NMR-based metabolomic analysis of cerebrospinal fluid and serum in neurological diseases--a diagnostic tool?

NMR-based metabolomics identification of potential serum biomarkers of disease progression in patients with multiple sclerosis

Multiple sclerosis (MS) is a chronic and progressive neurological disorder, characterized by neuroinflammation and demyelination within the central nervous system (CNS). The etiology and the pathogenesis of MS are still unknown. Till now, no satisfactory treatments, diagnostic and prognostic biomarkers are available for MS. Therefore, we aimed to investigate metabolic alterations in patients with MS compared to controls and across MS subtypes. Metabolic profiles of serum samples from patients with MS (n = 90) and healthy control (n = 30) were determined by Nuclear Magnetic Resonance (1H-NMR) Spectroscopy using cryogenic probe. This approach was also utilized to identify significant differences between the metabolite profiles of the MS groups (primary progressive, secondary progressive, and relapsing-remitting) and the healthy controls. Concentrations of nine serum metabolites (adenosine triphosphate (ATP), tryptophan, formate, succinate, glutathione, inosine, histidine, pantothenate, and nicotinamide adenine dinucleotide (NAD)) were significantly higher in patients with MS compared to control. SPMS serum exhibited increased pantothenate and tryptophan than in PPMS. In addition, lysine, myo-inositol, and glutamate exhibited the highest discriminatory power (0.93, 95% CI 0.869-0.981; 0.92, 95% CI 0.859-0.969; 0.91, 95% CI 0.843-0.968 respectively) between healthy control and MS. Using NMR- based metabolomics, we identified a set of metabolites capable of classifying MS patients and controls. These findings confirmed untargeted metabolomics as a useful approach for the discovery of possible novel biomarkers that could aid in the diagnosis of the disease.

Potential Metabolite Biomarkers of Multiple Sclerosis from Multiple Biofluids

Multiple sclerosis (MS) is a chronic and progressive neurological disorder without a cure, but early intervention can slow disease progression and improve the quality of life for MS patients. Obtaining an accurate diagnosis for MS is an arduous and error-prone task that requires a combination of a detailed medical history, a comprehensive neurological exam, clinical tests such as magnetic resonance imaging, and the exclusion of other possible diseases. A simple and definitive biofluid test for MS does not exist, but is highly desirable. To address this need, we employed NMR-based metabolomics to identify potentially unique metabolite biomarkers of MS from a cohort of age and sex-matched samples of cerebrospinal fluid (CSF), serum, and urine from 206 progressive MS (PMS) patients, 46 relapsing-remitting MS (RRMS) patients, and 99 healthy volunteers without a MS diagnosis. We identified 32 metabolites in CSF that varied between the control and PMS patients. Utilizing patient-matched serum samples, we were able to further identify 31 serum metabolites that may serve as biomarkers for PMS patients. Lastly, we identified 14 urine metabolites associated with PMS. All potential biomarkers are associated with metabolic processes linked to the pathology of MS, such as demyelination and neuronal damage. Four metabolites with identical profiles across all three biofluids were discovered, which demonstrate their potential value as cross-biofluid markers of PMS. We further present a case for using metabolic profiles from PMS patients to delineate biomarkers of RRMS. Specifically, three metabolites exhibited a variation from healthy volunteers without MS through RRMS and PMS patients. The consistency of metabolite changes across multiple biofluids, combined with the reliability of a receiver operating characteristic classification, may provide a rapid diagnostic test for MS.

Time-frequency analysis reveals an association between the specific nuclear magnetic resonance (NMR) signal properties of serum samples and arteriosclerotic lesion progression in a diabetes mouse model

Diabetes causes arteriosclerosis, primarily due to persistent hyperglycemia, subsequently leading to various cardiovascular events. No method has been established for directly detecting and evaluating arteriosclerotic lesions from blood samples of diabetic patients, as the mechanism of arteriosclerotic lesion formation, which involves complex molecular biological processes, has not been elucidated. "NMR modal analysis" is a technology that enables visualization of specific nuclear magnetic resonance (NMR) signal properties of blood samples. We hypothesized that this technique could be used to identify changes in blood status associated with the progression of arteriosclerotic lesions in the context of diabetes. The study aimed to assess the possibility of early detection and evaluation of arteriosclerotic lesions by NMR modal analysis of serum samples from diabetes model mice. Diabetes model mice (BKS.Cg db/db) were bred in a clean room and fed a normal diet. Blood samples were collected and centrifuged. Carotid arteries were collected for histological examination by hematoxylin and eosin staining on weeks 10, 14, 18, 22, and 26. The serum was separated and subjected to NMR modal analysis and biochemical examination. Mice typically show hyperglycemia at an early stage (8 weeks old), and pathological findings of a previous study showed that more than half of mice had atheromatous plaques at 18 weeks old, and severe arteriosclerotic lesions were observed in almost all mice after 22 weeks. Partial least squares regression analysis was performed, which showed that the mice were clearly classified into two groups with positive and negative score values within 18 weeks of age. The findings of this study revealed that NMR modal properties of serum are associated with arteriosclerotic lesions. Thus, it may be worth exploring the possibility that the risk of cardiovascular events in diabetic patients could be assessed using serum samples.

Epigenetic regulation of inflammation: The metabolomics connection

Epigenetic factors are considered the regulator of complex machinery behind inflammatory disorders and significantly contributed to the expression of inflammation-associated genes. Epigenetic modifications modulate variation in the expression pattern of target genes without affecting the DNA sequence. The current knowledge of epigenetic research focused on their role in the pathogenesis of various inflammatory diseases that causes morbidity and mortality worldwide. Inflammatory diseases are categorized as acute and chronic based on the disease severity and are regulated by the expression pattern of various genes. Hence, understanding the role of epigenetic modifications during inflammation progression will contribute to the disease outcomes and therapeutic approaches. This review also focuses on the metabolomics approach associated with the study of inflammatory disorders. Inflammatory responses and metabolic regulation are highly integrated and various advanced techniques are adopted to study the metabolic signature molecules. Here we discuss several metabolomics approaches used to link inflammatory disorders and epigenetic changes. We proposed that deciphering the mechanism behind the inflammation-metabolism loop may have immense importance in biomarkers research and may act as a principal component in drug discovery as well as therapeutic applications.

Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm

Magnetic resonance spectroscopy offers information about metabolite changes in the organism, which can be used in diagnosis. While short echo time proton spectra exhibit more distinguishable metabolites compared with proton spectra acquired with long echo times, their quantification (and providing estimates of metabolite concentrations) is more challenging. They are hampered by a background signal, which originates mainly from macromolecules (MM) and mobile lipids. An improved version of the quantification algorithm QUantitation based on quantum ESTimation (QUEST), with MM prior knowledge (QUEST-MM), dedicated to proton signals and invoking appropriate prior knowledge on MM, is proposed and tested. From a single acquisition, it enables better metabolite quantification, automatic estimation of the background, and additional automatic quantification of MM components, thus improving its applicability in the clinic. The proposed algorithm may facilitate studies that involve patients with pathological MM in the brain. QUEST-MM and three QUEST-based strategies for quantifying short echo time signals are compared in terms of bias-variance trade-off and Cramér-Rao lower bound estimates. The performances of the methods are evaluated through extensive Monte Carlo studies. In particular, the histograms of the metabolite and MM amplitude distributions demonstrate the performances of the estimators. They showed that QUEST-MM works better than QUEST (Subtract approach) and is a good alternative to QUEST when measured MM signal is unavailable or unsuitable. Quantification with QUEST-MM is shown for 1 H in vivo rat brain signals obtained with the SPECIAL pulse sequence at 9.4 T, and human brain signals obtained, respectively, with STEAM at 4 T and PRESS at 3 T. QUEST-MM is implemented in jMRUI and will be available for public use from version 7.1.

Metabolomic profiling of CSF and blood serum elucidates general and sex-specific patterns for mild cognitive impairment and Alzheimer's disease patients

Background

Beta-amyloid (Abeta) and tau protein in cerebrospinal fluid (CSF) are established diagnostic biomarkers for Alzheimer's disease (AD). However, these biomarkers may not the only ones existing parameters that reflect Alzheimer's disease neuropathological change. The use of quantitative metabolomics approach could provide novel insights into dementia progression and identify key metabolic alterations in CSF and serum.

Methods

In the present study, we quantified a set of 45 metabolites in CSF (71 patients) and 27 in serum (76 patients) in patients with mild cognitive impairment (MCI), AD, and controls using nuclear magnetic resonance (NMR)-based metabolomics.

