Metabolomics Profiling As a Diagnostic Tool in Severe Traumatic Brain Injury

Easy-Amanida: An R Shiny application for the meta-analysis of aggregate results in clinical metabolomics using Amanida and Webchem

Meta-analysis is a useful tool in clinical research, as it combines the results of multiple clinical studies to improve precision when answering a particular scientific question. While there has been a substantial increase in publications using meta-analysis in various clinical research topics, the number of published meta-analyses in metabolomics is significantly lower compared to other omics disciplines. Metabolomics is the study of small chemical compounds in living organisms, which provides important insights into an organism's phenotype. However, the wide variety of compounds and the different experimental methods used in metabolomics make it challenging to perform a thorough meta-analysis. Additionally, there is a lack of consensus on reporting statistical estimates, and the high number of compound naming synonyms further complicates the process. Easy-Amanida is a new tool that combines two R packages, "amanida" and "webchem", to enable meta-analysis of aggregate statistical data, like p-value and fold-change, while ensuring the compounds naming harmonization. The Easy-Amanida app is implemented in Shiny, an R package add-on for interactive web apps, and provides a workflow to optimize the naming combination. This article describes all the steps to perform the meta-analysis using Easy-Amanida, including an illustrative example for interpreting the results. The use of aggregate statistics metrics extends the use of Easy-Amanida beyond the metabolomics field.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

Curcumin alleviates traumatic brain injury induced by gas explosion through modulating gut microbiota and suppressing the LPS/TLR4/MyD88/NF-κB pathway

Gas explosions (GE) are a prevalent and widespread cause of traumatic brain injury (TBI) in coal miners. However, the impact and mechanism of curcumin on GE-induced TBI in rats remain unclear. In this study, we simulated GE-induced TBI in rats and administered curcumin orally at a dose of 100 mg/kg every other day for 7 days to modulate the gut microbiota in TBI rats. We employed 16S rRNA sequencing and LC-MS/MS metabolomic analysis to investigate changes in the intestinal flora and its metabolic profile. Additionally, we utilized ELISA, protein assays, and immunohistochemistry to assess neuroinflammatory signaling molecules for validation. In a rat TBI model, GE resulted in weight loss, pathological abnormalities, and cortical hemorrhage. Treatment with curcumin significantly mitigated histological abnormalities and microscopic mitochondrial structural changes in brain tissue. Furthermore, curcumin treatment markedly ameliorated GE-induced brain dysfunction by reducing the levels of several neuroinflammatory signaling molecules, including neuron-specific enolase, interleukin (IL)-1β, IL-6, and cryptothermic protein 3. Notably, curcumin reshaped the gut microbiome by enhancing evenness, richness, and composition. Prevotella_9, Alloprevotella, Bacilli, Lactobacillales, Proteobacteria, and Gammaproteobacteria were identified as prominent members of the gut microbiota, increasing the linear discriminant analysis scores and specifically enhancing the abundance of bacteria involved in the nuclear factor (NF)-κB signaling pathway, such as Lachnospiraceae and Roseburia. Additionally, there were substantial alterations in serum metabolites associated with metabolic NF-κB signaling pathways in the model group. Curcumin administration reduced serum lipopolysaccharide levels and downregulated downstream Toll-like receptor (TLR)4/myeloid differentiation primary response 88 (MyD88)/NF-κB signaling. Furthermore, curcumin alleviated GE-induced TBI in rats by modulating the gut microbiota and its metabolites. Based on these protective effects, curcumin may exert its influence on the gut microbiota and the TLR4/MyD88/NF-κB signaling pathways to ameliorate GE-induced TBI.

Untargeted Metabolomic Analyses of Body Fluids to Differentiate TBI DOC and NTBI DOC

OBJECTIVE

To investigate the metabolomic differences between Traumatic brain injury (TBI) disorder of consciousness (DOC) patients and non-traumatic brain injury (NTBI) DOC patients by using cerebrospinal fluid (CSF), serum and urine samples beneficial to understand the pathological mechanism differences between the two etiologies, provide potential clues for the subsequent treatment and prognosis, and investigate the metabolome differences and similarities between TBI and NTBI among three different body fluids.

METHODS

In total, 24 TBI DOC subjects and 29 NTBI DOC subjects were enrolled. CSF, serum and urine samples from TBI DOC and NTBI DOC patients were collected and analyzed by performing UPLC-MS. The statistical methods and pathway analyses were applied to discover potential biomarkers and altered metabolic functions.

