Inflammatory biomarkers to predict the prognosis of acute bacterial and viral infections

Biomarkers in sepsis

Sepsis is a life-threatening condition characterized by dysregulated host response to infection leading to organ dysfunction. Despite advances in understanding its pathology, sepsis remains a global health concern and remains a major contributor to mortality. Timely identification is crucial for improving clinical outcomes, as delayed treatment significantly impacts survival. Accordingly, biomarkers play a pivotal role in diagnosis, risk stratification, and management. This review comprehensively discusses various biomarkers in sepsis and their potential application in antimicrobial stewardship and risk assessment. Biomarkers such as white blood cell count, neutrophil to lymphocyte ratio, erythrocyte sedimentation rate, C-reactive protein, interleukin-6, presepsin, and procalcitonin have been extensively studied for their diagnostic and prognostic value as well as in guiding antimicrobial therapy. Furthermore, this review explores the role of biomarkers in risk stratification, emphasizing the importance of identifying high-risk patients who may benefit from specific therapeutic interventions. Moreover, the review discusses the emerging field of transcriptional diagnostics and metagenomic sequencing. Advances in sequencing have enabled the identification of host response signatures and microbial genomes, offering insight into disease pathology and aiding species identification. In conclusion, this review provides a comprehensive overview of the current understanding and future directions of biomarker-based approaches in sepsis diagnosis, management, and personalized therapy.

Peripheral PD-1+NK cells could predict the 28-day mortality in sepsis patients

Background

Unbalanced inflammatory response is a critical feature of sepsis, a life-threatening condition with significant global health burdens. Immune dysfunction, particularly that involving different immune cells in peripheral blood, plays a crucial pathophysiological role and shows early warning signs in sepsis. The objective is to explore the relationship between sepsis and immune subpopulations in peripheral blood, and to identify patients with a higher risk of 28-day mortality based on immunological subtypes with machine-learning (ML) model.

Methods

Patients were enrolled according to the sepsis-3 criteria in this retrospective observational study, along with age- and sex-matched healthy controls (HCs). Data on clinical characteristics, laboratory tests, and lymphocyte immunophenotyping were collected. XGBoost and k-means clustering as ML approaches, were employed to analyze the immune profiles and stratify septic patients based on their immunological subtypes. Cox regression survival analysis was used to identify potential biomarkers and to assess their association with 28-day mortality. The accuracy of biomarkers for mortality was determined by the area under the receiver operating characteristic (ROC) curve (AUC) analysis.

Results

The study enrolled 100 septic patients and 89 HCs, revealing distinct lymphocyte profiles between the two groups. The XGBoost model discriminated sepsis from HCs with an area under the receiver operating characteristic curve of 1.0 and 0.99 in the training and testing set, respectively. Within the model, the top three highest important contributions were the percentage of CD38+CD8+T cells, PD-1+NK cells, HLA-DR+CD8+T cells. Two clusters of peripheral immunophenotyping of septic patients by k-means clustering were conducted. Cluster 1 featured higher proportions of PD1+ NK cells, while cluster 2 featured higher proportions of naïve CD4+T cells. Furthermore, the level of PD-1+NK cells was significantly higher in the non-survivors than the survivors (15.1% vs 8.6%, P<0.01). Moreover, the levels of PD1+ NK cells combined with SOFA score showed good performance in predicting the 28-day mortality in sepsis (AUC=0.91,95%CI 0.82-0.99), which is superior to PD1+ NK cells only(AUC=0.69, sensitivity 0.74, specificity 0.64, cut-off value of 11.25%). In the multivariate Cox regression, high expression of PD1+ NK cells proportion was related to 28-day mortality (aHR=1.34, 95%CI 1.19 to 1.50; P<0.001).

Conclusion

The study provides novel insights into the association between PD1+NK cell profiles and prognosis of sepsis. Peripheral immunophenotyping could potentially stratify the septic patients and identify those with a high risk of 28-day mortality.

Regulation of proteostasis and innate immunity via mitochondria-nuclear communication

Mitochondria are perhaps best known as the "powerhouse of the cell" for their role in ATP production required for numerous cellular activities. Mitochondria have emerged as an important signaling organelle. Here, we first focus on signaling pathways mediated by mitochondria-nuclear communication that promote protein homeostasis (proteostasis). We examine the mitochondrial unfolded protein response (UPRmt) in C. elegans, which is regulated by a transcription factor harboring both a mitochondrial- and nuclear-targeting sequence, the integrated stress response in mammals, as well as the regulation of chromatin by mitochondrial metabolites. In the second section, we explore the role of mitochondria-to-nuclear communication in the regulation of innate immunity and inflammation. Perhaps related to their prokaryotic origin, mitochondria harbor molecules also found in viruses and bacteria. If these molecules accumulate in the cytosol, they elicit the same innate immune responses as viral or bacterial infection.

