological alteration that influences the clinical treatment and prognosis of sepsis. Recent studies have suggested that the programmed cell death 1 signaling pathway is involved in the formation of immunosuppression in sepsis. In this review, we systematically present the mechanisms of immune dysregulation in sepsis and elucidate the expression and regulatory effects of the programmed cell death 1 signaling pathway on immune cells associated with sepsis. We then specify current research developments and prospects for the application of the programmed cell death 1 signaling pathway in immunomodulatory therapy for sepsis. Several open questions and future research are discussed at the end.

Persistent inflammation-immunosuppression-catabolism syndrome in patients with systemic lupus erythematosus

OBJECTIVE

To evaluate the clinical characteristics and prognosis of systemic lupus erythematosus (SLE) with persistent inflammation-immunosuppression-catabolism syndrome (PICS).

METHODS

We retrospectively analyzed patients with SLE who were admitted to the renal intensive care unit (ICU) for over 14 days at Jinling Hospital from July 2010 to July 2018. According to the diagnostic criteria of PICS, we divided the SLE patients into a PICS group and a non-PICS group. We performed a multivariate Cox regression analysis on the risk factors for death in these two groups by comparing the clinical features and prognosis.

RESULTS

A total of 96 SLE patients met the inclusion and exclusion criteria of this study, including 61 patients in the PICS group and 35 patients in the non-PICS group. The PICS group patients required a longer length of stay in ICU with higher inflammatory indicators (such as C-reactive protein, procalcitonin and interleukin-6) and lower immune levels (such as total, CD3 + , CD4 + , CD8 + and CD20 + lymphocytes) compared to the non-PICS group patients (P < 0.01). Hemoglobin, platelets, serum creatinine, serum blood urea nitrogen and SLE Disease Activity Index (SLE-DAI) score in the PICS group were lower than those in the non-PICS group (P < 0.05), suggesting severe hematological injury in the PICS group and relatively severe renal damage in the non-PICS group. The rates of PICS combined with sepsis, acute respiratory distress syndrome, mechanical ventilation, gram-positive bacteria, gram-negative bacteria, fungi and double infections were higher than those in the non-PICS group (P < 0.05). The 3-year survival rate was 50.82% in the PICS group and 85.71% in the non-PICS group. The 3-year renal survival rate was 32.79% in the PICS group and 51.43% in the non-PICS group. Multivariate Cox regression found that the total lymphocyte count during ICU admission was an independent risk factor for death in SLE patients with PICS.

CONCLUSION

Patients with SLE complicated with PICS had longer ICU stays, a lower level of SLE activity, a higher risk of secondary infection and a significantly lower survival rate than non-PICS patients.

An immune genes signature for predicting mortality in sepsis patients

A growing body of evidence indicates that the immune system plays a central role in sepsis. By analyzing immune genes, we sought to establish a robust gene signature and develop a nomogram that could predict mortality in patients with sepsis. Herein, data were extracted from the Gene Expression Omnibus and Biological Information Database of Sepsis (BIDOS) databases. We enrolled 479 participants with complete survival data using the GSE65682 dataset, and grouped them randomly into training (n = 240) and internal validation (n = 239) sets based on a 1:1 proportion. GSE95233 was set as the external validation dataset (n=51). We validated the expression and prognostic value of the immune genes using the BIDOS database. We established a prognostic immune genes signature (including ADRB2, CTSG, CX3CR1, CXCR6, IL4R, LTB, and TMSB10) via LASSO and Cox regression analyses in the training set. Based on the training and validation sets, the Receiver Operating Characteristic curves and Kaplan-Meier analysis revealed that the immune risk signature has good predictive power in predicting sepsis mortality risk. The external validation cases also showed that mortality rates in the high-risk group were higher than those in the low-risk group. Subsequently, a nomogram integrating the combined immune risk score and other clinical features was developed. Finally, a web-based calculator was built to facilitate a convenient clinical application of the nomogram. In summary, the signature based on the immune gene holds potential as a novel prognostic predictor for sepsis.

