Biological Phenotyping in Sepsis and Acute Respiratory Distress Syndrome

Sepsis in surgical patients: Personalized medicine in the future treatment of sepsis

Sepsis results when a severe infection overwhelms the normal regulatory mechanisms of the immune system, resulting in a dysregulated host response characterized by new-onset organ failure. A wide range of infectious challenges can induce sepsis, resulting in an even wider range of maladaptive immune responses. This makes sepsis a syndromic diagnosis without a unifying, underlying molecular mechanism. The next step toward personalized medicine for sepsis is to resolve the heterogeneity across the universe of septic patients in order to establish pathobiologically homogenous sepsis "endotypes" that have uniformly defined changes in physiology and immunology. Defining the mechanisms of immune dysfunction within these endotypes will provide a roadmap for the application of immunomodulatory therapies for sepsis. This approach can drive in a paradigm shift in sepsis treatment, moving beyond supportive care and toward active efforts to restore normal immune function.

Histone lactylation-regulated METTL3 promotes ferroptosis via m6A-modification on ACSL4 in sepsis-associated lung injury

Elevated lactate levels are a significant biomarker of sepsis and are positively associated with sepsis-related mortality. Sepsis-associated lung injury (ALI) is a leading cause of poor prognosis in clinical patients. However, the underlying mechanisms of lactate's involvement in sepsis-associated ALI remain unclear. In this study, we demonstrate that lactate regulates N6-methyladenosine (m6A) modification levels by facilitating p300-mediated H3K18la binding to the METTL3 promoter site. The METTL3-mediated m6A modification is enriched in ACSL4, and its mRNA stability is regulated through a YTHDC1-dependent pathway. Furthermore, short-term lactate stimulation upregulates ACSL4, which promotes mitochondria-associated ferroptosis. Inhibition of METTL3 through knockdown or targeted inhibition effectively suppresses septic hyper-lactate-induced ferroptosis in alveolar epithelial cells and mitigates lung injury in septic mice. Our findings suggest that lactate induces ferroptosis via the GPR81/H3K18la/METTL3/ACSL4 axis in alveolar epithelial cells during sepsis-associated ALI. These results reveal a histone lactylation-driven mechanism inducing ferroptosis through METTL3-mediated m6A modification. Targeting METTL3 represents a promising therapeutic strategy for patients with sepsis-associated ALI.

The Lipid Intensive Drug Therapy for Sepsis Phase II Pilot Clinical Trial

OBJECTIVES

Low cholesterol levels in early sepsis patients are associated with mortality. We sought to test if IV lipid emulsion administration to sepsis patients with low cholesterol levels would prevent a decline or increase total cholesterol levels at 48 hours.

DESIGN

Phase II, adaptive, randomized pilot clinical trial powered for 48 patients.

SETTING

Emergency department or ICU of an academic medical center.

PATIENTS

Sepsis patients (first 24 hr) with Sequential Organ Failure Assessment greater than or equal to 4 or shock.

INTERVENTIONS

Patients meeting study criteria, including screening total cholesterol levels less than or equal to 100 mg/dL or high-density lipoprotein cholesterol (HDL-C) + low-density lipoprotein cholesterol (LDL-C) less than or equal to 70 mg/dL, were randomized to receive one of three doses of lipid emulsion administered twice in 48 hours or no drug (controls). The primary endpoint was a change in serum total cholesterol (48 hr - enrollment) between groups.

MEASUREMENTS AND MAIN RESULTS

Forty-nine patients were enrolled and randomized. Two patients randomized to lipid emulsion were withdrawn before drug administration. Data for 24 control patients and 23 lipid emulsion patients were analyzed. The mean change in total cholesterol from enrollment to 48 hours was not different between groups and was 5 mg/dL ( sd 20) for lipid emulsion patients, and 2 mg/dL ( sd 18) for control patients ( p = 0.62). The mean changes in HDL-C and LDL-C were similar between groups. Mean change in triglycerides was elevated in lipid emulsion patients (61 mg/dL, sd 87) compared with controls (20 mg/dL, sd 70, p = 0.086). The 48-hour change in SOFA score was -2 (interquartile range [IQR] -4, -1) for control patients and -2 (IQR -3, 0) for lipid emulsion patients ( p = 0.46).

CONCLUSIONS

Administration of IV lipid emulsion to early sepsis patients with low cholesterol levels did not influence change in cholesterol levels from enrollment to 48 hours.

From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. To impact clinical care, identification of subpopulations must do more than differentiate prognosis. It must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway, but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry, and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields.