RESULTS

When comparing TBI DOC and NTBI DOC, 36, 31 and 52 differential metabolites were obtained in CSF, serum and urine, respectively. The functional analysis of differential metabolites obtained in CSF, serum and urine were all related to amino acid metabolism. Except for amino acid metabolism, metabolic biomarkers in CSF, serum and urine mainly focus on central function, cognitive function, necrosis and apoptosis and neurological function, respectively. In CSF, the highest AUC was 0.864 (Isoproturon) and 0.816 (Proline betaine). Then, the AUC of NFurfurylformamide in serum was 0.941, while the AUC of Dihydronepetalactone and Doxepin N-oxide glucuronide were 1.0 in urine.

CONCLUSION

CSF, serum and urine metabolomic analyses could differentiate TBI DOC from NTBI DOC and functional analyses showed a metabolic change difference between TBI DOC and NTBI DOC.

The longitudinal biochemical profiling of TBI in a drop weight model of TBI

Traumatic brain injury (TBI) is a major cause of mortality and disability worldwide, particularly among individuals under the age of 45. It is a complex, and heterogeneous disease with a multifaceted pathophysiology that remains to be elucidated. Metabolomics has the potential to identify metabolic pathways and unique biochemical profiles associated with TBI. Herein, we employed a longitudinal metabolomics approach to study TBI in a weight drop mouse model to reveal metabolic changes associated with TBI pathogenesis, severity, and secondary injury. Using proton nuclear magnetic resonance (1H NMR) spectroscopy, we biochemically profiled post-mortem brain from mice that suffered mild TBI (N = 25; 13 male and 12 female), severe TBI (N = 24; 11 male and 13 female) and sham controls (N = 16; 11 male and 5 female) at baseline, day 1 and day 7 following the injury. 1H NMR-based metabolomics, in combination with bioinformatic analyses, highlights a few significant metabolites associated with TBI severity and perturbed metabolism related to the injury. We report that the concentrations of taurine, creatinine, adenine, dimethylamine, histidine, N-Acetyl aspartate, and glucose 1-phosphate are all associated with TBI severity. Longitudinal metabolic observation of brain tissue revealed that mild TBI and severe TBI lead distinct metabolic profile changes. A multi-class model was able to classify the severity of injury as well as time after TBI with estimated 86% accuracy. Further, we identified a high degree of correlation between respective hemisphere metabolic profiles (r > 0.84, p < 0.05, Pearson correlation). This study highlights the metabolic changes associated with underlying TBI severity and secondary injury. While comprehensive, future studies should investigate whether: (a) the biochemical pathways highlighted here are recapitulated in the brain of TBI sufferers and (b) if the panel of biomarkers are also as effective in less invasively harvested biomatrices, for objective and rapid identification of TBI severity and prognosis.

A metabolomic and proteomic analysis of pathologic hypercoagulability in traumatic brain injury patients after dura violation

BACKGROUND

The coagulopathy of traumatic brain injury (TBI) remains poorly understood. Contradictory descriptions highlight the distinction between systemic and local coagulation, with descriptions of systemic hypercoagulability despite intracranial hypocoagulopathy. This perplexing coagulation profile has been hypothesized to be due to tissue factor release. The objective of this study was to assess the coagulation profile of TBI patients undergoing neurosurgical procedures. We hypothesize that dura violation is associated with higher tissue factor and conversion to a hypercoagulable profile and unique metabolomic and proteomic phenotype.

METHODS

This is a prospective, observational cohort study of all adult TBI patients at an urban, Level I trauma center who underwent a neurosurgical procedure from 2019 to 2021. Whole blood samples were collected before and then 1 hour following dura violation. Citrated rapid and tissue plasminogen activator (tPA) thrombelastography (TEG) were performed, in addition to measurement of tissue factory activity, metabolomics, and proteomics.

RESULTS

Overall, 57 patients were included. The majority (61%) were male, the median age was 52 years, 70% presented after blunt trauma, and the median Glasgow Coma Score was 7. Compared with pre-dura violation, post-dura violation blood demonstrated systemic hypercoagulability, with a significant increase in clot strength (maximum amplitude of 74.4 mm vs. 63.5 mm; p < 0.0001) and a significant decrease in fibrinolysis (LY30 on tPAchallenged TEG of 1.4% vs. 2.6%; p = 0.04). There were no statistically significant differences in tissue factor. Metabolomics revealed notable increases in metabolites involved in late glycolysis, cysteine, and one-carbon metabolites, and metabolites involved in endothelial dysfunction/arginine metabolism/responses to hypoxia. Proteomics revealed notable increase in proteins related to platelet activation and fibrinolysis inhibition.

