Bench-to-bedside review: future novel diagnostics for sepsis - a systems biology approach

Role of diagnostic tests for sepsis in children: a review

Paediatric sepsis has a significant global impact and highly heterogeneous clinical presentation. The clinical pathway encompasses recognition, escalation and de-escalation. In each aspect, diagnostics have a fundamental influence over outcomes in children. Biomarkers can aid in creating a larger low-risk group of children from those in the clinical grey area who would otherwise receive antibiotics 'just in case'. Current biomarkers include C reactive protein and procalcitonin, which are limited in their clinical use to guide appropriate and rapid treatment. Biomarker discovery has focused on single biomarkers, which, so far, have not outperformed current biomarkers, as they fail to recognise the complexity of sepsis. The identification of multiple host biomarkers that may form a panel in a clinical test has the potential to recognise the complexity of sepsis and provide improved diagnostic performance. In this review, we discuss novel biomarkers and novel ways of using existing biomarkers in the assessment and management of sepsis along with the significant challenges in biomarker discovery at present. Validation of biomarkers is made less meaningful due to methodological heterogeneity, including variations in sepsis diagnosis, biomarker cut-off values and patient populations. Therefore, the utilisation of platform studies is necessary to improve the efficiency of biomarkers in clinical practice.

Combined metabolomic and proteomic analysis of sepsis related acute liver injury and its pathogenesis research

BACKGROUND

Sepsis-induced acute liver injury is common in patients in intensive care units. However, the exact mechanism of this condition remains unclear. The purpose of this study was to investigate the roles and mechanisms of proteins and metabolites in the liver tissue of mice after sepsis and elucidate the molecular biological mechanisms of sepsis-related liver injury.

METHODS

First, a lipopolysaccharide (LPS)-induced sepsis mouse model was established. Then, according to alanine aminotransferase (ALT) and aspartate aminotransferase (AST) detection in mouse serum and liver histopathological examination (HE) staining, the septic mice were divided into two groups: acute liver injury after sepsis and nonacute liver injury after sepsis. Metabolomics and proteomic analyses were performed on the liver tissues of the two groups of mice to identify significantly different metabolites and proteins. The metabolomics and proteomics results were further analysed to identify the biological indicators and pathogenesis related to the occurrence and development of sepsis-related acute liver injury at the protein and metabolite levels.

RESULTS

A total of 14 differentially expressed proteins and 46 differentially expressed metabolites were identified. Recombinant Erythrocyte Membrane Protein Band 4.2 (Epb42) and adenosine diphosphate (ADP) may be the key proteins and metabolites responsible for sepsis-related acute liver injury, according to the correlation analysis of proteomics and metabolomics. The expression of the differential protein Epb42 was further verified by western blot (WB) detection.

CONCLUSIONS

Our study suggests that the differential protein Epb42 may be key proteins causing sepsis-associated acute liver injury, providing new and valuable information on the possible mechanism of sepsis-associated acute liver injury.

New Insights in Immunometabolism in Neonatal Monocytes and Macrophages in Health and Disease

It is well established that the neonatal immune system is different from the adult immune system. A major task of the neonatal immune system is to bridge the achievement of tolerance towards harmless antigens and commensal bacteria while providing protection against pathogens. This is highly important because neonates are immunologically challenged directly after birth by a rigorous change from a semi-allogeneic sterile environment into a world rich with microbes. A so called disease tolerogenic state is typical for neonates and is anticipated to prevent immunopathological damage potentially at the cost of uncontrolled pathogen proliferation. As a consequence, neonates are more susceptible than adults to life-threatening infections. At the basis of a well-functioning immune response, both for adults and neonates, innate immune cells such as monocytes and monocyte-derived macrophages play an essential role. A well-responsive monocyte will alter its cellular metabolism to subsequently induce certain immune effector function, a process which is called immunometabolism. Immunometabolism has received extensive attention in the last decade; however, it has not been broadly studied in neonates. This review focuses on carbohydrate metabolism in monocytes and macrophages in neonates. We will exhibit pathways involving glycolysis, the tricarboxylic acid (TCA) cycle and oxidative phosphorylation and their role in shaping neonates' immune systems to a favorable tolerogenic state. More insight into these pathways will elucidate potential treatments targets in life-threatening conditions including neonatal sepsis or expose potential targets which can be used to induce tolerance in conditions where tolerance is harmfully impaired such as in autoimmune diseases.

A hypoxia- and lactate metabolism-related gene signature to predict prognosis of sepsis: discovery and validation in independent cohorts

BACKGROUND

High throughput gene expression profiling is a valuable tool in providing insight into the molecular mechanism of human diseases. Hypoxia- and lactate metabolism-related genes (HLMRGs) are fundamentally dysregulated in sepsis and have great predictive potential. Therefore, we attempted to build an HLMRG signature to predict the prognosis of patients with sepsis.

METHODS

Three publicly available transcriptomic profiles of peripheral blood mononuclear cells from patients with sepsis (GSE65682, E-MTAB-4421 and E-MTAB-4451, total n = 850) were included in this study. An HLMRG signature was created by employing Cox regression and least absolute shrinkage and selection operator estimation. The CIBERSORT method was used to analyze the abundances of 22 immune cell subtypes based on transcriptomic data. Metascape was used to investigate pathways related to the HLMRG signature.

RESULTS

We developed a prognostic signature based on five HLMRGs (ERO1L, SIAH2, TGFA, TGFBI, and THBS1). This classifier successfully discriminated patients with disparate 28-day mortality in the discovery cohort (GSE65682, n = 479), and consistent results were observed in the validation cohort (E-MTAB-4421 plus E-MTAB-4451, n = 371). Estimation of immune infiltration revealed significant associations between the risk score and a subset of immune cells. Enrichment analysis revealed that pathways related to antimicrobial immune responses, leukocyte activation, and cell adhesion and migration were significantly associated with the HLMRG signature.

CONCLUSIONS

Identification of a prognostic signature suggests the critical role of hypoxia and lactate metabolism in the pathophysiology of sepsis. The HLMRG signature can be used as an efficient tool for the risk stratification of patients with sepsis.

Machine learning approaches to the human metabolome in sepsis identify metabolic links with survival

Background

Metabolic predictors and potential mediators of survival in sepsis have been incompletely characterized. We examined whether machine learning (ML) tools applied to the human plasma metabolome could consistently identify and prioritize metabolites implicated in sepsis survivorship, and whether these methods improved upon conventional statistical approaches.

Methods

Plasma gas chromatography–liquid chromatography mass spectrometry quantified 411 metabolites measured ≤ 72 h of ICU admission in 60 patients with sepsis at a single center (Brigham and Women’s Hospital, Boston, USA). Seven ML approaches were trained to differentiate survivors from non-survivors. Model performance predicting 28 day mortality was assessed through internal cross-validation, and innate top-feature (metabolite) selection and rankings were compared across the 7 ML approaches and with conventional statistical methods (logistic regression). Metabolites were consensus ranked by a summary, ensemble ML ranking procedure weighing their contribution to mortality risk prediction across multiple ML models.

