Monitoring immunomodulation in patients with sepsis

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

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

Transitions of blood immune endotypes and improved outcome by anakinra in COVID-19 pneumonia: an analysis of the SAVE-MORE randomized controlled trial

BACKGROUND

Endotype classification may guide immunomodulatory management of patients with bacterial and viral sepsis. We aimed to identify immune endotypes and transitions associated with response to anakinra (human interleukin 1 receptor antagonist) in participants in the SAVE-MORE trial.

METHODS

Adult patients hospitalized with radiological findings of PCR-confirmed severe pneumonia caused by SARS-CoV-2 and plasma-soluble urokinase plasminogen activator receptor levels of ≥ 6 ng/ml in the SAVE-MORE trial (NCT04680949) were characterized at baseline and days 4 and 7 of treatment using a previously defined 33-messenger RNA classifier to assign an immunological endotype in blood. Endpoints were changes in endotypes and progression to severe respiratory failure (SRF) associated with anakinra treatment.

RESULTS

At baseline, 23.2% of 393 patients were designated as inflammopathic, 41.1% as adaptive, and 35.7% as coagulopathic. Only 23.9% were designated as the same endotype at days 4 and 7 compared to baseline, while all other patients transitioned between endotypes. Anakinra-treated patients were more likely to remain in the adaptive endotype during 7-day treatment (24.4% vs. 9.9%; p < 0.001). Anakinra also protected patients with coagulopathic endotype at day 7 against SRF compared to placebo (27.8% vs. 55.9%; p = 0.013).

CONCLUSION

We identify an association between endotypes defined using blood transcriptome and anakinra therapy for COVID-19 pneumonia, with anakinra-treated patients shifting toward endotypes associated with a better outcome, mainly the adaptive endotype. Trial registration ClinicalTrials.gov, NCT04680949, December 23, 2020.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

T cell activation profiles can distinguish gram negative/positive bacterial sepsis and are associated with ICU discharge

Introduction

Sepsis is a life-threatening complication resulting from a dysregulated host response to a serious infection, of which bacteria are the most common cause. A rapid differentiation of the gram negative (G^-)/gram positive (G⁺) pathogens facilitates antibiotic treatment, which in turn improves patients' survival.

Methods

We performed a prospective, observational study of adult patients in intensive care unit (ICU) unit and underwent the analysis of peripheral blood lymphocyte subsets, cytokines and other clinical indexes. The enrolled 94 patients were divided into no infection group (n=28) and bacterial sepsis group (n=66), and the latter group was subdivided into G^- (n=46) and G⁺ (n=20) sepsis subgroups.

Results

The best immune biomarker which differentiated the diagnosis of G^- sepsis from G⁺ sepsis, included activation markers of CD69, human leukocyte antigen DR (HLA-DR) on CD3⁺CD8⁺T subset. The ratio of CD3⁺CD4⁺CD69⁺T/CD3⁺CD8⁺CD69⁺T (odds ratio (OR): 0.078(0.012,0.506), P = 0.008), PCT>0.53 ng/ml (OR: 9.31(1.36,63.58), P = 0.023), and CO₂CP<26.5 mmol/l (OR: 10.99(1.29, 93.36), P = 0.028) were predictive of G^- sepsis (versus G⁺ sepsis), and the area under the curve (AUC) was 0.947. Additionally, the ratio of CD3⁺CD4⁺CD69⁺T/CD3⁺CD8⁺CD69⁺T ≤ 0.2697 was an independent risk factor for poor ICU discharge in G^- sepsis patients (HR: 0.34 (0.13, 0.88), P=0.026).

Conclusion

We conclude that enhanced activation of T cells may regulate the excessive inflammatory response of G^- bacterial sepsis, and that T cell activation profiles can rapidly distinguish G^- sepsis from G⁺ sepsis and are associated with ICU discharge.

C-Terminal Fibronectin Exerts Beneficial Effects in Reducing Tissue Damage and Modulating Macrophage Function in a Murine Septic Model

Background

Fibronectin (FN) can improve organ function and slow the progression of sepsis, but full-length FN is hard to be exacted as a therapeutic.

Objective

This study aimed to investigate the beneficial effects of C-terminal heparin-binding domain polypeptide of FN (rhFNHC-36) in a cecal ligation and puncture (CLP)-mediated murine septic model and explore its regulatory effects on macrophages.