Results

We found significantly reduced CSF (1.32-fold, p = 0.0195) and serum (1.47-fold, p = 0.0484) levels of the ketone body acetoacetate in AD and MCI patients. Additionally, we found decreased levels (1.20-fold, p = 0.0438) of the branched-chain amino acid (BCAA) valine in the CSF of AD patients with increased valine degradation pathway metabolites (such as 3-hydroxyisobutyrate and α-ketoisovalerate). Moreover, we discovered that CSF 2-hydroxybutyrate is dramatically reduced in the MCI patient group (1.23-fold, p = 0.039). On the other hand, vitamin C (ascorbate) was significantly raised in CSF of these patients (p = 0.008). We also identified altered CSF protein content, 1,5-anhydrosorbitol and fructose as further metabolic shifts distinguishing AD from MCI. Significantly decreased serum levels of the amino acid ornithine were seen in the AD dementia group when compared to healthy controls (1.36-fold, p = 0.011). When investigating the effect of sex, we found for AD males the sign of decreased 2-hydroxybutyrate and acetoacetate in CSF while for AD females increased serum creatinine was identified.

Conclusion

Quantitative NMR metabolomics of CSF and serum was able to efficiently identify metabolic changes associated with dementia groups of MCI and AD patients. Further, we showed strong correlations between these changes and well-established metabolomic and clinical indicators like Abeta.

Dysregulation of Amino Acid, Lipid, and Acylpyruvate Metabolism in Idiopathic Intracranial Hypertension: A Non-targeted Case Control and Longitudinal Metabolomic Study

Background: Idiopathic intracranial hypertension (IIH) is characterized by increased intracranial pressure occurring predominantly in women with obesity. The pathogenesis is not understood. We have applied untargeted metabolomic analysis using ultrahigh-performance liquid chromatography-mass spectrometry to characterize the cerebrospinal fluid (CSF) and serum in IIH compared to control subjects. Methods and findings: Samples were collected from IIH patients (n = 66) with active disease at baseline and again at 12 months following therapeutic weight loss. Control samples were collected from gender- and weight-matched healthy controls (n = 20). We identified annotated metabolites in CSF, formylpyruvate and maleylpyruvate/fumarylpyruvate, which were present at lower concentrations in IIH compared to control subjects and returned to values observed in controls following weight loss. These metabolites showed the opposite trend in serum at baseline. Multiple amino acid metabolic pathways and lipid classes were perturbed in serum and CSF in IIH alone. Serum lipid metabolite pathways were significantly increased in IIH. Conclusions: We observed a number of differential metabolic pathways related to amino acid, lipid, and acylpyruvate metabolism, in IIH compared to controls. These pathways were associated with clinical measures and normalized with disease remission. Perturbation of these metabolic pathways provides initial understanding of disease dysregulation in IIH.

Metabolomics of Cerebrospinal Fluid in Multiple Sclerosis Compared With Healthy Controls: A Pilot Study

Background

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) leading to the loss of myelin and axons. Diagnosis is based on clinical findings, MRI, and analysis of cerebrospinal fluid (CSF). CSF is an ultrafiltrate of plasma and reflects inflammatory processes in the CNS. The aim of this study was to perform metabolomics analysis of CSF in patients after the first attack of MS and healthy controls and try to find new specific analytes for MS including those potentially predicting disease activities at the onset.

Methods

We collected CSF from 19 patients (16 females, aged 19–55 years) after the first attack of clinical symptoms who fulfilled revised McDonald criteria of MS and CSF of 19 controls (16 females, aged 19–50 years). Analyses of CSF samples were provided using the high-performance liquid chromatography system coupled with a mass spectrometer with a high-resolution detector (TripleTOF 5600, AB Sciex, Canada).

Results

Approximately 130 selected analytes were identified, and 30 of them were verified. During the targeted analysis, a significant decrease in arginine and histidine and a less significant decrease in the levels of asparagine, leucine/isoleucine, and tryptophan, together with a significant increase of palmitic acid in the patient group, were found.

Conclusion

We observed significant differences in amino and fatty acids in the CSF of newly diagnosed patients with MS in comparison with controls. The most significant changes were observed in levels of arginine, histidine, and palmitic acid that may predict inflammatory disease activity. Further studies are necessary to support these findings as potential biomarkers of MS.

Altered Plasma Metabolic Profiles in Chinese Patients With Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune disease that leads to the demyelination of nerve axons. An increasing number of studies suggest that patients with MS exhibit altered metabolic profiles, which might contribute to the course of MS. However, the alteration of metabolic profiles in Chinese patients with MS and their potential roles in regulating the immune system remain elusive. In this study, we performed a global untargeted metabolomics approach in plasma samples from 22 MS-affected Chinese patients and 21 healthy subjects. A total of 42 differentially abundant metabolites (DAMs) belonging to amino acids, lipids, and carbohydrates were identified in the plasma of MS patients and compared with those in healthy controls. We observed an evident reduction in the levels of amino acids, such as L-tyrosine, L-isoleucine, and L-tryptophan, whereas there was a great increase in the levels of L-glutamic acid and L-valine in MS-affected patients. The levels of lipid and carbohydrate metabolites, such as sphingosine 1-phosphate and myo-inositol, were also reduced in patients with MS. In addition, the concentrations of proinflammatory cytokines, such as IL-17 and TNF-α, were significantly increased, whereas those of several anti-inflammatory cytokines and chemokines, such as IL-1ra, IL-7, and MIP-1α, were distinctly reduced in the plasma of MS patients compared with those in healthy subjects. Interestingly, some DAMs, such as L-tryptophan and sphingosine 1-phosphate, showed an evident negative correlation with changes in the level of TNF-α and IL-17, while tightly positively correlating with altered concentrations of anti-inflammatory cytokines and chemokines, such as MIP-1α and RANTES. Our results revealed that altered metabolomic profiles might contribute to the pathogenesis and course of MS disease by modulating immuno-inflammatory responses in the peripheral system, which is essential for eliciting autoimmune responses in the central nervous system, thus resulting in the progression of MS. This study provides potential clues for developing therapeutic strategies for MS in the near future.

Contribution of Metabolomics to Multiple Sclerosis Diagnosis, Prognosis and Treatment

Metabolomics-based technologies map in vivo biochemical changes that may be used as early indicators of pathological abnormalities prior to the development of clinical symptoms in neurological conditions. Metabolomics may also reveal biochemical pathways implicated in tissue dysfunction and damage and thus assist in the development of novel targeted therapeutics for neuroinflammation and neurodegeneration. Metabolomics holds promise as a non-invasive, high-throughput and cost-effective tool for early diagnosis, follow-up and monitoring of treatment response in multiple sclerosis (MS), in combination with clinical and imaging measures. In this review, we offer evidence in support of the potential of metabolomics as a biomarker and drug discovery tool in MS. We also use pathway analysis of metabolites that are described as potential biomarkers in the literature of MS biofluids to identify the most promising molecules and upstream regulators, and show novel, still unexplored metabolic pathways, whose investigation may open novel avenues of research.

Multiple Sclerosis Biomarker Discoveries by Proteomics and Metabolomics Approaches

Multiple sclerosis (MS) is an autoimmune inflammatory disorder of the central nervous system (CNS) resulting in demyelination and axonal loss in the brain and spinal cord. The precise pathogenesis and etiology of this complex disease are still a mystery. Despite many studies that have been aimed to identify biomarkers, no protein marker has yet been approved for MS. There is urgently needed for biomarkers, which could clarify pathology, monitor disease progression, response to treatment, and prognosis in MS. Proteomics and metabolomics analysis are powerful tools to identify putative and novel candidate biomarkers. Different human compartments analysis using proteomics, metabolomics, and bioinformatics approaches has generated new information for further clarification of MS pathology, elucidating the mechanisms of the disease, finding new targets, and monitoring treatment response. Overall, omics approaches can develop different therapeutic and diagnostic aspects of complex disorders such as multiple sclerosis, from biomarker discovery to personalized medicine.

Potential role of indolelactate and butyrate in multiple sclerosis revealed by integrated microbiome-metabolome analysis

Multiple sclerosis (MS) is an immune-mediated disease whose precise etiology is unknown. Several studies found alterations in the microbiome of individuals with MS, but the mechanism by which it may affect MS is poorly understood. Here we analyze the microbiome of 129 individuals with MS and find that they harbor distinct microbial patterns compared with controls. To study the functional consequences of these differences, we measure levels of 1,251 serum metabolites in a subgroup of subjects and unravel a distinct metabolite signature that separates affected individuals from controls nearly perfectly (AUC = 0.97). Individuals with MS are found to be depleted in butyrate-producing bacteria and in bacteria that produce indolelactate, an intermediate in generation of the potent neuroprotective antioxidant indolepropionate, which we found to be lower in their serum. We identify microbial and metabolite candidates that may contribute to MS and should be explored further for their causal role and therapeutic potential.

