The Metabolic Profile of Plasma During Epileptogenesis in a Rat Model of Lithium-Pilocarpine-Induced Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) arises mostly because of an initial injury. Certain stimuli can make a normal brain prone to repeated, spontaneous seizures via a process called epileptogenesis. This study examined the plasma metabolomics profile in rats with the induced TLE to identify feasible biomarkers that can distinguish progression of epileptogenesis in three different time points and reveal the underlying mechanisms of epileptogenesis. Status epilepticus (SE) was induced by repetitive intraperitoneal injections of low-dose lithium chloride-pilocarpine hydrocholoride. Blood samples were collected 48 h, 1 week, and 6 weeks after SE, respectively. Plasma metabolites were analyzed by nuclear magnetic resonance (NMR) spectrometry. Statistical analysis was performed using MetaboAnalyst 6.0. An orthogonal partial least squares discriminant analysis (OPLS-DA) model was employed to represent variations between the TLE model groups and respective controls. Volcano plot analysis was used to identify key features, applying a fold-change criterion of 1.5 and a t-test threshold of 0.05. 48 h after SE, dimethyl sulfone (DMSO2) and creatinine levels were decreased, whereas glycine and creatine levels were increased. The only metabolite that changed 1 week after SE was pyruvic acid, which was increased compared to its control level. Lactic acid, pyruvic acid, and succinic acid levels were increased 6 weeks after SE. The identified metabolites were especially related to the tricarboxylic acid cycle and glycine, serine, and threonine metabolism. The results illustrate that distinct plasma metabolites can function as phase-specific biomarkers in TLE and reveal new insights into the mechanisms underlying SE.

GC-MS uncovers unique metabolic markers of drug-resistant epilepsy in capillary but not venous dried blood spots

This study compared the effectiveness of capillary dried blood spots (DBS) versus venous DBS in detecting metabolic changes related to drug-resistant epilepsy (DRE). DBS samples were collected from 142 epilepsy patients (58 drug-resistant, 84 drug-responsive) via venipuncture or fingerstick capillary sampling. Metabolomic analysis using gas chromatography-mass spectrometry compared DBS metabolite profiles between the two groups. While venous DBS profiles showed no distinct patterns, capillary DBS profiles revealed clustering patterns in principal components analysis, with the first two principal components explaining 14.5 %, and 13.5 % of the total variance, respectively. Orthogonal PLS-DA confirmed group discrimination (R2Y=0.989, Q2=0.742). Drug-resistant patients exhibited elevated capillary DBS levels of glutamine, pyruvic acid, and serine, and decreased palmitic acid compared to drug-responsive patients. Pathway analysis revealed disruptions in amino acid metabolism, neurotransmission, and cellular energy regulation. Elevated glutamine levels may contribute to an imbalance between excitatory glutamate and inhibitory GABA neurotransmission, key factors in epileptogenesis and drug resistance. Capillary DBS, likely enriched with arterial blood supply to the brain, appears to better capture central nervous system metabolic disturbances compared to venous DBS containing systemic contributions. This minimally invasive capillary DBS approach offers effective metabolic profiling of brain conditions like DRE, for monitoring disease progression and treatment response, enhancing personalized patient management in epilepsy.

Hippocampal metabolic profile during epileptogenesis in the pilocarpine model of epilepsy