CONCLUSION

A systemic hypercoagulability is observed in TBI patients, characterized by increased clot strength and decreased fibrinolysis and a unique metabolomic and proteomics phenotype independent of tissue factor levels.

Metabolomics in severe traumatic brain injury: a scoping review

BACKGROUND

Diagnosis and prognostication of severe traumatic brain injury (sTBI) continue to be problematic despite years of research efforts. There are currently no clinically reliable biomarkers, though advances in protein biomarkers are being made. Utilizing Omics technology, particularly metabolomics, may provide new diagnostic biomarkers for sTBI. Several published studies have attempted to determine the specific metabolites and metabolic pathways involved; these studies will be reviewed.

AIMS

This scoping review aims to summarize the current literature concerning metabolomics in sTBI, review the comprehensive data, and identify commonalities, if any, to define metabolites with potential clinical use. In addition, we will examine related metabolic pathways through pathway analysis.

METHODS

Scoping review methodology was used to examine the current literature published in Embase, Scopus, PubMed, and Medline. An initial 1090 publications were identified and vetted with specific inclusion criteria. Of these, 20 publications were selected for further examination and summary. Metabolic data was classified using the Human Metabolome Database (HMDB) and arranged to determine the 'recurrent' metabolites and classes found in sTBI. To help understand potential mechanisms of injury, pathway analysis was performed using these metabolites and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database.

RESULTS

Several metabolites related to sTBI and their effects on biological pathways were identified in this review. Across the literature, proline, citrulline, lactate, alanine, valine, leucine, and serine all decreased in adults post sTBI, whereas both octanoic and decanoic acid increased. Hydroxy acids and organooxygen compounds generally increased following sTBI, while most carboxylic acids decreased. Pathway analysis showed significantly affected glycine and serine metabolism, glycolysis, branched-chain amino acid (BCAA) metabolism, and other amino acid metabolisms. Interestingly, no tricarboxylic acid cycle metabolites were affected.

CONCLUSION

Aside from a select few metabolites, classification of a metabolic profile proved difficult due to significant ambiguity between study design, sample size, type of sample, metabolomic detection techniques, and other confounding variables found in sTBI literature. Given the trends found in some studies, further metabolomics investigation of sTBI may be useful to identify clinically relevant metabolites.

Whole-Blood Metabolomics of a Rat Model of Repetitive Concussion

Mild traumatic brain injury (mTBI) and repetitive mTBI (RmTBI) are silent epidemics, and so far, there is no objective diagnosis. The severity of the injury is solely based on the Glasgow Coma Score (GCS) scale. Most patients suffer from one or more behavioral abnormalities, such as headache, amnesia, cognitive decline, disturbed sleep pattern, anxiety, depression, and vision abnormalities. Additionally, most neuroimaging modalities are insensitive to capture structural and functional alterations in the brain, leading to inefficient patient management. Metabolomics is one of the established omics technologies to identify metabolic alterations, mostly in biofluids. NMR-based metabolomics provides quantitative metabolic information with non-destructive and minimal sample preparation. We employed whole-blood NMR analysis to identify metabolic markers using a high-field NMR spectrometer (800 MHz). Our approach involves chemical-free sample pretreatment and minimal sample preparation to obtain a robust whole-blood metabolic profile from a rat model of concussion. A single head injury was given to the mTBI group, and three head injuries to the RmTBI group. We found significant alterations in blood metabolites in both mTBI and RmTBI groups compared with the control, such as alanine, branched amino acid (BAA), adenosine diphosphate/adenosine try phosphate (ADP/ATP), creatine, glucose, pyruvate, and glycerphosphocholine (GPC). Choline was significantly altered only in the mTBI group and formate in the RmTBI group compared with the control. These metabolites corroborate previous findings in clinical and preclinical cohorts. Comprehensive whole-blood metabolomics can provide a robust metabolic marker for more accurate diagnosis and treatment intervention for a disease population.