Protective Effects of 28-O-Caffeoyl Betulin (B-CA) on the Cerebral Cortex of Ischemic Rats Revealed by a NMR-Based Metabolomics Analysis

28-O-caffeoyl betulin (B-CA) has been demonstrated to reduce the cerebral infarct volume caused by transient middle cerebral artery occlusion (MCAO) injury. B-CA is a novel derivative of naturally occurring caffeoyl triterpene with little information associated with its pharmacological target(s). To date no data is available regarding the effect of B-CA on brain metabolism. In the present study, a 1H-NMR-based metabolomics approach was applied to investigate the therapeutic effects of B-CA on brain metabolism following MCAO in rats. Global metabolic profiles of the cortex in acute period (9 h after focal ischemia onset) after MCAO were compared between the groups (sham; MCAO + vehicle; MCAO + B-CA). MCAO induced several changes in the ipsilateral cortex of ischemic rats, which consequently led to the neuronal damage featured with the downregulation of NAA, including energy metabolism dysfunctions, oxidative stress, and neurotransmitter metabolism. Treatment with B-CA showed statistically significant rescue effects on the ischemic cortex of MCAO rats. Specifically, treatment with B-CA ameliorated the energy metabolism dysfunctions (back-regulating the levels of succinate, lactate, BCAAs, and carnitine), oxidative stress (upregulating the level of glutathione), and neurotransmitter metabolism disturbances (back-regulating the levels of γ-aminobutyric acid and acetylcholine) associated with the progression of ischemic stroke. With the administration of B-CA, the levels of three phospholipid related metabolites (O-phosphocholine, O-phosphoethanolamine, sn-glycero-3-phosphocholine) and NAA improved significantly. Overall, our findings suggest that treatment with B-CA may provide neuroprotection by augmenting the metabolic changes observed in the cortex following MCAO in rats.

An emerging potential of metabolomics in multiple sclerosis: a comprehensive overview

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the nervous system that primarily affects young adults. Although the exact etiology of the disease remains obscure, it is clear that alterations in the metabolome contribute to this process. As such, defining a reliable and disease-specific metabolome has tremendous potential as a diagnostic and therapeutic strategy for MS. Here, we provide an overview of studies aimed at identifying the role of metabolomics in MS. These offer new insights into disease pathophysiology and the contributions of metabolic pathways to this process, identify unique markers indicative of treatment responses, and demonstrate the therapeutic effects of drug-like metabolites in cellular and animal models of MS. By and large, the commonly perturbed pathways in MS and its preclinical model include lipid metabolism involving alpha-linoleic acid pathway, nucleotide metabolism, amino acid metabolism, tricarboxylic acid cycle, d-ornithine and d-arginine pathways with collective role in signaling and energy supply. The metabolomics studies suggest that metabolic profiling of MS patient samples may uncover biomarkers that will advance our understanding of disease pathogenesis and progression, reduce delays and mistakes in diagnosis, monitor the course of disease, and detect better drug targets, all of which will improve early therapeutic interventions and improve evaluation of response to these treatments.

Metabolomic Biomarkers of Multiple Sclerosis: A Systematic Review

Background

Magnetic resonance imaging (MRI), cerebrospinal fluid (CSF) analysis, and the McDonald’s clinical criteria are currently utilized tools in diagnosing multiple sclerosis. However, a more conclusive, consistent, and efficient way of diagnosing multiple sclerosis (MS) is yet to be discovered. A potential biomarker, discovered using advances in high-throughput sequencing such as nuclear magnetic resonance (NMR) spectroscopy and other “Omics”-based techniques, may make diagnosis and prognosis more reliable resulting in a more personalized and targeted treatment regime and improved outcomes. The aim of this review was to systematically search the literature for potential biomarkers from any bodily fluid that could consistently and accurately diagnose MS and/or indicate disease progression.

Methods

A systematic literature review of EMBASE, PubMed (MEDLINE), The Cochrane Library, and CINAHL databases produced over a thousand potential studies. Inclusion criteria stated studies with potential biomarker outcomes for people with MS were to be included in the review. Studies were limited to those with human participants who had a clinically defined diagnosis of MS and published in English, with no limit placed on date of publication or the type of bodily fluid sampled.

Results

A total of 1,805 studies were recorded from the literature search. A total of 1,760 studies were removed based on their abstract, with a further 18 removed after considering the full text. A total of 30 studies were considered relevant and had their data retrieved and analyzed. Due to the heterogeneity of focus and results from the refined studies, a narrative synthesis was favored.

Conclusion

Several promising candidate biomarkers suitable for clinical application in MS have been studied. It is recommended follow-up studies with larger sample sizes be completed on several potential biomarkers.

Targeted metabolomic profiling of cerebrospinal fluid from patients with progressive multifocal leukoencephalopathy

Progressive multifocal leukoencephalopathy (PML), caused by JC polyomavirus, is a demyelinating disease of the central nervous system that primarily affects oligodendrocytes. It can cause significant morbidity and mortality. An early diagnosis is of high relevance as timely immune reconstitution is essential. However, diagnosis can be challenging if virus detection via cerebrospinal fluid (CSF) PCR remains negative. Hence, identifying CSF biomarkers for this disease is of crucial importance. We applied a targeted metabolomic screen to CSF from 23 PML patients and eight normal pressure hydrocephalus (NPH) patients as controls. Out of 188 potentially detectable metabolites, 48 (13 amino acids, 4 biogenic amines, 1 acylcarnitine, 21 phosphatidylcholines, 8 sphingolipids, and the sum of hexoses) passed the quality screen and were included in the analyses. Even though there was a tendency towards lower concentrations in PML (mostly of phosphatidylcholines and sphingomyelins), none of the differences between PML and controls in individual metabolite concentrations reached statistical significance (lowest p = 0.104) and there were no potential diagnostic biomarkers (highest area under the ROC curve 0.68). Thus, CSF metabolite changes in PML are likely subtle and possibly larger group sizes and broader metabolite screens are needed to identify potential CSF metabolite biomarkers for PML.

Pursuing Experimental Reproducibility: An Efficient Protocol for the Preparation of Cerebrospinal Fluid Samples for NMR-based Metabolomics and Analysis of Sample Degradation

NMR-based metabolomics investigations of human biofluids offer great potential to uncover new biomarkers. In contrast to protocols for sample collection and biobanking, procedures for sample preparation prior to NMR measurements are still heterogeneous, thus compromising the comparability of the resulting data. Herein, we present results of an investigation of the handling of cerebrospinal fluid (CSF) samples for NMR metabolomics research. Origins of commonly observed problems when conducting NMR experiments on this type of sample are addressed, and suitable experimental conditions in terms of sample preparation and pH control are discussed. Sample stability was assessed by monitoring the degradation of CSF samples by NMR, hereby identifying metabolite candidates, which are potentially affected by sample storage. A protocol was devised yielding consistent spectroscopic data as well as achieving overall sample stability for robust analysis. We present easy to adopt standard operating procedures with the aim to establish a shared sample handling strategy that facilitates and promotes inter-laboratory comparison, and the analysis of sample degradation provides new insights into sample stability.

Altered Cerebrospinal Fluid Concentrations of Hydrophobic and Hydrophilic Compounds in Early Stages of Multiple Sclerosis-Metabolic Profile Analyses

The lack of a single predictive or diagnostic test in multiple sclerosis (MS) remains a major obstacle in the patient’s care. The aim of this study was to investigate metabolic profiles, especially lipids in cerebrospinal fluid (CSF) using ¹H-NMR spectroscopy and metabolomics analysis to discriminate MS patient group from the control ones. In this study, 19 MS patients and 19 controls, without neurological problems, patients were enrolled. To obtain the CSF metabolic profiles, NMR spectroscopy was used. Hydrophilic and hydrophobic compounds were analyzed using univariate and multivariate supervised analysis orthogonal partial least square discriminant analysis (OPLS-DA). Targeted OPLS-DA analysis of 32 hydrophilic and 17 hydrophobic compounds obtained 9 hydrophilic metabolites and 8 lipid functional groups which had the highest contribution to patient’s group separation. Lower concentrations of CSF hydrophilic and hydrophobic compounds were observed in MS patients as compared to control group. Acetone, choline, urea, 1,3-dimethylurate, creatinine, isoleucine, myo-inositol, leucine, and 3-OH butyrate; saturated and monounsaturated acyl groups of ω–9, ω–7, ω–6, ω–3, and fatty acid, triglycerides, 1,3-DG, 1-MG, and unassigned component signal at 3.33 ppm were the most important signal compounds in group separation. Analysis of metabolic profile of raw CSF and their lipid extract shows decreased levels of many compounds and led to the conclusion that MS patients could have a disturbance in many metabolic pathways perhaps leading to the decreased level of acetyl-CoA and/or inflammation. CSF metabolic profile analyses could be used as a fingerprint for early MS diagnosis.