Integrated clustering of multiple immune marker trajectories reveals different immunotypes in severely injured patients

BACKGROUND

The immune response of critically ill patients, such as those with sepsis, severe trauma, or major surgery, is heterogeneous and dynamic, but its characterization and impact on outcomes are poorly understood. Until now, the primary challenge in advancing our understanding of the disease has been to concurrently address both multiparametric and temporal aspects.

METHODS

We used a clustering method to identify distinct groups of patients, based on various immune marker trajectories during the first week after admission to ICU. In 339 severely injured patients, we initially longitudinally clustered common biomarkers (both soluble and cellular parameters), whose variations are well-established during the immunosuppressive phase of sepsis. We then applied this multi-trajectory clustering using markers composed of whole blood immune-related mRNA.

RESULTS

We found that both sets of markers revealed two immunotypes, one of which was associated with worse outcomes, such as increased risk of hospital-acquired infection and mortality, and prolonged hospital stays. This immunotype showed signs of both hyperinflammation and immunosuppression, which persisted over time.

CONCLUSION

Our study suggest that the immune system of critically ill patients can be characterized by two distinct longitudinal immunotypes, one of which included patients with a persistently dysregulated and impaired immune response. This work confirms the relevance of such methodology to stratify patients and pave the way for further studies using markers indicative of potential immunomodulatory drug targets.

The deubiquitinase OTUD1 deubiquitinates TIPE2 and plays a protective role in sepsis-induced lung injury by targeting TAK1-mediated MAPK and NF-κB signaling

Ovarian tumor domain-containing protease 1 (OTUD1) is a critical negative regulator that promotes innate immune homeostasis and is extensively involved in the pathogenesis of sepsis. In this study, we performed a powerful integration of multiomics analysis and an experimental mechanistic investigation to elucidate the immunoregulatory role of OTUD1 in sepsis at the clinical, animal and cellular levels. Our study revealed the upregulation of OTUD1 expression and the related distinctive alterations observed via multiomics profiling in clinical and experimental sepsis. Importantly, in vivo and in vitro, OTUD1 was shown to negatively regulate inflammatory responses and play a protective role in sepsis-induced pathological lung injury by mechanistically inhibiting the activation of the transforming growth factor-beta-activated kinase 1 (TAK1)-mediated mitogen-activated protein kinase (MAPK) and nuclear factor kappa-B (NF-κB) signaling pathways in the present study. Subsequently, we probed the molecular mechanisms underlying OTUD1's regulation of NF-κB and MAPK pathways by pinpointing the target proteins that OTUD1 can deubiquitinate. Drawing upon prior research conducted in our laboratory, it has been demonstrated that tumor necrosis factor-α-induced protein 8-like 2 (TIPE2) performs a protective function in septic lung injury and septic encephalopathy by suppressing the NF-κB and MAPK pathways. Hence, we hypothesized that TIPE2 might be a target protein of OTUD1. Additional experiments, including Co-IP, immunofluorescence co-localization, and Western blotting, revealed that OTUD1 indeed has the ability to deubiquitinate TIPE2. In summary, OTUD1 holds potential as an immunoregulatory and inflammatory checkpoint agent, and could serve as a promising therapeutic target for sepsis-induced lung injury.

Biomarker-Based Risk Stratification Tool in Pediatric Acute Respiratory Distress Syndrome: Single-Center, Longitudinal Validation in a 2014-2019 Cohort

OBJECTIVES

The Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model (PARDSEVERE) used age and three plasma biomarkers measured within 24 hours of pediatric acute respiratory distress syndrome (ARDS) onset to predict mortality in a pilot cohort of 152 patients. However, longitudinal performance of PARDSEVERE has not been evaluated, and it is unclear whether the risk model can be used to prognosticate after day 0. We, therefore, sought to determine the test characteristics of PARDSEVERE model and population over the first 7 days after ARDS onset.

DESIGN

Secondary unplanned post hoc analysis of data from a prospective observational cohort study carried out 2014-2019.

SETTING

University-affiliated PICU.

PATIENTS

Mechanically ventilated children with ARDS.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Between July 2014 and December 2019, 279 patients with ARDS had plasma collected at day 0, 266 at day 3 (11 nonsurvivors, two discharged between days 0 and 3), and 207 at day 7 (27 nonsurvivors, 45 discharged between days 3 and 7). The actual prevalence of mortality on days 0, 3, and 7, was 23% (64/279), 14% (38/266), and 13% (27/207), respectively. The PARDSEVERE risk model for mortality on days 0, 3, and 7 had area under the receiver operating characteristic curve (AUROC [95% CI]) of 0.76 (0.69-0.82), 0.68 (0.60-0.76), and 0.74 (0.65-0.83), respectively. The AUROC data translate into prevalence thresholds for the PARDSEVERE model for mortality (i.e., using the sensitivity and specificity values) of 37%, 27%, and 24% on days 0, 3, and 7, respectively. Negative predictive value (NPV) was high throughout (0.87-0.90 for all three-time points).