Temporal lobe epilepsy (TLE) is a common form of refractory epilepsy in adulthood. The metabolic profile of epileptogenesis is still poorly investigated. Elucidation of such a metabolic profile using animal models of epilepsy could help identify new metabolites and pathways involved in the mechanisms of epileptogenesis process. In this study, we evaluated the metabolic profile during the epileptogenesis periods. Using a pilocarpine model of epilepsy, we analyzed the global metabolic profile of hippocampal extracts by untargeted metabolomics based on ultra-performance liquid chromatography-high-resolution mass spectrometry, at three time points (3 h, 1 week, and 2 weeks) after status epilepticus (SE) induction. We demonstrated that epileptogenesis periods presented different hippocampal metabolic profiles, including alterations of metabolic pathways of amino acids and lipid metabolism. Six putative metabolites (tryptophan, N-acetylornithine, N-acetyl-L-aspartate, glutamine, adenosine, and cholesterol) showed significant different levels during epileptogenesis compared to their respective controls. These putative metabolites could be associated with the imbalance of neurotransmitters, mitochondrial dysfunction, and cell loss observed during both epileptogenesis and epilepsy. With these findings, we provided an overview of hippocampal metabolic profiles during different stages of epileptogenesis that could help investigate pathways and respective metabolites as predictive tools in epilepsy.

Exploration of urine metabolic biomarkers for new-onset, untreated pediatric epilepsy: A gas and liquid chromatography mass spectrometry-based metabolomics study

OBJECTIVE

The discovery of objective indicators for recent epileptic seizures will help confirm the diagnosis of epilepsy and evaluate therapeutic effects. Past studies had shortcomings such as the inclusion of patients under treatment and those with various etiologies that could confound the analysis results significantly. We aimed to minimize such confounding effects and to explore the small molecule biomarkers associated with the recent occurrence of epileptic seizures using urine metabolomics.

METHODS

This is a multicenter prospective study. Subjects included pediatric patients aged 2 to 12 years old with new-onset, untreated epilepsy, who had had the last seizure within 1 month before urine collection. Controls included healthy children aged 2 to 12 years old. Those with underlying or chronic diseases, acute illnesses, or recent administration of medications or supplements were excluded. Targeted metabolome analysis of spot urine samples was conducted using gas chromatography (GC)- and liquid chromatography (LC)-tandem mass spectrometry (MS/MS).

RESULTS

We enrolled 17 patients and 21 controls. Among 172 metabolites measured by GC/MS/MS and 41 metabolites measured by LC/MS/MS, only taurine was consistently reduced in the epilepsy group. This finding was subsequently confirmed by the absolute quantification of amino acids. No other metabolites were consistently altered between the two groups.

CONCLUSIONS

Urine metabolome analysis, which covers a larger number of metabolites than conventional biochemistry analyses, found no consistently altered small molecule metabolites except for reduced taurine in epilepsy patients compared to healthy controls. Further studies with larger samples, subjects with different ages, expanded target metabolites, and the investigation of plasma samples are required.

Metabolomic changes in adults with status epilepticus: A human case-control study

OBJECTIVE

Status epilepticus (SE) is a life-threatening prolonged epileptic seizure that affects ~40 per 100 000 people yearly worldwide. The persistence of seizures may lead to excitotoxic processes, neuronal loss, and neuroinflammation, resulting in long-term neurocognitive and functional disabilities. A better understanding of the pathophysiological mechanisms underlying SE consequences is crucial for improving SE management and preventing secondary neuronal injury.

METHODS

We conducted a comprehensive untargeted metabolomic analysis, using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS), on plasma and cerebrospinal fluid (CSF) samples from 78 adult patients with SE and 107 control patients without SE, including 29 with CSF for both groups. The metabolomic fingerprints were compared between patients with SE and controls. Metabolites with differences in relative abundances that could not be attributed to treatment or nutrition provided in the intensive care unit were isolated. Enrichment analysis was performed on these metabolites to identify the most affected pathways.

RESULTS

We identified 76 metabolites in the plasma and 37 in the CSF that exhibited differential expression in patients with SE compared to controls. The enrichment analysis revealed that metabolic dysregulations in patients with SE affected primarily amino acid metabolism (including glutamate, alanine, tryptophan, glycine, and serine metabolism), pyrimidine metabolism, and lipid homeostasis. Specifically, patients with SE had elevated levels of pyruvate, quinolinic acid, and keto butyric acid levels, along with lower levels of arginine, N-acetylaspartylglutamate (NAAG), tryptophan, uracil, and uridine. The tryptophan kynurenine pathway was identified as the most significantly altered in SE, resulting in the overproduction of quinolinic acid, an N-methyl-d-aspartate (NMDA) receptor agonist with pro-inflammatory properties.