Results

Median (IQR) patient age was 58 (47, 62) years, 45% were women, and median (IQR) SOFA score was 9 (6, 12). Mortality at 28 days was 42%. The models’ specificity ranged from 0.619 to 0.821. Partial least squares regression-discriminant analysis and nearest shrunken centroids prioritized the greatest number of metabolites identified by at least one other method. Penalized logistic regression demonstrated top-feature results that were consistent with many ML methods. Across the plasma metabolome, the 13 metabolites with the strongest linkage to mortality defined through an ensemble ML importance score included lactate, bilirubin, kynurenine, glycochenodeoxycholate, phenylalanine, and others. Four of these top 13 metabolites (3-hydroxyisobutyrate, indoleacetate, fucose, and glycolithocholate sulfate) have not been previously associated with sepsis survival. Many of the prioritized metabolites are constituents of the tryptophan, pyruvate, phenylalanine, pentose phosphate, and bile acid pathways.

Conclusions

We identified metabolites linked with sepsis survival, some confirming prior observations, and others representing new associations. The application of ensemble ML feature-ranking tools to metabolomic data may represent a promising statistical platform to support biologic target discovery.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40635-022-00445-8.

Comparison of the diagnostic accuracy of monocyte distribution width and procalcitonin in sepsis cases in the emergency department: a prospective cohort study

Background

Early diagnosis and treatment of patients with sepsis reduce mortality significantly. In terms of exploring new diagnostic tools of sepsis, monocyte distribution width (MDW), as part of the white blood cell (WBC) differential count, was first reported in 2017. MDW greater than 20 and abnormal WBC count together provided a satisfactory accuracy and was proposed as a novel diagnostic tool of sepsis. This study aimed to compare MDW and procalcitonin (PCT)’s diagnostic accuracy on sepsis in the emergency department.

Methods

This was a single-center prospective cohort study. Laboratory examinations including complete blood cell and differentiation count (CBC/DC), MDW, PCT were obtained while arriving at the ED. We divided patients into non-infection, infection without systemic inflammatory response syndrome (SIRS), infection with SIRS, and sepsis-3 groups. This study’s primary outcome is the sensitivity and specificity of MDW, PCT, and MDW + WBC in differentiating septic and non-septic patients. In addition, the cut-off value for MDW was established to maximize sensitivity at an optimal level of specificity.

Results

From May 2019 to September 2020, 402 patients were enrolled for data analysis. Patient number in each group was: non-infection 64 (15.9%), infection without SIRS 82 (20.4%), infection with SIRS 202 (50.2%), sepsis-3 15 (7.6%). The AUC of MDW, PCT, and MDW + WBC to predict infection with SIRS was 0.753, 0.704, and 0.784, respectively (p < 0.01). The sensitivity, specificity, PPV, and NPV of MDW using 20 as the cutoff were 86.4%, 54.2%, 76.4%, and 70%, compared to 32.9%, 88%, 82.5%, and 43.4% using 0.5 ng/mL as the PCT cutoff value. On combing MDW and WBC count, the sensitivity and NPV further increased to 93.4% and 80.3%, respectively. In terms of predicting sepsis-3, the AUC of MDW, PCT, and MDW + WBC was 0.72, 0.73, and 0.70, respectively. MDW, using 20 as cutoff, exhibited sensitivity, specificity, PPV, and NPV of 90.6%, 37.1%, 18.7%, and 96.1%, respectively, compared to 49.1%, 78.6%, 26.8%, and 90.6% when 0.5 ng/mL PCT was used as cutoff.

Conclusions

In conclusion, MDW is a more sensitive biomarker than PCT in predicting infection-related SIRS and sepsis-3 in the ED. MDW < 20 shows a higher NPV to exclude sepsis-3. Combining MDW and WBC count further improves the accuracy in predicting infection with SIRS but not sepsis-3.

Trial registration The study was retrospectively registered to the ClinicalTrial.gov (NCT04322942) on March 26th, 2020.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06999-4.

Endothelial Damage in Sepsis: The Importance of Systems Biology

The early diagnosis and appropriate stratification of sepsis continues to be one of the most important challenges in modern medicine. Single isolated biomarkers have not been enough to improve diagnostic and prognostic strategies and to progress toward therapeutic goals. The information generated by the human genome project has allowed a more holistic approach to the problem. The integration of genomics, transcriptomics, proteomics and metabolomics in sepsis has allowed us to progress in the knowledge of new pathways which are pathophysiologically involved in this disease. Thus, we have understood the importance of and complex interaction between the inflammatory response and the endothelium. Understanding the role of important parts of the microcirculation, such as the endothelial glycocalyx and its interaction with the inflammatory response, has provided early recognition elements for clinical practice that allow the rational use of traditional medical interventions in sepsis. This comprehensive approach, which differs from the classical mechanistic approach, uses systems biology to increase the diagnostic and prognostic spectrum of endothelial damage biomarkers in sepsis, and to provide information on new pathways involved in the pathophysiology of the disease. This, in turn, provides tools for perfecting traditional medical interventions, using them at the appropriate times according to the disease's pathophysiological context, while at the same time discovering new and improved therapeutic alternatives. We have the challenge of transferring this ideal scenario to our daily clinical practice to improve our patients' care. The purpose of this article is to provide a general description of the importance of systems biology in integrating the complex interaction between the endothelium and the inflammatory response in sepsis.

Evaluation of the Molecular Mechanisms of Sepsis Using Proteomics

Sepsis is a complex syndrome promoted by pathogenic and host factors; it is characterized by dysregulated host responses and multiple organ dysfunction, which can lead to death. However, its underlying molecular mechanisms remain unknown. Proteomics, as a biotechnology research area in the post-genomic era, paves the way for large-scale protein characterization. With the rapid development of proteomics technology, various approaches can be used to monitor proteome changes and identify differentially expressed proteins in sepsis, which may help to understand the pathophysiological process of sepsis. Although previous reports have summarized proteomics-related data on the diagnosis of sepsis and sepsis-related biomarkers, the present review aims to comprehensively summarize the available literature concerning “sepsis”, “proteomics”, “cecal ligation and puncture”, “lipopolysaccharide”, and “post-translational modifications” in relation to proteomics research to provide novel insights into the molecular mechanisms of sepsis.

Serum proteomics reveals disorder of lipoprotein metabolism in sepsis

This study illustrated that lipoprotein and lipid metabolism might play a significant role in patients with sepsis and that complement activation was significantly enriched in patients with sepsis-associated encephalopathy.

Sepsis is defined as an organ dysfunction syndrome and it has high mortality worldwide. This study analysed the proteome of serum from patients with sepsis to characterize the pathological mechanism and pathways involved in sepsis. A total of 59 patients with sepsis were enrolled for quantitative proteomic analysis. Weighted gene co-expression network analysis (WGCNA) was performed to construct a co-expression network specific to sepsis. Key regulatory modules that were detected were highly correlated with sepsis patients and related to multiple functional groups, including plasma lipoprotein particle remodeling, inflammatory response, and wound healing. Complement activation was significantly associated with sepsis-associated encephalopathy. Triglyceride/cholesterol homeostasis was found to be related to sepsis-associated acute kidney injury. Twelve hub proteins were identified, which might be predictive biomarkers of sepsis. External validation of the hub proteins showed their significantly differential expression in sepsis patients. This study identified that plasma lipoprotein processes played a crucial role in sepsis patients, that complement activation contributed to sepsis-associated encephalopathy, and that triglyceride/cholesterol homeostasis was associated with sepsis-associated acute kidney injury.

