CSF sphingolipids are correlated with neuroinflammatory cytokines and differentiate neuromyelitis optica spectrum disorder from multiple sclerosis

BACKGROUND

There is a need for biomarkers of disease progression and therapeutic response in multiple sclerosis (MS). This study aimed to identify cerebrospinal fluid (CSF) lipids that differentiate MS from other neuroinflammatory conditions and correlate with Expanded Disability Status Scale (EDSS) scores, gadolinium-enhancing lesions or inflammatory mediators.

METHODS

Lipids and inflammatory cytokines/chemokines were quantified with liquid chromatography-tandem mass spectrometry and multiplex ELISA, respectively, in CSF from people with untreated MS, neuromyelitis optica spectrum disorder (NMOSD), other inflammatory neurological diseases and non-inflammatory neurological diseases (NIND). Analytes were compared between groups using analysis of variance, and correlations were assessed with Pearson's analysis.

RESULTS

Twenty-five sphingolipids and four lysophosphatidylcholines were significantly higher in NMOSD compared with MS and NIND cases, whereas no lipids differed significantly between MS and NIND. A combination of three sphingolipids differentiated NMOSD from MS with the area under the curve of 0.92 in random forest models. Ninety-four lipids, including those that differentiated NMOSD from MS, were positively correlated with macrophage migration inhibitory factor (MIF) and 37 lipids were positively correlated with CSF protein in two independent MS cohorts. EDSS was inversely correlated with cholesterol ester CE(16:0) in both MS cohorts. In contrast, MIF and soluble triggering receptor expressed on myeloid cells 2 were positively associated with EDSS.

CONCLUSIONS

CSF sphingolipids are positively correlated with markers of neuroinflammation and differentiate NMOSD from MS. The inverse correlation between EDSS and CE(16:0) levels may reflect poor clearance of cholesterol released during myelin break-down and warrants further investigation as a biomarker of therapeutic response.

Recent Advances in Metabolomics and Lipidomics Studies in Human and Animal Models of Multiple Sclerosis

Multiple sclerosis (MS) is a neurodegenerative and inflammatory disease of the central nervous system (CNS) that leads to a loss of myelin. There are three main types of MS: relapsing-remitting MS (RRMS) and primary and secondary progressive disease (PPMS, SPMS). The differentiation in the pathogenesis of these two latter courses is still unclear. The underlying mechanisms of MS are yet to be elucidated, and the treatment relies on immune-modifying agents. Recently, lipidomics and metabolomics studies using human biofluids, mainly plasma and cerebrospinal fluid (CSF), have suggested an important role of lipids and metabolites in the pathophysiology of MS. In this review, the results from studies on metabolomics and lipidomics analyses performed on biological samples of MS patients and MS-like animal models are presented and analyzed. Based on the collected findings, the biochemical pathways in human and animal cohorts involved were investigated and biological mechanisms and the potential role they have in MS are discussed. Limitations and challenges of metabolomics and lipidomics approaches are presented while concluding that metabolomics and lipidomics may provide a more holistic approach and provide biomarkers for early diagnosis of MS disease.

Metabolomics and Biochemical Benefits of Multivitamin and Multimineral Supplementation in Healthy Individuals: A Pilot Study

Scientific evidence regarding the effectiveness of vitamin and mineral supplements in healthy individuals remains scarce. In a randomized, double-blind study, 30 healthy individuals were assigned to receive a single daily dose of multivitamin and multimineral supplementation or a double daily dose for 30 days. Before and after the intake, an untargeted metabolomics assay for serum metabolites was conducted by hydrophilic interaction liquid chromatography-mass spectrometry, and clinical assessments of peripheral blood samples were performed. A paired t-test for metabolic analysis, adjusted using the false discovery rate (FDR) and p-value correction method (rate of change > 2 and FDR < 0.05), the Shapiro-Wilk test, Student's t-test, and the Mann-Whitney U test were applied depending on the variable, with a 5% significance level. An impact on oxidative stress was observed, with a significant reduction in homocysteine levels and an increment of pyridoxic acid (vitamin B6). The effect on energy metabolism was shown by a significant increase in diverse metabolites, such as linoleoylcarnitine. Serum iron and calcium levels were also impacted. Overall, we observed a nutritional balance compatible with a good state of health. In conclusion, beneficial effects on adult health were demonstrated in relation to oxidative stress, energy metabolism, and nutritional balance.

Towards a better understanding of idiopathic epilepsy through metabolic fingerprinting of cerebrospinal fluid in dogs

Cerebrospinal fluid metabolomics is a promising research technology in the elucidation of nervous system disorders. Therefore, in this work, a cerebrospinal fluid (CSF) metabolomics method using liquid chromatography coupled to mass spectrometry was optimized and validated to cover a wide range of metabolites. An acceptable coefficient of variance regarding instrumental, within-lab and intra-assay precision was found for 95, 70 and 96 of 102 targeted metabolites, together with 1256, 676 and 976 untargeted compounds, respectively. Moreover, approximately 75% of targeted metabolites and 50% of untargeted compounds displayed good linearity across different dilution ranges. Consequently, metabolic alterations in CSF of dogs with idiopathic epilepsy (IE) were studied by comparing CSF of dogs diagnosed with IE (Tier II) to dogs with non-brain related disease. Targeted metabolome analysis revealed higher levels of cortisol, creatinine, glucose, hippuric acid, mannose, pantothenol, and 2-phenylethylamine (P values < 0.05) in CSF of dogs with IE, whereas CSF of dogs with IE showed lower levels of spermidine (P value = 0.02). Untargeted CSF metabolic fingerprints discriminated dogs with IE from dogs with non-brain related disease using Orthogonal Partial Least Squares Discriminant Analysis (R2(Y) = 0.997, Q2(Y) = 0.828), from which norepinephrine was putatively identified as an important discriminative metabolite.

The sphingosine 1-phosphate analogue, FTY720, modulates the lipidomic signature of the mouse hippocampus

The small-molecule drug, FTY720 (fingolimod), is a synthetic sphingosine 1-phosphate (S1P) analogue currently used to treat relapsing-remitting multiple sclerosis in both adults and children. FTY720 can cross the blood-brain barrier (BBB) and, over time, accumulate in lipid-rich areas of the central nervous system (CNS) by incorporating into phospholipid membranes. FTY720 has been shown to enhance cell membrane fluidity, which can modulate the functions of glial cells and neuronal populations involved in regulating behaviour. Moreover, direct modulation of S1P receptor-mediated lipid signalling by FTY720 can impact homeostatic CNS physiology, including neurotransmitter release probability, the biophysical properties of synaptic membranes, ion channel and transmembrane receptor kinetics, and synaptic plasticity mechanisms. The aim of this study was to investigate how chronic FTY720 treatment alters the lipid composition of CNS tissue in adolescent mice at a key stage of brain maturation. We focused on the hippocampus, a brain region known to be important for learning, memory, and the processing of sensory and emotional stimuli. Using mass spectrometry-based lipidomics, we discovered that FTY720 increases the fatty acid chain length of hydroxy-phosphatidylcholine (PCOH) lipids in the mouse hippocampus. It also decreases PCOH monounsaturated fatty acids (MUFAs) and increases PCOH polyunsaturated fatty acids (PUFAs). A total of 99 lipid species were up-regulated in the mouse hippocampus following 3 weeks of oral FTY720 exposure, whereas only 3 lipid species were down-regulated. FTY720 also modulated anxiety-like behaviours in young mice but did not affect spatial learning or memory formation. Our study presents a comprehensive overview of the lipid classes and lipid species that are altered in the hippocampus following chronic FTY720 exposure and provides novel insight into cellular and molecular mechanisms that may underlie the therapeutic or adverse effects of FTY720 in the central nervous system.