SIGNIFICANCE

This study has identified several pathways that may play pivotal roles in SE consequences, such as the tryptophan kynurenine pathway. These findings offer novel perspectives for the development of neuroprotective therapeutics.

Tetrastigma hemsleyanum suppresses neuroinflammation in febrile seizures rats via regulating PKC-δ/caspase-1 signaling pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Tetrastigma hemsleyanum Diels et Gilg (T. hemsleyanum, Sanyeqing) has been used in the prevention and treatment of repetitive Febrile seizures (FS) over the centuries in China.

AIM OF THE STUDY

T. hemsleyanum exerts wide pharmacological action, which has been widely used for treating various diseases, including infantile febrile seizure. However, the systematic study on this herb's material basis and the functional mechanism is lacking. This study intended to systematically elucidate the mechanism of T. hemsleyanum against febrile seizures.

MATERIALS AND METHODS

The efficacy of T. hemsleyanum was estimated by using a hot bath as a model of FS, the onset and duration of seizure, morphological structure changes of hippocampal neurons as well as magnetoencephalography were applied to evaluate the effects. Meanwhile, the bioactive components of T. hemsleyanum responsible for the therapeutic effect of T. hemsleyanum on FS were identified by UPLC-MS/MS. Then we systematically elucidated the mechanism of T. hemsleyanum based on metabonomics, transcriptomics, network pharmacological and experimental validation.

RESULTS

In a hyperthermia-induced FS model of rats, T. hemsleyanum significantly increased the seizure latency and decreased seizure duration, alleviating the abnormal delta and gamma band activity during epileptic discharge. Furthermore, ten chemical components of ethanol extracts from T. hemsleyanum were identified by UPLC-MS/MS, including quercetin, kaempferol, and procyanidin B1 and so on, which was consistent with the network pharmacology prediction. The serum metabolomics indicated that T. hemsleyanum mainly acts on inflammation regulation and neuroprotection by the glycerophospholipid metabolism pathway. Ninety-two potential targets of T. hemsleyanum on FS were identified by network pharmacology, and TNF, IL-6, and IL-1β were considered the pivotal targets. In the hippocampus transcriptomics, 17 KEGG pathways were identified after T. hemsleyanum treatment compared with the FS model group, among which 15 pathways overlapped with those identified by network pharmacology, and the PKC-δ/caspase-1 signaling pathway was a critical node. Finally, in vivo experiments also verified T. hemsleyanum inhibited the activation of microglia and resulted in a significant reduction in the level of PKCδ, NLRC4, caspase-1, IL-1β, IL-6 and TNF-α in hippocampus of FS rats.

CONCLUSIONS

Our study suggested that the therapeutic effect of T. hemsleyanum on FS might be regulated by inhibiting the neuroinflammation, thus exerting an anticonvulsant effect in vivo, and the mechanism might be related to regulating the PKC-δ/caspase-1 signaling pathway.

Multi-omics Integration and Epilepsy: Towards a Better Understanding of Biological Mechanisms

The epilepsies are a group of complex neurological disorders characterised by recurrent seizures. Approximately 30% of patients fail to respond to anti-seizure medications, despite the recent introduction of many new drugs. The molecular processes underlying epilepsy development are not well understood and this knowledge gap impedes efforts to identify effective targets and develop novel therapies against epilepsy. Omics studies allow a comprehensive characterisation of a class of molecules. Omics-based biomarkers have led to clinically validated diagnostic and prognostic tests for personalised oncology, and more recently for non-cancer diseases. We believe that, in epilepsy, the full potential of multi-omics research is yet to be realised and we envisage that this review will serve as a guide to researchers planning to undertake omics-based mechanistic studies.