Biochemical Differences in Cerebrospinal Fluid between Secondary Progressive and Relapsing⁻Remitting Multiple Sclerosis

To better understand the pathophysiological differences between secondary progressive multiple sclerosis (SPMS) and relapsing-remitting multiple sclerosis (RRMS), and to identify potential biomarkers of disease progression, we applied high-resolution mass spectrometry (HRMS) to investigate the metabolome of cerebrospinal fluid (CSF). The biochemical differences were determined using partial least squares discriminant analysis (PLS-DA) and connected to biochemical pathways as well as associated to clinical and radiological measures. Tryptophan metabolism was significantly altered, with perturbed levels of kynurenate, 5-hydroxytryptophan, 5-hydroxyindoleacetate, and N-acetylserotonin in SPMS patients compared with RRMS and controls. SPMS patients had altered kynurenine compared with RRMS patients, and altered indole-3-acetate compared with controls. Regarding the pyrimidine metabolism, SPMS patients had altered levels of uridine and deoxyuridine compared with RRMS and controls, and altered thymine and glutamine compared with RRMS patients. Metabolites from the pyrimidine metabolism were significantly associated with disability, disease activity and brain atrophy, making them of particular interest for understanding the disease mechanisms and as markers of disease progression. Overall, these findings are of importance for the characterization of the molecular pathogenesis of SPMS and support the hypothesis that the CSF metabolome may be used to explore changes that occur in the transition between the RRMS and SPMS pathologies.

Metabonomics reveals peripheral and central short-chain fatty acid and amino acid dysfunction in a naturally occurring depressive model of macaques

PURPOSE

Depression is a complex psychiatric disorder. Various depressive rodent models are usually constructed based on different pathogenesis hypotheses.

MATERIALS AND METHODS

Herein, using our previously established naturally occurring depressive (NOD) model in a non-human primate (cynomolgus monkey, Macaca fascularis), we performed metabolomics analysis of cerebrospinal fluid (CSF) from NOD female macaques (N=10) and age-and gender-matched healthy controls (HCs) (N=12). Multivariate statistical analysis was used to identify the differentially expressed metabolites between the two groups. Ingenuity Pathways Analysis and MetaboAnalyst were applied for predicted pathways and biological functions analysis.

RESULTS

Totally, 37 metabolites responsible for discriminating the two groups were identified. The NOD macaques were mainly characterized by perturbations of fatty acid biosynthesis, ABC transport system, and amino acid metabolism (eg, aspartate, glycine, serine, and threonine metabolism). Interestingly, we found that eight altered CSF metabolites belonging to short-chain fatty acids and amino acids were also observed in the serum of NOD macaques (N=13 per group).

CONCLUSION

Our findings suggest that peripheral and central short-chain fatty acids and amino acids are implicated in the onset of depression.

Metabolic fingerprinting of joint tissue of collagen-induced arthritis (CIA) rat: In vitro, high resolution NMR (nuclear magnetic resonance) spectroscopy based analysis

Rheumatoid arthritis (RA) is a systemic autoimmune disease whose major characteristics persistent joint inflammation that results in joint destruction and failure of the function. Collagen-induced arthritis (CIA) rat is an autoimmune disease model and in many ways shares features with RA. The CIA is associated with systemic manifestations, including alterations in the metabolism. Nuclear magnetic resonance (NMR) spectroscopy-based metabolomics has been successfully applied to the perchloric acid extract of the joint tissue of CIA rat and control rat for the analysis of aqueous metabolites. GPC (Glycerophosphocholine), carnitine, acetate, and creatinine were important discriminators of CIA rats as compared to control rats. Level of lactate (significance; p = 0.004), alanine (p = 0.025), BCA (Branched-chain amino acids) (p = 0.006) and creatinine (p = 0.023) was significantly higher in CIA rats as compared to control rats. Choline (p = 0.038) and GPC (p = 0.009) were significantly reduced in CIA rats as compared to control rats. Choline to GPC correlation was good and negative (Pearson correlation = -0.63) for CIA rats as well as for control rats (Pearson correlation = -0.79). All these analyses collectively considered as metabolic fingerprinting of the joint tissue of CIA rat as compared to control rat. The metabolic fingerprinting of joint tissue of CIA rats was different as compared to control rats. The metabolic fingerprinting reflects inflammatory disease activity in CIA rats with synovitis, demonstrating that underlying inflammatory process drives significant changes in metabolism that can be measured in the joint tissue. Therefore, the outcome of this study may be helpful for understanding the mechanism of metabolic processes in RA. This may be also helpful for the development of advanced diagnostic methods and therapy for RA.

Metabolic alterations in multiple sclerosis and the impact of vitamin D supplementation

BACKGROUND

Our goal was to identify changes in the metabolome in multiple sclerosis (MS) and how vitamin D supplementation alters metabolic profiles in MS patients and healthy controls.

METHODS

We applied global untargeted metabolomics to plasma from a cross-sectional cohort of age- and sex-matched MS patients and controls and a second longitudinal cohort of MS patients and healthy controls who received 5,000 IU cholecalciferol daily for 90 days. We applied partial least squares discriminant analysis, weighted correlation network analysis (WGCNA), and pathway analysis to the metabolomics data. Generalized estimating equations models were used to assess change in WGCNA-identified module scores or metabolite pathways with vitamin D supplementation.

RESULTS

Utilizing multiple analytical techniques, we identified metabolic alterations in oxidative stress (γ-glutamyl amino acid, glutathione) and xenobiotic metabolism (benzoate, caffeine) in MS patients compared with healthy controls in the first cohort. In the vitamin D supplementation cohort, we identified two sets of metabolites altered differentially between MS patients and healthy controls with vitamin D supplementation. The first included markers of oxidative stress and protein oxidation (P = 0.006), while the second contained lysolipids and fatty acids (P = 0.03).

CONCLUSIONS

Using metabolomics, we identified alterations in oxidative stress and xenobiotic metabolism in MS patients and subsequently demonstrated a reduction of oxidative stress markers with vitamin D supplementation in healthy controls but not in MS patients. We demonstrate the utility of metabolomics in identifying aberrant metabolic processes and in monitoring the ability of therapeutic interventions to correct these abnormalities.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01667796.

FUNDING

This study was supported by NIH grant K23 NS067055, grants from the Race to Erase MS, the National Multiple Sclerosis Society, the American Academy of Neurology, and North American Research Committee on Multiple Sclerosis.

Traumatic Brain Injury Alters the Metabolism and Facilitates Alzheimer's Disease in a Murine Model

A majority of Alzheimer's disease (AD) cases are sporadic without known cause. People who suffered from traumatic brain injury (TBI) are more likely to develop neurodegeneration and cognitive impairments. However, the role of TBI in pathophysiology of AD remains elusive. The present study intended to explore the effect of TBI on metabolism and its role in AD pathogenesis. We subjected double transgenic AD model mice APP23/PS45 to TBI. We found that TBI promoted β-secretase cleavage of amyloid β precursor protein and amyloid β protein deposition, and exuberated the cognitive impairments in AD mouse models. ¹H nuclear magnetic resonance (¹H-NMR)-based metabolomics with multivariate analysis was performed to investigate the characteristic metabolites and the related metabolic pathways in the serum and urine samples of the mice. TBI affected the metabolic patterns, methylamine metabolism, and amino acid metabolism in serum samples. Urinary metabolites showed that glycolysis and the tricarboxylic acid (TCA) cycle were perturbed. The results indicate that TBI might facilitate Alzheimer's pathogenesis by altering metabolism and inducing mitochondrial dysfunction. The study suggests that metabolite changes could also serve as biomarkers for TBI-induced neurodegeneration.

Metabolomic profiling of CSF in multiple sclerosis and neuromyelitis optica spectrum disorder by nuclear magnetic resonance

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are inflammatory diseases of the central nervous system. Although several studies have characterized the metabolome in the cerebrospinal fluid (CSF) from MS and NMOSD patients, comparative analyses between them and between the relapse and the remission of each disease have not been performed. Both univariate and multivariate analyses were used to compare 1H-NMR spectra of CSF from MS, NMOSD, and healthy controls (HCs). The statistical analysis showed alterations of eight metabolites that were dependent on the disease. Levels of 2-hydroxybutyrate, acetone, formate, and pyroglutamate were higher and levels of acetate and glucose were lower in both MS and NMOSD. Citrate was lower in MS patients, whereas lactate was higher in only NMOSD specifically. The shared feature of metabolic changes between MS and NMOSD may be related to altered energy metabolism and fatty acid biosynthesis in the brain. Another analysis to characterize relapse and remission status showed that isoleucine and valine were down-regulated in MS relapse compared to MS remission. The other metabolites identified in the disease comparison showed the same alterations regardless of disease activity. These findings would be helpful in understanding the biological background of these diseases, and distinguishing between MS and NMOSD, as well as determining the disease activity.

