Inflammatory multiple-sclerosis plaques generate characteristic metabolic profiles in cerebrospinal fluid

Central pathways causing fatigue in neuro-inflammatory and autoimmune illnesses

BACKGROUND

The genesis of severe fatigue and disability in people following acute pathogen invasion involves the activation of Toll-like receptors followed by the upregulation of proinflammatory cytokines and the activation of microglia and astrocytes. Many patients suffering from neuroinflammatory and autoimmune diseases, such as multiple sclerosis, Parkinson's disease and systemic lupus erythematosus, also commonly suffer from severe disabling fatigue. Such patients also present with chronic peripheral immune activation and systemic inflammation in the guise of elevated proinflammtory cytokines, oxidative stress and activated Toll-like receptors. This is also true of many patients presenting with severe, apparently idiopathic, fatigue accompanied by profound levels of physical and cognitive disability often afforded the non-specific diagnosis of chronic fatigue syndrome.

DISCUSSION

Multiple lines of evidence demonstrate a positive association between the degree of peripheral immune activation, inflammation and oxidative stress, gray matter atrophy, glucose hypometabolism and cerebral hypoperfusion in illness, such as multiple sclerosis, Parkinson's disease and chronic fatigue syndrome. Most, if not all, of these abnormalities can be explained by a reduction in the numbers and function of astrocytes secondary to peripheral immune activation and inflammation. This is also true of the widespread mitochondrial dysfunction seen in otherwise normal tissue in neuroinflammatory, neurodegenerative and autoimmune diseases and in many patients with disabling, apparently idiopathic, fatigue. Given the strong association between peripheral immune activation and neuroinflammation with the genesis of fatigue the latter group of patients should be examined using FLAIR magnetic resonance imaging (MRI) and tested for the presence of peripheral immune activation.

SUMMARY

It is concluded that peripheral inflammation and immune activation, together with the subsequent activation of glial cells and mitochondrial damage, likely account for the severe levels of intractable fatigue and disability seen in many patients with neuroimmune and autoimmune diseases.This would also appear to be the case for many patients afforded a diagnosis of Chronic Fatigue Syndrome.

Metabolomic profiling in multiple sclerosis: insights into biomarkers and pathogenesis

Metabolomics enables the provision of sensitive bio-markers of disease. We performed 800 MHz 1H-nuclear magnetic resonance (NMR) spectroscopic analyses of cerebrospinal fluid (CSF) specimens to identify biomarkers of multiple sclerosis (MS), yielding reproducible detection of 15 metabolites from MS ( n=15) and non-MS ( n=17) patients. Mean levels of choline, myo-inositol and threonate were increased, whereas 3-hydroxybutyrate, citrate, phenylalanine, 2-hydroxyisovalerate and mannose were decreased in MS-derived CSF ( p<0.05), suggesting alterations to energy and phospholipid metabolism. Multivariate hierarchal cluster analysis indicated a high correlation within the metabolite profiles, significantly clustering samples into the two clinical groups, which was corroborated using principal components analysis. CSF metabolomics have the capacity to yield quantitative biomarkers and insights into the pathogenesis of MS.

Serum analysis by 1H nuclear magnetic resonance spectroscopy: a new tool for distinguishing neuromyelitis optica from multiple sclerosis

BACKGROUND

Neuromyelitis optica (NMO) and multiple sclerosis (MS), two inflammatory demyelinating diseases, are characterized by different therapeutic strategies. Currently, the only biological diagnostic tool available to distinguish NMO from MS is the specific serum autoantibody that targets aquaporin 4, but its sensitivity is low.

OBJECTIVE

To assess the diagnostic accuracy of metabolomic biomarker profiles in these two neurological conditions, compared to control patients.

METHODS

We acquired serum spectra (47 MS, 44 NMO and 42 controls) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy. We used multivariate pattern recognition analysis to identify disease-specific metabolic profiles.

RESULTS

The (1)H-NMR spectroscopic analysis evidenced two metabolites, originating probably from astrocytes, scyllo-inositol and acetate, as promising serum biomarkers of MS and NMO, respectively. In 87.8% of MS patients, scyllo-inositol increased 0.15 to 3-fold, compared to controls and in 74.3% of NMO patients, acetate increased 0.4 to 7-fold, compared to controls. Using these two metabolites simultaneously, we can discriminate MS versus NMO patients (sensitivity, 94.3%; specificity, 90.2%).

CONCLUSION

This study demonstrates the potential of (1)H-NMR spectroscopy of serum as a novel, promising analytical tool to discriminate populations of patients affected by NMO or MS.