Insights into the development of pentylenetetrazole-induced epileptic seizures from dynamic metabolomic changes

Epilepsy is often considered to be a progressive neurological disease, and the nature of this progression remains unclear. Understanding the overall and common metabolic changes of epileptic seizures can provide novel clues for their control and prevention. Herein, a chronic kindling animal model was established to obtain generalized tonic-clonic seizures via the repeated injections of pentylenetetrazole (PTZ) at subconvulsive dose. Dynamic metabolomic changes in plasma and urine from PTZ-kindled rats at the different kindling phases were explored using NMR-based metabolomics, in combination with behavioral assessment, brain neurotransmitter measurement, electroencephalography and histopathology. The increased levels of glucose, lactate, glutamate, creatine and creatinine, together with the decreased levels of pyruvate, citrate and succinate, ketone bodies, asparagine, alanine, leucine, valine and isoleucine in plasma and/or urine were involved in the development and progression of seizures. These altered metabolites reflected the pathophysiological processes including the compromised energy metabolism, the disturbed amino acid metabolism, the peripheral inflammation and changes in gut microbiota functions. NMR-based metabolomics could provide brain disease information by the dynamic plasma and urinary metabolic changes during chronic epileptic seizures, yielding classification of seizure stages and profound insights into controlling epilepsy via targeting deficient energy metabolism.

Central Nervous System Metabolism in Autism, Epilepsy and Developmental Delays: A Cerebrospinal Fluid Analysis

Neurodevelopmental disorders are associated with metabolic pathway imbalances; however, most metabolic measurements are made peripherally, leaving central metabolic disturbances under-investigated. Cerebrospinal fluid obtained intraoperatively from children with autism spectrum disorder (ASD, n = 34), developmental delays (DD, n = 20), and those without known DD/ASD (n = 34) was analyzed using large-scale targeted mass spectrometry. Eighteen also had epilepsy (EPI). Metabolites significantly related to ASD, DD and EPI were identified by linear models and entered into metabolite-metabolite network pathway analysis. Common disrupted pathways were analyzed for each group of interest. Central metabolites most involved in metabolic pathways were L-cysteine, adenine, and dodecanoic acid for ASD; nicotinamide adenine dinucleotide phosphate, L-aspartic acid, and glycine for EPI; and adenosine triphosphate, L-glutamine, ornithine, L-arginine, L-lysine, citrulline, and L-homoserine for DD. Amino acid and energy metabolism pathways were most disrupted in all disorders, but the source of the disruption was different for each disorder. Disruption in vitamin and one-carbon metabolism was associated with DD and EPI, lipid pathway disruption was associated with EPI and redox metabolism disruption was related to ASD. Two microbiome metabolites were also detected in the CSF: shikimic and cis-cis-muconic acid. Overall, this study provides increased insight into unique metabolic disruptions in distinct but overlapping neurodevelopmental disorders.

Revealing the Antiepileptic Effect of α-Asaronol on Pentylenetetrazole-Induced Seizure Rats Using NMR-Based Metabolomics

α-Asaronol from Acorus tatarinowii (known as "Shichangpu" in Traditional Chinese medicine) has been proved to possess more efficient antiepileptic activity and lower toxicity than α-asarone (namely "Xixinnaojiaonang" as an antiepileptic drug in China) in our previous study. However, the molecular mechanism of α-asaronol against epilepsy needs to be known if to become a novel antiepileptic medicine. Nuclear magnetic resonance (NMR)-based metabolomics was applied to investigate the metabolic patterns of plasma and the brain tissue extract from pentylenetetrazole (PTZ)-induced seizure rats when treated with α-asaronol or α-asarone. The results showed that α-asaronol can regulate the metabolomic level of epileptic rats to normal to some extent, and four metabolic pathways were associated with the antiepileptic effect of α-asaronol, including alanine, aspartate, and glutamate metabolism; synthesis and degradation of ketone bodies; glutamine and glutamate metabolism; and glycine, serine, and threonine metabolism. It was concluded that α-asaronol plays a vital role in enhancing energy metabolism, regulating the balance of excitatory and inhibitory neurotransmitters, and inhibiting cell membrane damage to prevent the occurrence of epilepsy. These findings are of great significance in developing α-asaronol into a promising antiepileptic drug derived from Traditional Chinese medicine.