Identification of altered brain metabolites associated with TNAP activity in a mouse model of hypophosphatasia using untargeted NMR-based metabolomics analysis

Tissue non-specific alkaline phosphatase (TNAP) is a key player of bone mineralization and TNAP gene (ALPL) mutations in human are responsible for hypophosphatasia (HPP), a rare heritable disease affecting the mineralization of bones and teeth. Moreover, TNAP is also expressed by brain cells and the severe forms of HPP are associated with neurological disorders, including epilepsy and brain morphological anomalies. However, TNAP's role in the nervous system remains poorly understood. To investigate its neuronal functions, we aimed to identify without any a priori the metabolites regulated by TNAP in the nervous tissue. For this purpose we used ¹ H- and ³¹ P NMR to analyze the brain metabolome of Alpl (Akp2) mice null for TNAP function, a well-described model of infantile HPP. Among 39 metabolites identified in brain extracts of 1-week-old animals, eight displayed significantly different concentration in Akp2^-/- compared to Akp2^+/+ and Akp2^+/- mice: cystathionine, adenosine, GABA, methionine, histidine, 3-methylhistidine, N-acetylaspartate (NAA), and N-acetyl-aspartyl-glutamate, with cystathionine and adenosine levels displaying the strongest alteration. These metabolites identify several biochemical processes that directly or indirectly involve TNAP function, in particular through the regulation of ecto-nucleotide levels and of pyridoxal phosphate-dependent enzymes. Some of these metabolites are involved in neurotransmission (GABA, adenosine), in myelin synthesis (NAA, NAAG), and in the methionine cycle and transsulfuration pathway (cystathionine, methionine). Their disturbances may contribute to the neurodevelopmental and neurological phenotype of HPP.

A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls

BACKGROUND

Fibromyalgia syndrome (FMS) is a chronic pain syndrome. A plausible pathogenesis of the disease is uncertain and the pursuit of measurable biomarkers for objective identification of affected individuals is a continuing endeavour in FMS research. Our objective was to perform an explorative metabolomics study (1) to elucidate the global urinary metabolite profile of patients suffering from FMS, and (2) to explore the potential of this metabolite information to augment existing medical practice in diagnosing the disease.

METHODS

We selected patients with a medical history of persistent FMS (n = 18), who described their recent state of the disease through the Fibromyalgia Impact Questionnaire (FIQR) and an in-house clinical questionnaire (IHCQ). Three control groups were used: first-generation family members of the patients (n = 11), age-related individuals without any indications of FMS or related conditions (n = 10), and healthy young (18-22 years) individuals (n = 20). All subjects were female and the biofluid under investigation was urine. Correlation analysis of the FIQR showed the FMS patients represented a well-defined disease group for this metabolomics study. Spectral analyses of urine were conducted using a 500 MHz ¹H nuclear magnetic resonance (NMR) spectrometer; data processing and analyses were performed using Matlab, R, SPSS and SAS software.

RESULTS AND DISCUSSION

Unsupervised and supervised multivariate analyses distinguished all three control groups and the FMS patients, and significant increases in metabolites related to the gut microbiome (hippuric, succinic and lactic acids) were observed. We have developed an algorithm for the diagnosis of FMS consisting of three metabolites - succinic acid, taurine and creatine - that have a good level of diagnostic accuracy (Receiver Operating Characteristic (ROC) analysis - area under the curve 90%) and on the pain and fatigue symptoms for the selected FMS patient group.

CONCLUSION

Our data and comparative analyses indicated an altered metabolic profile of patients with FMS, analytically detectable within their urine. Validation studies may substantiate urinary metabolites to supplement information from medical assessment, tender-point measurements and FIQR questionnaires for an improved objective diagnosis of FMS.

Role of Gasotransmitters in Oxidative Stresses, Neuroinflammation, and Neuronal Repair

To date, three main gasotransmitters, that is, hydrogen sulfide (H₂S), carbon monoxide (CO), and nitric oxide (NO), have been discovered to play major bodily physiological roles. These gasotransmitters have multiple functional roles in the body including physiologic and pathologic functions with respect to the cellular or tissue quantities of these gases. Gasotransmitters were originally known to have only detrimental and noxious effects in the body but that notion has much changed with years; vast studies demonstrated that these gasotransmitters are precisely involved in the normal physiological functioning of the body. From neuromodulation, oxidative stress subjugation, and cardiovascular tone regulation to immunomodulation, these gases perform critical roles, which, should they deviate from the norm, can trigger the genesis of a number of neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD). The purpose of this review is to discuss at great length physical and chemical properties and physiological actions of H₂S, NO, and CO as well as shedding light on recently researched molecular targets. We particularly put emphasis on the roles in neuronal inflammation and neurodegeneration and neuronal repair.

Changes in urinary metabolomic profile during relapsing renal vasculitis

Current biomarkers of renal disease in systemic vasculitis lack predictive value and are insensitive to early damage. To identify novel biomarkers of renal vasculitis flare, we analysed the longitudinal urinary metabolomic profile of a rat model of anti-neutrophil cytoplasmic antibody (ANCA) vasculitis. Wistar-Kyoto (WKY) rats were immunised with human myeloperoxidase (MPO). Urine was obtained at regular intervals for 181 days, after which relapse was induced by re-challenge with MPO. Urinary metabolites were assessed in an unbiased fashion using nuclear magnetic resonance (NMR) spectroscopy, and analysed using partial least squares discriminant analysis (PLS-DA) and partial least squares regression (PLS-R). At 56 days post-immunisation, we found that rats with vasculitis had a significantly different urinary metabolite profile than control animals; the observed PLS-DA clusters dissipated between 56 and 181 days, and re-emerged with relapse. The metabolites most altered in rats with active or relapsing vasculitis were trimethylamine N-oxide (TMAO), citrate and 2-oxoglutarate. Myo-inositol was also moderately predictive. The key urine metabolites identified in rats were confirmed in a large cohort of patients using liquid chromatography–mass spectrometry (LC-MS). Hypocitraturia and elevated urinary myo-inositol remained associated with active disease, with the urine myo-inositol:citrate ratio being tightly correlated with active renal vasculitis.

Metabolomic analysis of CSF indicates brain metabolic impairment precedes hematological indices of anemia in the iron-deficient infant monkey

OBJECTIVES

Iron deficiency (ID) anemia leads to long-term neurodevelopmental deficits by altering iron-dependent brain metabolism. The objective of the study was to determine if ID induces metabolomic abnormalities in the cerebrospinal fluid (CSF) in the pre-anemic stage and to ascertain the aspects of abnormal brain metabolism affected.

METHODS

Standard hematological parameters [hemoglobin (Hgb), mean corpuscular volume (MCV), transferrin (Tf) saturation, and zinc protoporphyrin/heme (ZnPP/H)] were compared at 2, 4, 6, 8, and 12 months in iron-sufficient (IS; n = 7) and iron-deficient (ID; n = 7) infant rhesus monkeys. Five CSF metabolite ratios were determined at 4, 8, and 12 months using ¹H NMR spectroscopy at 16.4 T and compared between groups and in relation to hematologic parameters.

RESULTS

ID infants developed ID (Tf saturation < 25%) by 4 months of age and all became anemic (Hgb < 110 g/L and MCV < 60 fL) at 6 months. Their heme indices normalized by 12 months. Pyruvate/glutamine and phosphocreatine/creatine (PCr/Cr) ratios in CSF were lower in the ID infants by 4 months (P < 0.05). The PCr/Cr ratio remained lower at 8 months (P = 0.02). ZnPP/H, an established blood marker of pre-anemic ID, was positively correlated with the CSF citrate/glutamine ratio (marginal correlation, 0.34; P < 0.001; family wise error rate = 0.001).

DISCUSSION

Metabolomic analysis of the CSF is sensitive for detecting the effects of pre-anemic ID on brain energy metabolism. Persistence of a lower PCr/Cr ratio at 8 months, even as hematological measures demonstrated recovery from anemia, indicate that the restoration of brain energy metabolism is delayed. Metabolomic platforms offer a useful tool for early detection of the impact of ID on brain metabolism in infants.

Metabolomic investigation of regional brain tissue dysfunctions induced by global cerebral ischemia

Background

To get a broader view of global ischemia-induced cerebral disorders at the metabolic level, a nuclear magnetic resonance-based metabolomic study was performed to evaluate the metabolic profile changes on regional brain tissues of female and male mice upon bilateral common carotid arteries occlusion (BCCAO) operation.