Development of an LC-MS/MS Method to Measure Sphingolipids in CSF from Patients with Multiple Sclerosis

Multiple sclerosis is an inflammatory and degenerative disease characterized by different clinical courses including relapsing multiple sclerosis (RMS) and primary progressive multiple sclerosis (PPMS). A hallmark of patients with multiple sclerosis (pwMS) includes a putative autoimmune response, which results in demyelination and neuroaxonal damage in the central nervous system. Sphingolipids in cerebrospinal fluid (CSF) have been proposed as potential biomarkers reflective of disease activity in pwMS. Hence, sensitive methods to accurately quantify sphingolipids in CSF are needed. In this study, we report the development of a sensitive high-throughput multiplexed liquid chromatography coupled to a tandem mass spectrometry method to perform quantitation on 14 species of sphingolipids in human CSF. We applied this method to measure CSF sphingolipids in healthy controls (n = 10), PPMS (n = 27), and RMS (n = 17) patients before and after ocrelizumab treatment. The median CSF levels of the 14 sphingolipids measured herein was higher in PPMS (17.2 ng/mL) and RMS (17.6 ng/mL) when compared with the healthy controls (13.8 ng/mL). Levels of sphingolipids were decreased by 8.6% at week 52 after treatment with ocrelizumab in RMS patients but not in PPMS patients. Specifically, C16 glucosylceramide (-26%; P = 0.004) and C18 ceramides (-13%; P = 0.042) decreased from baseline in RMS patients. Additionally, in PPMS patients C16 glucosylceramide levels correlated with CSF neurofilament heavy levels at baseline (Rho =0.532; P = 0.004) and after treatment (Rho =0.424; P = 0.028). Collectively, these results indicate that CSF sphingolipid levels are altered in pwMS and treatment with ocrelizumab results in significant shifts in the sphingolipid profile that may reflect a reduction in disease activity supporting further investigation into sphingolipids as tools to monitor disease state. SIGNIFICANCE STATEMENT: This study describes the development of a new method to measure 14 sphingolipid species in CSF. These results demonstrate that sphingolipids levels are elevated in CSF from pwMS compared to healthy controls. Distinct sphingolipid signatures were observed between patients with different clinical disease courses, and these lipid signatures changed after treatment with ocrelizumab, especially in RMS patients. This method enables further investigation into the role of sphingolipids as candidate biomarkers in pwMS and other central nervous system disorders.

Metabolomics of Cerebrospinal Fluid Amino and Fatty Acids in Early Stages of Multiple Sclerosis

Multiple sclerosis (MS) is a demyelinating and neurodegenerative autoimmune disease of the central nervous system (CNS) damaging myelin and axons. Diagnosis is based on the combination of clinical findings, magnetic resonance imaging (MRI) and analysis of cerebrospinal fluid (CSF). Metabolomics is a systematic study that allows us to track amounts of different metabolites in a chosen medium. The aim of this study was to establish metabolomic differences between the cerebrospinal fluid of patients in the early stages of multiple sclerosis and healthy controls, which could potentially serve as markers for predicting disease activity. We collected CSF from 40 patients after the first attack of clinical symptoms who fulfilled revised McDonald criteria of MS, and the CSF of 33 controls. Analyses of CSF samples were performed by using the high-performance liquid chromatography system coupled with a mass spectrometer with a high-resolution detector. Significant changes in concentrations of arginine, histidine, spermidine, glutamate, choline, tyrosine, serine, oleic acid, stearic acid and linoleic acid were observed. More prominently, Expanded Disability Status Scale values significantly correlated with lower concentrations of histidine. We conclude that these metabolites could potentially play a role as a biomarker of disease activity and predict presumable inflammatory changes.

Metabolite Alterations in Autoimmune Diseases: A Systematic Review of Metabolomics Studies

Autoimmune diseases, characterized by the immune system's loss of self-tolerance, lack definitive diagnostic tests, necessitating the search for reliable biomarkers. This systematic review aims to identify common metabolite changes across multiple autoimmune diseases. Following PRISMA guidelines, we conducted a systematic literature review by searching MEDLINE, ScienceDirect, Google Scholar, PubMed, and Scopus (Elsevier) using keywords "Metabolomics", "Autoimmune diseases", and "Metabolic changes". Articles published in English up to March 2023 were included without a specific start date filter. Among 257 studies searched, 88 full-text articles met the inclusion criteria. The included articles were categorized based on analyzed biological fluids: 33 on serum, 21 on plasma, 15 on feces, 7 on urine, and 12 on other biological fluids. Each study presented different metabolites with indications of up-regulation or down-regulation when available. The current study's findings suggest that amino acid metabolism may serve as a diagnostic biomarker for autoimmune diseases, particularly in systemic lupus erythematosus (SLE), multiple sclerosis (MS), and Crohn's disease (CD). While other metabolic alterations were reported, it implies that autoimmune disorders trigger multi-metabolite changes rather than singular alterations. These shifts could be consequential outcomes of autoimmune disorders, representing a more complex interplay. Further studies are needed to validate the metabolomics findings associated with autoimmune diseases.

Metabolomic Changes in Patients Affected by Multiple Sclerosis and Treated with Fingolimod

Current treatment for Multiple Sclerosis (MS) consists of a multidisciplinary approach including disease-modifying therapies. The response to treatment is heterogeneous, representing a crucial challenge in the classification of patients. Metabolomics is an innovative tool that can identifies biomarkers/predictors of treatment response. We aimed to evaluate plasma metabolic changes in a group of naïve Relapsing-Remitting MS patients starting Fingolimod treatment, to find specific metabolomic features that predict the therapeutic response as well as the possible side effects. The study included 42 Relapsing-Remitting MS blood samples, of which 30 were classified as responders after two years of FINGO treatment, whereas 12 patients were Not-Responders. For fifteen patients, samples were collected at four time points: before starting the therapy; at six months after the initiation; at twelve months after; and at twenty-four months after initiation. The serum was analysed through Nuclear Magnetic Resonance and multivariate and univariate statistical analysis. Considering the single comparison between each time point, it was possible to identify a set of metabolites changing their concentrations based on the drug intake. FINGO influences aminoacidic and energy metabolisms and reduces oxidative stress and the activity of the immune system, both typical features of MS.

Microbe-bridged disease-metabolite associations identification by heterogeneous graph fusion

MOTIVATION

Metabolomics has developed rapidly in recent years, and metabolism-related databases are also gradually constructed. Nowadays, more and more studies are being carried out on diverse microbes, metabolites and diseases. However, the logics of various associations among microbes, metabolites and diseases are limited understanding in the biomedicine of gut microbial system. The collection and analysis of relevant microbial bioinformation play an important role in the revelation of microbe-metabolite-disease associations. Therefore, the dataset that integrates multiple relationships and the method based on complex heterogeneous graphs need to be developed.