Metabolomics Provides Novel Insights into Epilepsy Diagnosis and Treatment: A Review

Epilepsy is one of the most common diseases of the central nervous system. The diagnosis of epilepsy mainly depends on electroencephalograms and symptomatology, while diagnostic biofluid markers are still lacking. In addition, approximately 30% of patients with epilepsy (PWE) show a poor response to the currently available anti-seizure medicines. An increasing number of studies have reported alterations in the blood, brain tissue, cerebrospinal fluid and urine metabolome in PWE and animal models of epilepsy. The aim of this review was to identify potential metabolic biomarkers and pathways that might facilitate diagnostic, therapeutic and prognostic determination in PWE and the understanding of the pathogenesis of the disease. The PubMed and Embase databases were searched for metabolomic studies of PWE and epileptic models published before December 2020. The study objectives, types of models and reported differentially altered metabolites were examined and compared. Pathway analyses were performed using MetaboAnalyst 5.0 online software. Thirty-five studies were included in this review. Metabolites such as glutamate, lactate and citrate were disturbed in both PWE and epileptic models, which might be potential biomarkers of epilepsy. Metabolic pathways including alanine, aspartate and glutamate metabolism; glycine, serine and threonine metabolism; glycerophospholipid metabolism; glyoxylate and dicarboxylate metabolism; and arginine and proline metabolism were involved in epilepsy. These pathways might play important roles in the pathogenesis of the disease. This review summarizes metabolites and metabolic pathways related to epilepsy and provides a novel perspective for the identification of potential biomarkers and therapeutic targets for epilepsy.

Alterations in Urine Metabolomics Following Sport-Related Concussion: A 1H NMR-Based Analysis

Objective: Millions of sport-related concussions (SRC) occur annually in North America, and current diagnosis of concussion is based largely on clinical evaluations. The objective of this study was to determine whether urinary metabolites are significantly altered post-SRC compared to pre-injury.

Setting: Outpatient sports medicine clinic.

Participants: Twenty-six male youth sport participants.

Methods: Urine was analyzed pre-injury and after SRC by ¹H NMR spectroscopy. Data were analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable importance analysis based on random variable combination (VIAVC) was applied to the entire data set and resulted in a panel of 18 features. Partial least square discriminant analysis was performed exploring the separation between pre-injury and post-SRC groups. Pathway topography analysis was completed to identify biological pathway involvement. Spearman correlations provide support for the relationships between symptom burden and length of return to play and quantifiable metabolic changes in the human urinary metabolome.

Results: Phenylalanine and 3-indoxysulfate were upregulated, while citrate, propylene glycol, 1-methylhistidine, 3-methylhistidine, anserine, and carnosine were downregulated following SRC. A receiver operator curve (ROC) tool constructed using the 18-feature classifier had an area under the curve (AUC) of 0.887. A pairwise t-test found an additional 19 altered features, 7 of which overlapped with the VIAVC analysis. Pathway topology analysis indicated that aminoacyl-tRNA biosynthesis and beta-alanine metabolism were the two pathways most significantly changed. There was a significant positive correlation between post-SRC 2-hydroxybutyrate and the length of return to play (ρ = 0.482, p = 0.02) as well as the number of symptoms and post-SRC lactose (ρ = 0.422, p = 0.036).