Initial antimicrobial management of sepsis

Sepsis is a common consequence of infection, associated with a mortality rate > 25%. Although community-acquired sepsis is more common, hospital-acquired infection is more lethal. The most common site of infection is the lung, followed by abdominal infection, catheter-associated blood steam infection and urinary tract infection. Gram-negative sepsis is more common than gram-positive infection, but sepsis can also be due to fungal and viral pathogens. To reduce mortality, it is necessary to give immediate, empiric, broad-spectrum therapy to those with severe sepsis and/or shock, but this approach can drive antimicrobial overuse and resistance and should be accompanied by a commitment to de-escalation and antimicrobial stewardship. Biomarkers such a procalcitonin can provide decision support for antibiotic use, and may identify patients with a low likelihood of infection, and in some settings, can guide duration of antibiotic therapy. Sepsis can involve drug-resistant pathogens, and this often necessitates consideration of newer antimicrobial agents.

Metabolomics Study Revealing the Potential Risk and Predictive Value of Fragmented QRS for Acute Myocardial Infarction

Patients with nonobstructive coronary artery disease (NOCAD) have high risk associated with acute myocardial infarction (AMI), and fragmented QRS (fQRS) has a predictive value of AMI after percutaneous coronary intervention (PCI). A cohort of 254 participants were recruited including 136 NOCAD and 118 AMI patients from Xi'an No. 1 Hospital. Comprehensive metabolomics was performed by UPLC-Q/TOF-MS with multivariate statistical analyses. Hazard ratios were measured to discriminate the prognostic in AMI after PCI between differential metabolites and fQRS. OPLS-DA separated metabolites from NOCAD and AMI in serum. A total of 23 differential metabolites were identified between NOCAD and AMI. In addition, four differential metabolites, namely, acetylglycine, threoninyl-glycine, glutarylglycine, and nonanoylcarnitine, were identified between fQRS and non-fQRS in AMI. The hazard ratios demonstrate that the metabolites were associated with the risk of cardiac death, recurrent angina, readmissions, and major adverse cardiovascular events, which may clarify the mechanism of fQRS as a predictor in the prognostic of AMI after PCI. This study identified novel differential metabolites to distinguish the difference from NOCAD to AMI and clarify the mechanism of fQRS in prognostic of AMI after PCI, which may provide novel insights into potential risks and prognostic of AMI.

Whole blood transcriptional responses of very preterm infants during late-onset sepsis

BACKGROUND

Host immune responses during late-onset sepsis (LOS) in very preterm infants are poorly characterised due to a complex and dynamic pathophysiology and challenges in working with small available blood volumes. We present here an unbiased transcriptomic analysis of whole peripheral blood from very preterm infants at the time of LOS.

METHODS

RNA-Seq was performed on peripheral blood samples (6-29 days postnatal age) taken at the time of suspected LOS from very preterm infants <30 weeks gestational age. Infants were classified based on blood culture positivity and elevated C-reactive protein concentrations as having confirmed LOS (n = 5), possible LOS (n = 4) or no LOS (n = 9). Bioinformatics and statistical analyses performed included pathway over-representation and protein-protein interaction network analyses. Plasma cytokine immunoassays were performed to validate differentially expressed cytokine pathways.

RESULTS

The blood leukocyte transcriptional responses of infants with confirmed LOS differed significantly from infants without LOS (1,317 differentially expressed genes). However, infants with possible LOS could not be distinguished from infants with no LOS or confirmed LOS. Transcriptional alterations associated with LOS included genes involved in pathogen recognition (mainly TLR pathways), cytokine signalling (both pro-inflammatory and inhibitory responses), immune and haematological regulation (including cell death pathways), and metabolism (altered cholesterol biosynthesis). At the transcriptional-level cytokine responses during LOS were characterised by over-representation of IFN-α/β, IFN-γ, IL-1 and IL-6 signalling pathways and up-regulation of genes for inflammatory responses. Infants with confirmed LOS had significantly higher levels of IL-1α and IL-6 in their plasma.

CONCLUSIONS

Blood responses in very preterm infants with LOS are characterised by altered host immune responses that appear to reflect unbalanced immuno-metabolic homeostasis.

Immunometabolic approaches to prevent, detect, and treat neonatal sepsis

The first days of postnatal life are energetically demanding as metabolic functions change dramatically to accommodate drastic environmental and physiologic transitions after birth. It is increasingly appreciated that metabolic pathways are not only crucial for nutrition but also play important roles in regulating inflammation and the host response to infection. Neonatal susceptibility to infection is increased due to a functionally distinct immune response characterized by high reliance on innate immune mechanisms. Interactions between metabolism and the immune response are increasingly recognized, as changes in metabolic pathways drive innate immune cell function and activation and consequently host response to pathogens. Moreover, metabolites, such as acetyl-coenzyme A (acetyl-CoA) and succinate have immunoregulatory properties and serve as cofactors for enzymes involved in epigenetic reprogramming or "training" of innate immune cells after an initial infectious exposure. Highly sensitive metabolomic approaches allow us to define alterations in metabolic signatures as they change during ontogeny and as perturbed by immunization or infection, thereby linking metabolic pathways to immune cell effector functions. Characterizing the ontogeny of immunometabolism will offer new opportunities to prevent, diagnose, and treat neonatal sepsis.

Multiple biomarkers of sepsis identified by novel time-lapse proteomics of patient serum

Serum components of sepsis patients vary with the severity of infection, the resulting inflammatory response, per individual, and even over time. Tracking these changes is crucial in properly treating sepsis. Hence, several blood-derived biomarkers have been studied for their potential in assessing sepsis severity. However, the classical approach of selecting individual biomarkers is problematic in terms of accuracy and efficiency. We therefore present a novel approach for detecting biomarkers using longitudinal proteomics data. This does not require a predetermined set of proteins and can therefore reveal previously unknown related proteins. Our approach involves examining changes over time of both protein abundance and post-translational modifications in serum, using two-dimensional gel electrophoresis (2D-PAGE). 2D-PAGE was conducted using serum from n = 20 patients, collected at five time points, starting from the onset of sepsis. Changes in protein spots were examined using 49 spots for which the signal intensity changed by at least two-fold over time. These were then screened for significant spikes or dips in intensity that occurred exclusively in patients with adverse outcome. Individual level variation was handled by a mixed effects model. Finally, for each time transition, partial correlations between spots were estimated through a Gaussian graphical model (GGM) based on the ridge penalty. Identifications of spots of interest by tandem mass spectrometry revealed that many were either known biomarkers for inflammation (complement components), or had previously been suggested as biomarkers for kidney failure (haptoglobin) or liver failure (ceruloplasmin). The latter two are common complications in severe sepsis. In the GGM, many of the tightly connected spots shared known biological functions or even belonged to the same protein; including hemoglobin chains and acute phase proteins. Altogether, these results suggest that our screening method can successfully identify biomarkers for disease states and cluster biologically related proteins using longitudinal proteomics data derived from 2D-PAGE.

Leukocyte Transcriptional Response in Sepsis

BACKGROUND

The complex host response to sepsis is incompletely understood. The aim of this investigation is to use leukocyte RNA sequencing to characterize biological functions, cellular pathways, and key regulatory molecules driving sepsis pathophysiology.

METHODS

This was a prospective, observational study of emergency department patients with sepsis, at an urban, academic, tertiary care center. In the derivation cohort, we collected blood at enrollment and 90 days after hospital discharge allowing each patient to serve as an internal control. We performed RNA sequencing to quantify transcriptional expression changes during sepsis and non-sepsis states. We then performed unsupervised and supervised analyses, as well as functional and pathway analyses. We selected the top down and upregulated genes and key regulatory molecules for validation. Validation occurred in a cohort of septic and non-septic using real-time PCR.