Monitoring of the Forgotten Immune System during Critical Illness-A Narrative Review

Immune organ failure is frequent in critical illness independent of its cause and has been acknowledged for a long time. Most patients admitted to the ICU, whether featuring infection, trauma, or other tissue injury, have high levels of alarmins expression in tissues or systemically which then activate innate and adaptive responses. Although necessary, this response is frequently maladaptive and leads to organ dysfunction. In addition, the counter-response aiming to restore homeostasis and repair injury can also be detrimental and contribute to persistent chronic illness. Despite intensive research on this topic in the last 40 years, the immune system is not routinely monitored in critical care units. In this narrative review we will first discuss the inflammatory response after acute illness and the players of maladaptive response, focusing on neutrophils, monocytes, and T cells. We will then go through commonly used biomarkers, like C-reactive protein, procalcitonin and pancreatic stone protein (PSP) and what they monitor. Next, we will discuss the strengths and limitations of flow cytometry and related techniques as an essential tool for more in-depth immune monitoring and end with a presentation of the most promising cell associated markers, namely HLA-DR expression on monocytes, neutrophil expression of CD64 and PD-1 expression on T cells. In sum, immune monitoring critically ill patients is a forgotten and missing piece in the monitoring capacity of intensive care units. New technology, including bed-side equipment and in deep cell phenotyping using emerging multiplexing techniques will likely allow the definition of endotypes and a more personalized care in the future.

Expert consensus on the monitoring and treatment of sepsis-induced immunosuppression

Emerged evidence has indicated that immunosuppression is involved in the occurrence and development of sepsis. To provide clinical practice recommendations on the immune function in sepsis, an expert consensus focusing on the monitoring and treatment of sepsis-induced immunosuppression was developed. Literature related to the immune monitoring and treatment of sepsis were retrieved from PubMed, Web of Science, and Chinese National Knowledge Infrastructure to design items and expert opinions were collected through an online questionnaire. Then, the Delphi method was used to form consensus opinions, and RAND appropriateness method was developed to provide consistency evaluation and recommendation levels for consensus opinions. This consensus achieved satisfactory results through two rounds of questionnaire survey, with 2 statements rated as perfect consistency, 13 as very good consistency, and 9 as good consistency. After summarizing the results, a total of 14 strong recommended opinions, 8 weak recommended opinions and 2 non-recommended opinions were produced. Finally, a face-to-face discussion of the consensus opinions was performed through an online meeting, and all judges unanimously agreed on the content of this consensus. In summary, this expert consensus provides a preliminary guidance for the monitoring and treatment of immunosuppression in patients with sepsis.

Multisite Metagenomic Next-Generation Sequencing Improved Diagnostic Performance for Sepsis-Associated Lymphopenia Patients

A precise and efficient microbiological diagnosis is essential for sepsis. Metagenomic next-generation sequencing (mNGS) is a novel technique for the diagnosis of infectious diseases, but its current application in multisite sampling and interpretation remains controversial. Therefore, this study was undertaken to evaluate the reliability of multisite mNGS tests and the efficiency of plasma mNGS based on lymphocyte subset counts. A prospective observational study was performed on the intubated patients with sepsis-associated lymphopenia from January 2020 to February 2022. During the study period, data on 71 patients with sepsis-induced lymphopenia were collected. Among the 125 mNGS tests, 95 were positive for pathogens, whereas of the 166 conventional microbiological tests (CMTs), 91 were positive. The comparison showed that 38 patients (53.5%) had at least one matched pair of plasma mNGS and CMT results, while for multisite sampling, 47 patients (66.2%) had at least one. Lymphocyte subset analysis showed that T lymphocyte (577 ± 317 versus 395 ± 207, P = 0.005) and CD4⁺ T lymphocyte (333 ± 199 versus 230 ± 120, P = 0.009) counts were lower in the matched group. According to receiver operating characteristic (ROC) analysis, a CD4⁺ T lymphocyte count lower than 266 cells/mm³ was predictive of a match result. For sepsis-associated lymphopenia patients, we found that multisite mNGS tests showed a higher positivity rate. With plasma mNGS, a lower CD4⁺ T lymphocyte count predicted a better match result with CMT. The lymphocyte subset analysis may promote the clinical interpretation of mNGS results. IMPORTANCE This study was undertaken to evaluate the reliability of pathogenic diagnoses based on multisite mNGS detection at the clinically suspected sites and to analyze the efficiency of plasma mNGS detection based on lymphocyte subset counts in patients with sepsis-associated lymphopenia.

