The Septic Neutrophil-Friend or Foe

PLASMA DYNAMICS OF NEUTROPHIL EXTRACELLULAR TRAPS AND CELL-FREE DNA IN SEPTIC AND NONSEPTIC VASOPLEGIC SHOCK: A PROSPECTIVE COMPARATIVE OBSERVATIONAL COHORT STUDY

ABSTRACT

Background: The association between neutrophil extracellular traps (NETs) and the requirement for vasopressor and inotropic support in vasoplegic shock is unclear. This study aimed to investigate the dynamics of plasma levels of NETs and cell-free DNA (cfDNA) up to 48 h after the admission to the intensive care unit (ICU) for management of vasoplegic shock of infectious (SEPSIS) or noninfectious (following cardiac surgery, CARDIAC) origin. Methods: This is a prospective, observational study of NETs and cfDNA plasma levels at 0H (admission) and then at 12H, 24H, and 48H in SEPSIS and CARDIAC patients. The vasopressor inotropic score (VIS), the Sequential Organ Failure Assessment (SOFA) score, and time spent with invasive ventilation, in ICU and in hospital, were recorded. Associations between NETs/cfDNA and VIS and SOFA were analyzed by Spearman's correlation (rho), and between NETs/cfDNA and ventilation/ICU/hospitalization times by generalized linear regression. Results: Both NETs and cfDNA remained elevated over 48 h in SEPSIS (n = 46) and CARDIAC (n = 30) patients, with time-weighted average concentrations greatest in SEPSIS (NETs median difference 0.06 [0.02-0.11], P = 0.005; cfDNA median difference 0.48 [0.20-1.02], P < 0.001). The VIS correlated to NETs (rho = 0.3-0.60 in SEPSIS, P < 0.01, rho = 0.36-0.57 in CARDIAC, P ≤ 0.01) and cfDNA (rho = 0.40-0.56 in SEPSIS, P < 0.01, rho = 0.38-0.47 in CARDIAC, P < 0.05). NETs correlated with SOFA. Neither NETs nor cfDNA were independently associated with ventilator/ICU/hospitalization times. Conclusion: Plasma levels of NETs and cfDNA correlated with the dose of vasopressors and inotropes administered over 48 h in patients with vasoplegic shock from sepsis or following cardiac surgery. NETs levels also correlated with organ dysfunction. These findings suggest that similar mechanisms involving release of NETs are involved in the pathophysiology of vasoplegic shock irrespective of an infectious or noninfectious etiology.

Generative modeling of biological shapes and images using a probabilistic α-shape sampler

Understanding morphological variation is an important task in many areas of computational biology. Recent studies have focused on developing computational tools for the task of sub-image selection which aims at identifying structural features that best describe the variation between classes of shapes. A major part in assessing the utility of these approaches is to demonstrate their performance on both simulated and real datasets. However, when creating a model for shape statistics, real data can be difficult to access and the sample sizes for these data are often small due to them being expensive to collect. Meanwhile, the current landscape of generative models for shapes has been mostly limited to approaches that use black-box inference-making it difficult to systematically assess the power and calibration of sub-image models. In this paper, we introduce the α -shape sampler: a probabilistic framework for generating realistic 2D and 3D shapes based on probability distributions which can be learned from real data. We demonstrate our framework using proof-of-concept examples and in two real applications in biology where we generate (i) 2D images of healthy and septic neutrophils and (ii) 3D computed tomography (CT) scans of primate mandibular molars. The α -shape sampler R package is open-source and can be downloaded at https://github.com/lcrawlab/ashapesampler.

PREDICTIVE VALUE OF NEUTROPHIL EXTRACELLULAR TRAP COMPONENTS FOR 28-DAY ALL-CAUSE MORTALITY IN PATIENTS WITH CARDIAC ARREST: A PILOT OBSERVATIONAL STUDY

ABSTRACT

Background: Ischemia-reperfusion after cardiac arrest (CA) activates peptidyl arginine deiminase and citrullinated histone H3 (CitH3), which leads to the formation of neutrophil extracellular traps (NETs). This study attempted to determine the alterations in NET components in post-CA patients as well as analyze the association of NETs with 28-day all-cause mortality. Methods : In this study, 95 patients with restoration of spontaneous circulation (ROSC) after CA were included. They were categorized into the survivor group (n = 32) and the nonsurvivor group (n = 63) according to their 28-day survival statuses. The control group comprised 20 healthy individuals. The blood samples were collected from the patients on days 1, 3, and 7 after ROSC and from the control subjects at the time of enrollment. The serum cell-free DNA (cfDNA) level was determined using the fluorescent labeling method, and the serum concentrations of NET components, including CitH3, myeloperoxidase, neutrophil elastase, and nucleosomes, were estimated using the enzyme-linked immunosorbent assay. Results : Compared with the control group, the serum NET components were significantly increased in the patients 1 week after ROSC (all P < 0.05). These components were significantly higher in the nonsurvivor group than in the survivor group (all P < 0.05). Spearman correlational analysis revealed that the components were positively correlated with Acute Physiology and Chronic Health Evaluation II scores (both P < 0.05). Binary logistic regression analysis indicated that serum cfDNA, CitH3, and nucleosomes on days 1 and 3 after ROSC were independent predictors of 28-day all-cause mortality. Furthermore, these parameters on day 1 after ROSC had the biggest areas under the receiver operating characteristic curves (0.876, 0.862, and 0.861, respectively). Conclusions: Elevated serum levels of cfDNA, CitH3, myeloperoxidase, neutrophil elastase, and nucleosomes were positively correlated with disease severity after ROSC. However, only serum CitH3, cfDNA, and nucleosomes on day 1 after ROSC showed a good predictive value for 28-day all-cause mortality.