RESULTS

The derivation cohort included 5 patients, and RNA sequencing revealed 916 unique mRNA transcripts differentially expressed during sepsis. Among these, 673 (73%) genes were upregulated, and 243 (27%) were downregulated. Functional enrichment analysis revealed a highly dynamic downstream effect of the transcriptional activity during sepsis. Of the 43 functional cellular pathways activated during sepsis, the top pathways were closely associated with inflammation and response to infection. Validation occurred in 18 septic and 25 non-septic control patients, with 34/45 (76%) of identified genes validated. The regulatory analysis identified several key regulators of sepsis.

CONCLUSIONS

Highly dynamic transcriptional activity occurs in leukocytes during sepsis, activating key cellular pathways and master regulatory molecules that drive the sepsis process.

Plasma proteomic changes during therapeutic hypothermia in resuscitated patients after cardiac arrest

Hypothermia is used for several h during cardiac and aortic surgery to protect ischemic organs. Therapeutic hypothermia (TH) is used for ≤24 h as a treatment for comatose patients after the return of spontaneous circulation (ROSC) following cardiac arrest. The proteomic approach may provide unbiased data on alterations in the abundance of proteins during TH. The objective of this study was to assess the effects of cooling/rewarming on the plasma proteome during TH after ROSC and to identify the mechanism underlying its therapeutic effects. A total of nine comatose adult patients, resuscitated shortly after cardiac arrest, were cooled to 34°C for 24 h and slowly rewarmed to 36°C. A quantitative gel-free proteomic analysis was performed using the isobaric tag for relative and absolute quantification labeling tandem mass spectrometry. Plasma samples were obtained prior to cooling and rewarming, and immediately after rewarming, from all patients during TH after ROSC. A total of 92 high-confidence proteins were identified. Statistically significant alterations were observed (>1.2-fold increase or <0.833-fold decrease) in the levels of 15 of those proteins (P=0.003–0.047), mainly proteins belonging to the acute-phase response or platelet degranulation. Unexpectedly, the levels of free hemoglobin (hemoglobin subunits α and β) were significantly downregulated during TH (P<0.05). The level of the terminal complement complex (SC5b-9) showed significant reduction after cooling (P=0.023). Although the acute-phase response proteins were upregulated, the abundance of complement proteins did not change, and the levels of SC5b-9 and free hemoglobin decreased during TH in patients after ROSC.

Multi-Omics Research Trends in Sepsis: A Bibliometric, Comparative Analysis Between the United States, the European Union 28 Member States, and China

"-Omics" research is in transition with the recent rise of multi-omics technology platforms. Integration of "-omics" and multi-omics research is of high priority in sepsis, a heterogeneous syndrome that is widely recognized as a global health burden and a priority biomedical funding field. We report here an original study on bibliometric trends in the use of "-omics" technologies, and multi-omics approaches in particular, in sepsis research in three (supra)national settings, the United States, the European Union 28 Member States (EU-28), and China. Using a 5-year longitudinal bibliometric study design from 2011 to 2015, we analyzed the sepsis-related research articles in English language that included at least one or multi-omics technologies in publicly available form in Medline (free full texts). We found that the United States has had the lead (almost one-third of publications) in the inclusion of an "-omics" or multi-omics technology in sepsis within the study period. However, both China and the EU-28 displayed a significant increase in the number of publications that employed one or more types of "-omics" research (p < 0.005), while the EU-28 displayed a significant increase especially in multi-omics research articles in sepsis (p < 0.05). Notably, more than half of the multi-omics research studies in the sepsis knowledge domain had a university or government/state funding source. Among the multi-omics research publications in sepsis, the combination of genomics and transcriptomics was the most frequent (40.5%), followed by genomics and proteomics (20.4%). We suggest that the lead of the United States in the field of "-omics" and multi-omics research in sepsis is likely at stake, with both the EU-28 and China rapidly increasing their research capacity. Moreover, "triple omics" that combine genomics, proteomics, and metabolomics analyses appear to be uncommon in sepsis, and yet much needed for triangulation of systems science data. These observations have implications for "-omics" technology policy and global research funding strategic foresight.

Metabolomics Study on the Effects of Salvianolic Acid B and Borneol for Treating Cerebral Ischemia in Rats by Ultra-Performance Liquid Chromatography Quadrupole Time-of-Flight Mass Spectrometry

Salviae miltiorrliza-borneol Jun-Shi coupled-herbs have been widely used for treatment of ischemia stroke. Salvianolic acid B was the most abundant and bioactive compound of Salviae miltiorrliza and used for prevention and treatment of cerebrovascular diseases. However, the scientific intension and compatible mechanism of Salvianolic acid B - borneol combination were still unknown. A metabolomics study approach based on ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) combined with a pathological study has been applied to study the metabolic disturbances of cerebral ischemia and evaluate the efficacies of Sal B and Sal B/borneol against cerebral ischemia in middle cerebral artery occlusion (MCAO) rats. The neuroprotection of Sal B and Sal B/borneol was reversed through the evaluation of neurological deficits, infarct volume, and neuronal apoptosis in MCAO model. The metabonomic analysis revealed that the MCAO-induced cerebral ischemia could be ameliorated by Sal B through improving the energy metabolism, lipids metabolism, inflammatory responses, and oxidant stress. Borneol could enhance the neuroprotective effects, was associated with the increased concentration of Sal B, and attenuate the function of sphingolipid metabolism pathway in cerebral ischemia rats. These findings perhaps clarify the mechanism of neuroprotective effects of treating ischemia stroke by Sal B or Sal B/borneol preliminarily through metabolomics and push the quality promotion and the composition of borneol/Sal B in secondary development of prescription.

Precision Medicine for Neonatal Sepsis

Neonatal sepsis remains a significant cause of morbidity and mortality especially in the preterm infant population. The ability to promptly and accurately diagnose neonatal sepsis based on clinical evaluation and laboratory blood tests remains challenging. Advances in high-throughput molecular technologies have increased investigations into the utility of transcriptomic, proteomic and metabolomic approaches as diagnostic tools for neonatal sepsis. A systems-level understanding of neonatal sepsis, obtained by using omics-based technologies (at the transcriptome, proteome or metabolome level), may lead to new diagnostic tools for neonatal sepsis. In particular, recent omic-based studies have identified distinct transcriptional signatures and metabolic or proteomic biomarkers associated with sepsis. Despite the emerging need for a systems biology approach, future studies have to address the challenges of integrating multi-omic data with laboratory and clinical meta-data in order to translate outcomes into precision medicine for neonatal sepsis. Omics-based analytical approaches may advance diagnostic tools for neonatal sepsis. More research is needed to validate the recent systems biology findings in order to integrate multi-dimensional data (clinical, laboratory and multi-omic) for future translation into precision medicine for neonatal sepsis. This review will discuss the possible applications of omics-based analyses for identification of new biomarkers and diagnostic signatures for neonatal sepsis, focusing on the immune-compromised preterm infant and considerations for clinical translation.

The Preseptic Period and Inflammatory Markers in the Prediction of the Course of Sepsis

Background

The aim of this study was to find a simple and easily accessible scoring system that could predict the development of sepsis in the preseptic period.