Methods

Mice were randomly assigned to four groups: unoperated control (Normal), sham operation control (Sham), CLP-operation with intravenous injection of phosphate-buffered saline (CLP+PBS), and CLP-operation with rhFNHC-36 treatment (CLP+rhFNHC-36). Blood and abdominal fluid samples were subjected to bacterial colony formation assays. Organs (liver, spleen, and lung) were undergone histopathological analyses and/or weighed to obtain organ indices. Serum interleukin-6 (IL-6) levels, nitric oxide (NO) release from isolated abdominal macrophages, and chemotactic effect of macrophages were measured with commercial kits. Surface programmed death ligand 1 (PD-L1) expression on macrophages was measured by flow cytometry.

Results

Mice in the CLP+PBS group showed a lower survival rate than that in the CLP+rhFNHC-36 group. Improved survival was associated with better clearance of bacterial pathogens, as evidenced by colony formation assays. The CLP-induced decrease in thymus and spleen indices was attenuated by rhFNHC-36 treatments. rhFNHC-36 alleviated sepsis-associated tissue damage in liver, spleen, and lung. CLP-mediated increases in plasma IL-6 levels were reversed by rhFNHC-36 treatment. NO levels in peritoneal macrophages after lipopolysaccharides (LPS)-stimulation in the CLP+rhFNHC-36 group were lower than that in the CLP+PBS group. Notably, macrophages from the CLP+rhFNHC-36 group retained better chemotaxis ability. After LPS challenge, these macrophages had a reduced percentage of PD-L1-positive cells compared to those in the CLP+PBS group.

Conclusion

rhFNHC-36 improved survival of mice with CLP-induced sepsis by reducing tissue damage and modulating macrophage function. Our work provides critical insight for developing FN-based and macrophages-targeted therapeutics for treating sepsis.

Increased monocyte distribution width in COVID-19 and sepsis arises from a complex interplay of altered monocyte cellular size and subset frequency

Introduction

Monocyte distribution width (MDW), a parameter generated alongside full blood counts (FBC) in new‐generation haematology analysers, has been proposed as a diagnostic test for severe infection/sepsis. It represents the standard deviation (SD) of the monocyte mean volume (MMV).

Methods

This study aimed to compare monocyte volumetric parameters retrieved by the UniCel DxH 900 haematology analyser (MMV and MDW) against corresponding parameters from the same sample measured using flow cytometry (forward scatter [FSC] mean and SD) in combination with phenotypic characterization of monocyte subtypes. We analysed blood samples from healthy individuals (n = 11) and patients with conditions associated with elevated MDW: sepsis (n = 26) and COVID‐19 (n = 15).

Results

Between‐instrument comparisons of monocyte volume parameters (MMV vs. FSC‐mean) showed relatively good levels of correlation, but comparisons across volume variability parameters (MDW vs. FSC‐SD) were poor. Stratification on sample type revealed this lack of correlation only within the sepsis group. Flow cytometry analysis revealed that in healthy controls intermediate monocytes are the largest and non‐classical the smallest cells. In each disease state, however, each monocyte subset undergoes different changes in volume and frequency that together determine the overall configuration of the monocyte population. Increased MDW was associated with reduced classical monocyte frequency and increased intermediate monocyte size. In COVID‐19, the range of monocyte sizes (smallest to largest) reduced, whereas in sepsis it increased.

Conclusion

Increased MDW in COVID‐19 and sepsis has no single flow cytometric phenotypic correlate. It represents—within a single value—the delicate equipoise between monocyte subset frequency and size.

Vaspin Alleviates Sepsis-Induced Cardiac Injury and Cardiac Inflammation by Inhibiting Kallikrein 7 in Mice

Background

Vaspin is an important adipokine that is involved in cardiovascular diseases. This study is aimed at investigating whether vaspin participates in sepsis-induced cardiac injury and explored the possible mechanism.

Methods

First, cecal ligation and puncture (CLP) and lipopolysaccharide (LPS) were used to establish a mouse model of sepsis, and cardiac vaspin expression was examined. In addition, after pretreatment with vaspin or phosphate-buffered saline (PBS), wild-type (WT) mice underwent CLP to establish a septic model and received sham as a control. Finally, WT mice and kallikrein 7 (KLK7-/-) mice were underwent CLP with or without vaspin pretreatment.

Results

Mice that underwent CLP and were administered LPS exhibited increased vaspin expression in both the heart and serum compared with sham- or saline-treated mice. In CLP mice, pretreatment with vaspin reduced mortality and alleviated the expression of cardiac injury markers and cardiac dysfunction. In addition, vaspin reduced the cardiac levels of CD45+ cells and CD68+ cells, alleviated the cardiac inflammatory response, and reduced cardiomyocyte apoptosis. The protective effects of vaspin on CLP mice were masked by the deletion of KLK7, which was demonstrated to be a downstream signal of vaspin.

Conclusions

Vaspin alleviates cardiac inflammation and plays a protective role in sepsis-induced cardiac injury by reducing KLK7 expression.