GC/MS-based metabolomic analysis of cerebrospinal fluid (CSF) from glioma patients

Metabolomics has recently undergone rapid development; however, metabolomic analysis in cerebrospinal fluid (CSF) is not a common practice. We analyzed the metabolite profiles of preoperative CSF samples from 32 patients with histologically confirmed glioma using gas chromatography/mass spectrometry (GC/MS). We assessed how alterations in the metabolite levels were related to the World Health Organization (WHO) tumor grades, tumor location, gadolinium enhancement on magnetic resonance imaging (MRI), and the isocitrate dehydrogenase (IDH) mutation status. Sixty-one metabolites were identified in the CSF from glioma patients using targeted, quantitative and non-targeted, semi-quantitative analysis. The citric and isocitric acid levels were significantly higher in the glioblastoma (GBM) samples than in the grades I-II and grade III glioma samples. In addition, the lactic and 2-aminopimelic acid levels were relatively higher in the GBM samples than in the grades I-II glioma samples. The CSF levels of the citric, isocitric, and lactic acids were significantly higher in grade I-III gliomas with mutant IDH than in those with wild-type IDH. The tumor location and enhancement obtained using MRI did not significantly affect the metabolite profiles. Higher CSF levels of lactic acid were statistically associated with a poorer prognosis in grades III-IV malignant gliomas. Our study suggests that the metabolomic analysis of CSF from glioma patients may be useful for predicting the glioma grade, metabolic state, and prognosis of gliomas.

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.

Metabolomic analysis of cerebral spinal fluid from patients with severe brain injury

Proton nuclear magnetic resonance (H-NMR) spectroscopic analysis of cerebral spinal fluid provides a quick, non-invasive modality for evaluating the metabolic activity of brain-injured patients. In a prospective study, we compared the CSF of 44 TBI patients and 13 non-injured control subjects. CSF was screened for ten parameters: β-glucose (Glu), lactate (Lac), propylene glycol (PG), glutamine (Gln), alanine (Ala), α-glucose (A-Glu), pyruvate (PYR), creatine (Cr), creatinine (Crt), and acetate (Ace). Using mixed effects measures, we discovered statistically significant differences between control and trauma concentrations (mM). TBI patients had significantly higher concentrations of PG, while statistical trends existed for lactate, glutamine, and creatine. TBI patients had a significantly decreased concentration of total creatinine. There were no significant differences between TBI patients and non-injured controls regarding β- or α-glucose, alanine, pyruvate or acetate. Correlational analysis between metabolites revealed that the strongest significant correlations in non-injured subjects were between β- and α-glucose (r = 0.74), creatinine and pyruvate (r = 0.74), alanine and creatine (r = 0.62), and glutamine and α-glucose (r = 0.60). For TBI patients, the strongest significant correlations were between lactate and α-glucose (r = 0.54), lactate and alanine (r = 0.53), and α-glucose and alanine (r = 0.48). The GLM and multimodel inference indicated that the combined metabolites of PG, glutamine, α-glucose, and creatinine were the strongest predictors for CMRO2, ICP, and GOSe. By analyzing the CSF of patients with TBI, our goal was to create a metabolomic fingerprint for brain injury.

Analyses of haptoglobin level in the cerebrospinal fluid and serum of patients with neuromyelitis optica and multiple sclerosis

BACKGROUND

Neuromyelitis optica (NMO), which was previously considered a variant of multiple sclerosis (MS), is characterized by recurrent optic neuritis and longitudinally extensive spinal cord lesions. It has been shown that the level of haptoglobin in cerebrospinal fluid (CSF) is elevated in NMO. However, it is uncertain whether this change is specific to NMO, or is also seen in MS and other neurological diseases.

METHODS

We used an enzyme-linked immunosorbent assay (ELISA) to measure the haptoglobin levels in the CSF and serum in 25 NMO, 16 MS, and 15 Alzheimer's disease (AD) patients and 22 controls.

RESULTS

The CSF haptoglobin concentration of the NMO patients (0.309±0.074mg/dl, P<0.001) was significantly higher than that of MS patients (0.081±0.016mg/dl) and AD patients (0.058±0.011mg/dl), and the controls (0.060±0.009mg/dl), whereas the serum haptoglobin and albumin concentrations in the serum and CSF did not differ significantly across groups. NMO patients (0.59±0.15, P=0.001) demonstrated a higher haptoglobin index than MS patients (0.13±0.01), AD patients (0.12±0.03), and the controls (0.17±0.04). Furthermore, the haptoglobin concentration and haptoglobin index in the CSF correlated significantly with the expanded disability scale score (EDSS) in NMO patients.