CONCLUSIONS

In this exploratory analysis of the PARDSEVERE model of mortality risk prediction in a population longitudinal series of data from days 0, 3, and 7 after ARDS diagnosis, the diagnostic performance is in the "acceptable" category. NPV was good. A major limitation is that actual mortality is far below the prevalence threshold for such testing. The model may, therefore, be more useful in cohorts with higher mortality rates (e.g., immunocompromised, other countries), and future enhancements to the model should be explored.

Joint modeling of monocyte HLA-DR expression trajectories predicts 28-day mortality in severe SARS-CoV-2 patients

The recent SarsCov2 pandemic has disrupted healthcare system notably impacting intensive care units (ICU). In severe cases, the immune system is dysregulated, associating signs of hyperinflammation and immunosuppression. In the present work, we investigated, using a joint modeling approach, whether the trajectories of cellular immunological parameters were associated with survival of COVID-19 ICU patients. This study is based on the REA-IMMUNO-COVID cohort including 538 COVID-19 patients admitted to ICU between March 2020 and May 2022. Measurements of monocyte HLA-DR expression (mHLA-DR), counts of neutrophils, of total lymphocytes, and of CD4+ and CD8+ subsets were performed five times during the first month after ICU admission. Univariate joint models combining survival at day 28 (D28), hospital discharge and longitudinal analysis of those biomarkers' kinetics with mixed-effects models were performed prior to the building of a multivariate joint model. We showed that a higher mHLA-DR value was associated with a lower risk of death. Predicted mHLA-DR nadir cutoff value that maximized the Youden index was 5414 Ab/C and led to an AUC = 0.70 confidence interval (95%CI) = [0.65; 0.75] regarding association with D28 mortality while dynamic predictions using mHLA-DR kinetics until D7, D12 and D20 showed AUCs of 0.82 [0.77; 0.87], 0.81 [0.75; 0.87] and 0.84 [0.75; 0.93]. Therefore, the final joint model provided adequate discrimination performances at D28 after collection of biomarker samples until D7, which improved as more samples were collected. After severe COVID-19, decreased mHLA-DR expression is associated with a greater risk of death at D28 independently of usual clinical confounders.

M-ClustEHR: A multimodal clustering approach for electronic health records

Sepsis refers to a potentially life-threatening situation where the immune system of the human body has an extreme response to an infection. In the presence of underlying comorbidities, the situation can become even worse and result in death. Employing unsupervised machine learning techniques, such as clustering, can assist in providing a better understanding of patient phenotypes by unveiling subgroups characterized by distinct sepsis progression and treatment patterns. More concretely, this study introduces M-ClustEHR, a clustering approach that utilizes medical data of multiple modalities by employing a multimodal autoencoder for learning comprehensive sepsis patient representations. M-ClustEHR consistently outperforms traditional clustering approaches in terms of several internal clustering performance metrics, as well as cluster stability in identifying phenotypes in the sepsis cohort. The unveiled patterns, supported by existing medical literature and clinicians, highlight the importance of multimodal clustering for advancing personalized sepsis care.

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

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

Biomarkers in Sepsis: A Current Review of New Technologies

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.

Identification and validation of sepsis subphenotypes using time-series data

Purpose

The recognition of sepsis as a heterogeneous syndrome necessitates identifying distinct subphenotypes to select targeted treatment.

Methods

Patients with sepsis from the MIMIC-IV database (2008-2019) were randomly divided into a development cohort (80%) and an internal validation cohort (20%). Patients with sepsis from the ICU database of Peking University People's Hospital (2008-2022) were included in the external validation cohort. Time-series k-means clustering analysis and dynamic time warping was performed to develop and validate sepsis subphenotypes by analyzing the trends of 21 vital signs and laboratory indicators within 24 h after sepsis onset. Inflammatory biomarkers were compared in the ICU database of Peking University People's Hospital, whereas treatment heterogeneity was compared in the MIMIC-IV database.