Results

Significant metabolic disorders were observed in both cerebral cortex and hippocampus tissues of the experimental mice upon global cerebral ischemic attack. Multiple amino acids were identified as the dominantly perturbed metabolites. It was also shown that although the metabolic profile change patterns in the brain tissues were quite similar in male and female BCCAO mice, metabolic disorders in the cortex tissues were more severe in the female mice than in the male mice.

Conclusions

In the present study, significant changes in amino acid metabolic pathways were confirmed in the early stage of global ischemia. Meanwhile, cerebral metabolic dysfunctions were more severe in the female BCCAO mice than in the male mice, suggesting that gender may play a role in different metabolic responses to the ischemic attack, which may provide an important hypothesis for a better understanding of the clinically observed gender-dependent pathological outcome of cerebral ischemia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12868-016-0256-9) contains supplementary material, which is available to authorized users.

(1)H-NMR analysis provides a metabolomic profile of patients with multiple sclerosis

Objective:

To investigate the metabolomic profiles of patients with multiple sclerosis (MS) and to define the metabolic pathways potentially related to MS pathogenesis.

Methods:

Plasma samples from 73 patients with MS (therapy-free for at least 90 days) and 88 healthy controls (HC) were analyzed by ¹H-NMR spectroscopy. Data analysis was conducted with principal components analysis followed by a supervised analysis (orthogonal partial least squares discriminant analysis [OPLS-DA]). The metabolites were identified and quantified using Chenomx software, and the receiver operating characteristic (ROC) curves were calculated.

Results:

The model obtained with the OPLS-DA identified predictive metabolic differences between the patients with MS and HC (R2X = 0.615, R2Y = 0.619, Q2 = 0.476; p < 0.001). The differential metabolites included glucose, 5-OH-tryptophan, and tryptophan, which were lower in the MS group, and 3-OH-butyrate, acetoacetate, acetone, alanine, and choline, which were higher in the MS group. The suitability of the model was evaluated using an external set of samples. The values returned by the model were used to build the corresponding ROC curve (area under the curve of 0.98).

Conclusion:

NMR metabolomic analysis was able to discriminate different metabolic profiles in patients with MS compared with HC. With the exception of choline, the main metabolic changes could be connected to 2 different metabolic pathways: tryptophan metabolism and energy metabolism. Metabolomics appears to represent a promising noninvasive approach for the study of MS.

An integrated mechanism of pediatric pseudotumor cerebri syndrome: evidence of bioenergetic and hormonal regulation of cerebrospinal fluid dynamics

Pseudotumor cerebri syndrome (PTCS) is defined by the presence of elevated intracranial pressure (ICP) in the setting of normal brain parenchyma and cerebrospinal fluid (CSF). Headache, vision changes, and papilledema are common presenting features. Up to 10% of appropriately treated patients may experience permanent visual loss. The mechanism(s) underlying PTCS is unknown. PTCS occurs in association with a variety of conditions, including kidney disease, obesity, and adrenal insufficiency, suggesting endocrine and/or metabolic derangements may occur. Recent studies suggest that fluid and electrolyte balance in renal epithelia is regulated by a complex interaction of metabolic and hormonal factors; these cells share many of the same features as the choroid plexus cells in the central nervous system (CNS) responsible for regulation of CSF dynamics. Thus, we posit that similar factors may influence CSF dynamics in both types of fluid-sensitive tissues. Specifically, we hypothesize that, in patients with PTCS, mitochondrial metabolites (glutamate, succinate) and steroid hormones (cortisol, aldosterone) regulate CSF production and/or absorption. In this integrated mechanism review, we consider the clinical and molecular evidence for each metabolite and hormone in turn. We illustrate how related intracellular signaling cascades may converge in the choroid plexus, drawing on evidence from functionally similar tissues.

A hypothetical astrocyte-microglia lactate shuttle derived from a 1H NMR metabolomics analysis of cerebrospinal fluid from a cohort of South African children with tuberculous meningitis

Tuberculosis meningitis (TBM) is the most severe form of extra-pulmonary tuberculosis and is particularly intense in small children; there is no universally accepted algorithm for the diagnosis and substantiation of TB infection, which can lead to delayed intervention, a high risk factor for morbidity and mortality. In this study a proton magnetic resonance (¹H NMR)-based metabolomics analysis and several chemometric methods were applied to data generated from lumber cerebrospinal fluid (CSF) samples from three experimental groups: (1) South African infants and children with confirmed TBM, (2) non-meningitis South African infants and children as controls, and (3) neurological controls from the Netherlands. A total of 16 NMR-derived CSF metabolites were identified, which clearly differentiated between the controls and TBM cases under investigation. The defining metabolites were the combination of perturbed glucose and highly elevated lactate, common to some other neurological disorders. The remaining 14 metabolites of the host's response to TBM were likewise mainly energy-associated indicators. We subsequently generated a hypothesis expressed as an "astrocyte-microglia lactate shuttle" (AMLS) based on the host's response, which emerged from the NMR-metabolomics information. Activation of microglia, as implied by the AMLS hypothesis, does not, however, present a uniform process and involves intricate interactions and feedback loops between the microglia, astrocytes and neurons that hamper attempts to construct basic and linear cascades of cause and effect; TBM involves a complex integration of the responses from the various cell types present within the CNS, with microglia and the astrocytes as main players.

Follicular adenomas exhibit a unique metabolic profile. ¹H NMR studies of thyroid lesions

Thyroid cancer is the most common endocrine malignancy. However, more than 90% of thyroid nodules are benign. It remains unclear whether thyroid carcinoma arises from preexisting benign nodules. Metabolomics can provide valuable and comprehensive information about low molecular weight compounds present in living systems and further our understanding of the biology regulating pathological processes. Herein, we applied ¹H NMR-based metabolic profiling to identify the metabolites present in aqueous tissue extracts of healthy thyroid tissue (H), non-neoplastic nodules (NN), follicular adenomas (FA) and malignant thyroid cancer (TC) as an alternative way of investigating cancer lesions. Multivariate statistical methods provided clear discrimination not only between healthy thyroid tissue and pathological thyroid tissue but also between different types of thyroid lesions. Potential biomarkers common to all thyroid lesions were identified, namely, alanine, methionine, acetone, glutamate, glycine, lactate, tyrosine, phenylalanine and hypoxanthine. Metabolic changes in thyroid cancer were mainly related to osmotic regulators (taurine and scyllo- and myo-inositol), citrate, and amino acids supplying the TCA cycle. Thyroid follicular adenomas were found to display metabolic features of benign non-neoplastic nodules and simultaneously displayed a partial metabolic profile associated with malignancy. This finding allows the discrimination of follicular adenomas from benign non-neoplastic nodules and thyroid cancer with similar accuracy. Moreover, the presented data indicate that follicular adenoma could be an individual stage of thyroid cancer development.

The 1H NMR profile of healthy dog cerebrospinal fluid

The availability of data for reference values in cerebrospinal fluid for healthy humans is limited due to obvious practical and ethical issues. The variability of reported values for metabolites in human cerebrospinal fluid is quite large. Dogs present great similarities with humans, including in cases of central nervous system pathologies. The paper presents the first study on healthy dog cerebrospinal fluid metabolomic profile using ¹H NMR spectroscopy. A number of 13 metabolites have been identified and quantified from cerebrospinal fluid collected from a group of 10 mix breed healthy dogs. The biological variability as resulting from the relative standard deviation of the physiological concentrations of the identified metabolites had a mean of 18.20% (range between 9.3% and 44.8%). The reported concentrations for metabolites may be used as normal reference values. The homogeneity of the obtained results and the low biologic variability show that the ¹H NMR analysis of the dog’s cerebrospinal fluid is reliable in designing and interpreting clinical and therapeutic trials in dogs with central nervous system pathologies.

The impact of inflammation on metabolomic profiles in patients with arthritis

Objective. Inflammatory arthritis is associated with systemic manifestations including alterations in metabolism. We used nuclear magnetic resonance (NMR) spectroscopy–based metabolomics to assess metabolic fingerprints in serum from patients with established rheumatoid arthritis (RA) and those with early arthritis.

Methods. Serum samples were collected from newly presenting patients with established RA who were naive for disease-modifying antirheumatic drugs, matched healthy controls, and 2 groups of patients with synovitis of ≤3 months' duration whose outcomes were determined at clinical followup. Serum metabolomic profiles were assessed using 1-dimensional ¹H-NMR spectroscopy. Discriminating metabolites were identified, and the relationships between metabolomic profiles and clinical variables including outcomes were examined.