RESULTS

In this study, we integrated some databases and extracted a variety of associations data among microbes, metabolites and diseases. After obtaining the three interconnected bilateral association data (microbe-metabolite, metabolite-disease and disease-microbe), we considered building a heterogeneous graph to describe the association data. In our model, microbes were used as a bridge between diseases and metabolites. In order to fuse the information of disease-microbe-metabolite graph, we used the bipartite graph attention network on the disease-microbe and metabolite-microbe bipartite graph. The experimental results show that our model has good performance in the prediction of various disease-metabolite associations. Through the case study of type 2 diabetes mellitus, Parkinson's disease, inflammatory bowel disease and liver cirrhosis, it is noted that our proposed methodology are valuable for the mining of other associations and the prediction of biomarkers for different human diseases.Availability and implementation: https://github.com/Selenefreeze/DiMiMe.git.

Metabolomics as a promising tool for improving understanding of multiple sclerosis: A review of recent advances

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system that usually affects young adults. The development of MS is closely related to the changes in the metabolome. Metabolomics studies have been performed using biofluids or tissue samples from rodent models and human patients to reveal metabolic alterations associated with MS progression. This review aims to provide an overview of the applications of metabolomics that for the investigations of the perturbed metabolic pathways in MS and to reveal the potential of metabolomics in personalizing treatments. In conclusion, informative variations of metabolites can be potential biomarkers in advancing our understanding of MS pathogenesis for MS diagnosis, predicting the progression of the disease, and estimating drug effects. Metabolomics will be a promising technique for improving clinical care in MS.

Thinking outside the box: non-canonical targets in multiple sclerosis

Multiple sclerosis (MS) is an immune-mediated disease of the central nervous system that causes demyelination, axonal degeneration and astrogliosis, resulting in progressive neurological disability. Fuelled by an evolving understanding of MS immunopathogenesis, the range of available immunotherapies for clinical use has expanded over the past two decades. However, MS remains an incurable disease and even targeted immunotherapies often fail to control insidious disease progression, indicating the need for new and exceptional therapeutic options beyond the established immunological landscape. In this Review, we highlight such non-canonical targets in preclinical MS research with a focus on five highly promising areas: oligodendrocytes; the blood-brain barrier; metabolites and cellular metabolism; the coagulation system; and tolerance induction. Recent findings in these areas may guide the field towards novel targets for future therapeutic approaches in MS.

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.

NMR based CSF metabolomics in tuberculous meningitis: correlation with clinical and MRI findings

We report the potential role of ¹H Nuclear Magnetic Resonance (NMR) based metabolomics in tuberculous meningitis (TBM). We also correlate the significant metabolites with clinical-radiological parameters. Forty-three patients with TBM were included, and their severity of meningitis was graded as stages I to III, and patients with positive Mycobacterium tuberculosis or its nucleic acid was considered as definite TBM. ¹H NMR-based metabolomic study was performed on (CSF) samples, and the significant metabolites compared to healthy controls were identified. Outcome at three months was defined as death, poor and good based on the modified Rankin Scale. These metabolites were compared between definite and probable groups of TBM, and also correlated with MRI findings. About 11 metabolites were found to be significant for distinguishing TBM from the controls. In TBM, lactate, glutamate, alanine, arginine, 2-hydroxyisobutyrate, formate, and cis-aconitate were upregulated, and glucose, fructose, glutamine, and myo-inositol were downregulated compared to the controls. For differentiating TBM from the controls, the AUC of the ROC curve generated using these significant metabolites was 0.99, with a 95% confidence interval from 0.96 to 1, demonstrating that these metabolites were able to classify cases with good sensitivity and specificity. Lactate concentration in CSF correlated with hemoglobin, CSF glucose, and infarction. The outcome did not correlate with metabolomics parameters. NMR-based CSF metabolomics have a potential role in differentiating TBM from the controls.

The Impact of Electroacupuncture Early Intervention on the Brain Lipidome in a Mouse Model of Post-traumatic Stress Disorder

The neuroprotective effect of electroacupuncture (EA) treatment has been well studied; growing evidence suggests that changes in lipid composition may be involved in the pathogenesis of post-traumatic stress disorder (PTSD) and may be a target for treatment. However, the influence of early EA intervention on brain lipid composition in patients with PTSD has never been investigated. Using a modified single prolonged stress (mSPS) model in mice, we assessed the anti-PTSD-like effects of early intervention using EA and evaluated changes in lipid composition in the hippocampus and prefrontal cortex (PFC) using a mass spectrometry-based lipidomic approach. mSPS induced changes in lipid composition in the hippocampus, notably in the content of sphingolipids, glycerolipids, and fatty acyls. These lipid changes were more robust than those observed in the PFC. Early intervention with EA after mSPS ameliorated PTSD-like behaviors and partly normalized mSPS-induced lipid changes, notably in the hippocampus. Cumulatively, our data suggest that EA may reverse mSPS-induced PTSD-like behaviors due to region-specific regulation of the brain lipidome, providing new insights into the therapeutic mechanism of EA.

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.

Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis

The metabolomics approach represents the last downstream phenotype and is widely used in clinical studies and drug discovery. In this paper, we outline recent advances in the metabolomics research of autoimmune diseases (ADs) such as rheumatoid arthritis (RA), multiple sclerosis (MuS), and systemic lupus erythematosus (SLE). The newly discovered biomarkers and the metabolic mechanism studies for these ADs are described here. In addition, studies elucidating the metabolic mechanisms underlying these ADs are presented. Metabolomics has the potential to contribute to pharmacotherapy personalization; thus, we summarize the biomarker studies performed to predict the personalization of medicine and drug response.

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.

New Insights into Multiple Sclerosis Mechanisms: Lipids on the Track to Control Inflammation and Neurodegeneration

Multiple sclerosis (MS) is a central nervous system disease with complex pathogenesis, including two main processes: immune-mediated inflammatory demyelination and progressive degeneration with axonal loss. Despite recent progress in our understanding and management of MS, availability of sensitive and specific biomarkers for these both processes, as well as neuroprotective therapeutic options targeted at progressive phase of disease, are still being sought. Given their abundance in the myelin sheath, lipids are believed to play a central role in underlying immunopathogenesis in MS and seem to be a promising subject of investigation in this field. On the basis of our previous research and a review of the literature, we discuss the current understanding of lipid-related mechanisms involved in active relapse, remission, and progression of MS. These insights highlight potential usefulness of lipid markers in prediction or monitoring the course of MS, particularly in its progressive stage, still insufficiently addressed. Furthermore, they raise hope for new, effective, and stage-specific treatment options, involving lipids as targets or carriers of therapeutic agents.