Neutrophil extracellular trap inhibition improves survival in neonatal mouse infectious peritonitis

BACKGROUND

Treatment of neonatal peritonitis and sepsis is challenging. Following infection, neutrophils elaborate neutrophil extracellular traps (NETs)-extracellular lattices of decondensed chromatin decorated with antimicrobial proteins. NETs, however, can augment pathogenic inflammation causing collateral damage. We hypothesized that NET inhibition would improve survival in experimental neonatal infectious peritonitis.

METHODS

We induced peritonitis in 7 to 10-day-old mice by intraperitoneal injection with cecal slurry. We targeted NETs by treating mice with neonatal NET-Inhibitory Factor (nNIF), an endogenous NET-inhibitor; Cl-amidine, a PAD4 inhibitor; DNase I, a NET degrading enzyme, or meropenem (an antibiotic). We determined peritoneal NET and cytokine levels and circulating platelet-neutrophil aggregates. Survival from peritonitis was followed for 6 days.

RESULTS

nNIF, Cl-amidine, and DNase I decreased peritoneal NET formation and inflammatory cytokine levels at 24 h compared to controls. nNIF, Cl-amidine, and DNase I decreased circulating platelet-neutrophil aggregates, and NET-targeting treatments significantly increased survival from infectious peritonitis compared to controls. Finally, nNIF administration significantly improved survival in mice treated with sub-optimal doses of meropenem even when treatment was delayed until 2 h after peritonitis induction.

CONCLUSIONS

NET inhibition improves survival in experimental neonatal infectious peritonitis, suggesting that NETs participate pathogenically in neonatal peritonitis and sepsis.

IMPACT

1. Neutrophil extracellular trap formation participates pathogenically in experimental neonatal infectious peritonitis. 2. NET-targeting strategies improve outcomes in a translational model of neonatal infectious peritonitis. 3. NET inhibition represents a potential target for drug development in neonatal sepsis and infectious peritonitis.

LEUKOCYTE PHENOTYPING IN SEPSIS USING OMICS, FUNCTIONAL ANALYSIS, AND IN SILICO MODELING

ABSTRACT

Sepsis is a major health issue and a leading cause of death in hospitals globally. The treatment of sepsis is largely supportive, and there are no therapeutics available that target the underlying pathophysiology of the disease. The development of therapeutics for the treatment of sepsis is hindered by the heterogeneous nature of the disease. The presence of multiple, distinct immune phenotypes ranging from hyperimmune to immunosuppressed can significantly impact the host response to infection. Recently, omics, biomarkers, cell surface protein expression, and immune cell profiles have been used to classify immune status of sepsis patients. However, there has been limited studies of immune cell function during sepsis and even fewer correlating omics and biomarker alterations to functional consequences. In this review, we will discuss how the heterogeneity of sepsis and associated immune cell phenotypes result from changes in the omic makeup of cells and its correlation with leukocyte dysfunction. We will also discuss how emerging techniques such as in silico modeling and machine learning can help in phenotyping sepsis patients leading to precision medicine.

[Pathophysiology of sepsis]

Up to now, sepsis is one of the most threatening diseases and its therapy remains challenging. Sepsis is currently defined as a severely dysregulated immune response to an infection resulting in organ dysfunction. The pathophysiology is mainly driven by exogenous PAMPs ("pathogen-associated molecular patterns") and endogenous DAMPs ("damage-associated molecular patterns"), which can activate PRRs ("pattern recognition receptors") on different cell types (mainly immune cells), leading to the initiation of manifold downstream pathways and a perpetuation of patients' immune response. Sepsis is neither an exclusive pro- nor an anti-inflammatory disease: both processes take place in parallel, resulting in an individual immunologic disease state depending on the severity of each component at different time points. Septic shock is a complex disorder of the macro- and microcirculation, provoking a severe lack of oxygenation further aggravating sepsis defining organ dysfunctions. An in-depth knowledge of the heterogeneity and the time-dependency of the septic immunopathology will be essential for the design of future sepsis trials and therapy planning in patients with sepsis. The big aim is to achieve a more individualized treatment strategy in patients suffering from sepsis or septic shock.