Conclusion: We found that ¹H NMR metabolomic urinary analysis can identify a set of metabolites that can correctly classify SRC with an accuracy of 81.6%, suggesting potential for a more objective method of characterizing SRC. Correlations to both the number of symptoms and length of return to play indicated that 2-hydroxybutyrate and lactose may have potential applications as biomarkers for sport-related concussion.

Metabolic Changes in Rat Plasma After Epilepsy by UPLC-MS/MS

Introduction:

Epilepsy is one of the most common neurological diseases in clinical practice. The combined application of metabolomics technology plays a great advantage in the screening of biomarkers.

Methods:

In this study, Wistar rats were used as experimental subjects to model intractable epilepsy and to detect the metabolic changes of small molecules in plasma. UPLC-MS/MS was used to determine the small molecules in rat plasma. UPLC HSS C18 (2.1mm×100mm, 1.7 μm) column was used for separation, column temperature of 40°C. The initial mobile phase was acetonitrile -0.3% formic acid with gradient elution, the flow rate was 0.3 mL/min, total running time 4.0 min. Quantitative analysis was performed with multi-response monitoring (MRM).

Results:

Compared to the control group, the L-Alanine and L-Arginine decreased in the Epilepsy group (p<0.05); while Cytosine, Adenosine, L-Tyrosine, Citric acid, Fructose increased (p<0.05).

Conclusion:

In the screening of epilepsy biomarkers using metabolomics, various amino acids that lead to increased energy production and neurotransmitter imbalance play an important role in epileptic seizures.

Differential ketogenic diet-induced shift in CSF lipid/carbohydrate metabolome of pediatric epilepsy patients with optimal vs. no anticonvulsant response: a pilot study

Background

The low carbohydrate, high fat ketogenic diet can be an effective anticonvulsant treatment in some pediatric patients with pharmacoresistant epilepsy. Its mechanism(s) of action, however, remain uncertain. Direct sampling of cerebrospinal fluid before and during metabolic therapy may reveal key changes associated with differential clinical outcomes. We characterized the relationship between seizure responsiveness and changes in lipid and carbohydrate metabolites.

Methods

We performed metabolomic analysis of cerebrospinal fluid samples taken before and during ketogenic diet treatment in patients with optimal response (100% seizure remission) and patients with no response (no seizure improvement) to search for differential diet effects in hallmark metabolic compounds in these two groups. Optimal responders and non-responders were similar in age range and included males and females. Seizure types and the etiologies or syndromes of epilepsy varied but did not appear to differ systematically between responders and non-responders.

Results

Analysis showed a strong effect of ketogenic diet treatment on the cerebrospinal fluid metabolome. Longitudinal and between-subjects analyses revealed that many lipids and carbohydrates were changed significantly by ketogenic diet, with changes typically being of larger magnitude in responders. Notably, responders had more robust changes in glucose and the ketone bodies β-hydroxybutyrate and acetoacetate than non-responders; conversely, non-responders had significant increases in fructose and sorbose, which did not occur in responders.

Conclusions

The data suggest that a differential and stronger metabolic response to the ketogenic diet may predict a better anticonvulsant response, and such variability is likely due to inherent biological factors of individual patients. Strategies to boost the metabolic response may be beneficial.

Protection of paeonol against epirubicin-induced hepatotoxicity: A metabolomic study