Clinical Theragnostic Signature of Extracellular Vesicles in Traumatic Brain Injury (TBI)

Traumatic brain injury (TBI) is a common cause of disability and fatality worldwide. Depending on the clinical presentation, it is a type of acquired brain damage that can be mild, moderate, or severe. The degree of patient's discomfort, prognosis, therapeutic approach, survival rates, and recurrence can all be strongly impacted by an accurate diagnosis made early on. The Glasgow Coma Scale (GCS), along with neuroimaging (MRI (Magnetic Resonance Imaging) and CT scan), is a neurological assessment tools used to evaluate and categorize the severity of TBI based on the patient's level of consciousness, eye opening, and motor response. Extracellular vesicles (EVs) are a growing domain, explaining neurological complications in a more detailed manner. EVs, in general, play a role in cellular communication. Its molecular signature such as DNA, RNA, protein, etc. contributes to the status (health or pathological stage) of the parental cell. Brain-derived EVs support more specific screening (diagnostic and prognostic) in TBI research. Therapeutic impact of EVs are more promising for aiding in TBI healing. It is nontoxic, biocompatible, and capable of crossing the blood-brain barrier (BBB) to transport therapeutic molecules. This review has highlighted the relationships between EVs and TBI theranostics, EVs and TBI-related clinical trials, and related research domain-associated challenges and solutions. This review motivates further exploration of associations between EVs and TBI and develops a better approach to TBI management.

Dexamethasone-Enhanced Continuous Online Microdialysis for Neuromonitoring of O2 after Brain Injury

Traumatic brain injury (TBI) is a major public health crisis in many regions of the world. Severe TBI may cause a primary brain lesion with a surrounding penumbra of tissue that is vulnerable to secondary injury. Secondary injury presents as progressive expansion of the lesion, possibly leading to severe disability, a persistent vegetive state, or death. Real time neuromonitoring to detect and monitor secondary injury is urgently needed. Dexamethasone-enhanced continuous online microdialysis (Dex-enhanced coMD) is an emerging paradigm for chronic neuromonitoring after brain injury. The present study employed Dex-enhanced coMD to monitor brain K⁺ and O₂ during manually induced spreading depolarization in the cortex of anesthetized rats and after controlled cortical impact, a widely used rodent model of TBI, in behaving rats. Consistent with prior reports on glucose, O₂ exhibited a variety of responses to spreading depolarization and a prolonged, essentially permanent decline in the days after controlled cortical impact. These findings confirm that Dex-enhanced coMD delivers valuable information regarding the impact of spreading depolarization and controlled cortical impact on O₂ levels in the rat cortex.

A New Approach in the Treatment of Traumatic Brain Injury: The Effects of Levosimendan on Necrosis, Apoptosis, and Oxidative Stress

OBJECTIVE

Traumatic brain injury (TBI) is an essential and common health problem worldwide. Levosimendan is an inotropic and vasodilator drug used to treat heart failure. Moreover, it exerts pleiotropic effects and, thus, protective effects on many organs. The present study aimed to investigate the effect of levosimendan on necrosis, apoptosis, and reactive oxygen species in rats with TBI.

METHODS

The study included 28 female Wistar-Albino rats weighing 200-250 g. The rats were divided into 4 groups with 7 rats each as follows: Group 1: No trauma group (Control), Group 2: Traumatized, untreated group (T), Group 3: Levosimendan was administered at a dose of 12 μg/kg intraperitoneally 1 hour after the trauma (L1), Group 4: Levosimendan was administered at a dose of 12 μg/kg intraperitoneally 2 hours after the concussion (L2). After the experiment, the rats were decapitated, and the brain tissue was removed. Necrosis was assessed with Cresyl violet staining, apoptosis was assessed with immunohistochemical analysis, superoxide dismutase and catalase levels were measured with the spectrophotometric method, and malondialdehyde (MDA) levels were assessed by High-Performance Liquid Chromatography.

RESULTS

The number of necrotic cells in the L1 and L2 groups was significantly lower than in the K and T groups (P = 0.015 and P = 0.03, respectively). Although the active caspase-3 level was signified considerably in the T, L1, and L2 groups compared to the K group, no significant difference was found among these 3 groups (P > 0.05). The results of superoxide dismutase levels were similar to those of active caspase-3. catalase level was significantly higher in the K group than in the T and L2 groups (P = 0.045). Malondialdehyde activity was considerably higher in the L1 and L2 groups compared to the K group (P = 0.023).

CONCLUSIONS

Our results indicated that levosimendan may exert a neuroprotective effect by reducing necrosis in TBI and that levosimendan does not affect apoptosis and antioxidant levels in TBI. Comprehensive studies are needed to elucidate the effect of levosimendan on TBI fully.

Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review

Traumatic brain injury (TBI) is not a single disease state but describes an array of conditions associated with insult or injury to the brain. While some individuals with TBI recover within a few days or months, others present with persistent symptoms that can cause disability, neuropsychological trauma, and even death. Understanding, diagnosing, and treating TBI is extremely complex for many reasons, including the variable biomechanics of head impact, differences in severity and location of injury, and individual patient characteristics. Because of these confounding factors, the development of reliable diagnostics and targeted treatments for brain injury remains elusive. We argue that the development of effective diagnostic and therapeutic strategies for TBI requires a deep understanding of human neurophysiology at the molecular level and that the framework of multiomics may provide some effective solutions for the diagnosis and treatment of this challenging condition. To this end, we present here a comprehensive review of TBI biomarker candidates from across the multiomic disciplines and compare them with known signatures associated with other neuropsychological conditions, including Alzheimer’s disease and Parkinson’s disease. We believe that this integrated view will facilitate a deeper understanding of the pathophysiology of TBI and its potential links to other neurological diseases.

Serum metabolome associated with severity of acute traumatic brain injury

Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relationship to severity of injury and patient outcome. We performed a comprehensive metabolomics study in a cohort of 716 patients with TBI and non-TBI reference patients (orthopedic, internal medicine, and other neurological patients) from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) cohort. We identified panels of metabolites specifically associated with TBI severity and patient outcomes. Choline phospholipids (lysophosphatidylcholines, ether phosphatidylcholines and sphingomyelins) were inversely associated with TBI severity and were among the strongest predictors of TBI patient outcomes, which was further confirmed in a separate validation dataset of 558 patients. The observed metabolic patterns may reflect different pathophysiological mechanisms, including protective changes of systemic lipid metabolism aiming to maintain lipid homeostasis in the brain.

Blood-based biomarkers and traumatic brain injury-A clinical perspective

Blood-based biomarkers are promising tools to complement clinical variables and imaging findings in the diagnosis, monitoring and outcome prediction of traumatic brain injury (TBI). Several promising biomarker candidates have been found for various clinical questions, but the translation of TBI biomarkers into clinical applications has been negligible. Measured biomarker levels are influenced by patient-related variables such as age, blood-brain barrier integrity and renal and liver function. It is not yet fully understood how biomarkers enter the bloodstream from the interstitial fluid of the brain. In addition, the diagnostic performance of TBI biomarkers is affected by sampling timing and analytical methods. In this focused review, the clinical aspects of glial fibrillary acidic protein, neurofilament light, S100 calcium-binding protein B, tau and ubiquitin C-terminal hydrolase-L1 are examined. Current findings and clinical caveats are addressed.

UPLC-Q-TOF/MS-based plasma metabolome to identify biomarkers and time of injury in traumatic brain injured rats

BACKGROUND

To identify the potent metabolic biomarkers and time of injury of traumatic brain injured (TBI).

METHODS

A total of 70 Sprague-Dawley rats were used to establish the TBI model in this study. The serum was collected at 3 h, 6 h, 12 h, 24 h, 3 days and 7 days after surgery. Ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry was performed to analyze metabolic changes in the serum of the TBI rats from different groups. The differences between the metabolic profiles of the rats in seven groups were analyzed using partial least squares discriminant analysis.

RESULTS

Metabolic profiling revealed significant differences between the sham-operated and other groups. A total of 49 potential TBI metabolite biomarkers were identified between the sham-operated group and the model groups at different time points. Among them, six metabolites (methionine sulfone, kynurenine, 3-hydroxyanthranilic acid, 3-Indolepropionic acid, citric acid and glycocholic acid) were identified as biomarkers of TBI to estimate the injury time.

CONCLUSION

Using metabolomic analysis, we identified new TBI serum biomarkers for accurate detection and determination of the timing of TBI injury.

The relationship of oleic acid/albumin molar ratio and clinical outcomes in leptospirosis

Human leptospirosis is an acute infectious zoonosis presenting specific lipid disorders. Previous in vitro studies showed both leptospira glycolipoprotein endotoxin, and high oleic acid levels were associated with Na/K-ATPase inhibition that is amplified by the reduction of circulating albumin levels. In this study, we aimed to investigate the relationship of oleic acid/albumin (OA/A) molar ratio and clinical outcomes in Leptospirosis. Through a prospective observational cohort study employing high-performance liquid chromatography (HPLC) we sequentially determined serum concentrations of nonesterified fatty acids (NEFA) and albumin in twenty-eight patients with severe leptospirosis since their hospital admission. Twenty patients recovered, and eight died. Data was distributed in two groups according to clinical outcomes. Oleic acid/albumin molar ratios (OA/A), initial samples, were higher than those in healthy donors. The ratio OA/A, however, persisted high in dying patients, whereas patients who survived had a reduction matching to healthy donors. Biochemical alterations suggest that cure is correlated to the reestablishment of the OA/A molar ratio, while fatal outcomes related to persisting OA/A imbalances. Analysis by receiver operating characteristic (ROC) showed the area under the curve of 0.864 and the cutoff value of 0.715 being associated with a high odds ratio. Lipid analysis from patients with leptospirosis had an acute high serum OA/A molar ratio, and sustained imbalance has a high odds ratio and strong correlation with mortality.