Findings

Three sub-phenotypes were identified in the development cohort. Type A patients (N = 2525, 47%) exhibited stable vital signs and fair organ function, type B (N = 1552, 29%) was exhibited an obvious inflammatory response and stable organ function, and type C (N = 1251, 24%) exhibited severely impaired organ function with a deteriorating tendency. Type C demonstrated the highest mortality rate (33%) and levels of inflammatory biomarkers, followed by type B (24%), whereas type A exhibited the lowest mortality rate (11%) and levels of inflammatory biomarkers. These subphenotypes were confirmed in both the internal and external cohorts, demonstrating similar features and comparable mortality rates. In type C patients, survivors had significantly lower fluid intake within 24 h after sepsis onset (median 2891 mL, interquartile range (IQR) 1530-5470 mL) than that in non-survivors (median 4342 mL, IQR 2189-7305 mL). For types B and C, survivors showed a higher proportion of indwelling central venous catheters (p < 0.05).

Conclusion

Three novel phenotypes of patients with sepsis were identified and validated using time-series data, revealing significant heterogeneity in inflammatory biomarkers, treatments, and consistency across cohorts.

Pharmacologic Treatments in Acute Respiratory Failure

Acute respiratory failure relies on supportive care using non-invasive and invasive oxygen and ventilatory support. Pharmacologic therapies for the most severe form of respiratory failure, acute respiratory distress syndrome (ARDS), are limited. This review focuses on the most promising therapies for ARDS, targeting different mechanisms that contribute to dysregulated inflammation and resultant hypoxemia. Significant heterogeneity exists within the ARDS population. Treatment requires prompt recognition of ARDS and an understanding of which patients may benefit most from specific pharmacologic interventions. The key to finding effective pharmacotherapies for ARDS may rely on deeper understanding of pathophysiology and bedside identification of ARDS subphenotypes.

Distinct functional neutrophil phenotypes in sepsis patients correlate with disease severity

Purpose

Sepsis is a clinical syndrome defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis is a highly heterogeneous syndrome with distinct phenotypes that impact immune function and response to infection. To develop targeted therapeutics, immunophenotyping is needed to identify distinct functional phenotypes of immune cells. In this study, we utilized our Organ-on-Chip assay to categorize sepsis patients into distinct phenotypes using patient data, neutrophil functional analysis, and proteomics.

Methods

Following informed consent, neutrophils and plasma were isolated from sepsis patients in the Temple University Hospital ICU (n=45) and healthy control donors (n=7). Human lung microvascular endothelial cells (HLMVEC) were cultured in the Organ-on-Chip and treated with buffer or cytomix ((TNF/IL-1β/IFNγ). Neutrophil adhesion and migration across HLMVEC in the Organ-on-Chip were used to categorize functional neutrophil phenotypes. Quantitative label-free global proteomics was performed on neutrophils to identify differentially expressed proteins. Plasma levels of sepsis biomarkers and neutrophil extracellular traps (NETs) were determined by ELISA.

Results

We identified three functional phenotypes in critically ill ICU sepsis patients based on ex vivo neutrophil adhesion and migration patterns. The phenotypes were classified as: Hyperimmune characterized by enhanced neutrophil adhesion and migration, Hypoimmune that was unresponsive to stimulation, and Hybrid with increased adhesion but blunted migration. These functional phenotypes were associated with distinct proteomic signatures and differentiated sepsis patients by important clinical parameters related to disease severity. The Hyperimmune group demonstrated higher oxygen requirements, increased mechanical ventilation, and longer ICU length of stay compared to the Hypoimmune and Hybrid groups. Patients with the Hyperimmune neutrophil phenotype had significantly increased circulating neutrophils and elevated plasma levels NETs.

Conclusion

Neutrophils and NETs play a critical role in vascular barrier dysfunction in sepsis and elevated NETs may be a key biomarker identifying the Hyperimmune group. Our results establish significant associations between specific neutrophil functional phenotypes and disease severity and identify important functional parameters in sepsis pathophysiology that may provide a new approach to classify sepsis patients for specific therapeutic interventions.

Circulating N-lactoyl-amino acids and N-formyl-methionine reflect mitochondrial dysfunction and predict mortality in septic shock

INTRODUCTION

Sepsis is a highly morbid condition characterized by multi-organ dysfunction resulting from dysregulated inflammation in response to acute infection. Mitochondrial dysfunction may contribute to sepsis pathogenesis, but quantifying mitochondrial dysfunction remains challenging.

OBJECTIVE

To assess the extent to which circulating markers of mitochondrial dysfunction are increased in septic shock, and their relationship to severity and mortality.

METHODS

We performed both full-scan and targeted (known markers of genetic mitochondrial disease) metabolomics on plasma to determine markers of mitochondrial dysfunction which distinguish subjects with septic shock (n = 42) from cardiogenic shock without infection (n = 19), bacteremia without sepsis (n = 18), and ambulatory controls (n = 19) - the latter three being conditions in which mitochondrial function, proxied by peripheral oxygen consumption, is presumed intact.