Lymphocyte trajectories are associated with prognosis in critically ill patients: A convenient way to monitor immune status

Background

Immunosuppression is a risk factor for poor prognosis of critically ill patients, but current monitoring of the immune status in clinical practice is still inadequate. Absolute lymphocyte count (ALC) is not only a convenient biomarker for immune status monitoring but is also suitable for clinical application. In this study, we aimed to explore different trajectories of ALC, and evaluate their relationship with prognosis in critically ill patients.

Methods

We retrospectively enrolled 10,619 critically ill patients admitted to a general intensive care unit (ICU) with 56 beds from February 2016 to May 2020. Dynamic ALC was defined as continuous ALC from before ICU admission to 5 days after ICU admission. Initial ALC was defined as the minimum ALC within 48 h after ICU admission. Group-based trajectory modeling (GBTM) was used to group critically ill patients according to dynamic ALC. Multivariate cox regression model was used to determine the independent association of trajectory endotypes with death and persistent inflammation, immunosuppression, catabolism syndrome (PICS).

Results

A total of 2022 critically ill patients were unsupervisedly divided into four endotypes based on dynamic ALC, including persistent lymphopenia endotype (n = 1,211; 58.5%), slowly rising endotype (n = 443; 22.6%), rapidly decreasing endotype (n = 281; 14.5%) and normal fluctuation endotype (n = 87; 4.4%). Among the four trajectory endotypes, the persistent lymphopenia endotype had the highest incidence of PICS (24.9%), hospital mortality (14.5%) and 28-day mortality (10.8%). In multivariate cox regression model, persistent lymphopenia was associated with increased risk of 28-day mortality (HR: 1.54; 95% CI: 1.06–2.23), hospital mortality (HR: 1.66; 95% CI: 1.20–2.29) and PICS (HR: 1.79; 95% CI: 1.09–2.94), respectively. Sensitivity analysis further confirmed that the ALC trajectory model of non-infected patients and non-elderly patients can accurately distinguished 91 and 90% of critically ill patients into the same endotypes as the original model, respectively.

Conclusion

The ALC trajectory model is helpful for grouping critically ill patients, and early persistent lymphopenia is associated with poor prognosis. Notably, persistent lymphopenia may be a robust signal of immunosuppression in critically ill patients.

Mental health and COVID-19 in a general population cohort in Spain (COVICAT study)

PURPOSE

Mental health conditions may affect outcome of COVID-19 disease, while exposure to stressors during the pandemic may impact mental health. The purpose of this study was to examine these factors in relation to ocurrence of depression and anxiety after the first outbreak in Spain.

METHODS

We contacted 9515 participants from a population-based cohort study in Catalonia between May and October 2020. We drew blood samples to establish infection to the virus. Pre-pandemic mental health conditions were confirmed through Electronic Health Registries. We used the Hospital Anxiety and Depression Scale to assess severe depression and anxiety post-pandemic. Exposure to proximal, financial and wider environment stressors during the lockdown were collected. We calculated Relative Risks (RR), adjusting for individual- and contextual covariates.

RESULTS

Pre-pandemic mental health disorders were not associated with SARS-CoV-2 infection , but were associated with severity of COVID-19 disease. People with pre-existing mental health disorders showed higher prevalence of severe depression (25.4%) and anxiety (37.8%) than those without prior mental disorders (4.9% and 10.1%). Living alone was a strong predictor of severe depression among mental health patients (RR = 1.6, 95% CI 1.2-2.2). Among those without prior mental health disorders, post-lockdown depression and anxiety were associated with household interpersonal conflicts (RR = 2.6, 95% CI 2.1-3.1; RR = 2.1, 95% CI 1.9-2.4) and financial instability (RR = 2.2, 95% CI 1.8-2.9; 1.9, 95% CI 1.6-2.2).

CONCLUSIONS

The COVID-19 pandemic and the lockdown were associated with increased post-lockdown depression and anxiety. Patients with pre-existing mental health conditions are a vulnerable group for severe COVID-19 disease.