Material/Methods

The study included 161 patients with a basal sequential organ failure assessment (SOFA) value of 2 or more. The sepsis group (n=83) comprised patients with infection reported in culture results; the control group (n=78) comprised patients not showing evidence of infection in blood, urine, and phlegm cultures; samples were taken on three consecutive days.

Results

The patients in both groups were divided into subgroups of non-survivor and survivor patients. The preseptic and septic SOFA score, neutrophil lymphocyte ratio (NLR), and procalcitonin (PRC) and lactate (Lac) values were determined to be statistically significantly higher in the sepsis group than in the control group. When the values related to sepsis were examined, a strong relationship was determined between sepsis and SOFA score, PRC values, and Lac values in the preseptic period and a weak relationship with NLR. In the model formed using multiple regression analysis with defined cutoff values for the preseptic and the septic periods, we found that in the septic period, a diagnosis of sepsis could be made with 83.8% accuracy. The diagnostic value of the same parameters evaluated in the preseptic period was 77.9%.

Conclusions

The diagnostic value of the combination of Lac, PRC, SOFA, and NLR were found to be similar in the preseptic period as the sepsis period; thus these combined values could safely be used for the early diagnosis of sepsis.

Transcriptomic data from two primary cell models stimulating human monocytes suggest inhibition of oxidative phosphorylation and mitochondrial function by N. meningitidis which is partially up-regulated by IL-10

Background

Biological interpretation of DNA microarray data may differ depending on underlying assumptions and statistical tests of bioinformatics tools used. We used Gene Set Enrichment Analysis (GSEA) and Ingenuity Pathway Analysis (IPA) to analyze previously generated DNA microarray data from human monocytes stimulated with N. meningitidis and IL-10 (“the model system”), and with meningococcal sepsis plasma before and after immunodepletion of IL-10 (“the patient plasma system”). The objectives were to compare if the two bioinformatics methods resulted in similar biological interpretation of the datasets, and to identify whether GSEA provided additional insight compared with IPA about the monocyte host response to meningococcal activation.

Results

In both experimental models, GSEA and IPA identified genes associated with pro-inflammatory innate immune activation, including TNF-signaling, Toll-like receptor signaling, JAK-STAT-signaling, and type I and type II interferon signaling. GSEA identified genes regulated by the presence of IL-10 with similar gene sets in both the model system and the patient plasma system. In the model system, GSEA and IPA in sum identified 170 genes associated with oxidative phosphorylation/mitochondrial function to be down-regulated in monocytes stimulated with meningococci. In the patient plasma system, GSEA and IPA in sum identified 122 genes associated with oxidative phosphorylation/mitochondrial dysfunction to be down-regulated by meningococcal sepsis plasma depleted for IL-10. Using IPA, we identified IL-10 to up-regulate 18 genes associated with oxidative phosphorylation/mitochondrial function that were down-regulated by N. meningitidis.

Conclusions

Biological processes associated with the gene expression changes in the model system of meningococcal sepsis were comparable with the results found in the patient plasma system. By combining GSEA with IPA, we discovered an inhibitory effect of N. meningitidis on genes associated with mitochondrial function and oxidative phosphorylation, and that IL-10 partially reverses this strong inhibitory effect, thereby identifying, to our knowledge, yet another group of genes where IL-10 regulates the effect of LPS. We suggest that relying on a single bioinformatics tool together with an arbitrarily chosen filtering criteria for data analysis may result in overlooking relevant biological processes and signaling pathways associated with genes differentially expressed between compared experimental conditions.

Electronic supplementary material

The online version of this article (10.1186/s12865-017-0229-5) contains supplementary material, which is available to authorized users.

Biomarkers in Sepsis

A biomarker is a characteristic by which a (patho)physiologic process can be identified. Biomarkers can be of diagnostic value (to discriminate infection from noninfectious conditions or to determine the causative pathogen), of prognostic value (assigning risk profiles and predict outcome), and in the future may be of theranostic value (aid in selection and monitoring of therapy). Systems biology provides a promising tool for the discovery of novel biomarkers. Biomarkers can be the key to personalized targeted treatment in the future clinical management of sepsis.

Deciphering the mechanism of Huang-Lian-Jie-Du-Decoction on the treatment of sepsis by formula decomposition and metabolomics: Enhancement of cholinergic pathways and inhibition of HMGB-1/TLR4/NF-κB signaling

Sepsis is the major cause of morbidity and mortality in surgical patients. Huang-Lian-Jie-Du-Decoction (HLJDD), a well-known Chinese herb formula, has long been used for the treatment of sepsis. In this investigation, by leaving one herb out each time, the four component herbs of HLJDD were reformulated to four HLJDD variants Form1-4, corresponding to the removal of Phellodendri Chinensis Cortex, Scutellariae Radix, Gardeniae Fructu and Coptidis Rhizoma, respectively. Metabolomics approach combined with histological inspection, biochemical measurement and molecular biology was used to investigate the treatment effects of HLJDD and its four variants on cecal ligation and puncture (CLP) model of sepsis, which were compared to decipher the formulating principles of HLJDD. Our results showed that HLJDD exhibit the strongest therapeutic effects in the CLP models as compared with the four variants, which could be ascribed to its most significant enhancement of cholinergic anti-inflammatory pathway and inhibition of HMGB-1/TLR4/NF-κB signaling pathway. Most of all, metabolites changed specifically between groups of HLJDD and its four variants were related with the exceptional treatment effects of HLJDD.

Mass spectrometry for the discovery of biomarkers of sepsis

Sepsis is a serious medical condition that occurs in 30% of patients in intensive care units (ICUs). Early detection of sepsis is key to prevent its progression to severe sepsis and septic shock, which can cause organ failure and death. Diagnostic criteria for sepsis are nonspecific and hinder a timely diagnosis in patients. Therefore, there is currently a large effort to detect biomarkers that can aid physicians in the diagnosis and prognosis of sepsis. Mass spectrometry is often the method of choice to detect metabolomic and proteomic changes that occur during sepsis progression. These "omics" strategies allow for untargeted profiling of thousands of metabolites and proteins from human biological samples obtained from septic patients. Differential expression of or modifications to these metabolites and proteins can provide a more reliable source of diagnostic biomarkers for sepsis. Here, we focus on the current knowledge of biomarkers of sepsis and discuss the various mass spectrometric technologies used in their detection. We consider studies of the metabolome and proteome and summarize information regarding potential biomarkers in both general and neonatal sepsis.

IL-6 gene polymorphisms and sepsis in icu adult romanian patients: a prospective study

Objectives: The goal of the study was to investigate the correlations between the interleukin-6 IL-6 -174 G/C and IL-6 -572 G/C gene polymorphisms and sepsis risk and severity in adult ICU patients.

Materials and Methods: We prospectively assessed 107 septic patients and divided them into two subgroups: organ dysfunction-free sepsis subgroup S (n=60) and septic shock subgroup SS (n=47). A control group of 96 healthy individuals was included. Both patients and controls underwent IL-6 -174 G/C and -572 G/C genotyping and circulating IL-6 in the study group which were measured from samples taken in the first day of sepsis diagnosis.

Results: No differences in the genotype frequencies of the two polymorphisms between study and control groups were identified. The GC genotype and C allele of IL-6 -572 G/C gene polymorphism was statistically significant more frequent in the organ dysfunction-free subgroup (p=0.01, p=0.004 respectively). No statistically significant differences for the IL-6 -174 G/C gene polymorphism were found between the two sepsis subgroups. Circulating IL-6 levels were significantly higher in the septic shock subgroup and among patients with GG genotypes of both studied polymorphisms.