RESULTS

Nine metabolites were significantly increased in septic shock compared to all three comparator groups. This list includes N-formyl-L-methionine (f-Met), a marker of dysregulated mitochondrial protein translation, and N-lactoyl-phenylalanine (lac-Phe), representative of the N-lactoyl-amino acids (lac-AAs), which are elevated in plasma of patients with monogenic mitochondrial disease. Compared to lactate, the clinical biomarker used to define septic shock, there was greater separation between survivors and non-survivors of septic shock for both f-Met and the lac-AAs measured within 24 h of ICU admission. Additionally, tryptophan was the one metabolite significantly decreased in septic shock compared to all other groups, while its breakdown product kynurenate was one of the 9 significantly increased.

CONCLUSION

Future studies which validate the measurement of lac-AAs and f-Met in conjunction with lactate could define a sepsis subtype characterized by mitochondrial dysfunction.

Advances and Challenges in Sepsis Management: Modern Tools and Future Directions

Sepsis, a critical condition marked by systemic inflammation, profoundly impacts both innate and adaptive immunity, often resulting in lymphopenia. This immune alteration can spare regulatory T cells (Tregs) but significantly affects other lymphocyte subsets, leading to diminished effector functions, altered cytokine profiles, and metabolic changes. The complexity of sepsis stems not only from its pathophysiology but also from the heterogeneity of patient responses, posing significant challenges in developing universally effective therapies. This review emphasizes the importance of phenotyping in sepsis to enhance patient-specific diagnostic and therapeutic strategies. Phenotyping immune cells, which categorizes patients based on clinical and immunological characteristics, is pivotal for tailoring treatment approaches. Flow cytometry emerges as a crucial tool in this endeavor, offering rapid, low cost and detailed analysis of immune cell populations and their functional states. Indeed, this technology facilitates the understanding of immune dysfunctions in sepsis and contributes to the identification of novel biomarkers. Our review underscores the potential of integrating flow cytometry with omics data, machine learning and clinical observations to refine sepsis management, highlighting the shift towards personalized medicine in critical care. This approach could lead to more precise interventions, improving outcomes in this heterogeneously affected patient population.

Inhibition of sphingosine kinase 1 attenuates LPS-induced acute lung injury by suppressing endothelial cell pyroptosis

Acute lung injury (ALI) is a frequent complication of sepsis, with pyroptosis playing a pivotal role. Analysis of Gene Expression Omnibus (GEO) mouse sepsis datasets revealed the upregulation of sphingosine kinase 1 (SphK1) in septic mouse lung tissues, which was validated in lipopolysaccharide (LPS)-treated mice. Therefore, this study aimed to explore the potential role and underlying mechanisms of SphK1, the primary kinase responsible for catalyzing the formation of the bioactive lipid sphingosine-1-phosphat, in sepsis development. Mice received an intraperitoneal injection of SphK1 inhibitor prior to LPS administration. Mouse lung vascular endothelial cells (MLVECs) were exposed to LPS and SphK1 inhibitor. The SphK1 inhibitor mitigated ALI, as evidenced by hematoxylin and eosin (H&E) staining and the wet-to-dry (W/D) weight ratio and reduced Evans blue dye leakage. Furthermore, the SphK1 inhibitor inhibited the activation of the NOD-like receptor protein 3 inflammasome and the subsequent induction of pyroptosis both in vivo and in vitro. Intriguingly, using co-immunoprecipitation (Co-IP) combined with mass spectrometry, our findings revealed that SphK1 associates with pyruvate kinase M2 (PKM2), facilitating PKM2 phosphorylation and its nuclear translocation. TEPP-46, which has the ability to stabilize PKM2 and inhibit the phosphorylation and nuclear translocation of PKM2, markedly reduced the expression of pyroptosis-associated markers and alleviated lung injury. Concludingly, our results suggest that targeting SphK1 is a promising therapeutic strategy for ALI.

Interferon-Gamma-Release assay and absolute CD8 lymphocyte count for acquired immunosuppression monitoring in critically ill patients

Guided biomarker-personalized immunotherapy is advancing rapidly as a means to rejuvenate immune function in injured patients who are the most immunosuppressed. A recent study introduced a fully automated interferon-γ release assay (IGRA) for monitoring the functionality of T lymphocytes in patients with septic shock. While a significant decrease in IFN-γ release capacity was observed, a significant correlation with CD8 lymphocyte absolute count was also reported, raising the question of whether ex-vivo IFN-γ production would be only a surrogate marker for lymphocyte count or if these two parameters conveyed distinct and complementary information. In a large cohort of more than 353 critically ill patients following various injuries (sepsis, trauma, major surgery), the primary objective of the present study was to simultaneously evaluate the association between ex vivo IFN-γ release and CD8 cell count with regard to adverse outcome. Our findings provide a clear-cut result, as they distinctly demonstrate that IGRA offers higher-quality information than CD8 count in terms of an independent association with the occurrence of an adverse outcome. These results strengthen the case for incorporating IGRA into the array of biomarkers of interest for defining endotypes in sepsis. This holds especially true given that fully automated tests are now readily available and could be used in routine clinical practice.