"Omics" in traumatic brain injury: novel approaches to a complex disease

BACKGROUND

To date, there is neither any pharmacological treatment with efficacy in traumatic brain injury (TBI) nor any method to halt the disease progress. This is due to an incomplete understanding of the vast complexity of the biological cascades and failure to appreciate the diversity of secondary injury mechanisms in TBI. In recent years, techniques for high-throughput characterization and quantification of biological molecules that include genomics, proteomics, and metabolomics have evolved and referred to as omics.

METHODS

In this narrative review, we highlight how omics technology can be applied to potentiate diagnostics and prognostication as well as to advance our understanding of injury mechanisms in TBI.

RESULTS

The omics platforms provide possibilities to study function, dynamics, and alterations of molecular pathways of normal and TBI disease states. Through advanced bioinformatics, large datasets of molecular information from small biological samples can be analyzed in detail and provide valuable knowledge of pathophysiological mechanisms, to include in prognostic modeling when connected to clinically relevant data. In such a complex disease as TBI, omics enables broad categories of studies from gene compositions associated with susceptibility to secondary injury or poor outcome, to potential alterations in metabolites following TBI.

CONCLUSION

The field of omics in TBI research is rapidly evolving. The recent data and novel methods reviewed herein may form the basis for improved precision medicine approaches, development of pharmacological approaches, and individualization of therapeutic efforts by implementing mathematical "big data" predictive modeling in the near future.

Proteomic analysis identifies plasma correlates of remote ischemic conditioning in the context of experimental traumatic brain injury

Remote ischemic conditioning (RIC), transient restriction and recirculation of blood flow to a limb after traumatic brain injury (TBI), can modify levels of pathology-associated circulating protein. This study sought to identify TBI-induced molecular alterations in plasma and whether RIC would modulate protein and metabolite levels at 24 h after diffuse TBI. Adult male C57BL/6 mice received diffuse TBI by midline fluid percussion or were sham-injured. Mice were assigned to treatment groups 1 h after recovery of righting reflex: sham, TBI, sham RIC, TBI RIC. Nine plasma metabolites were significantly lower post-TBI (six amino acids, two acylcarnitines, one carnosine). RIC intervention returned metabolites to sham levels. Using proteomics analysis, twenty-four putative protein markers for TBI and RIC were identified. After application of Benjamini–Hochberg correction, actin, alpha 1, skeletal muscle (ACTA1) was found to be significantly increased in TBI compared to both sham groups and TBI RIC. Thus, identified metabolites and proteins provide potential biomarkers for TBI and therapeutic RIC in order to monitor disease progression and therapeutic efficacy.

Integrative Analysis of Circulating Metabolite Profiles and Magnetic Resonance Imaging Metrics in Patients with Traumatic Brain Injury

Recent evidence suggests that patients with traumatic brain injuries (TBIs) have a distinct circulating metabolic profile. However, it is unclear if this metabolomic profile corresponds to changes in brain morphology as observed by magnetic resonance imaging (MRI). The aim of this study was to explore how circulating serum metabolites, following TBI, relate to structural MRI (sMRI) findings. Serum samples were collected upon admission to the emergency department from patients suffering from acute TBI and metabolites were measured using mass spectrometry-based metabolomics. Most of these patients sustained a mild TBI. In the same patients, sMRIs were taken and volumetric data were extracted (138 metrics). From a pool of 203 eligible screened patients, 96 met the inclusion criteria for this study. Metabolites were summarized as eight clusters and sMRI data were reduced to 15 independent components (ICs). Partial correlation analysis showed that four metabolite clusters had significant associations with specific ICs, reflecting both the grey and white matter brain injury. Multiple machine learning approaches were then applied in order to investigate if circulating metabolites could distinguish between positive and negative sMRI findings. A logistic regression model was developed, comprised of two metabolic predictors (erythronic acid and myo-inositol), which, together with neurofilament light polypeptide (NF-L), discriminated positive and negative sMRI findings with an area under the curve of the receiver-operating characteristic of 0.85 (specificity = 0.89, sensitivity = 0.65). The results of this study show that metabolomic analysis of blood samples upon admission, either alone or in combination with protein biomarkers, can provide valuable information about the impact of TBI on brain structural changes.