Paeonol extracted from the Moutan Cortex, possesses hepatoprotective activity against epirubicin (EPI)-induced liver damage. This study evaluated the protective effect of paeonol on EPI-induced hepatotoxicity and explored the underlying metabolomic mechanism. Breast tumor-bearing mice were randomly divided into three groups: control, EPI, and EPI + paeonol treatment. Mice received a tail i.v. injection of EPI every other day for 3 cycles or/and intragastrically (i.g.) administered paeonol daily for 6 days. Hematoxylin-eosin (HE) staining and biochemical detection were used to determine the degree of damage. A gas chromatography-mass spectrometry (GC-MS) technique was established to determine the metabolites. PLS-DA and PCA were used to investigate metabolic changes. HE staining and biochemical detection results showed that EPI caused serious liver damage while paeonol ameliorated it. The results of mass spectrogram, partial least squares-discriminate analysis (PLS-DA), and principal component analysis (PCA) demonstrated that lipid, amino acid, and energy metabolism involving seven metabolites were obviously changed by EPI and reversed by paeonol. Additionally, paeonol inhibited EPI-induced activation of adenosine monophosphate activated protein kinase/mammalian target of Rapamycin (AMPK/mTOR) signalling pathway. Our results demonstrated the hepatoprotective effect of paeonol on EPI-induced hepatotoxicity in mice, provided potential biomarkers for early assessment of EPI-induced liver injury and illuminated the metabolic mechanism underlying paeonol-related hepatic protection.

Exploratory Cortex Metabolic Profiling Revealed the Sedative Effect of Amber in Pentylenetetrazole-Induced Epilepsy-Like Mice

Epilepsy is a common clinical syndrome characterized by sudden and recurrent attacks and temporary central nervous system dysfunction caused by excessive discharge of neurons in the brain. Amber, a fossilized organic substance formed by the resins of conifers and leguminous plants, was prescribed to tranquilize the mind in China. In this paper, the antiepileptic effect of amber was evaluated by a pentylenetetrazole (PTZ)-induced epileptic model. An untargeted metabolomics approach was applied to investigate metabolic changes in the epileptic model, which was based on HILIC-UHPLC-MS/MS multivariate statistical analysis and metabolism network analysis. The outcome of this study suggested that 35 endogenous metabolites showed marked perturbations. Moreover, four metabolism pathways were mainly involved in epilepsy. After treatment by amber, the endogenous metabolites had a marked tendency to revert back to the situation of the control group which was consistent with phenobarbital. This study characterized the pentylenetetrazole-induced epileptic model and provided new evidence for the sedative effect of amber.

Critical review of reporting of the data analysis step in metabolomics

INTRODUCTION

We present the first study to critically appraise the quality of reporting of the data analysis step in metabolomics studies since the publication of minimum reporting guidelines in 2007.

OBJECTIVES

The aim of this study was to assess the standard of reporting of the data analysis step in metabolomics biomarker discovery studies and to investigate whether the level of detail supplied allows basic understanding of the steps employed and/or reuse of the protocol. For the purposes of this review we define the data analysis step to include the data pretreatment step and the actual data analysis step, which covers algorithm selection, univariate analysis and multivariate analysis.

METHOD

We reviewed the literature to identify metabolomic studies of biomarker discovery that were published between January 2008 and December 2014. Studies were examined for completeness in reporting the various steps of the data pretreatment phase and data analysis phase and also for clarity of the workflow of these sections.

RESULTS

We analysed 27 papers, published anytime in 2008 until the end of 2014 in the area or biomarker discovery in serum metabolomics. The results of this review showed that the data analysis step in metabolomics biomarker discovery studies is plagued by unclear and incomplete reporting. Major omissions and lack of logical flow render the data analysis' workflows in these studies impossible to follow and therefore replicate or even imitate.

CONCLUSIONS

While we await the holy grail of computational reproducibility in data analysis to become standard, we propose that, at a minimum, the data analysis section of metabolomics studies should be readable and interpretable without omissions such that a data analysis workflow diagram could be extrapolated from the study and therefore the data analysis protocol could be reused by the reader. That inconsistent and patchy reporting obfuscates reproducibility is a given. However even basic understanding and reuses of protocols are hampered by the low level of detail supplied in the data analysis sections of the studies that we reviewed.

GC-MS-Based metabolomics discovers a shared serum metabolic characteristic among three types of epileptic seizures

OBJECTIVE

Understanding the overall and common metabolic changes of seizures can provide novel clues for their control and prevention. Here, we aim to investigate the global metabolic feature of serum for three types of seizures.