Neutrophil extracellular traps and their implications in airway inflammatory diseases

Neutrophil extracellular traps (NETs) are essential for immune defense and have been increasingly recognized for their role in infection and inflammation. In the context of airway inflammatory diseases, there is growing evidence suggesting the involvement and significance of NETs. This review aims to provide an overview of the formation mechanisms and components of NETs and their impact on various airway inflammatory diseases, including acute lung injury/ARDS, asthma, chronic obstructive pulmonary disease (COPD) and cystic fibrosis. By understanding the role of NETs in airway inflammation, we can gain valuable insights into the underlying pathogenesis of these diseases and identify potential targets for future therapeutic strategies that either target NETs formation or modulate their harmful effects. Further research is warranted to elucidate the complex interactions between NETs and airway inflammation and to develop targeted therapies that can effectively mitigate their detrimental effects while preserving their beneficial functions in host defense.

The pathophysiology of sepsis and precision-medicine-based immunotherapy

Sepsis remains a major cause of morbidity and mortality in both low- and high-income countries. Antibiotic therapy and supportive care have significantly improved survival following sepsis in the twentieth century, but further progress has been challenging. Immunotherapy trials for sepsis, mainly aimed at suppressing the immune response, from the 1990s and 2000s, have largely failed, in part owing to unresolved patient heterogeneity in the underlying immune disbalance. The past decade has brought the promise to break this blockade through technological developments based on omics-based technologies and systems medicine that can provide a much larger data space to describe in greater detail the immune endotypes in sepsis. Patient stratification opens new avenues towards precision medicine approaches that aim to apply immunotherapies to sepsis, on the basis of precise biomarkers and molecular mechanisms defining specific immune endotypes. This approach has the potential to lead to the establishment of immunotherapy as a successful pillar in the treatment of sepsis for future generations.

Mitigation of Sepsis-Induced Acute Lung Injury by BMSC-Derived Exosomal miR-125b-5p Through STAT3-Mediated Suppression of Macrophage Pyroptosis

Introduction

Sepsis is a syndrome characterized by high morbidity and mortality rates. One of its most severe complications is acute lung injury, which exhibits a multitude of clinical and biological features, including macrophage pyroptosis. This study investigates the regulatory effects of exosomes derived from Bone Marrow-Derived Mesenchymal Stem Cells (BMSCs) on sepsis-associated acute lung injury (ALI) and explores the potential mechanisms mediated by exosomal miRNAs.

Methods

Exosomes were isolated from primary BMSCs of adult C57BL/6J mice using differential centrifugation. Their uptake and distribution in both in vitro and in vivo contexts were validated. Key sepsis-associated hub gene signal transducer and activator of transcription 3 (STAT3) and its upstream non-coding miR-125b-5p were elucidated through a combination of bioinformatics, machine learning, and miRNA sequencing. Subsequently, the therapeutic potential of BMSC-derived exosomes in alleviating sepsis-induced acute lung injury was substantiated. Moreover, the functionalities of miR-125b-5p and STAT3 were corroborated through miR-125b-5p inhibitor and STAT3 agonist interventions, employing gain and loss-of-function strategies both in vitro and in vivo. Finally, a dual-luciferase reporter assay reaffirmed the interaction between miR-125b-5p and STAT3.

Results

We isolated exosomes from primary BMSCs and confirmed their accumulation in the mouse lung as well as their uptake by macrophages in vitro. This study identified the pivotal sepsis-associated hub gene STAT3 and demonstrated that exosomes derived from BMSCs can target STAT3, thereby inhibiting macrophage pyroptosis. MiR-125b-5p inhibition experiments showed that exosomes mitigate macrophage pyroptosis and lung injury by delivering miR-125b-5p. STAT3 overexpression experiments validated that miR-125b-5p reduces macrophage pyroptosis and lung injury by suppressing STAT3. Furthermore, a dual-luciferase reporter assay confirmed the binding interaction between miR-125b-5p and STAT3.