Results. The serum metabolic fingerprint in established RA was clearly distinct from that of healthy controls. In early arthritis, we were able to stratify the patients according to the level of current inflammation, with C-reactive protein correlating with metabolic differences in 2 separate groups (P < 0.001). Lactate and lipids were important discriminators of inflammatory burden in both early arthritis patient groups. The sensitivities and specificities of models to predict the development of either RA or persistent arthritis in patients with early arthritis were low.

Conclusion. The metabolic fingerprint reflects inflammatory disease activity in patients with synovitis, demonstrating that underlying inflammatory processes drive significant changes in metabolism that can be measured in the peripheral blood. The identification of metabolic alterations may provide insights into disease mechanisms operating in patients with inflammatory arthritis.

Application of (1)h NMR spectroscopy-based metabolomics to sera of tuberculosis patients

Nuclear magnetic resonance (NMR) spectroscopy is an ideal platform for the metabolic analysis of biofluids due to its high reproducibility, nondestructiveness, nonselectivity in metabolite detection, and the ability to simultaneously quantify multiple classes of metabolites. Tuberculosis (TB) is a chronic wasting inflammatory disease characterized by multisystem involvement, which can cause metabolic derangements in afflicted patients. In this study, we combined multivariate pattern recognition (PR) analytical techniques with (1)H NMR spectroscopy to explore the metabolic profile of sera from TB patients. A total of 77 serum samples obtained from patients with TB (n = 38) and healthy controls (n = 39) were investigated. Orthogonal partial least-squares discriminant analysis (OPLS-DA) was capable of distinguishing TB patients from controls and establishing a TB-specific metabolite profile. A total of 17 metabolites differed significantly in concentration between the two groups. Serum samples from TB patients were characterized by increased concentrations of 1-methylhistidine, acetoacetate, acetone, glutamate, glutamine, isoleucine, lactate, lysine, nicotinate, phenylalanine, pyruvate, and tyrosine, accompanied by reduced concentrations of alanine, formate, glycine, glycerolphosphocholine, and low-density lipoproteins relative to control subjects. Our study reveals the metabolic profile of sera from TB patients and indicates that NMR-based methods can distinguish TB patients from healthy controls. NMR-based metabolomics has the potential to be developed into a novel clinical tool for TB diagnosis or therapeutic monitoring and could contribute to an improved understanding of disease mechanisms.

Metabolic profiling predicts response to anti-tumor necrosis factor α therapy in patients with rheumatoid arthritis

Objective

Anti–tumor necrosis factor (anti-TNF) therapies are highly effective in rheumatoid arthritis (RA) and psoriatic arthritis (PsA), but a significant number of patients exhibit only a partial or no therapeutic response. Inflammation alters local and systemic metabolism, and TNF plays a role in this. We undertook this study to determine if the patient's metabolic fingerprint prior to therapy could predict responses to anti-TNF agents.

Methods

Urine was collected from 16 RA patients and 20 PsA patients before and during therapy with infliximab or etanercept. Urine metabolic profiles were assessed using nuclear magnetic resonance spectroscopy. Discriminating metabolites were identified, and the relationship between metabolic profiles and clinical outcomes was assessed.

Results

Baseline urine metabolic profiles discriminated between RA patients who did or did not have a good response to anti-TNF therapy according to European League Against Rheumatism criteria, with a sensitivity of 88.9% and a specificity of 85.7%, with several metabolites contributing (in particular histamine, glutamine, xanthurenic acid, and ethanolamine). There was a correlation between baseline metabolic profiles and the magnitude of change in the Disease Activity Score in 28 joints from baseline to 12 months in RA patients (P = 0.04). In both RA and PsA, urinary metabolic profiles changed between baseline and 12 weeks of anti-TNF therapy. Within the responders, urinary metabolite changes distinguished between etanercept and infliximab treatment.

Conclusion

The clear relationship between urine metabolic profiles of RA patients at baseline and their response to anti-TNF therapy may allow development of novel approaches to the optimization of therapy. Differences in metabolic profiles during treatment with infliximab and etanercept in RA and PsA may reflect distinct mechanisms of action.

Cerebral biochemical pathways in experimental autoimmune encephalomyelitis and adjuvant arthritis: a comparative metabolomic study

Many diseases, including brain disorders, are associated with perturbations of tissue metabolism. However, an often overlooked issue is the impact that inflammations outside the brain may have on brain metabolism. Our main goal was to study similarities and differences between brain metabolite profiles of animals suffering from experimental autoimmune encephalomyelitis (EAE) and adjuvant arthritis (AA) in Lewis rat models. Our principal objective was the determination of molecular protagonists involved in the metabolism underlying these diseases. EAE was induced by intraplantar injection of complete Freund’s adjuvant (CFA) and spinal-cord homogenate (SC-H), whereas AA was induced by CFA only. Naive rats served as controls (n = 9 for each group). Two weeks after inoculation, animals were sacrificed, and brains were removed and processed for metabolomic analysis by NMR spectroscopy or for immunohistochemistry. Interestingly, both inflammatory diseases caused similar, though not identical, changes in metabolites involved in regulation of brain cell size and membrane production: among the osmolytes, taurine and the neuronal marker, N-acetylaspartate, were decreased, and the astrocyte marker, myo-inositol, slightly increased in both inoculated groups compared with controls. Also ethanolamine-containing phospholipids, sources of inflammatory agents, and several glycolytic metabolites were increased in both inoculated groups. By contrast, the amino acids, aspartate and isoleucine, were less concentrated in CFA/SC-H and control vs. CFA rats. Our results suggest that inflammatory brain metabolite profiles may indicate the existence of either cerebral (EAE) or extra-cerebral (AA) inflammation. These inflammatory processes may act through distinct pathways that converge toward similar brain metabolic profiles. Our findings open new avenues for future studies aimed at demonstrating whether brain metabolic effects provoked by AA are pain/stress-mediated and/or due to the presence of systemic proinflammatory molecules. Regardless of the nature of these mechanisms, our findings may be of interest for future clinical studies, e.g. by in-vivo magnetic resonance spectroscopy.

Metabolomics--a novel window into inflammatory disease

Inflammation is an important component of normal responses to infection and injury. However, chronic activation of the immune system, due to aberrant responses to normal stimuli, can lead to the establishment of a persistent inflammatory state. Such inflammatory conditions are often debilitating, and are associated with a number of important co-morbidities including cardiovascular disease. Resting non-proliferative tissues have distinctive metabolic activities and requirements, which differ considerably from those in infiltrating immune cells, which are undergoing proliferation and differentiation. Immune responses in tissues may therefore be modulated by the relative abundance of substrates in the inflamed site. In turn immune cell activity can feed back and affect metabolic behaviour of the tissues, as most clearly demonstrated in cachexia - the loss of cellular mass driven by tumour necrosis factor-alpha (TNF-α) a key mediator of the inflammatory response. Here we discuss the potential for metabolomic analysis to clarify the interactions between inflammation and metabolic changes underlying many diseases. We suggest that an increased understanding of the interaction between inflammation and cellular metabolism, energy substrate use, tissue breakdown markers, the microbiome and drug metabolites, may provide novel insight into the regulation of inflammatory diseases.

Metabolomics of cerebrospinal fluid from humans treated for rabies

Rabies is a rapidly progressive lyssavirus encephalitis that is statistically 100% fatal. There are no clinically effective antiviral drugs for rabies. An immunologically naïve teenager survived rabies in 2004 through improvised supportive care; since then, 5 additional survivors have been associated with use of the so-called Milwaukee Protocol (MP). The MP applies critical care focused on the altered metabolic and physiologic states associated with rabies. The aim of this study was to examine the metabolic profile of cerebrospinal fluid (CSF) from rabies patients during clinical progression of rabies encephalitis in survivors and nonsurvivors and to compare these samples with control CSF samples. Unsupervised clustering algorithms distinguished three stages of rabies disease and identified several metabolites that differentiated rabies survivors from those who subsequently died, in particular, metabolites related to energy metabolism and cell volume control. Moreover, for those patients who survived, the trajectory of their metabolic profile tracked toward the control profile and away from the rabies profile. NMR metabolomics of human rabies CSF provide new insights into the mechanisms of rabies pathogenesis, which may guide future therapy of this disease.

