Serum Metabolomics as a Powerful Tool in Distinguishing Trauma from Other Critical Illness Conditions

Critical illness is highly variable, complicating patient care and recovery. We have previously used metabolomics to investigate several causes of intensive care unit admission, seeking to assess changes in metabolism occurring with each condition. We present a meta-analysis of these serum metabolomes, exploring how the metabolomes differ with each condition. We also present how mass spectrometry-based metabolomics could be used for predictive monitoring. Serum metabolites were previously quantified using nuclear magnetic resonance spectroscopy in patients with traumatic injury, respiratory failure, pancreatitis, and combat trauma. Healthy controls are also included. Spectral features were analyzed with principal component analysis (PCA) to explore patterns in patients’ underlying conditions. PCA suggests trauma metabolic profiles, particularly combat casualties, differ from other conditions. Principal components 2 and 3, accounting for 16% of the variation in the model, distinguish samples obtained from trauma patients. Metabolomics is a powerful tool for quantifying variability in critical illness, highlighting trauma as separate from other conditions. This observation is in line with the -omics literature, which has described a massive global “genomic storm” in response to severe injury. Mass spectrometry highlights this extreme variability, which occurs in ICU patients but not healthy controls. With new technology, metabolomics could be used to bring faster, individualized patient care to the ICU

Modeling the Heart as a Communication System

Electrical communication between cardiomyocytes can be perturbed during arrhythmia, but these perturbations are not captured by conventional electrocardiographic metrics. We developed a theoretical framework to quantify electrical communication using information theory metrics in 2-dimensional cell lattice models of cardiac excitation propagation. The time series generated by each cell was coarse-grained to 1 when excited or 0 when resting. The Shannon entropy for each cell was calculated from the time series during four clinically important heart rhythms: normal heartbeat, anatomical reentry, spiral reentry, and multiple reentry. We also used mutual information to perform spatial profiling of communication during these cardiac arrhythmias. We found that information sharing between cells was spatially heterogeneous. In addition, cardiac arrhythmia significantly impacted information sharing within the heart. Entropy localized the path of the drifting core of spiral reentry, which could be an optimal target of therapeutic ablation. We conclude that information theory metrics can quantitatively assess electrical communication among cardiomyocytes. The traditional concept of the heart as a functional syncytium sharing electrical information cannot predict altered entropy and information sharing during complex arrhythmia. Information theory metrics may find clinical application in the identification of rhythm-specific treatments which are currently unmet by traditional electrocardiographic techniques.Comment: 26 pages (including Appendix), 6 figures, 8 videos (not uploaded due to size limitation

Metabolic networks in a porcine model of trauma and hemorrhagic shock demonstrate different control mechanism with carbohydrate pre-feed

Background: Treatment with oral carbohydrate prior to trauma and hemorrhage confers a survival benefit in small animal models. The impact of fed states on survival in traumatically injured humans is unknown. This work uses regulatory networks to examine the effect of carbohydrate pre-feeding on metabolic response to polytrauma and hemorrhagic shock in a clinically-relevant large animal model. Methods: Male Yorkshire pigs were fasted overnight (n = 64). Pre-fed animals (n = 32) received an oral bolus of Karo\textregistered\syrup before sedation. All animals underwent a standardized trauma, hemorrhage, and resuscitation protocol. Serum samples were obtained at set timepoints. Proton NMR was used to identify and quantify serum metabolites. Metabolic regulatory networks were constructed from metabolite concentrations and rates of change in those concentrations to identify controlled nodes and controlling nodes of the network. Results: Oral carbohydrate pre-treatment was not associated with survival benefit. Six metabolites were identified as controlled nodes in both groups: adenosine, cytidine, glycerol, hypoxanthine, lactate, and uridine. Distinct groups of controlling nodes were associated with controlled nodes; however, the composition of these groups depended on feeding status. Conclusions: A common metabolic output, typically associated with injury and hypoxia, results from trauma and hemorrhagic shock. However, this output is directed by different metabolic inputs depending upon the feeding status of the subject. Nodes of the network that are related to mortality can potentially be manipulated for therapeutic effect; however, these nodes differ depending upon feeding status