Association between newborn screening analytes and hypoxic ischemic encephalopathy

Hypoxic ischemic encephalopathy (HIE) is a major cause of neonatal mortality and morbidity. Our study sought to examine whether patterns of newborn screening analytes differed between infants with and without neonatal HIE in order to identify opportunities for potential use of these analytes for diagnosis in routine clinical practice. We linked a population-based newborn screening registry with health databases to identify cases of HIE among term infants (≥37 weeks' gestation) in Ontario from 2010-2015. Correlations between HIE and screening analytes were examined using multivariable logistic regression models containing clinical factors and individual screening analytes (acyl-carnitines, amino acids, fetal-to-adult hemoglobin ratio, endocrine markers, and enzymes). Among 731,841 term infants, 3,010 were diagnosed with HIE during the neonatal period. Multivariable models indicated that clinical variables alone or in combination with hemoglobin values were not associated with HIE diagnosis. Although the model was improved after adding acyl-carnitines and amino acids, the ability of the model to identify infants with HIE was moderate. Our findings indicate that analytes associated with catabolic stress were altered in infants with HIE; however, future research is required to determine whether amino acid and acyl-carnitine profiles could hold clinical utility in the early diagnosis or clinical management of HIE. In particular, further research should examine whether cord blood analyses can be used to identify HIE within a clinically useful timeframe or to guide treatment and predict long-term health outcomes.

A prospective pilot study using metabolomics discloses specific fatty acid, catecholamine and tryptophan metabolic pathways as possible predictors for a negative outcome after severe trauma

Background

We wanted to define metabolomic patterns in plasma to predict a negative outcome in severe trauma patients.

Methods

A prospective pilot study was designed to evaluate plasma metabolomic patterns, established by liquid chromatography coupled to mass spectrometry, in patients allocated to an intensive care unit (in the University Hospital Arnau de Vilanova, Lleida, Spain) in the first hours after a severe trauma (n = 48). Univariate and multivariate statistics were employed to establish potential predictors of mortality.

Results

Plasma of patients non surviving to trauma (n = 5) exhibited a discriminating metabolomic pattern, involving basically metabolites belonging to fatty acid and catecholamine synthesis as well as tryptophan degradation pathways. Thus, concentration of several metabolites exhibited an area under the receiver operating curve (ROC) higher than 0.84, including 3-indolelactic acid, hydroxyisovaleric acid, phenylethanolamine, cortisol, epinephrine and myristic acid. Multivariate binary regression logistic revealed that patients with higher myristic acid concentrations had a non-survival odds ratio of 2.1 (CI 95% 1.1–3.9).

Conclusions

Specific fatty acids, catecholamine synthesis and tryptophan degradation pathways could be implicated in a negative outcome after trauma. The metabolomic study of severe trauma patients could be helpful for biomarker proposal.

Electronic supplementary material

The online version of this article (10.1186/s13049-019-0631-5) contains supplementary material, which is available to authorized users.

The Application of Omics Technologies to Study Axon Regeneration and CNS Repair

Traumatic brain and spinal cord injuries cause permanent disability. Although progress has been made in understanding the cellular and molecular mechanisms underlying the pathophysiological changes that affect both structure and function after injury to the brain or spinal cord, there are currently no cures for either condition. This may change with the development and application of multi-layer omics, new sophisticated bioinformatics tools, and cutting-edge imaging techniques. Already, these technical advances, when combined, are revealing an unprecedented number of novel cellular and molecular targets that could be manipulated alone or in combination to repair the injured central nervous system with precision. In this review, we highlight recent advances in applying these new technologies to the study of axon regeneration and rebuilding of injured neural circuitry. We then discuss the challenges ahead to translate results produced by these technologies into clinical application to help improve the lives of individuals who have a brain or spinal cord injury.