Metabolomic analysis of cerebrospinal fluid indicates iron deficiency compromises cerebral energy metabolism in the infant monkey

Iron deficiency anemia affects many pregnant women and young infants worldwide. The health impact is significant, given iron's known role in many body functions, including oxidative and lipid metabolism, protein synthesis and brain neurochemistry. The following research determined if (1)H NMR spectroscopy-based metabolomic analysis of cerebrospinal fluid (CSF) could detect the adverse influence of early life iron deficiency on the central nervous system. Using a controlled dietary model in 43 infant primates, distinct differences were found in spectra acquired at 600 MHz from the CSF of anemic monkeys. Three metabolite ratios, citrate/pyruvate, citrate/lactate and pyruvate/glutamine ratios, differed significantly in the iron deficient infant and then normalized following the consumption of dietary iron and improvement of clinical indices of anemia in the heme compartment. This distinctive metabolomic profile associated with anemia in the young infant indicates that CSF can be employed to track the neurological effects of iron deficiency and benefits of iron supplementation.

A pilot metabolic profiling study in serum of patients with chronic kidney disease based on (1) H-NMR-spectroscopy

BACKGROUND

Chronic kidney disease (CKD) is the end point of a number of renal and systemic diseases. The metabolomics with a highly multiplexed and efficient manner is a challenging goal in nephrology.

METHODS

A (1) H-NMR based metabolomics approach was applied to establish a human CKD serum metabolic profile. Serum samples were obtained from CKD patients with four stages (N= 80) and healthy controls (N= 28). The data acquired by CMPG spectrum were further processed by pattern recognition (PR) analysis. Principal components analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA) was capable of clustering the disease groups and establishing disease-specific metabolites profile.

RESULTS

The classification models could grade CKD patients with considerably high value of Q(2) and R(2) . The significant endogenous metabolites that contributed to distinguish CKD in different stages included the products of glycolysis (glucose, lactate), amino acids (valine, alanine, glutamate, glycine), organic osmolytes (betaine, myo-inositol, taurine, glycerophosphcholine), and so on. Based on these metabolites, the model for diagnosing patients with CKD achieved the sensitivity and specificity of 100%.

CONCLUSION

The study illustrated that serum metabolic profile was altered in response to renal dysfunction and the progression of CKD. The identified metabolic biomarkers may provide useful information for the diagnosis of CKD, especially in early stages.

Interpretation and visualization of non-linear data fusion in kernel space: study on metabolomic characterization of progression of multiple sclerosis

Background

In the last decade data fusion has become widespread in the field of metabolomics. Linear data fusion is performed most commonly. However, many data display non-linear parameter dependences. The linear methods are bound to fail in such situations. We used proton Nuclear Magnetic Resonance and Gas Chromatography-Mass Spectrometry, two well established techniques, to generate metabolic profiles of Cerebrospinal fluid of Multiple Sclerosis (MScl) individuals. These datasets represent non-linearly separable groups. Thus, to extract relevant information and to combine them a special framework for data fusion is required.

Methodology

The main aim is to demonstrate a novel approach for data fusion for classification; the approach is applied to metabolomics datasets coming from patients suffering from MScl at a different stage of the disease. The approach involves data fusion in kernel space and consists of four main steps. The first one is to extract the significant information per data source using Support Vector Machine Recursive Feature Elimination. This method allows one to select a set of relevant variables. In the next step the optimized kernel matrices are merged by linear combination. In step 3 the merged datasets are analyzed with a classification technique, namely Kernel Partial Least Square Discriminant Analysis. In the final step, the variables in kernel space are visualized and their significance established.

Conclusions

We find that fusion in kernel space allows for efficient and reliable discrimination of classes (MScl and early stage). This data fusion approach achieves better class prediction accuracy than analysis of individual datasets and the commonly used mid-level fusion. The prediction accuracy on an independent test set (8 samples) reaches 100%. Additionally, the classification model obtained on fused kernels is simpler in terms of complexity, i.e. just one latent variable was sufficient. Finally, visualization of variables importance in kernel space was achieved.

Analysis of bacterial biofilms using NMR-based metabolomics

Infectious diseases can be difficult to cure, especially if the pathogen forms a biofilm. After decades of extensive research into the morphology, physiology and genomics of biofilm formation, attention has recently been directed toward the analysis of the cellular metabolome in order to understand the transformation of a planktonic cell to a biofilm. Metabolomics can play an invaluable role in enhancing our understanding of the underlying biological processes related to the structure, formation and antibiotic resistance of biofilms. A systematic view of metabolic pathways or processes responsible for regulating this 'social structure' of microorganisms may provide critical insights into biofilm-related drug resistance and lead to novel treatments. This review will discuss the development of NMR-based metabolomics as a technology to study medically relevant biofilms. Recent advancements from case studies reviewed in this manuscript have shown the potential of metabolomics to shed light on numerous biological problems related to biofilms.

Metabolomic study of serum from rabbits with acute acalculous cholecystitis

OBJECTIVES

(1)H-NMR is a powerful approach of metabolomics. This study aimed to apply it to detect the serum metabolites in rabbits with acute acalculous cholecystitis (AAC), and to analyze their potential roles in AAC.

METHODS

Fourteen rabbits were randomly divided into two groups, the AAC group and the CON group. In the AAC rabbit model, Escherichia coli solution was injected into the gallbladder, while same volume of saline, instead of E. coli solution, was injected into the gallbladder of the CON rabbit. General morphological, light microscopic and transmission electron microscopic observations were used to evaluate the model. Metabolic profiles of serum from rabbits with AAC were investigated through (1)H-NMR spectroscopy coupled with multivariate statistical analysis, such as principal components analysis and orthogonal partial least-squares discriminant analysis.

RESULTS

The pathohistology of gallbladders showed a significant difference between the two groups, proving the successful induction of inflammation in the gallbladders of the AAC group. The serum concentration of lipids (LDL and VLDL) increased during AAC, while the concentrations of phospholipids, lactic acid, 3-hydroxybutyric acid, lysine, citric acid, asparagine, histidine, glucose and some other small molecular metabolites decreased.

CONCLUSION

The profiling of serum metabolites in rabbits with acute acalculous cholecystitis changed significantly. These changes referred to the metabolic disturbance of carbohydrate, amino acids and lipids, inhibition of immunological functions and inflammation reaction.

Update on the pathophysiology and management of idiopathic intracranial hypertension

Idiopathic intracranial hypertension is a disease of unknown aetiology, typically affecting young obese women, producing a syndrome of increased intracranial pressure without identifiable cause. Despite a large number of hypotheses and publications over the past decade, the aetiology is still unknown. Vitamin A metabolism, adipose tissue as an actively secreting endocrine tissue and cerebral venous abnormalities are areas of active study regarding the pathophysiology of idiopathic intracranial hypertension. There continues to be no evidence based consensus or formal guidelines regarding management and treatment of the disease. Treatment studies show that the diagnostic lumbar puncture is a valuable intervention beyond its diagnostic importance, and that weight management is critical. However, many questions remain regarding the efficacy of acetazolamide, CSF shunting procedures and cerebral transverse venous sinus stenting.

Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis

Background

Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these pathologies. Proteomics and metabolomics methods provide invaluable information on the biomolecular content of CSF and thereby on the possible status of the central nervous system, including neurological pathologies. The combined information provides a more complete description of CSF content. Extracting the full combined information requires a combined analysis of different datasets i.e. fusion of the data.

Results

A novel fusion method is presented and applied to proteomics and metabolomics data from a pre-clinical model of multiple sclerosis: an Experimental Autoimmune Encephalomyelitis (EAE) model in rats. The method follows a mid-level fusion architecture. The relevant information is extracted per platform using extended canonical variates analysis. The results are subsequently merged in order to be analyzed jointly. We find that the combined proteome and metabolome data allow for the efficient and reliable discrimination between healthy, peripherally inflamed rats, and rats at the onset of the EAE. The predicted accuracy reaches 89% on a test set. The important variables (metabolites and proteins) in this model are known to be linked to EAE and/or multiple sclerosis.

Conclusions

Fusion of proteomics and metabolomics data is possible. The main issues of high-dimensionality and missing values are overcome. The outcome leads to higher accuracy in prediction and more exhaustive description of the disease profile. The biological interpretation of the involved variables validates our fusion approach.

Metabolomic analysis of human disease and its application to the eye

Metabolomics, the analysis of the metabolite profile in body fluids or tissues, is being applied to the analysis of a number of different diseases as well as being used in following responses to therapy. While genomics involves the study of gene expression and proteomics the expression of proteins, metabolomics investigates the consequences of the activity of these genes and proteins. There is good reason to think that metabolomics will find particular utility in the investigation of inflammation, given the multi-layered responses to infection and damage that are seen. This may be particularly relevant to eye disease, which may have tissue specific and systemic components. Metabolomic analysis can inform us about ocular or other body fluids and can therefore provide new information on pathways and processes involved in these responses. In this review, we explore the metabolic consequences of disease, in particular ocular conditions, and why the data may be usefully and uniquely assessed using the multiplexed analysis inherent in the metabolomic approach.