Conclusion: We underline the possible role of IL-6 -572 G/C as a marker of severe evolution. There is no evidence of a direct role of IL-6 -174 G/C gene polymorphism in sepsis risk and outcome. Il-6 levels are correlated with sepsis severity but not with variant genotype of investigated IL-6 gene polymorphisms.

The Relevance of Coding Gene Polymorphysms of Cytokines and Cellular Receptors in Sepsis

Sepsis is an injurious systemic host response to infection, which can often lead to septic shock and death. Recently, the immune-pathogenesis and genomics of sepsis have become a research topic focusing on the establishment of diagnostic and prognostic biomarkers. As yet, none have been identified as having the necessary specificity to be used independently of other factors in this respect. However the accumulation of current evidence regarding genetic variations, especially the single nucleotide polymorphisms (SNPs) of cytokines and other innate immunity determinants, partially explains the susceptibility and individual differences of patients with regard to the evolution of sepsis. This article outlines the role of genetic variation of some serum proteins which have the potential to be used as biomarker values in evaluating sepsis susceptibility and the progression of the condition.

Pharmacogenomics and pharmacogenetics for the intensive care unit: a narrative review

PURPOSE

Knowledge of how alterations in pharmacogenomics and pharmacogenetics may affect drug therapy in the intensive care unit (ICU) has received little study. We review the clinically relevant application of pharmacogenetics and pharmacogenomics to drugs and conditions encountered in the ICU.

SOURCE

We selected relevant literature to illustrate the important concepts contained within.

PRINCIPAL FINDINGS

Two main approaches have been used to identify genetic abnormalities - the candidate gene approach and the genome-wide approach. Genetic variability in response to drugs may occur as a result of alterations of drug-metabolizing (cytochrome P [CYP]) enzymes, receptors, and transport proteins leading to enhancement or delay in the therapeutic response. Of relevance to the ICU, genetic variation in CYP-450 isoenzymes results in altered effects of midazolam, fentanyl, morphine, codeine, phenytoin, clopidogrel, warfarin, carvedilol, metoprolol, HMG-CoA reductase inhibitors, calcineurin inhibitors, non-steroidal anti-inflammatory agents, proton pump inhibitors, and ondansetron. Changes in cholinesterase enzyme function may affect the disposition of succinylcholine, benzylisoquinoline muscle relaxants, remifentanil, and hydralazine. Genetic variation in transport proteins leads to differences in the response to opioids and clopidogrel. Polymorphisms in drug receptors result in altered effects of β-blockers, catecholamines, antipsychotic agents, and opioids. Genetic variation also contributes to the diversity and incidence of diseases and conditions such as sepsis, malignant hyperthermia, drug-induced hypersensitivity reactions, cardiac channelopathies, thromboembolic disease, and congestive heart failure.

CONCLUSION

Application of pharmacogenetics and pharmacogenomics has seen improvements in drug therapy. Ongoing study and incorporation of these concepts into clinical decision making in the ICU has the potential to affect patient outcomes.

Systematic Molecular Phenotyping: A Path Toward Precision Emergency Medicine?

Precision medicine is an emerging approach to disease treatment and prevention that considers variability in patient genes, environment, and lifestyle. However, little has been written about how such research impacts emergency care. Recent advances in analytical techniques have made it possible to characterize patients in a more comprehensive and sophisticated fashion at the molecular level, promising highly individualized diagnosis and treatment. Among these techniques are various systematic molecular phenotyping analyses (e.g., genomics, transcriptomics, proteomics, and metabolomics). Although a number of emergency physicians use such techniques in their research, widespread discussion of these approaches has been lacking in the emergency care literature and many emergency physicians may be unfamiliar with them. In this article, we briefly review the underpinnings of such studies, note how they already impact acute care, discuss areas in which they might soon be applied, and identify challenges in translation to the emergency department (ED). While such techniques hold much promise, it is unclear whether the obstacles to translating their findings to the ED will be overcome in the near future. Such obstacles include validation, cost, turnaround time, user interface, decision support, standardization, and adoption by end-users.

Characterization and differentiation of equine experimental local and early systemic inflammation by expression responses of inflammation-related genes in peripheral blood leukocytes

Background

Local inflammation may progress into systemic inflammation. To increase our understanding of the basic immunological processes during transition of equine local inflammation into a systemic state, investigation into the equine systemic immune response to local inflammation is warranted. Therefore, the aim of this study was to investigate the innate peripheral blood leukocyte (PBL) immune response to local inflammation in horses, and to compare this response with the PBL immune response during the early phase of acute systemic inflammation. Expression of 22 selected inflammation-related genes was measured in whole blood leukocytes from 6 horses in an experimental cross-over model of lipopolysaccharide- (LPS-) induced acute synovitis (3 μg LPS intraarticularly; locally inflamed [LI] horses) and endotoxemia (1 μg LPS/kg intravenously; systemically inflamed [SI] horses). Multiple clinical and hematological/biochemical examinations were performed, and serial blood samples were analyzed by reverse transcription quantitative real-time PCR. Post-induction expression profiles of all genes were compared between study groups using principal component analysis (PCA) and hierarchical clustering.

Results

Moderate synovitis and mild systemic inflammation of approximately 24 h duration was confirmed by clinical and paraclinical observations in LI and SI horses, respectively. In the LI group, samples obtained 3–16 h post-injection showed distinct clustering in the PCA compared with baseline levels, indicating a transcriptional response to local inflammation in PBLs in this time interval. There was no clinical or hematological indication of actual systemic inflammation. There was a clear separation of all LI samples from all SI samples in two distinct clusters, indicating that expression profiles in the two study groups were different, independent of time since LPS injection. Co-regulated genes formed four clusters across study groups which were distinctly differently regulated. Only few of individual genes displayed different expression between the study groups at all times after LPS injection.

Conclusions

Local inflammation in horses initiated an innate transcriptional response in PBLs, which differed from the transcriptional response during the early phase of systemic inflammation. This study may provide new insights into the immunobiology of PBLs during the transition of local inflammation into a systemic state.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-016-0706-8) contains supplementary material, which is available to authorized users.

A molecular biomarker to diagnose community-acquired pneumonia on intensive care unit admission

RATIONALE

Community-acquired pneumonia (CAP) accounts for a major proportion of intensive care unit (ICU) admissions for respiratory failure and sepsis. Diagnostic uncertainty complicates case management, which may delay appropriate cause-specific treatment.

OBJECTIVES

To characterize the blood genomic response in patients with suspected CAP and identify a candidate biomarker for the rapid diagnosis of CAP on ICU admission.

METHODS

The study comprised two cohorts of consecutively enrolled patients treated for suspected CAP on ICU admission. Patients were designated CAP (cases) and no-CAP patients (control subjects) by post hoc assessment. The first (discovery) cohort (101 CAP and 33 no-CAP patients) was enrolled between January 2011 and July 2012; the second (validation) cohort (70 CAP and 30 no-CAP patients) between July 2012 and June 2013. Blood was collected within 24 hours of ICU admission.