Bulk RNA Sequencing With Integrated Single-Cell RNA Sequencing Identifies BCL2A1 as a Potential Diagnostic and Prognostic Biomarker for Sepsis

Background

Sepsis is one of the leading causes of morbidity and mortality worldwide in the intensive care unit (ICU). The prognosis of the disease strongly depends on rapid diagnosis and appropriate treatment. Thus, some new and accurate sepsis-related biomarkers are pressing needed and their efficiency should be carefully demonstrated.

Methods

Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were applied to detect sepsis and monocyte/macrophage-related genes. Least absolute shrinkage and selection operator (LASSO) and random forest regression analyses were used in combination to screen out prognostic genes. Single-cell RNA sequence profiling was utilized to further verify the expression of these genes on a single cell level. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were also applied to verify the diagnostic value of the target biomarkers.

Results

The intersections of the genes detected by differential expression and WGCNA analyses identified 141 overlapping candidate genes that were closely related to sepsis and macrophages. The LASSO and random forest regression analyses further screened out 17 prognostic genes. Single-cell RNA sequencing analysis detected that FCGR1A and BCL2A1 might be potential biomarkers for sepsis diagnosis and the diagnostic efficacy of BCL2A1 was further validated by ROC curve and DCA.

Conclusions

It was revealed that BCL2A1 had good diagnostic and prognostic value for sepsis, and that it can be applied as a potential and novel biomarker for the management of the disease.

Key Signature Genes of Early Terminal Granulocytic Differentiation Distinguish Sepsis From Systemic Inflammatory Response Syndrome on Intensive Care Unit Admission

Infection can induce granulopoiesis. This process potentially contributes to blood gene classifiers of sepsis in systemic inflammatory response syndrome (SIRS) patients. This study aimed to identify signature genes of blood granulocytes from patients with sepsis and SIRS on intensive care unit (ICU) admission. CD15+ cells encompassing all stages of terminal granulocytic differentiation were analyzed. CD15 transcriptomes from patients with sepsis and SIRS on ICU admission and presurgical controls (discovery cohort) were subjected to differential gene expression and pathway enrichment analyses. Differential gene expression was validated by bead array in independent sepsis and SIRS patients (validation cohort). Blood counts of granulocyte precursors were determined by flow cytometry in an extension of the validation cohort. Despite similar transcriptional CD15 responses in sepsis and SIRS, enrichment of canonical pathways known to decline at the metamyelocyte stage (mitochondrial, lysosome, cell cycle, and proteasome) was associated with sepsis but not SIRS. Twelve of 30 validated genes, from 100 selected for changes in response to sepsis rather than SIRS, were endo-lysosomal. Revisiting the discovery transcriptomes revealed an elevated expression of promyelocyte-restricted azurophilic granule genes in sepsis and myelocyte-restricted specific granule genes in sepsis followed by SIRS. Blood counts of promyelocytes and myelocytes were higher in sepsis than in SIRS. Sepsis-induced granulopoiesis and signature genes of early terminal granulocytic differentiation thus provide a rationale for classifiers of sepsis in patients with SIRS on ICU admission. Yet, the distinction of this process from noninfectious tissue injury-induced granulopoiesis remains to be investigated.

The association between circulating neutrophil extracellular trap related biomarkers and retinal vein occlusion incidence: A case-control pilot study

Retinal vein occlusion (RVO) is the second most common retinal vascular disorders and causes visual damage in a large population. Neutrophil extracellular traps (NETs) formation (NETosis) is an important cause of vascular diseases, however, the association between NETs related biomarkers and RVO development remained unclear. In this pilot study, a total of 77 RVO cases and 48 controls were included between Jan 2020 and July 2020. Besides, the circulating levels of three NETs related markers, cell-free DNA (cfDNA), myeloperoxidase (MPO)-DNA and citrullinated histone H3 (H3Cit), were detected in all the participants and thus the association between NETosis and RVO incidence was analyzed. Advanced assays were conducted to investigate the inflammation and thrombosis related biomarkers in RVO cases with higher or lower NETs biomarkers. When the results were considered, it was found that NETs biomarkers, including cfDNA, MPO-DNA and H3Cit, were increased in the RVO cases comparing with the controls (P < 0.05). Through the receiver operating characteristic (ROC) analyses, we found that circulating NETs related biomarkers demonstrated potential diagnostic effects for RVO and the AUCs of plasma cfDNA, MPO-DNA and H3Cit were 0.859, 0.871 and 0.928, respectively (P < 0.001). Through analyzing the correlations between circulating NETs markers and RVO stages and durations, inflammatory markers as well as thrombotic indexes, it was found that NETs were related with the RVO subtypes, inflammatory status and thrombus formation. In conclusion, the plasma NETs remnants are significantly increased in RVO cases. Besides, advanced studies demonstrate that inflammation as well as thrombus formation might be involved in this association.