N1-acetylspermidine is a determinant of hair follicle stem cell fate

Stem cell differentiation is accompanied by increased mRNA translation. The rate of protein biosynthesis is influenced by the polyamines putrescine, spermidine and spermine, which are essential for cell growth and stem cell maintenance. However, the role of polyamines as endogenous effectors of stem cell fate and whether they act through translational control remains obscure. Here, we investigate the function of polyamines in stem cell fate decisions using hair follicle stem cell (HFSC) organoids. Compared to progenitor cells, HFSCs showed lower translation rates, correlating with reduced polyamine levels. Surprisingly, overall polyamine depletion decreased translation but did not affect cell fate. In contrast, specific depletion of natural polyamines mediated by spermidine/spermine N1-acetyltransferase (SSAT; also known as SAT1) activation did not reduce translation but enhanced stemness. These results suggest a translation-independent role of polyamines in cell fate regulation. Indeed, we identified N1-acetylspermidine as a determinant of cell fate that acted through increasing self-renewal, and observed elevated N1-acetylspermidine levels upon depilation-mediated HFSC proliferation and differentiation in vivo. Overall, this study delineates the diverse routes of polyamine metabolism-mediated regulation of stem cell fate decisions.

This article has an associated First Person interview with the first author of the paper.

Summary: Reduced protein synthesis is required for stem cell functions. Here, we delineate a complex interplay of polyamines and mRNA translation that determines hair follicle stem cell fate decisions.

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.

Transient receptor potential ankyrin 1 contributes to the lysophosphatidylcholine-induced oxidative stress and cytotoxicity in OLN-93 oligodendrocyte

Transient receptor potential ankyrin 1 (TRPA1), the non-selective cation channel, was found that can mediate the generation of multiple sclerosis, while the mechanism is still controversial. Lysophosphatidylcholine (LPC) is a critical trigger of multiple sclerosis which results from the syndrome of neuronal inflammation and demyelination. In this work, we suggested that TRPA1 can mediate the LPC-induced oxidative stress and cytotoxicity in OLN-93 oligodendrocyte. The expression of TRPA1 in OLN-93 was detected by using quantitative real-time PCR (qRT-PCR) and immunofluorescence. The calcium overload induced by LPC via TRPA1 was detected by calcium imaging. The mechanism of LPC-induced mitochondrial reactive oxygen species (mtROS) generation, mitochondria membrane depolarization, nitric oxide (NO) increase, and development of superoxide production via TRPA1 was verified by using confocal imaging. The cell injury elicited by LPC via TRPA1 was confirmed by both CCK-8 and LDH cytotoxicity detection. These results indicate that TRPA1 plays an important role of the LPC-induced oxidative stress and cell damage in OLN-93 oligodendrocyte. Therefore, inhibition of TRPA1 may protect the LPC-induced demyelination.

Brain energy metabolism and multiple sclerosis: progress and prospects

Multiple sclerosis (MS) is an autoimmune disease accompanied with nerve pain and paralysis. Although various pathogenic causes of MS have been suggested, including genetic and environmental factors, how MS occurs remains unclear. Moreover, MS should be diagnosed based on clinical experiences because of no disease-specific biomarker and currently available treatments for MS just can reduce relapsing frequency or severity with little effects on disease disability. Therefore, more efforts are required to identify pathophysiology of MS and diagnosis markers. Recent evidence indicates another aspect of MS pathogenesis, energy failure in the central nervous system (CNS). For instance, inflammation that is a characteristic MS symptom and occurs frequently in the CNS of MS patients can result into energy failure in mitochondria and cytosol. Indeed, metabolomics studies for MS have reported energy failure in oxidative phosphorylation and alteration of aerobic glycolysis. Therefore, studies on the metabolism in the CNS may provide another insight for understanding complexity of MS and pathogenesis, which would facilitate the discovery of promising strategies for developing therapeutics to treat MS. This review will provide an overview on recent progress of metabolomic studies for MS, with a focus on the fluctuation of energy metabolism in MS.

Metabolomic Profiling in Neuromyelitis Optica Spectrum Disorder Biomarker Discovery

There is no specific test for diagnosing neuromyelitis optica spectrum disorder (NMOSD), a disabling autoimmune disease of the central nervous system. Instead, diagnosis relies on ruling out other related disorders with overlapping clinical symptoms. An urgency for NMOSD biomarker discovery is underscored by adverse responses to treatment following misdiagnosis and poor prognosis following the delayed onset of treatment. Pathogenic autoantibiotics that target the water channel aquaporin-4 (AQP4) and myelin oligodendrocyte glycoprotein (MOG) contribute to NMOSD pathology. The importance of early diagnosis between AQP4-Ab⁺ NMOSD, MOG-Ab⁺ NMOSD, AQP4-Ab⁻ MOG-Ab⁻ NMOSD, and related disorders cannot be overemphasized. Here, we provide a comprehensive data collection and analysis of the currently known metabolomic perturbations and related proteomic outcomes of NMOSD. We highlight short chain fatty acids, lipoproteins, amino acids, and lactate as candidate diagnostic biomarkers. Although the application of metabolomic profiling to individual NMOSD patient care shows promise, more research is needed.

Lipidomic UPLC-MS/MS Profiles of Normal-Appearing White Matter Differentiate Primary and Secondary Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a neurodegenerative inflammatory disease where an autoimmune response to components of the central nervous system leads to a loss of myelin and subsequent neurological deterioration. People with MS can develop primary or secondary progressive disease (PPMS, SPMS) and differentiation of the specific differences in the pathogenesis of these two courses, at the molecular level, is currently unclear. Recently, lipidomics studies using human biofluids, mainly plasma and cerebrospinal fluid, have highlighted a possible role for lipids in the initiation and progression of MS. However, there is a lack of lipidomics studies in MS on CNS tissues, such as normal-appearing white matter (NAWM), where local inflammation initially occurs. Herein, we developed an untargeted reverse phase ultra-performance liquid chromatography time of flight tandem mass spectrometry (RP-UPLC-TOF MS^E)-based workflow, in combination with multivariate and univariate statistical analysis, to assess significant differences in lipid profiles in brain NAWM from post-mortem cases of PPMS, SPMS and controls. Groups of eight control, nine PPMS and seven SPMS NAWM samples were used. Correlation analysis of the identified lipids by RP-UPLC-TOF MS^E was undertaken to remove those lipids that correlated with age, gender and post-mortem interval as confounding factors. We demonstrate that there is a significantly altered lipid profile of control cases compared with MS cases and that progressive disease, PPMS and SPMS, can be differentiated on the basis of the lipidome of NAWM with good sensitivity, specificity and prediction accuracy based on receiver operating characteristic (ROC) curve analysis. Metabolic pathway analysis revealed that the most altered lipid pathways between PPMS and SPMS were glycerophospholipid metabolism, glycerophosphatidyl inositol (GPI) anchor synthesis and linoleic acid metabolism. Further understanding of the impact of these lipid alterations described herein associated with progression will provide an increased understanding of the mechanisms underpinning progression and highlight possible new therapeutic targets.

Changes in Amino Acid and Acylcarnitine Plasma Profiles for Distinguishing Patients with Multiple Sclerosis from Healthy Controls

McDonald criteria and magnetic resonance imaging (MRI) are used for the diagnosis of multiple sclerosis (MS); nevertheless, it takes a considerable amount of time to make a clinical decision. Amino acid and fatty acid metabolic pathways are disturbed in MS, and this information could be useful for diagnosis. The aim of our study was to find changes in amino acid and acylcarnitine plasma profiles for distinguishing patients with multiple sclerosis from healthy controls. We have applied a targeted metabolomics approach based on tandem mass-spectrometric analysis of amino acids and acylcarnitines in dried plasma spots followed by multivariate statistical analysis for discovery of differences between MS (n = 16) and control (n = 12) groups. It was found that partial least square discriminant analysis yielded better group classification as compared to principal component linear discriminant analysis and the random forest algorithm. All the three models detected noticeable changes in the amino acid and acylcarnitine profiles in the MS group relative to the control group. Our results hold promise for further development of the clinical decision support system.