Metabolomics identifies circadian desynchronization and distinct intra-patient variability patterns in critical illness

Data were taken for 5 ICU patients and 5 healthy controls. Study participant ID's are preserved across the files. Healthy control IDs: CR_P_01, CR_P_02, CR_P_03, CR_P_05, CR_P_06 ICU patient IDs: CR_P_07, CR_P_08, CR_P_10, CR_P_11, CR_P_12Background: Synchronized circadian rhythms play a key role in coordinating physiologic health. Desynchronized circadian rhythms may predispose individuals to disease or be indicative of underlying disease. ICU patients likely experience desynchronized circadian rhythms due to disruptive environmental conditions in the ICU and underlying pathophysiology. This observational pilot study was undertaken to determine if circadian rhythms are altered in ICU patients relative to healthy controls by profiling circadian rhythms in vital signs and plasma metabolites. Methods: We monitored circadian rhythms in 5 healthy controls and 5 ICU patients for 24 hours. Heart rate and blood pressure were measured every 30 minutes, temperature was measured every hour, and blood was sampled for mass spectrometry-based plasma metabolomics every 4 hours. Bedside sound levels were measured every minute. Circadian rhythms were evaluated in vitals and plasma metabolites individually and in each group using the cosinor method. Results: ICU patient rooms were significantly louder than healthy controls’ rooms and average noise levels were above EPA recommendations. Healthy controls generally had significant circadian rhythms individually and as a group. While a few ICU patients had significant circadian rhythms in isolated variables, no significant rhythms were identified in ICU patients as a group, except in cortisol. This indicates a lack of coherence in circadian phases and amplitudes among ICU patients. Finally, principal component analysis of metabolic profiles showed surprising patterns in plasma sample clustering. Each ICU patient’s samples were clearly discernable in individual clusters, separate from a single cluster of healthy controls. Conclusions: ICU patients’ circadian rhythms show significant desynchronization compared to healthy controls. Clustering of plasma metabolic profiles suggests that metabolomics could be used to track individual patients. Our results show global disordering of metabolism and the circadian system in ICU patients which should be characterized further in order to determine implications for patient care

Metabolomics in COPD Acute Respiratory Failure Requiring Noninvasive Positive Pressure Ventilation

We aimed to investigate whether metabolomic analysis can discriminate acute respiratory failure due to COPD exacerbation from respiratory failure due to heart failure and pneumonia. Since COPD exacerbation is often overdiagnosed, we focused on those COPD exacerbations that were severe enough to require noninvasive mechanical ventilation. We enrolled stable COPD subjects and patients with acute respiratory failure requiring noninvasive mechanical ventilation due to COPD, heart failure, and pneumonia. We excluded subjects with history of both COPD and heart failure and patients with obstructive sleep apnea and obstructive lung disease other than COPD. We performed metabolomics analysis using NMR. We constructed partial least squares discriminant analysis (PLS-DA) models to distinguish metabolic profiles. Serum (p=0.001, R2 = 0.397, Q2 = 0.058) and urine metabolic profiles (p<0.001, R2 = 0.419, Q2 = 0.142) were significantly different between the four diagnosis groups by PLS-DA. After excluding stable COPD patients, the metabolomes of the various respiratory failure groups did not cluster separately in serum (p=0.2, R2 = 0.631, Q2 = 0.246) or urine (p=0.065, R2 = 0.602, Q2 = −0.134). However, several metabolites in the serum were reduced in patients with COPD exacerbation and pneumonia. We did not find a metabolic profile unique to COPD exacerbation, but we were able to clearly and reliably distinguish stable COPD patients from patients with respiratory failure in both serum and urine

A four-compartment metabolomics analysis of the liver, muscle, serum, and urine response to polytrauma with hemorrhagic shock following carbohydrate prefeed.