Targeted urine metabolomics in preterm neonates with intraventricular hemorrhage

Intraventricular hemorrhage (IVH) is a major cause of morbidity and mortality in preterm neonates. Elucidation of the mechanisms underlying IVH and/or development of disease biomarkers is essential. The aim of the study was to investigate the urine metabolic profile of preterm neonates (gestational age < 32 weeks) IVH and explore the role of metabolomics in understanding pathophysiological mechanisms of the disease from which novel biomarkers could be derived. In this single-center, prospective, case-control study, urine samples were collected from seven preterm infants with early IVH (IVH group) and from 11 preterm ones without IVH (control group) on days 1, 3 and 9 of life. Urine metabolites were evaluated using targeted liquid chromatography-tandem mass spectrometry. Demographic and perinatal-clinical characteristics were recorded. Univariate and multivariate statistical analyses were performed. Orthogonal Partial Least Squares-Discriminant Analysis showed that the study groups differed significantly due to alternation in 20 out of the 40 metabolites detected in the urine. Elevated differentiated metabolites included energy intermediates and other important compounds, whereas reduced ones various amino acids, hypoxanthine and nicotinamide. A set of metabolites showed high performance as indicators of IVH, especially during day 1. As evidenced by metabolomics, preterm neonates with IVH demonstrate significant metabolism perturbations. Potentially, a selected panel of metabolites could be used as urine biomarkers of IVH development and/or progression in high-risk preterm infants.

Serum Metabolites Associated with Computed Tomography Findings after Traumatic Brain Injury

There is a need to rapidly detect patients with traumatic brain injury (TBI) who require head computed tomography (CT). Given the energy crisis in the brain following TBI, we hypothesized that serum metabolomics would be a useful tool for developing a set of biomarkers to determine the need for CT and to distinguish among different types of injuries observed. Logistical regression models using metabolite data from the discovery cohort (n = 144, Turku, Finland) were used to distinguish between patients with traumatic intracranial findings and those with negative findings on head CT. The resultant models were then tested in the validation cohort (n = 66, Cambridge, United Kingdom). The levels of glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 were also quantified in the serum from the same patients. Despite there being significant differences in the protein biomarkers in patients with TBI, the model that determined the need for a CT scan validated poorly (area under the curve [AUC] = 0.64: Cambridge patients). However, using a combination of six metabolites (two amino acids, three sugar derivatives, and one ketoacid) it was possible to discriminate patients with intracranial abnormalities on CT and patients with a normal CT (AUC = 0.77 in Turku patients and AUC = 0.73 in Cambridge patients). Further, a combination of three metabolites could distinguish between diffuse brain injuries and mass lesions (AUC = 0.87 in Turku patients and AUC = 0.68 in Cambridge patients). This study identifies a set of validated serum polar metabolites, which associate with the need for a CT scan. Additionally, serum metabolites can also predict the nature of the brain injury. These metabolite markers may prevent unnecessary CT scans, thus reducing the cost of diagnostics and radiation load.

Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe

It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted.

Metabolomics and Lipidomics of Ischemic Stroke

Ischemic stroke is a sudden loss of brain function due to the reduction of blood flow. Brain tissues cease to function with subsequent activation of the ischemic cascade. Metabolomics and lipidomics are modern disciplines that characterize the metabolites and lipid components of a biological system, respectively. Because the pathogenesis of ischemic stroke is heterogeneous and multifactorial, it is crucial to establish comprehensive metabolomic and lipidomic approaches to elucidate these alterations in this disease. Fortunately, metabolomic and lipidomic studies have the distinct advantages of identifying tissue/mechanism-specific biomarkers, predicting treatment and clinical outcome, and improving our understanding of the pathophysiologic basis of disease states. Therefore, recent applications of these analytical approaches in the early diagnosis of ischemic stroke were discussed. In addition, the emerging roles of metabolomics and lipidomics on ischemic stroke were summarized, in order to gain new insights into the mechanisms underlying ischemic stroke and in the search for novel metabolite biomarkers and their related pathways.

Traumatic brain injury: classification, models, and markers

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality worldwide. Due to its high incidence rate and often long-term sequelae, TBI contributes significantly to increasing costs of health care expenditures annually. Unfortunately, advances in the field have been stifled by patient and injury heterogeneity that pose a major challenge in TBI prevention, diagnosis, and treatment. In this review, we briefly discuss the causes of TBI, followed by its prevalence, classification, and pathophysiology. The current imaging detection methods and animal models used to study brain injury are examined. We discuss the potential use of molecular markers in detecting and monitoring the progression of TBI, with particular emphasis on microRNAs as a novel class of molecular modulators of injury and its repair in the neural tissue.

Biomarkers Associated with the Outcome of Traumatic Brain Injury Patients

This review focuses on biomarkers associated with the outcome of traumatic brain injury (TBI) patients, such as caspase-3; total antioxidant capacity; melatonin; S100B protein; glial fibrillary acidic protein (GFAP); glutamate; lactate; brain-derived neurotrophic factor (BDNF); substance P; neuron-specific enolase (NSE); ubiquitin carboxy-terminal hydrolase L-1 (UCH-L1); tau; decanoic acid; and octanoic acid.