A metabolic perspective on CSF-mediated neurodegeneration in multiple sclerosis

Multiple sclerosis is an autoimmune demyelinating disorder of the CNS, characterized by inflammatory lesions and an underlying neurodegenerative process, which is more prominent in patients with progressive disease course. It has been proposed that mitochondrial dysfunction underlies neuronal damage, the precise mechanism by which this occurs remains uncertain. To investigate potential mechanisms of neurodegeneration, we conducted a functional screening of mitochondria in neurons exposed to the CSF of multiple sclerosis patients with a relapsing remitting (n = 15) or a progressive (secondary, n = 15 or primary, n = 14) disease course. Live-imaging of CSF-treated neurons, using a fluorescent mitochondrial tracer, identified mitochondrial elongation as a unique effect induced by the CSF from progressive patients. These morphological changes were associated with decreased activity of mitochondrial complexes I, III and IV and correlated with axonal damage. The effect of CSF treatment on the morphology of mitochondria was characterized by phosphorylation of serine 637 on the dynamin-related protein DRP1, a post-translational modification responsible for unopposed mitochondrial fusion in response to low glucose conditions. The effect of neuronal treatment with CSF from progressive patients was heat stable, thereby prompting us to conduct an unbiased exploratory lipidomic study that identified specific ceramide species as differentially abundant in the CSF of progressive patients compared to relapsing remitting multiple sclerosis. Treatment of neurons with medium supplemented with ceramides, induced a time-dependent increase of the transcripts levels of specific glucose and lactate transporters, which functionally resulted in progressively increased glucose uptake from the medium. Thus ceramide levels in the CSF of patients with progressive multiple sclerosis not only impaired mitochondrial respiration but also decreased the bioavailability of glucose by increasing its uptake. Importantly the neurotoxic effect of CSF treatment could be rescued by exogenous supplementation with glucose or lactate, presumably to compensate the inefficient fuel utilization. Together these data suggest a condition of 'virtual hypoglycosis' induced by the CSF of progressive patients in cultured neurons and suggest a critical temporal window of intervention for the rescue of the metabolic impairment of neuronal bioenergetics underlying neurodegeneration in multiple sclerosis patients.

Multi-Platform Characterization of Cerebrospinal Fluid and Serum Metabolome of Patients Affected by Relapsing-Remitting and Primary Progressive Multiple Sclerosis

Background: Multiple sclerosis (MS) is a chronic immunemediated disease of the central nervous system with a highly variable clinical presentation and disease progression. In this study, we investigate the metabolomics profile of patients affected by relapsing–remitting MS (RRMS)and primary progressive MS (PPMS), in order to find potential biomarkers to distinguish between the two forms. Methods: Cerebrospinal Fluid CSF and blood samples of 34 patients (RRMS n = 22, PPMS n = 12) were collected. Nuclear magnetic resonance (¹H-NMR) and mass spectrometry (coupled with a gas chromatography and liquid chromatography) were used as analytical techniques. Subsequently, a multivariate statistical analysis was performed; the resulting significant variables underwent U-Mann–Whitney test and correction for multiple comparisons. Receiver Operating Characteristic ROC curves were built and the pathways analysis was conducted. Results: The analysis of the serum and the CSF of the two classes, allowed the identification of several altered metabolites (lipids, biogenic amines, and amino acids). The pathways analysis indicated the following pathways were affected: Glutathione metabolism, nitrogen metabolism, glutamine–glutamate metabolism, arginine–ornithine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis etc. Conclusion: The analysis allowed the identification of a set of metabolites able to classify RRMS and PPMS patients, each of whom express different patterns of metabolites in the two biofluids.

Ponatinib Induces Vascular Toxicity through the Notch-1 Signaling Pathway

Ponatinib, a third-generation tyrosine kinase inhibitor (TKI), is the only approved TKI that is effective against T315I mutations in patients with chronic myeloid leukemia (CML). Specific activation of Notch signaling in CML cells by ponatinib can be considered as the “on-target effect” on the tumor and represents a therapeutic approach for CML. Nevertheless, ponatinib-induced vascular toxicity remains a serious concern, with underlying mechanisms being poorly understood. We aimed to determine the mechanisms of ponatinib-induced vascular toxicity, defining associated signaling pathways and identifying potential rescue strategies. We exposed human umbilical endothelial cells (HUVECs) to ponatinib or vehicle in the presence or absence of the neutralizing factor anti-Notch-1 antibody for exposure times of 0–72 h. Label-free proteomics and network analysis showed that protein cargo of HUVECs treated with ponatinib triggered apoptosis and inhibited vasculature development. We validated the proteomic data showing the inhibition of matrigel tube formation, an up-regulation of cleaved caspase-3 and a downregulation of phosphorylated AKT and phosphorylated eNOS. We delineated the signaling of ponatinib-induced vascular toxicity, demonstrating that ponatinib inhibits endothelial survival, reduces angiogenesis and induces endothelial senescence and apoptosis via the Notch-1 pathway. Ponatinib induced endothelial toxicity in vitro. Hyperactivation of Notch-1 in the vessels can lead to abnormal vascular development and vascular dysfunction. By hyperactivating Notch-1 in the vessels, ponatinib exerts an “on-target off tumor effect”, which leads to deleterious effects and may explain the drug’s vasculotoxicity. Selective blockade of Notch-1 prevented ponatinib-induced vascular toxicity.

Considerations for mass spectrometry-based multi-omic analysis of clinical samples

Introduction: The role of mass spectrometry in biomolecule analysis has become paramount over the last several decades ranging in the analysis across model systems and human specimens. Accordingly, the presence of mass spectrometers in clinical laboratories has also expanded alongside the number of researchers investigating the protein, lipid, and metabolite composition of an array of biospecimens. With this increase in the number of omic investigations, it is important to consider the entire experimental strategy from sample collection and storage, data collection and analysis.Areas covered: In this short review, we outline considerations for working with clinical (e.g. human) specimens including blood, urine, and cerebrospinal fluid, with emphasis on sample handling, profiling composition, targeted measurements and relevance to disease. Discussions of integrated genomic or transcriptomic datasets are not included. A brief commentary is also provided regarding new technologies with clinical relevance.Expert opinion: The role of mass spectrometry to investigate clinically related specimens is on the rise and the ability to integrate multiple omics datasets from mass spectrometry measurements will be crucial to further understanding human health and disease.