Conclusion

Exosomes derived from BMSCs, serving as carriers for delivering miR-125b-5p, can downregulate STAT3, thereby inhibiting macrophage pyroptosis and alleviating sepsis-associated ALI. These significant findings provide valuable insights into the potential development of ALI therapies centred around exosomes derived from BMSC.

Development of genomic phenotype and immunophenotype of acute respiratory distress syndrome using autophagy and metabolism-related genes

Background

Distinguishing ARDS phenotypes is of great importance for its precise treatment. In the study, we attempted to ascertain its phenotypes based on metabolic and autophagy-related genes and infiltrated immune cells.

Methods

Transcription datasets of ARDS patients were obtained from Gene expression omnibus (GEO), autophagy and metabolic-related genes were from the Human Autophagy Database and the GeneCards Database, respectively. Autophagy and metabolism-related differentially expressed genes (AMRDEGs) were further identified by machine learning and processed for constructing the nomogram and the risk prediction model. Functional enrichment analyses of differentially expressed genes were performed between high- and low-risk groups. According to the protein-protein interaction network, these hub genes closely linked to increased risk of ARDS were identified with CytoHubba. ssGSEA and CIBERSORT was applied to analyze the infiltration pattern of immune cells in ARDS. Afterwards, immunologically characterized and molecular phenotypes were constructed according to infiltrated immune cells and hub genes.

Results

A total of 26 AMRDEGs were obtained, and CTSB and EEF2 were identified as crucial AMRDEGs. The predictive capability of the risk score, calculated based on the expression levels of CTSB and EEF2, was robust for ARDS in both the discovery cohort (AUC = 1) and the validation cohort (AUC = 0.826). The mean risk score was determined to be 2.231332, and based on this score, patients were classified into high-risk and low-risk groups. 371 differential genes in high- and low-risk groups were analyzed. ITGAM, TYROBP, ITGB2, SPI1, PLEK, FGR, MPO, S100A12, HCK, and MYC were identified as hub genes. A total of 12 infiltrated immune cells were differentially expressed and have correlations with hub genes. According to hub genes and implanted immune cells, ARDS patients were divided into two different molecular phenotypes (Group 1: n = 38; Group 2: n = 19) and two immune phenotypes (Cluster1: n = 22; Cluster2: n = 35), respectively.

Conclusion

This study picked up hub genes of ARDS related to autophagy and metabolism and clustered ARDS patients into different molecular phenotypes and immunophenotypes, providing insights into the precision medicine of treating patients with ARDS.

Metabolism and Nutrition in Sepsis: In Need of a Paradigm Shift

BACKGROUND

Sepsis continues to cause significant morbidity and mortality despite technological advancements in medical management. While sepsis is defined as organ dysfunction owing to the dysregulated host response to infection, our understanding of the dysregulation of the host response remains incomplete.

SUMMARY

Many metabolic derangements that occur during sepsis, including those associated with anorexia, hyperglycemia, and proteolysis, have largely been considered maladaptive. Supportive medical and nutritional interventions targeted at correcting these metabolic derangements have not led to improved outcomes, suggesting a reappraisal of our approach to metabolism and nutrition in critically ill septic patients is needed.

KEY MESSAGES

Explanations of the lack of efficacy of these clinical interventions may include targeting the wrong metric or patient population, or the possibility that some of these metabolic changes could be protective. In this mini-review, we propose a paradigm shift that is needed in metabolism and nutrition management in sepsis.

Clinical Sepsis Phenotypes in Critically Ill Patients

Sepsis, defined as the life-threatening dysregulated host response to an infection leading to organ dysfunction, is considered as one of the leading causes of mortality worldwide, especially in intensive care units (ICU). Moreover, sepsis remains an enigmatic clinical syndrome, with complex pathophysiology incompletely understood and a great heterogeneity both in terms of clinical expression, patient response to currently available therapeutic interventions and outcomes. This heterogeneity proves to be a major obstacle in our quest to deliver improved treatment in septic critical care patients; thus, identification of clinical phenotypes is absolutely necessary. Although this might be seen as an extremely difficult task, nowadays, artificial intelligence and machine learning techniques can be recruited to quantify similarities between individuals within sepsis population and differentiate them into distinct phenotypes regarding not only temperature, hemodynamics or type of organ dysfunction, but also fluid status/responsiveness, trajectories in ICU and outcome. Hopefully, we will eventually manage to determine both the subgroup of septic patients that will benefit from a therapeutic intervention and the correct timing of applying the intervention during the disease process.