MEASUREMENTS AND MAIN RESULTS

Blood microarray analysis of CAP and no-CAP patients revealed shared and distinct gene expression patterns. A 78-gene signature was defined for CAP, from which a FAIM3:PLAC8 gene expression ratio was derived with area under curve of 0.845 (95% confidence interval, 0.764-0.917) and positive and negative predictive values of 83% and 81%, respectively. Robustness of the FAIM3:PLAC8 ratio was ascertained by quantitative polymerase chain reaction in the validation cohort. The FAIM3:PLAC8 ratio outperformed plasma procalcitonin and IL-8 and IL-6 in discriminating between CAP and no-CAP patients.

CONCLUSIONS

CAP and no-CAP patients presented shared and distinct blood genomic responses. We propose the FAIM3:PLAC8 ratio as a candidate biomarker to assist in the rapid diagnosis of CAP on ICU admission. Clinical trial registered with www.clinicaltrials.gov (NCT 01905033).

Recent developments in severe sepsis research: from bench to bedside and back

Severe sepsis remains a worldwide threat, not only in industrialized countries, due to their aging population, but also in developing countries where there still are numerous cases of neonatal and puerperal sepsis. Tools for early diagnosis, a prerequisite for rapid and appropriate antibiotic therapy, are still required. In this review, we highlight some recent developments in our understanding of the associated systemic inflammatory response that help deciphering pathophysiology (e.g., epigenetic, miRNA, regulatory loops, compartmentalization, apoptosis and synergy) and discuss some of the consequences of sepsis (e.g., immune status, neurological and muscular alterations). We also emphasize the challenge to better define animal models and discuss past failures in clinical investigations in order to define new efficient therapies.

Haematological malignancy in the intensive care unit: microbiology results and mortality

BACKGROUND

Mortality prediction models of patients with a haematological malignancy admitted to an intensive care unit (ICU) do not include the presence of neutropenia and microbiology results. We performed a registry-based retrospective study of haematology patients admitted to the ICU to investigate the relation between neutropenia, microbiology results and outcome of these patients.

METHODS

Neutropenia and microbiology culture results within 24 h before or after ICU admission of patients with a haematological malignancy admitted between 2004 and 2010 were described and analysed for association with 28-day mortality.

RESULTS

We identified 234 individual patients with a current malignant haematological condition, of which 27% were neutropenic and 21% had a positive blood culture at admission. Most prevalent from blood cultured species were Escherichia coli and coagulase-negative staphylococci. The overall 28-day mortality was 38%. In patients with a positive blood culture but no neutropenia, 28-day mortality was 28% and in patients with neutropenia but without positive blood culture, it was 36%. The 28-day mortality of patients with both neutropenia and a positive blood culture was 55% with an adjusted (for APACHE-II score) hazard ratio (HR) of 1.8 (95%CI 1.0-3.4) compared to other hematologic patients admitted to the ICU.

CONCLUSION

In patients with haematological malignancy admitted to the ICU, culture results are diverse. The combination of neutropenia and positive blood culture is associated with increased 28-day mortality. We suggest this could be of additional value when assessing mortality risk in this patient group.

Status and perspective of lab-on-a-chip systems for common diseases: a systematic review from 2003 to 2013

BACKGROUND

Lab-on-a-chip systems (LOCs) are a useful aid for the individualization of therapeutic algorithms at the point-of-care.

MATERIALS & METHODS

We performed a systematic literature review on LOCs for diseases with a global impact for healthcare.

RESULTS

A total of 1007 articles matched the previously specified search criteria, thereof 65 studies could be included in this review. A total of 55 different LOCs were evaluated, most for diagnosis or monitoring of cancer (n = 24). For other diseases we found considerably less analyzed LOCs. The analytical performance of the LOCs was usually very good, 37 (67%) LOCs had a sensitivity higher than 90%.

CONCLUSION

Although LOC systems performance has been positively evaluated in the great majority of studies, the testing was mostly limited to the research laboratory setting rather than real-world scenarios.

Prognosis Biomarkers of Severe Sepsis and Septic Shock by 1H NMR Urine Metabolomics in the Intensive Care Unit

Early diagnosis and patient stratification may improve sepsis outcome by a timely start of the proper specific treatment. We aimed to identify metabolomic biomarkers of sepsis in urine by ¹H-NMR spectroscopy to assess the severity and to predict outcomes. Urine samples were collected from 64 patients with severe sepsis or septic shock in the ICU for a ¹H NMR spectra acquisition. A supervised analysis was performed on the processed spectra, and a predictive model for prognosis (30-days mortality/survival) of sepsis was constructed using partial least-squares discriminant analysis (PLS-DA). In addition, we compared the prediction power of metabolomics data respect the Sequential Organ Failure Assessment (SOFA) score. Supervised multivariate analysis afforded a good predictive model to distinguish the patient groups and detect specific metabolic patterns. Negative prognosis patients presented higher values of ethanol, glucose and hippurate, and on the contrary, lower levels of methionine, glutamine, arginine and phenylalanine. These metabolites could be part of a composite biopattern of the human metabolic response to sepsis shock and its mortality in ICU patients. The internal cross-validation showed robustness of the metabolic predictive model obtained and a better predictive ability in comparison with SOFA values. Our results indicate that NMR metabolic profiling might be helpful for determining the metabolomic phenotype of worst-prognosis septic patients in an early stage. A predictive model for the evolution of septic patients using these metabolites was able to classify cases with more sensitivity and specificity than the well-established organ dysfunction score SOFA.

Activated Complement Factors as Disease Markers for Sepsis

Sepsis is a leading cause of death in the United States and worldwide. Early recognition and effective management are essential for improved outcome. However, early recognition is impeded by lack of clinically utilized biomarkers. Complement factors play important roles in the mechanisms leading to sepsis and can potentially serve as early markers of sepsis and of sepsis severity and outcome. This review provides a synopsis of recent animal and clinical studies of the role of complement factors in sepsis development, together with their potential as disease markers. In addition, new results from our laboratory are presented regarding the involvement of the complement factor, mannose-binding lectin, in septic shock patients. Future clinical studies are needed to obtain the complete profiles of complement factors/their activated products during the course of sepsis development. We anticipate that the results of these studies will lead to a multipanel set of sepsis biomarkers which, along with currently used laboratory tests, will facilitate earlier diagnosis, timely treatment, and improved outcome.

Dynamic expression of leukocyte innate immune genes in whole blood from horses with lipopolysaccharide-induced acute systemic inflammation

Background

In horses, insights into the innate immune processes in acute systemic inflammation are limited even though these processes may be highly important for future diagnostic and therapeutic advances in high-mortality disease conditions as the systemic inflammatory response syndrome (SIRS) and sepsis. Therefore, the aim of this study was to investigate the expression of 31 selected blood leukocyte immune genes in an equine model of acute systemic inflammation to identify significantly regulated genes and to describe their expression dynamics during a 24-h experimental period. Systemic inflammation was induced in 6 adult horses by the intravenous injection of 1 μg lipopolysaccharide (LPS) per kg btw. Sixteen blood samples were collected for each horse at predetermined intervals and analyzed by reverse transcription quantitative real-time PCR. Post-induction expression levels for each gene were compared with baseline levels.

Results

Systemic inflammation was confirmed by the presence of clinical and hematological changes which were consistent with SIRS. The clinical response to LPS was transient and brief as all horses except one showed unaltered general demeanor after 24 h. Twenty-two leukocyte genes were significantly regulated at at least one time point during the experimental period. By close inspection of the temporal responses the dynamic changes in mRNA abundance revealed a very rapid onset of both pro- and anti-inflammatory mediators and a substantial variation in both expression magnitudes and duration of changes between genes. A majority of the 22 significantly regulated genes peaked within the first 8 h after induction, and an on-going, albeit tightly controlled, regulation was seen after 24 h despite approximate clinical recovery.