Toxic Peripheral Neuropathies: Agents and Mechanisms

Toxic peripheral neuropathies are an important form of acquired polyneuropathy produced by a variety of xenobiotics and different exposure scenarios. Delineating the mechanisms of neurotoxicants and determining the degenerative biological pathways triggered by peripheral neurotoxicants will facilitate the development of sensitive and specific biochemical-based methods for identifying neurotoxicants, designing therapeutic interventions, and developing structure-activity relationships for predicting potential neurotoxicants. This review presents an overview of the general concepts of toxic peripheral neuropathies with the goal of providing insight into why certain agents target the peripheral nervous system and produce their associated lesions. Experimental data and the main hypotheses for the mechanisms of selected agents that produce neuronopathies, axonopathies, or myelinopathies including covalent or noncovalent modifications, compromised energy or protein biosynthesis, and oxidative injury and disruption of ionic gradients across membranes are presented. The relevance of signaling between the main components of peripheral nerve, that is, glia, neuronal perikaryon, and axon, as a target for neurotoxicants and the contribution of active programmed degenerative pathways to the lesions observed in toxic peripheral neuropathies is also discussed.

Integration of lipidomics and metabolomics for in-depth understanding of cellular mechanism and disease progression

Mass spectrometry (MS)-based omics technologies are now widely used to profile small molecules in multiple matrices to confer comprehensive snapshots of cellular metabolic phenotypes. The metabolomes of cells, tissues, and organisms comprise a variety of molecules including lipids, amino acids, sugars, organic acids, and so on. Metabolomics mainly focus on the hydrophilic classes, while lipidomics has emerged as an independent omics owing to the complexities of the organismal lipidomes. The potential roles of lipids and small metabolites in disease pathogenesis have been widely investigated in various human diseases, but system-level understanding is largely lacking, which could be partly attributed to the insufficiency in terms of metabolite coverage and quantitation accuracy in current analytical technologies. While scientists are continuously striving to develop high-coverage omics approaches, integration of metabolomics and lipidomics is becoming an emerging approach to mechanistic investigation. Integration of metabolome and lipidome offers a complete atlas of the metabolic landscape, enabling comprehensive network analysis to identify critical metabolic drivers in disease pathology, facilitating the study of interconnection between lipids and other metabolites in disease progression. In this review, we summarize omics-based findings on the roles of lipids and metabolites in the pathogenesis of selected major diseases threatening public health. We also discuss the advantages of integrating lipidomics and metabolomics for in-depth understanding of molecular mechanism in disease pathogenesis.

Prediction of disease-related metabolites using bi-random walks

Metabolites play a significant role in various complex human disease. The exploration of the relationship between metabolites and diseases can help us to better understand the underlying pathogenesis. Several network-based methods have been used to predict the association between metabolite and disease. However, some methods ignored hierarchical differences in disease network and failed to work in the absence of known metabolite-disease associations. This paper presents a bi-random walks based method for disease-related metabolites prediction, called MDBIRW. First of all, we reconstruct the disease similarity network and metabolite functional similarity network by integrating Gaussian Interaction Profile (GIP) kernel similarity of diseases and GIP kernel similarity of metabolites, respectively. Then, the bi-random walks algorithm is executed on the reconstructed disease similarity network and metabolite functional similarity network to predict potential disease-metabolite associations. At last, MDBIRW achieves reliable performance in leave-one-out cross validation (AUC of 0.910) and 5-fold cross validation (AUC of 0.924). The experimental results show that our method outperforms other existing methods for predicting disease-related metabolites.

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.

Direct-infusion based metabolomics unveils biochemical profiles of inborn errors of metabolism in cerebrospinal fluid

BACKGROUND

For inborn errors of metabolism (IEM), metabolomics is performed for three main purposes: 1) development of next generation metabolic screening platforms, 2) identification of new biomarkers in predefined patient cohorts and 3) for identification of new IEM. To date, plasma, urine and dried blood spots are used. We anticipate that cerebrospinal fluid (CSF) holds additional - valuable - information, especially for IEM with neurological involvement. To expand metabolomics to CSF, we here tested whether direct-infusion high-resolution mass spectrometry (DI-HRMS) based non-quantitative metabolomics could correctly capture the biochemical profile of patients with an IEM in CSF.

METHODS

Eleven patient samples, harboring eight different IEM, and thirty control samples were analyzed using DI-HRMS. First we assessed whether the biochemical profile of the control samples represented the expected profile in CSF. Next, each patient sample was assigned a 'most probable diagnosis' by an investigator blinded for the known diagnoses of the patients.

RESULTS

the biochemical profile identified using DI-HRMS in CSF samples resembled the known profile, with - among others - the highest median intensities for mass peaks annotated with glucose, lactic acid, citric acid and glutamine. Subsequent analysis of patient CSF profiles resulted in correct 'most probable diagnoses' for all eleven patients, including non-ketotic hyperglycinaemia, propionic aciduria, purine nucleoside phosphorylase deficiency, argininosuccinic aciduria, tyrosinaemia type I, hyperphenylalaninemia and hypermethioninaemia.

CONCLUSION

We here demonstrate that DI-HRMS based non-quantitative metabolomics accurately captures the biochemical profile of this set of patients in CSF, opening new ways for using metabolomics in CSF in the metabolic diagnostic laboratory.

Integrated Lipidomics and Metabolomics Analysis of Tears in Multiple Sclerosis: An Insight into Diagnostic Potential of Lacrimal Fluid

Metabolomics based on mass spectrometry represents an innovative approach to characterize multifactorial diseases, such as multiple sclerosis (MuS). To date, the most important biomarker source for MuS diagnosis is the cerebrospinal fluid. However, an important goal for research is to identify new molecules in more easily accessible biological fluids. A very interesting biofluid in MuS is represented by tears, considered as an intermediate fluid between the cerebrospinal fluid and serum. In this work, we developed a merged strategy for the analysis of lipids containing choline by Liquid Chromatography coupled to Tandem Mass Spectrometry (LC-MS/MS), as well as for the targeted analysis of free carnitine, acylcarnitines and aminoacids by direct infusion mass spectrometry. Samples for both metabolomics and lipidomics approaches were obtained in a single extraction procedure from tears of patients affected by MuS and healthy controls. Tear lipidomics showed 30 phospholipids significantly modulated and, notably, many sphingomyelins resulted lower in MuS. Moreover, the metabolomics approach carried out both on tears and serum highlighted the diagnostic potential of specific aminoacids and acylcarnitines. In conclusion, the metabolic profiling of tears appears to reflect the pathological conditions of the central nervous system, suggesting that the molecular repository of tears can be considered as a source of potential biomarkers for MuS.

Metabolome-based signature of disease pathology in MS

BACKGROUND

Diagnostic delays are common for multiple sclerosis (MS) since diagnosis typically depends on the presentation of nonspecific clinical symptoms together with radiologically-determined central nervous system (CNS) lesions. It is important to reduce diagnostic delays as earlier initiation of disease modifying therapies mitigates long-term disability. Developing a metabolomic blood-based MS biomarker is attractive, but prior efforts have largely focused on specific subsets of metabolite classes or analytical platforms. Thus, there are opportunities to interrogate metabolite profiles using more expansive and comprehensive approaches for developing MS biomarkers and for advancing our understanding of MS pathogenesis.