Searching for New Biomarkers to Assess COVID-19 Patients: A Pilot Study

During the initial diagnosis of urgent medical conditions, which include acute infectious diseases, it is important to assess the severity of the patient's clinical state as quickly as possible. Unlike individual biochemical or physiological indicators, derived indices make it possible to better characterize a complex syndrome as a set of symptoms, and therefore quickly take a set of adequate measures. Recently, we reported on novel diagnostic indices containing butyrylcholinesterase (BChE) activity, which is decreased in COVID-19 patients. Also, in these patients, the secretion of von Willebrand factor (vWF) increases, which leads to thrombosis in the microvascular bed. The objective of this study was the determination of the concentration and activity of vWF in patients with COVID-19, and the search for new diagnostic indices. One of the main objectives was to compare the prognostic values of some individual and newly derived indices. Patients with COVID-19 were retrospectively divided into two groups: survivors (n = 77) and deceased (n = 24). According to clinical symptoms and computed tomography (CT) results, the course of disease was predominantly moderate in severity. The first blood sample (first point) was taken upon admission to the hospital, the second sample (second point)-within 4-6 days after admission. Along with the standard spectrum of biochemical indicators, BChE activity (BChEa or BChEb for acetylthiocholin or butyrylthiocholin, respectively), malondialdehyde (MDA), and vWF analysis (its antigen level, AGFW, and its activity, ActWF) were determined and new diagnostic indices were derived. The pooled sensitivity, specificity, and area under the receiver operating curve (AUC), as well as Likelihood ratio (LR) and Odds ratio (OR) were calculated. The level of vWF antigen in the deceased group was 1.5-fold higher than the level in the group of survivors. Indices that include vWF antigen levels are superior to indices using vWF activity. It was found that the index [Urea] × [AGWF] × 1000/(BChEb × [ALB]) had the best discriminatory power to predict COVID-19 mortality (AUC = 0.91 [0.83, 1.00], p < 0.0001; OR = 72.0 [7.5, 689], p = 0.0002). In addition, [Urea] × 1000/(BChEb × [ALB]) was a good predictor of mortality (AUC = 0.95 [0.89, 1.00], p < 0.0001; OR = 31.5 [3.4, 293], p = 0.0024). The index [Urea] × [AGWF] × 1000/(BChEb × [ALB]) was the best predictor of mortality associated with COVID-19 infection, followed by [Urea] × 1000/(BChEb × [ALB]). After validation in a subsequent cohort, these two indices could be recommended for diagnostic laboratories.

Targeting the host response in sepsis: current approaches and future evidence

Sepsis, a dysregulated host response to infection characterized by organ failure, is one of the leading causes of death worldwide. Disbalances of the immune response play an important role in its pathophysiology. Patients may develop simultaneously or concomitantly states of systemic or local hyperinflammation and immunosuppression. Although a variety of effective immunomodulatory treatments are generally available, attempts to inhibit or stimulate the immune system in sepsis have failed so far to improve patients' outcome. The underlying reason is likely multifaceted including failure to identify responders to a specific immune intervention and the complex pathophysiology of organ dysfunction that is not exclusively caused by immunopathology but also includes dysfunction of the coagulation system, parenchymal organs, and the endothelium. Increasing evidence suggests that stratification of the heterogeneous population of septic patients with consideration of their host response might led to treatments that are more effective. The purpose of this review is to provide an overview of current studies aimed at optimizing the many facets of host response and to discuss future perspectives for precision medicine approaches in sepsis.

Proteomic Profiling of Early Secreted Proteins in Response to Lipopolysaccharide-Induced Vascular Endothelial Cell EA.hy926 Injury

Sepsis is a crucial public health problem with a high mortality rate caused by a dysregulated host immune response to infection. Vascular endothelial cell injury is an important hallmark of sepsis, which leads to multiple organ failure and death. Early biomarkers to diagnose sepsis may provide early intervention and reduce risk of death. Damage-associated molecular patterns (DAMPs) are host nuclear or cytoplasmic molecules released from cells following tissue damage. We postulated that DAMPs could potentially be a novel sepsis biomarker. We used an in vitro model to determine suitable protein-DAMPs biomarkers for early sepsis diagnosis. Low and high lipopolysaccharide (LPS) doses were used to stimulate the human umbilical vein endothelial cell line EA.hy926 for 24, 48, and 72 h. Results showed that cell viability was reduced in both dose-dependent and time-dependent manners. Cell injury was corroborated by a significant increase in lactate dehydrogenase (LDH) activity within 24 h in cell-conditioned medium. Secreted protein-DAMPs in the supernatant, collected at different time points within 24 h, were characterized using shotgun proteomics LC-MS/MS analysis. Results showed that there were 2233 proteins. Among these, 181 proteins from the LPS-stimulated EA.hy926 at 1, 12, and 24 h were significantly different from those of the control. Twelve proteins were up-regulated at all three time points. Furthermore, a potential interaction analysis of predominant DAMPs-related proteins using STITCH 5.0 revealed the following associations with pathways: response to stress; bacterium; and LPS (GO:0080134; 0009617; 0032496). Markedly, alpha-2-HS-glycoprotein (AHSG or fetuin-A) and lactotransferrin (LTF) potentially presented since the first hour of LPS stimulation, and were highly up-regulated at 24 h. Taken together, we reported proteomic profiling of vascular endothelial cell-specific DAMPs in response to early an in vitro LPS stimulation, suggesting that these early damage-response protein candidates could be novel early biomarkers associated with sepsis.

Detection of infections by computerized capture of peaks in longitudinally measured C-reactive protein levels

We developed four algorithms for the automatic capture of C-reactive protein (CRP) peaks in 296 adult patients with acute myeloid leukemia who had bloodstream infection (BSI) episodes, negative blood cultures (BCs) or possible infections where no BCs were performed. The algorithms detected CRP peaks for 418-446 of the 586 documented BSI episodes (71.3-76.1%) and 2714-3118 of the 4382 negative BCs (61.9-71.2%). The four algorithms captured 382-789 CRP peaks in which there were neither BSI episodes nor negative BCs. We conclude that automatic capture of CRP peaks is a tool for the monitoring of BSI episodes and possibly other infections in patients with acute myeloid leukemia.