Rationale: Septic shock is a significant cause of morbidity and mortality in the pediatric population. Early recognition of septic shock and appropriate treatment increase survival rate; thus, developing new diagnostic tools may improve patients’ outcomes. Objectives: To determine whether a metabolomics approach could be useful in the diagnosis and prognosis of septic shock in pediatric intensive care unit (PICUs). Methods: Serum samples were collected from 60 patients with septic shock, 40 PICU patients with systemic inflammatory response syndrome (not suspected of having an infection), and 40 healthy children. Proton nuclear magnetic resonance spectroscopy spectra were analyzed and quantified using targeted profiling methodology. Measurements and Main Results: Multivariate statistical analysis was applied to detect specific patterns in metabolic profiles and to highlight differences between patient samples. Supervised analysis afforded good predictive models and managed to separate patient populations. Some of the metabolite concentrations identified in serum samples changed markedly, indicating their influence on the separation between patient groups. These metabolites represent a composite biopattern of the pediatric metabolic response to septic shock and might be considered as the basis for a biomarker panel for the diagnosis of septic shock and its mortality in PICU. Conclusions: Our results indicate that nuclear magnetic resonance metabolite profiling might serve as a promising approach for the diagnosis and prediction of mortality in septic shock in a pediatric population and that quantitative metabolomics methods can be applied in the clinical evaluations of pediatric septic shock.

Rationale: In septic animal models mesenchymal stem (stromal) cells (MSCs) modulate inflammation, enhance tissue repair and pathogen clearance, and reduce death. Objectives: To conduct a phase I dose escalation trial of MSCs in septic shock with the primary objective of examining the safety and tolerability of MSCs. Methods: We enrolled nine participants within 24 hours of admission to the ICU. A control cohort of 21 participants was enrolled before starting the MSC interventional cohort to characterize expected adverse events (AEs) and to serve as a comparator for the intervention cohort. Three separate MSC dose cohorts, with three participants per cohort, received a single intravenous dose of 0.3, 1.0, and 3.0 × 106 cells/kg. A prespecified safety plan monitored participants for the occurrence of AEs; cytokines were collected at prespecified time points. Measurements and Main Results: Ages of participants in the interventional versus observational cohorts were median of 71 (range, 38–91) and 61 (range, 23–95). Acute Physiology and Chronic Health Evaluation scores were median of 25 (range, 11–28) and 26 (range, 17–32). MSC doses ranged from 19 to 250 million cells. There were no prespecified MSC infusion–associated or serious unexpected AEs, nor any safety or efficacy signals for the expected AEs or the measured cytokines between the interventional and observational cohorts. Conclusions: The infusion of freshly cultured allogenic bone marrow–derived MSCs, up to a dose of 3 million cells/kg (250 million cells), into participants with septic shock seems safe. Clinical trial registered with www.clinicaltrials.gov (NCT02421484).

Introduction: Septic shock is a major life-threatening condition in critically ill patients and it is well known that early recognition of septic shock and expedient initiation of appropriate treatment improves patient outcome. Unfortunately, to date no single compound has shown sufficient sensitivity and specificity to be used as a routine biomarker for early diagnosis and prognosis of septic shock in the intensive care unit (ICU). Therefore, the identification of new diagnostic tools remains a priority for increasing the survival rate of ICU patients. In this study, we have evaluated whether a combined nuclear magnetic resonance spectroscopy-based metabolomics and a multiplex cytokine/chemokine profiling approach could be used for diagnosis and prognostic evaluation of septic shock patients in the ICU. Methods: Serum and plasma samples were collected from septic shock patients and ICU controls (ICU patients with the systemic inflammatory response syndrome but not suspected of having an infection). ¹H Nuclear magnetic resonance spectra were analyzed and quantified using the targeted profiling methodology. The analysis of the inflammatory mediators was performed using human cytokine and chemokine assay kits. Results: By using multivariate statistical analysis we were able to distinguish patient groups and detect specific metabolic and cytokine/chemokine patterns associated with septic shock and its mortality. These metabolites and cytokines/chemokines represent candidate biomarkers of the human response to septic shock and have the potential to improve early diagnosis and prognosis of septic shock. Conclusions: Our findings show that integration of quantitative metabolic and inflammatory mediator data can be utilized for the diagnosis and prognosis of septic shock in the ICU.

Metabolomics is a tool that has been used for the diagnosis and prognosis of specific diseases. The purpose of this study was to examine if metabolomics could be used as a potential diagnostic and prognostic tool for H1N1 pneumonia. Our hypothesis was that metabolomics can potentially be used early for the diagnosis and prognosis of H1N1 influenza pneumonia. 1H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to profile the metabolome in 42 patients with H1N1 pneumonia, 31 ventilated control subjects in the intensive care unit (ICU), and 30 culture-positive plasma samples from patients with bacterial community-acquired pneumonia drawn within the first 24 h of hospital admission for diagnosis and prognosis of disease. We found that plasma-based metabolomics from samples taken within 24 h of hospital admission can be used to discriminate H1N1 pneumonia from bacterial pneumonia and nonsurvivors from survivors of H1N1 pneumonia. Moreover, metabolomics is a highly sensitive and specific tool for the 90-day prognosis of mortality in H1N1 pneumonia. This study demonstrates that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU on the basis of plasma samples taken within 24 h of hospital/ICU admission, early in the course of disease.

Traumatic brain injury (TBI) is one of the leading causes of disability and mortality worldwide. The TBI pathogenesis can induce broad pathophysiological consequences and clinical outcomes attributed to the complexity of the brain. Thus, the diagnosis and prognosis are important issues for the management of mild, moderate, and severe forms of TBI. Metabolomics of readily accessible biofluids is a promising tool for establishing more useful and reliable biomarkers of TBI than using clinical findings alone. Metabolites are an integral part of all biochemical and pathophysiological pathways. Metabolomic processes respond to the internal and external stimuli resulting in an alteration of metabolite concentrations. Current high-throughput and highly sensitive analytical tools are capable of detecting and quantifying small concentrations of metabolites, allowing one to measure metabolite alterations after a pathological event when compared to a normal state or a different pathological process. Further, these metabolic biomarkers could be used for the assessment of injury severity, discovery of mechanisms of injury, and defining structural damage in the brain in TBI. Metabolic biomarkers can also be used for the prediction of outcome, monitoring treatment response, in the assessment of or prognosis of post-injury recovery, and potentially in the use of neuroplasticity procedures. Metabolomics can also enhance our understanding of the pathophysiological mechanisms of TBI, both in primary and secondary injury. Thus, this review presents the promising application of metabolomics for the assessment of TBI as a stand-alone platform or in association with proteomics in the clinical setting.