A complement atlas identifies interleukin-6-dependent alternative pathway dysregulation as a key druggable feature of COVID-19

Improvements in COVID-19 treatments, especially for the critically ill, require deeper understanding of the mechanisms driving disease pathology. The complement system is not only a crucial component of innate host defense but can also contribute to tissue injury. Although all complement pathways have been implicated in COVID-19 pathogenesis, the upstream drivers and downstream effects on tissue injury remain poorly defined. We demonstrate that complement activation is primarily mediated by the alternative pathway, and we provide a comprehensive atlas of the complement alterations around the time of respiratory deterioration. Proteomic and single-cell sequencing mapping across cell types and tissues reveals a division of labor between lung epithelial, stromal, and myeloid cells in complement production, in addition to liver-derived factors. We identify IL-6 and STAT1/3 signaling as an upstream driver of complement responses, linking complement dysregulation to approved COVID-19 therapies. Furthermore, an exploratory proteomic study indicates that inhibition of complement C5 decreases epithelial damage and markers of disease severity. Collectively, these results support complement dysregulation as a key druggable feature of COVID-19.

Circulatory HMGB1 is an early predictive and prognostic biomarker of ARDS and mortality in a swine model of polytrauma

Acute respiratory distress syndrome (ARDS) is a leading cause of morbidity and mortality in polytrauma patients. Pharmacological treatments of ARDS are lacking, and ARDS patients rely on supportive care. Accurate diagnosis of ARDS is vital for early intervention and improved outcomes but is presently delayed up to days. The use of biomarkers for early identification of ARDS development is a potential solution. Inflammatory mediators high-mobility group box 1 (HMGB1), syndecan-1 (SDC-1), and C3a have been previously proposed as potential biomarkers. For this study, we analyzed these biomarkers in animals undergoing smoke inhalation and 40% total body surface area burns, followed by intensive care for 72 h post-injury (PI) to determine their association with ARDS and mortality. We found that the levels of inflammatory mediators in serum were affected, as well as the degree of HMGB1 and Toll-like receptor 4 (TLR4) signal activation in the lung. The results showed significantly increased HMGB1 expression levels in animals that developed ARDS compared with those that did not. Receiver operating characteristic (ROC) analysis showed that HMGB1 levels at 6 h PI were significantly associated with ARDS development (AUROC=0.77) and mortality (AUROC=0.82). Logistic regression analysis revealed that levels of HMGB1 ≥24.10 ng/ml are associated with a 13-fold higher incidence of ARDS [OR:13.57 (2.76-104.3)], whereas the levels of HMGB1 ≥31.39 ng/ml are associated with a 12-fold increase in mortality [OR: 12.00 (2.36-93.47)]. In addition, we found that mesenchymal stem cell (MSC) therapeutic treatment led to a significant decrease in systemic HMGB1 elevation but failed to block SDC-1 and C3a increases. Immunohistochemistry analyses showed that smoke inhalation and burn injury induced the expression of HMGB1 and TLR4 and stimulated co-localization of HMGB1 and TLR4 in the lung. Interestingly, MSC treatment reduced the presence of HMGB1, TLR4, and the HMGB1-TLR4 co-localization. These results show that serum HMGB1 is a prognostic biomarker for predicting the incidence of ARDS and mortality in swine with smoke inhalation and burn injury. Therapeutically blocking HMGB1 signal activation might be an effective approach for attenuating ARDS development in combat casualties or civilian patients.

Anti-inflammatory therapies for acute respiratory distress syndrome

INTRODUCTION

Treatments for the acute respiratory distress syndrome (ARDS) are mainly supportive, and ventilatory management represents a key approach in these patients. Despite progress in pharmacotherapy, anti-inflammatory strategies for the treatment of ARDS have shown controversial results. Positive outcomes with pharmacologic and nonpharmacologic treatments have been found in two different biological subphenotypes of ARDS, suggesting that, with a personalized medicine approach, pharmacotherapy for ARDS can be effective.

AREAS COVERED

This article reviews the literature concerning anti-inflammatory therapies for ARDS, focusing on pharmacological and stem-cell therapies, including extracellular vesicles.

EXPERT OPINION

Despite advances, ARDS treatments remain primarily supportive. Ventilatory and fluid management are important strategies in these patients that have demonstrated significant impacts on outcome. Anti-inflammatory drugs have shown some benefits, primarily in preclinical research and in specific clinical scenarios, but no recommendations are available from guidelines to support their use in patients with ARDS, except in particular settings such as different subphenotypes, specific etiologies, or clinical trials. Personalized medicine seems promising insofar as it may identify specific subgroups of patients with ARDS who may benefit from anti-inflammatory treatment. However, additional efforts are needed to move subphenotype characterization from bench to bedside.