Conclusions

This first broad study of gene expressions in blood leukocytes during equine acute LPS-induced systemic inflammation thoroughly characterized a highly regulated and dynamic innate immune response. These results provide new insights into the molecular mechanisms of equine systemic inflammation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12917-015-0450-5) contains supplementary material, which is available to authorized users.

The role of proteomics in understanding biological mechanisms of sepsis

Sepsis is a systemic inflammatory state caused by infection. Complications of this infection with multiple organ failure lead to more lethal conditions, such as severe sepsis and septic shock. Sepsis is one of the leading causes of US deaths. Novel biomarkers with high sensitivity and specificity may be helpful for early diagnosis of sepsis and for improvement of patient outcomes through the development of new therapies. Mass spectrometry-based proteomics offers powerful tools to identify such biomarkers and furthermore to give insight to fundamental mechanisms of this clinical condition. In this review, we summarize findings from proteomics studies of sepsis and how their applications have provided more understanding into the pathogenesis of septic infection. Literatures related to "proteomics", "sepsis", "systemic inflammatory response syndrome", "severe sepsis", "septic infection", and "multiple organ dysfunction syndrome" were searched using PubMed. Findings about neonatal and adult sepsis are discussed separately. Within the adult sepsis studies, results are grouped based on the models (e.g., human or animal). Across investigations in clinical populations and in rodent and mammalian animal models, biological pathways, such as inflammatory and acute phase response, coagulation, complement, mitochondrial energy metabolism, chaperones, and oxidative stress, are altered at the protein level. These proteomics studies have discovered many novel biomarker candidates of septic infection. Validation the clinical use of these biomarker candidates may significantly impact the diagnosis and prognosis of sepsis. In addition, the molecular mechanisms revealed by these studies may also guide the development of more effective treatments.

Management of hyponatremia in various clinical situations

OPINION STATEMENT

Hyponatremia is the most common electrolyte abnormality in both inpatient and outpatient settings. The condition primarily results from the combination of impaired free water excretion due to elevated vasopressin levels in conjunction with a source of free water intake. Recent studies have revealed that even mild and asymptomatic hyponatremia is associated with deleterious consequences. It is an independent risk factor for mortality and is also associated with increased length of hospitalization and hospital costs. Even mild chronic hyponatremia can result in subtle neurologic impairment and bone demineralization, leading to falls and associated bone fractures in the elderly. Hyponatremia can be a difficult condition to treat, with varying therapeutic strategies based on the etiology, severity, duration, and extent of neurologic symptoms. The ideal magnitude of correction is also controversial, as both inadequate therapy and overly aggressive therapy can result in neurologic injury. Formulas that have been devised to aid in the treatment of hyponatremia can be inaccurate in that they fail to adequately account for the renal response to therapy. Hyponatremic encephalopathy is the most serious complication of hyponatremia, and can result in permanent neurologic impairment or death if left untreated. Individuals most at risk for developing hyponatremic encephalopathy are postmenarchal women, children under 16 years of age, patients with central nervous system disease or hypoxemia, and patients in the postoperative setting. The preferred therapy for hyponatremic encephalopathy is a 100-ml bolus of 3 % sodium chloride (513 mEq/L) administered in repeated doses until symptoms reverse, with the goal of increasing the serum sodium 5-6 mEq/L. Vasopressin (V2) antagonists (vaptans) are not appropriate for the management of acute hyponatremic encephalopathy, as the onset of action is not sufficiently rapid and the increase in sodium is not predictable. Vaptans are primarily indicated for the treatment of asymptomatic hyponatremia due to SIAD that is refractory to conventional measures.

Circulating cytokines in predicting development of severe acute pancreatitis

Introduction

Severe acute pancreatitis (AP) is associated with high morbidity and mortality. Early prediction of severe AP is needed to improve patient outcomes. The aim of the present study was to find novel cytokines or combinations of cytokines that can be used for the early identification of patients with AP at risk for severe disease.

Methods

We performed a prospective study of 163 nonconsecutive patients with AP, of whom 25 had severe AP according to the revised Atlanta criteria. Admission serum levels of 48 cytokines and growth factors were determined using Bio-Plex Pro Human Cytokine Assay 21-plex and 27-plex magnetic bead suspension panels. Admission plasma levels of C-reactive protein (CRP), creatinine and calcium were measured for comparison. In subgroup analyses, we assessed the cytokine profiles of patients with severe AP (n = 14) who did not have organ dysfunction (OD) upon admission (modified Marshall score <2).

Results

Of 14 cytokines elevated in the severe AP group, interleukin 6 (IL-6) and hepatocyte growth factor (HGF) levels were independent prognostic markers of severe AP. IL-6, HGF and a combination of them predicted severe AP with sensitivities of 56.0%, 60.0% and 72.0%, respectively, and specificities of 90.6%, 92.8% and 89.9%, respectively. The corresponding positive likelihood ratio (LR+) values were 5.9, 8.3 and 7.1, respectively. The predictive values of CRP, creatinine and calcium were comparable to those of the cytokines. In subgroup analyses of patients with severe AP and without OD upon admission, we found that IL-8, HGF and granulocyte colony-stimulating factor (G-CSF) levels predicted the development of severe AP, with G-CSF being the most accurate cytokine at a sensitivity of 35.7%, a specificity of 96.1% and a LR+ of 9.1.

Conclusions

IL-6 and HGF levels upon admission have prognostic value for severe AP which is similar to levels of CRP, creatinine and calcium. Although IL-6 and HGF, as either single or combined markers, were not perfect in identifying patients at risk for severe AP, the possibility that combining them with novel prognostic markers other than cytokines might improve prognostic accuracy needs to be studied. The accuracy of IL-8, HGF and G-CSF levels in predicting severe AP in patients without clinical signs of OD upon admission warrants larger studies.

Functional genomics in the study of mind-body therapies

BACKGROUND

Mind-body therapies (MBTs) are used throughout the world in treatment, disease prevention, and health promotion. However, the mechanisms by which MBTs exert their positive effects are not well understood. Investigations into MBTs using functional genomics have revolutionized the understanding of MBT mechanisms and their effects on human physiology.

METHODS

We searched the literature for the effects of MBTs on functional genomics determinants using MEDLINE, supplemented by a manual search of additional journals and a reference list review.

RESULTS

We reviewed 15 trials that measured global or targeted transcriptomic, epigenomic, or proteomic changes in peripheral blood. Sample sizes ranged from small pilot studies (n=2) to large trials (n=500). While the reliability of individual genes from trial to trial was often inconsistent, genes related to inflammatory response, particularly those involved in the nuclear factor-kappa B (NF-κB) pathway, were consistently downregulated across most studies.

CONCLUSION

In general, existing trials focusing on gene expression changes brought about by MBTs have revealed intriguing connections to the immune system through the NF-κB cascade, to telomere maintenance, and to apoptotic regulation. However, these findings are limited to a small number of trials and relatively small sample sizes. More rigorous randomized controlled trials of healthy subjects and specific disease states are warranted. Future research should investigate functional genomics areas both upstream and downstream of MBT-related gene expression changes-from epigenomics to proteomics and metabolomics.