METHODS

To identify putative blood-based MS biomarkers, we comprehensively interrogated the metabolite profiles in 12 non-Hispanic white, non-smoking, male MS cases who were drug naïve for 3 months prior to biospecimen collection and 13 non-Hispanic white, non-smoking male controls who were frequency matched to cases by age and body mass index. We performed untargeted two-dimensional gas chromatography and time-of-flight mass spectrometry (GCxGC-TOFMS) and targeted lipidomic and amino acid analysis on serum. 325 metabolites met quality control and supervised machine learning was used to identify metabolites most informative for MS status. The discrimination potential of these select metabolites were assessed using receiver operator characteristic curves based on logistic models; top candidate metabolites were defined as having area under the curves (AUC) >80%. The associations between whole-genome expression data and the top candidate metabolites were examined, followed by pathway enrichment analyses. Similar associations were examined for 175 putative MS risk variants and the top candidate metabolites.

RESULTS

12 metabolites were determined to be informative for MS status, of which 6 had AUCs >80%: pyroglutamate, laurate, acylcarnitine C14:1, N-methylmaleimide, and 2 phosphatidylcholines (PC ae 40:5, PC ae 42:5). These metabolites participate in glutathione metabolism, fatty acid metabolism/oxidation, cellular membrane composition, and transient receptor potential channel signaling. Pathway analyses based on the gene expression association for each metabolite suggested enrichment for pathways associated with apoptosis and mitochondrial dysfunction. Interestingly, the predominant MS genetic risk allele HLA-DRB1×15:01 was associated with one of the 6 top metabolites.

CONCLUSION

Our analysis represents the most comprehensive description of metabolic changes associated with MS in serum, to date, with the inclusion of genomic and genetic information. We identified atypical metabolic processes that differed between MS patients and controls, which may enable the development of biological targets for diagnosis and treatment.

NMR metabolomics of cerebrospinal fluid differentiates inflammatory diseases of the central nervous system

BACKGROUND

Myriad infectious and noninfectious causes of encephalomyelitis (EM) have similar clinical manifestations, presenting serious challenges to diagnosis and treatment. Metabolomics of cerebrospinal fluid (CSF) was explored as a method of differentiating among neurological diseases causing EM using a single CSF sample.

METHODOLOGY/PRINCIPAL FINDINGS

1H NMR metabolomics was applied to CSF samples from 27 patients with a laboratory-confirmed disease, including Lyme disease or West Nile Virus meningoencephalitis, multiple sclerosis, rabies, or Histoplasma meningitis, and 25 controls. Cluster analyses distinguished samples by infection status and moderately by pathogen, with shared and differentiating metabolite patterns observed among diseases. CART analysis predicted infection status with 100% sensitivity and 93% specificity.

CONCLUSIONS/SIGNIFICANCE

These preliminary results suggest the potential utility of CSF metabolomics as a rapid screening test to enhance diagnostic accuracies and improve patient outcomes.

Spatial and molecular changes of mouse brain metabolism in response to immunomodulatory treatment with teriflunomide as visualized by MALDI-MSI

Multiple sclerosis (MS) is an immune-mediated neurodegenerative disease of the central nervous system (CNS). One of the most promising recent medications for MS is teriflunomide. Its primary mechanism of action is linked to effects on the peripheral immune system by inhibiting dihydroorotate dehydrogenase (DHODH)-catalyzed de novo pyrimidine synthesis and reducing the expansion of lymphocytes in the peripheral immune system. Some in vitro studies suggested, however, that it can also have a direct effect on the CNS compartment. This potential alternative mode of action depends on the drug's capacity to traverse the blood-brain barrier (BBB) and to exert an effect on the complex network of brain biochemical pathways. In this paper, we demonstrate the application of high-resolution/high-accuracy matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry for molecular imaging of the mouse brain coronal sections from animals treated with teriflunomide. Specifically, in order to assess the effect of teriflunomide on the mouse CNS compartment, we investigated the feasibility of teriflunomide to traverse the BBB. Secondly, we systematically evaluated the spatial and semi-quantitative brain metabolic profiles of 24 different endogenous compounds after 4-day teriflunomide administration. Even though the drug was not detected in the examined cerebral sections (despite the high detection sensitivity of the developed method), in-depth study of the endogenous metabolic compartment revealed noticeable alterations as a result of teriflunomide administration compared to the control animals. The observed differences, particularly for purine and pyrimidine nucleotides as well as for glutathione and carbohydrate metabolism intermediates, shed some light on the potential impact of teriflunomide on the mouse brain metabolic networks. Graphical Abstract.

Metabolome analysis for investigating host-gut microbiota interactions

Dysbiosis of the gut microbiome is associated with host health conditions. Many diseases have shown to have correlations with imbalanced microbiota, including obesity, inflammatory bowel disease, cancer, and even neurodegeneration disorders. Metabolomics studies targeting small molecule metabolites that impact the host metabolome and their biochemical functions have shown promise for studying host-gut microbiota interactions. Metabolome analysis determines the metabolites being discussed for their biological implications in host-gut microbiota interactions. To facilitate understanding the critical aspects of metabolome analysis, this article reviewed (1) the sample types used in host-gut microbiome studies; (2) mass spectrometry (MS)-based analytical methods and (3) useful tools for MS-based data processing/analysis. In addition to the most frequently used sample type, feces, we also discussed others biosamples, such as urine, plasma/serum, saliva, cerebrospinal fluid, exhaled breaths, and tissues, to better understand gut metabolite systemic effects on the whole organism. Gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), three powerful tools that can be utilized to study host-gut microbiota interactions, are included with examples of their applications. After obtaining big data from MS-based instruments, noise removal, peak detection, missing value imputation, and data analysis are all important steps for acquiring valid results in host-gut microbiome research. The information provided in this review will help new researchers aiming to join this field by providing a global view of the analytical aspects involved in gut microbiota-related metabolomics studies.

Enhanced release of acid sphingomyelinase-enriched exosomes generates a lipidomics signature in CSF of Multiple Sclerosis patients

Multiple Sclerosis (MuS) is a complex multifactorial neuropathology, resulting in heterogeneous clinical presentation. A very active MuS research field concerns the discovery of biomarkers helpful to make an early and definite diagnosis. The sphingomyelin pathway has emerged as a molecular mechanism involved in MuS, since high levels of ceramides in cerebrospinal fluid (CSF) were related to axonal damage and neuronal dysfunction. Ceramides are the hydrolysis products of sphingomyelins through a reaction catalyzed by a family of enzymes named sphingomyelinases, which were recently related to myelin repair in MuS. Here, using a lipidomic approach, we observed low levels of several sphingomyelins in CSF of MuS patients compared to other inflammatory and non-inflammatory, central or peripheral neurological diseases. Starting by this result, we investigated the sphingomyelinase activity in CSF, showing a significantly higher enzyme activity in MuS. In support of these results we found high number of total exosomes in CSF of MuS patients and a high number of acid sphingomyelinase-enriched exosomes correlated to enzymatic activity and to disease severity. These data are of diagnostic relevance and show, for the first time, high number of acid sphingomyelinase-enriched exosomes in MuS, opening a new window for therapeutic approaches/targets in the treatment of MuS.

Proteomic and metabolomic characterization of streptozotocin-induced diabetic nephropathy in TIMP3-deficient mice

AIMS

The tissue inhibitor of metalloproteinase TIMP3 is a stromal protein that restrains the activity of both protease and receptor in the extracellular matrix and has been found to be down-regulated in diabetic nephropathy (DN), the leading cause of end-stage renal disease in developed countries.