OBJECTIVE:Hemorrhagic shock accompanied by injury represents a major physiologic stress. Fasted animals are often used to study hemorrhagic shock (with injury). A fasted state is not guaranteed in the general human population. The objective of this study was to determine if fed animals would exhibit a different metabolic profile in response to hemorrhagic shock with trauma when compared to fasted animals. METHODS:Proton (1H) NMR spectroscopy was used to determine concentrations of metabolites from four different compartments (liver, muscle, serum, urine) taken at defined time points throughout shock/injury and resuscitation. PLS-DA was performed and VIP lists established for baseline, shock and resuscitation (10 metabolites for each compartment at each time interval) on metabolomics data from surviving animals. RESULTS:Fed status prior to the occurrence of hemorrhagic shock with injury alters the metabolic course of this trauma and potentially affects mortality. The death rate for CPF animals is higher than FS animals (47 vs 28%). The majority of deaths occur post-resuscitation suggesting reperfusion injury. The metabolomics response to shock reflects priorities evident at baseline. FS animals raise the baseline degree of proteolysis to provide additional amino acids for energy production while CPF animals rely on both glucose and, to a lesser extent, amino acids. During early resuscitation levels of metabolites associated with energy production drop, suggesting diminished demand. CONCLUSIONS:Feeding status prior to the occurrence of hemorrhagic shock with injury alters the metabolic course of this trauma and potentially affects mortality. The response to shock reflects metabolic priorities at baseline

Fed State Prior to Hemorrhagic Shock and Polytrauma in a Porcine Model Results in Altered Liver Transcriptomic Response

<div><p>Hemorrhagic shock is a leading cause of trauma-related mortality in both civilian and military settings. Resuscitation often results in reperfusion injury and survivors are susceptible to developing multiple organ failure (MOF). The impact of fed state on the overall response to shock and resuscitation has been explored in some murine models but few clinically relevant large animal models. We have previously used metabolomics to establish that the fed state results in a different metabolic response in the porcine liver following hemorrhagic shock and resuscitation. In this study, we used our clinically relevant model of hemorrhagic shock and polytrauma and the Illumina HiSeq platform to determine if the liver transcriptomic response is also altered with respect to fed state. Functional analysis of the response to shock and resuscitation confirmed several typical responses including carbohydrate metabolism, cytokine inflammation, decreased cholesterol synthesis, and apoptosis. Our findings also suggest that the fasting state, relative to a carbohydrate prefed state, displays decreased carbohydrate metabolism, increased cytoskeleton reorganization and decreased inflammation in response to hemorrhagic shock and reperfusion. Evidence suggests that this is a consequence of a shrunken, catabolic state of the liver cells which provides an anti-inflammatory condition that partially mitigates hepatocellar damage.</p></div

Purine degradation/salvage pathway.

<p>Metabolomics evidence from four compartments suggests alternate routes for observed differences in purine abundances. ATP is degraded in a series of reactions to uric acid or allantoin. Under non-stress conditions, this degradation process proceeds at a low level. When physiologic conditions change, intermediates in the pathway can be diverted to meet these demands. For example, during fasting, IMP can be salvaged for the production of ATP thus reducing the level of HX. In our study, HX levels are higher at baseline in liver of CPF animals. We propose that this observation is a result of increased salvage in FS animals. During ischemia 5'-nucleotidase acts on AMP to generate adenosine, a potential vasodilator. In our study, adenosine levels are ~3X higher in the liver of CPF animals when compared to FS animals suggesting a greater need for vasodilation. Metabolites in red were identified as VIP metabolites by PLS-DA analysis. Letters in superscript indicate the compartment the metabolite was observed in: liver (L), muscle (M), serum (S), or urine (U).</p