METHODS

We recruited 27 patients who had experienced a seizure within 48h (including 11 who had a generalized seizure, nine who had a generalized seizure secondary to partial seizure and seven who had a partial seizure) and 23 healthy controls. We analyzed the global metabolic changes of serum after seizures using gas chromatography-mass spectrometry-based metabolomics. Based on differential metabolites, the metabolic pathways and their potential to diagnose seizures were analyzed, and metabolic differences among three types of seizures were compared.

RESULTS

The metabolic profiles of serum were distinctive between the seizure group and the controls but were not different among the three types of seizures. Compared to the controls, patients with seizures had higher levels of lactate, butanoic acid, proline and glutamate and lower levels of palmitic acid, linoleic acid, elaidic acid, trans-13-octadecenoic acid, stearic acid, citrate, cysteine, glutamine, asparagine, and glyceraldehyde in the serum. Furthermore, these differential metabolites had common change trends among the three types of seizures. Related pathophysiological processes reflected by these metabolites are energy deficit, inflammation, nervous excitation and neurotoxicity. Importantly, transamination inhibition is suspected to occur in seizures. Lactate, glyceraldehyde and trans-13-octadecenoic acid in serum jointly enabled a precision of 92.9% for diagnosing seizures.

CONCLUSIONS

There is a common metabolic feature in three types of seizures. Lactate, glyceraldehyde and trans-13-octadecenoic acid levels jointly enable high-precision seizure diagnosis.

Metabolic changes in rat urine after acute paraquat poisoning and discriminated by support vector machine

Paraquat is quick-acting and non-selective, killing green plant tissue on contact; it is also toxic to human beings and animals. In this study, we developed a urine metabonomic method by gas chromatography-mass spectrometry to evaluate the effect of acute paraquat poisoning on rats. Pattern recognition analysis, including both partial least squares discriminate analysis and principal component analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the levels of benzeneacetic acid and hexadecanoic acid of the acute paraquat poisoning group (intragastric administration 36 mg/kg) increased, while the levels of butanedioic acid, pentanedioic acid, altronic acid decreased. Based on these urinary metabolomics data, support vector machine was applied to discriminate the metabolomic change of paraquat groups from the control group, which achieved 100% classification accuracy. In conclusion, metabonomic method combined with support vector machine can be used as a useful diagnostic tool in paraquat-poisoned rats.

GC-MS based metabolomics identification of possible novel biomarkers for schizophrenia in peripheral blood mononuclear cells

Schizophrenia is a debilitating mental disorder. Currently, the lack of disease biomarkers to support objective laboratory tests constitutes a bottleneck in the clinical diagnosis of schizophrenia. Here, a gas chromatography-mass spectrometry (GC-MS) based metabolomic approach was applied to characterize the metabolic profile of schizophrenia subjects (n = 69) and healthy controls (n = 85) in peripheral blood mononuclear cells (PBMCs) to identify and validate biomarkers for schizophrenia. Multivariate statistical analysis was used to visualize group discrimination and to identify differentially expressed metabolites in schizophrenia subjects relative to healthy controls. The multivariate statistical analysis demonstrated that the schizophrenia group was significantly distinguishable from the control group. In total, 18 metabolites responsible for the discrimination between the two groups were identified. These differential metabolites were mainly involved in energy metabolism, oxidative stress and neurotransmitter metabolism. A simplified panel of PBMC metabolites consisting of pyroglutamic acid, sorbitol and tocopherol-α was identified as an effective diagnostic tool, yielding an area under the receiver operating characteristic curve (AUC) of 0.82 in the training samples (45 schizophrenia subjects and 50 healthy controls) and 0.71 in the test samples (24 schizophrenic patients and 35 healthy controls). Taken together, these findings help to develop diagnostic tools for schizophrenia.