METHODS

In order to gain deeper insights on the association of loss of TIMP3 and DN, we performed differential proteomic analysis of kidney and blood metabolic profiling of wild-type and Timp3-knockout mice before and after streptozotocin (STZ) treatment, widely used to induce insulin deficiency and hyperglycemia.

RESULTS

Kidney proteomic data and blood metabolic profiles suggest significant alterations of peroxisomal and mitochondrial fatty acids β-oxidation in Timp3-knockout mice compared to wild-type mice under basal condition. These alterations were exacerbated in response to STZ treatment.

CONCLUSIONS

Proteomic and metabolomic approaches showed that loss of TIMP3 alone or in combination with STZ treatment results in significant alterations of kidney lipid metabolism and peripheral acylcarnitine levels, supporting the idea that loss of TIMP3 may generate a phenotype more prone to DN.

Mass-spectrometric profiling of cerebrospinal fluid reveals metabolite biomarkers for CNS involvement in varicella zoster virus reactivation

Background

Varicella zoster virus (VZV) reactivation spans the spectrum from uncomplicated segmental herpes zoster to life-threatening disseminated CNS infection. Moreover, in the absence of a small animal model for this human pathogen, studies of pathogenesis at the organismal level depend on analysis of human biosamples. Changes in cerebrospinal fluid (CSF) metabolites may reflect critical aspects of host responses and end-organ damage in neuroinfection and neuroinflammation. We therefore applied a targeted metabolomics screen of CSF to three clinically distinct forms of VZV reactivation and infectious and non-infectious disease controls in order to identify biomarkers for CNS involvement in VZV reactivation.

Methods

Metabolite profiles were determined by targeted liquid chromatography-mass spectrometry in CSF from patients with segmental zoster (shingles, n = 14), facial nerve zoster (n = 16), VZV meningitis/encephalitis (n = 15), enteroviral meningitis (n = 10), idiopathic Bell’s palsy (n = 11), and normal pressure hydrocephalus (n = 15).

Results

Concentrations of 88 metabolites passing quality assessment clearly separated the three VZV reactivation forms from each other and from the non-infected samples. Internal cross-validation identified four metabolites (SM C16:1, glycine, lysoPC a C26:1, PC ae C34:0) that were particularly associated with VZV meningoencephalitis. SM(OH) C14:1 accurately distinguished facial nerve zoster from Bell’s palsy. Random forest construction revealed even more accurate classifiers (signatures comprising 2–4 metabolites) for most comparisons. Some of the most accurate biomarkers correlated only weakly with CSF leukocyte count, indicating that they do not merely reflect recruitment of inflammatory cells but, rather, specific pathophysiological mechanisms. Across all samples, only the sum of hexoses and the amino acids arginine, serine, and tryptophan correlated negatively with leukocyte count. Increased expression of the metabolites associated with VZV meningoencephalitis could be linked to processes relating to neuroinflammation/immune activation, neuronal signaling, and cell stress, turnover, and death (e.g., autophagy and apoptosis), suggesting that these metabolites might sense processes relating to end-organ damage.

Conclusions

The results provide proof-of-concept for the value of CSF metabolites as (1) disease-associated signatures suggesting pathophysiological mechanisms, (2) degree and nature of neuroinflammation, and (3) biomarkers for diagnosis and risk stratification of VZV reactivation and, likely, neuroinfections due to other pathogens.

Trial registration

Not applicable (non-interventional study).

Electronic supplementary material

The online version of this article (10.1186/s12974-017-1041-0) contains supplementary material, which is available to authorized users.

Shifting paradigms in multiple sclerosis: from disease-specific, through population-specific toward patient-specific

PURPOSE OF REVIEW

In recent years we notice paradigm shifts in the understanding of multiple sclerosis (MS), leading to important transition in the patients' management. This review discusses some of the recent findings and developments underlying the conceptual changes being translated from 'treating the disease' to 'treating the patient' with MS (PwMS).

RECENT FINDINGS

Applying advanced technologies combined with cross-disciplinary efforts in the fields of neuropathology, neuroimmunology, neurobiology, and neuroimaging, together with clinical neurology provided support for the notion that MS is not a single disease but rather a spectrum. Predictive markers of disease subtypes, disease activity and response to therapy are being developed; some already applied to practice, allowing informed management. In parallel, population-specific issues, some genetic-driven, others caused by environmental (sun-exposure, life-style, etc.), gender-related (hormones) and epigenetic factors, are being elucidated. Additionally, patient empowerment-based approaches, including integration of patient-reported outcome measures (PRO) as well as tools to enhance patients' adherence to medications, are being developed, some already provided as part of emerging mobile-health technologies.

SUMMARY

Developments in the MS field, elucidating disease subtypes and interpopulation diversities, together with integration of patient-centered approaches, allow transition toward precision medicine in MS clinical trials and patient care.

Metabolomics approaches in experimental allergic encephalomyelitis

A myelin basic protein (MBP)-induced experimental allergic encephalomyelitis (EAE) involves paraplegia due to a reversible thoracolumbar spinal cord impairment. The aims of this study were thus to find significant metabolic biomarkers of inflammation and identify the site of inflammation in the central nervous system (CNS) during the acute signs in of the disease using metabolomics. All the EAE samples were associated with higher levels of lactate, ascorbate, glucose and amino acids, and decreased level of N-acetyl-aspartate (NAA) compared to the control group. A decreased NAA level has been particularly shown in lumbar spinal cord in relationship with the clinical signs.

Metabolic profiling reveals biochemical pathways and potential biomarkers associated with the pathogenesis of Krabbe disease

Krabbe disease (KD) is caused by mutations in the galactosylceramidase (GALC) gene, which encodes a lysosomal enzyme that degrades galactolipids, including galactosylceramide and galactosylsphingosine (psychosine). GALC deficiency results in progressive intracellular accumulation of psychosine, which is believed to be the main cause for the demyelinating neurodegeneration in KD pathology. Umbilical cord blood transplantation slows disease progression when performed presymptomatically but carries a significant risk of morbidity and mortality. Accurate presymptomatic diagnosis is therefore critical to facilitate the efficacy of existing transplant approaches and to avoid unnecessary treatment of children who will not develop KD. Unfortunately, current diagnostic criteria, including GALC activity, genetic analysis, and psychosine measurement, are insufficient for secure presymptomatic diagnosis. This study performs a global metabolomic analysis to identify pathogenetic metabolic pathways and novel biomarkers implicated in the authentic mouse model of KD known as twitcher. At a time point before onset of signs of disease, twitcher hindbrains had metabolic profiles similar to WT, with the exception of a decrease in metabolites related to glucose energy metabolism. Many metabolic pathways were altered after early signs of disease in the twitcher, including decreased phospholipid turnover, restricted mitochondrial metabolism of branched-chain amino acids, increased inflammation, and changes in neurotransmitter metabolism and osmolytes. Hypoxanthine, a purine derivative, is increased before signs of disease appear, suggesting its potential as a biomarker for early diagnosis of KD. Additionally, given the early changes in glucose metabolism in the pathogenesis of KD, diagnostic modalities that report metabolic function, such as positron emission tomography, may be useful in KD. © 2016 Wiley Periodicals, Inc.