The pathophysiology of sepsis and precision-medicine-based immunotherapy

Impact of P2Y12 inhibitors on clinical outcomes in sepsis-3 patients receiving aspirin: a propensity score matched analysis

BACKGROUND

Sepsis is a life-threatening disease accompanied by disorders of the coagulation and immune systems. P2Y12 inhibitors, widely used for arterial thrombosis prevention and treatment, possess recently discovered anti-inflammatory properties, raising potential for improved sepsis prognosis.

METHOD

We conducted a retrospective analysis using the data from Medical Information Mart for Intensive Care-IV database. Patients were divided into an aspirin-alone group versus a combination group based on the use of a P2Y12 inhibitor or not. Differences in 30-day mortality, length of stay (LOS) in intensive care unit (ICU), LOS in hospital, bleeding events and thrombotic events were compared between the two groups.

RESULT

A total of 1701 pairs of matched patients were obtained by propensity score matching. We found that no statistically significant difference in 30-day mortality in aspirin-alone group and combination group (15.3% vs. 13.7%, log-rank p = 0.154). In addition, patients received P2Y12 inhibitors had a higher incidence of gastrointestinal bleeding (0.5% vs. 1.6%, p = 0.004) and ischemic stroke (1.7% vs. 2.9%, p = 0.023), despite having a shorter LOS in hospital (11.1 vs. 10.3, days, p = 0.043). Cox regression showed that P2Y12 inhibitor was not associated with 30-day mortality (HR = 1.14, 95% CI 0.95-1.36, p = 0.154).

CONCLUSION

P2Y12 inhibitors did not provide a survival benefit for patients with sepsis 3 and even led to additional adverse clinical outcomes.

Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes

Our limited understanding of the pathophysiological mechanisms that operate during sepsis is an obstacle to rational treatment and clinical trial design. There is a critical lack of data from low- and middle-income countries where the sepsis burden is increased which inhibits generalized strategies for therapeutic intervention. Here we perform RNA sequencing of whole blood to investigate longitudinal host response to sepsis in a Ghanaian cohort. Data dimensional reduction reveals dynamic gene expression patterns that describe cell type-specific molecular phenotypes including a dysregulated myeloid compartment shared between sepsis and COVID-19. The gene expression signatures reported here define a landscape of host response to sepsis that supports interventions via targeting immunophenotypes to improve outcomes.

Clinical biomarker profiles reveals gender differences and mortality factors in sepsis

Background

Sepsis is a major contributor to global morbidity and mortality, affecting millions each year. Notwithstanding the decline in sepsis incidence and mortality over decades, gender disparities in sepsis outcomes persist, with research suggesting higher mortality rates in males.

Methods

This retrospective study aims to delineate gender-specific clinical biomarker profiles impacting sepsis progression and mortality by examining sepsis cases and related clinical data from the past three years. Propensity score matching was used to select age-matched healthy controls for comparison.

Results

Among 265 sepsis patients, a significantly higher proportion were male (60.8%, P<0.001). While mortality did not significantly differ by gender, deceased patients were significantly older (mean 69 vs 43 years, P=0.003), more likely to have hypertension (54% vs 25%, P=0.019), and had higher SOFA scores (mean ~10 vs 4, P<0.01) compared to survivors. Principal Component Analysis (PCA) showed clear separation between sepsis patients and healthy controls. 48 serum biomarkers were significantly altered in sepsis, with Triiodothyronine, Apolipoprotein A, and Serum cystatin C having the highest diagnostic value by ROC analysis. Gender-stratified comparisons identified male-specific (e.g. AFP, HDLC) and female-specific (e.g. Rheumatoid factor, Interleukin-6) diagnostic biomarkers. Deceased patients significantly differed from survivors, with 22 differentially expressed markers; Antithrombin, Prealbumin, HDL cholesterol, Urea nitrogen and Hydroxybutyrate had the highest diagnostic efficiency for mortality.

Conclusion

These findings enhance our understanding of gender disparities in sepsis and may guide future therapeutic strategies. Further research is warranted to validate these biomarker profiles and investigate the molecular mechanisms underlying these gender differences in sepsis outcomes.

Use of Immune Profiling Panel to assess the immune response of septic patients for prediction of worsening as a composite endpoint

Sepsis induces intense, dynamic and heterogeneous host response modulations. Despite improvement of patient management, the risk of mortality and healthcare-associated infections remains high. Treatments to counterbalance immune response are under evaluation, but effective biomarkers are still lacking to perform patient stratification. The design of the present study was defined to alleviate the limitations of existing literature: we selected patients who survived the initial hyperinflammatory response and are still hospitalized at day 5-7 after ICU admission. Using the Immune Profiling Panel (IPP), a fully automated RT-qPCR multiplex prototype, we optimized a machine learning model combining the IPP gene expression levels for the identification of patients at high risk of worsening, a composite endpoint defined as death or secondary infection, within one week after sampling. This was done on 332 sepsis patients selected from two retrospective studies. The IPP model identified a high-risk group comprising 30% of patients, with a significant increased proportion of worsening events at day 28 compared to the low-risk group (49% vs. 28%, respectively). These preliminary results underline the potential clinical application of IPP for sepsis patient stratification in a personalized medicine perspective, that will be confirmed in a larger prospective multicenter study.

Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients

Sepsis is characterized by a dysfunctional host response to infection culminating in life-threatening organ failure that requires complex patient management and rapid intervention. Timely diagnosis of the underlying cause of sepsis is crucial, and identifying those at risk of complications and death is imperative for triaging treatment and resource allocation. Here, we explored the potential of explainable machine learning models to predict mortality and causative pathogen in sepsis patients. By using a modelling pipeline employing multiple feature selection algorithms, we demonstrate the feasibility of identifying integrative patterns from clinical parameters, plasma biomarkers, and extensive phenotyping of blood immune cells. While no single variable had sufficient predictive power, models that combined five and more features showed a macro area under the curve (AUC) of 0.85 to predict 90-day mortality after sepsis diagnosis, and a macro AUC of 0.86 to discriminate between Gram-positive and Gram-negative bacterial infections. Parameters associated with the cellular immune response contributed the most to models predictive of 90-day mortality, most notably, the proportion of T cells among PBMCs, together with expression of CXCR3 by CD4+ T cells and CD25 by mucosal-associated invariant T (MAIT) cells. Frequencies of Vδ2+ γδ T cells had the most profound impact on the prediction of Gram-negative infections, alongside other T-cell-related variables and total neutrophil count. Overall, our findings highlight the added value of measuring the proportion and activation patterns of conventional and unconventional T cells in the blood of sepsis patients in combination with other immunological, biochemical, and clinical parameters.

Epirubicin for the Treatment of Sepsis and Septic Shock (EPOS-1): study protocol for a randomised, placebo-controlled phase IIa dose-escalation trial

INTRODUCTION

Sepsis remains the major cause of death among hospitalised patients in intensive care. While targeting sepsis-causing pathogens with source control or antimicrobials has had a dramatic impact on morbidity and mortality of sepsis patients, this strategy remains insufficient for about one-third of the affected individuals who succumb. Pharmacological targeting of mechanisms that reduce sepsis-defining organ dysfunction may be beneficial. When given at low doses, the anthracycline epirubicin promotes tissue damage control and lessens the severity of sepsis independently of the host-pathogen load by conferring disease tolerance to infection. Since epirubicin at higher doses can be myelotoxic, a first dose-response trial is necessary to assess the potential harm of this drug in this new indication.

METHODS AND ANALYSIS

Epirubicin for the Treatment of Sepsis and Septic Shock-1 is a randomised, double-blind, placebo-controlled phase 2 dose-escalation phase IIa clinical trial to assess the safety of epirubicin as an adjunctive in patients with sepsis. The primary endpoint is the 14-day myelotoxicity. Secondary and explorative outcomes include 30-day and 90-day mortality, organ dysfunction, pharmacokinetic/pharmacodynamic (PK/PD) and cytokine release. Patients will be randomised in three consecutive phases. For each study phase, patients are randomised to one of the two study arms (epirubicin or placebo) in a 4:1 ratio. Approximately 45 patients will be recruited. Patients in the epirubicin group will receive a single dose of epirubicin (3.75, 7.5 or 15 mg/m2 depending on the study phase. After each study phase, a data and safety monitoring board will recommend continuation or premature stopping of the trial. The primary analyses for each dose level will report the proportion of myelotoxicity together with a 95% CI. A potential dose-toxicity association will be analysed using a logistic regression model with dose as a covariate. All further analyses will be descriptive.

ETHICS AND DISSEMINATION

The protocol is approved by the German Federal Institute for Drugs and Medical Devices. The results will be submitted for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT05033808.

AQP3 and AQP9-Contrary Players in Sepsis?

Sepsis involves an immunological systemic response to a microbial pathogenic insult, leading to a cascade of interconnected biochemical, cellular, and organ-organ interaction networks. Potential drug targets can depict aquaporins, as they are involved in immunological processes. In immune cells, AQP3 and AQP9 are of special interest. In this study, we tested the hypothesis that these aquaporins are expressed in the blood cells of septic patients and impact sepsis survival. Clinical data, routine laboratory parameters, and blood samples from septic patients were analyzed on day 1 and day 8 after sepsis diagnosis. AQP expression and cytokine serum concentrations were measured. AQP3 mRNA expression increased over the duration of sepsis and was correlated with lymphocyte count. High AQP3 expression was associated with increased survival. In contrast, AQP9 expression was not altered during sepsis and was correlated with neutrophil count, and low levels of AQP9 were associated with increased survival. Furthermore, AQP9 expression was an independent risk factor for sepsis lethality. In conclusion, AQP3 and AQP9 may play contrary roles in the pathophysiology of sepsis, and these results suggest that AQP9 may be a novel drug target in sepsis and, concurrently, a valuable biomarker of the disease.