CONCLUSIONS

The high CSF haptoglobin concentration in NMO may be explained by increased intrathecal haptoglobin synthesis. The correlation between CSF haptoglobin concentration/haptoglobin index and EDSS highlights the potential of haptoglobin as a biomarker of NMO.

Lipidome analysis in multiple sclerosis reveals protein lipoxidative damage as a potential pathogenic mechanism

Metabolomic and lipidomic analyses have been used for the profiling of neurodegenerative processes, both in targeted and untargeted approaches. In this work we have applied these techniques to the study of CSF samples of multiple sclerosis (MS) patients (n = 9), compared with samples of non-MS individuals (n = 9) using mass-spectrometry. We have used western-blot and analyzed cell culture to confirm pathogenic pathways suggested by mass-spectrometric measurements. The results of the untargeted approach of metabolomics and lipidomics suggest the existence of several metabolites and lipids discriminating both populations. Applying targeted lipidomic analyses focused to a pathogenic pathway in MS, oxidative stress, reveal that the lipid peroxidation marker 8-iso-prostaglandin F2α is increased in CSF from MS patients. Furthermore, as lipid peroxidation exerts its pathogenical effects through protein modification, we studied the incidence of protein lipoxidation, revealing specific increases in carboxymethylated, neuroketal and malondialdehyde-mediated protein modifications in proteins of CSF from MS patients, despite the absence of their precursors glyoxal and methylglyoxal. Finally, we report that the level of neuroketal-modified proteins correlated with a hitherto unknown increased amount of autoantibodies against lipid peroxidation-modified proteins in CSF, without compensation by signaling induced by lipid peroxidation via peroxisome proliferator-activated receptor γ (PPARγ). The results, despite the limitation of being obtained in a small population, strongly suggest that autoimmunity against in situ produced epitopes derived from lipid peroxidation can be a relevant pathogenic factor in MS.

Metabolic disturbances associated with systemic lupus erythematosus

The metabolic disturbances that underlie systemic lupus erythematosus are currently unknown. A metabolomic study was executed, comparing the sera of 20 SLE patients against that of healthy controls, using LC/MS and GC/MS platforms. Validation of key differences was performed using an independent cohort of 38 SLE patients and orthogonal assays. SLE sera showed evidence of profoundly dampened glycolysis, Krebs cycle, fatty acid β oxidation and amino acid metabolism, alluding to reduced energy biogenesis from all sources. Whereas long-chain fatty acids, including the n3 and n6 essential fatty acids, were significantly reduced, medium chain fatty acids and serum free fatty acids were elevated. The SLE metabolome exhibited profound lipid peroxidation, reflective of oxidative damage. Deficiencies were noted in the cellular anti-oxidant, glutathione, and all methyl group donors, including cysteine, methionine, and choline, as well as phosphocholines. The best discriminators of SLE included elevated lipid peroxidation products, MDA, gamma-glutamyl peptides, GGT, leukotriene B4 and 5-HETE. Importantly, similar elevations were not observed in another chronic inflammatory autoimmune disease, rheumatoid arthritis. To sum, comprehensive profiling of the SLE metabolome reveals evidence of heightened oxidative stress, inflammation, reduced energy generation, altered lipid profiles and a pro-thrombotic state. Resetting the SLE metabolome, either by targeting selected molecules or by supplementing the diet with essential fatty acids, vitamins and methyl group donors offers novel opportunities for disease modulation in this disabling systemic autoimmune ailment.

Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples

The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

Quantitative proteomics and metabolomics analysis of normal human cerebrospinal fluid samples

The analysis of cerebrospinal fluid (CSF) is used in biomarker discovery studies for various neurodegenerative central nervous system (CNS) disorders. However, little is known about variation of CSF proteins and metabolites between patients without neurological disorders. A baseline for a large number of CSF compounds appears to be lacking. To analyze the variation in CSF protein and metabolite abundances in a number of well-defined individual samples of patients undergoing routine, non-neurological surgical procedures, we determined the variation of various proteins and metabolites by multiple analytical platforms. A total of 126 common proteins were assessed for biological variations between individuals by ESI-Orbitrap. A large spread in inter-individual variation was observed (relative standard deviations [RSDs] ranged from 18 to 148%) for proteins with both high abundance and low abundance. Technical variation was between 15 and 30% for all 126 proteins. Metabolomics analysis was performed by means of GC-MS and nuclear magnetic resonance (NMR) imaging and amino acids were specifically analyzed by LC-MS/MS, resulting in the detection of more than 100 metabolites. The variation in the metabolome appears to be much more limited compared with the proteome: the observed RSDs ranged from 12 to 70%. Technical variation was less than 20% for almost all metabolites. Consequently, an understanding of the biological variation of proteins and metabolites in CSF of neurologically normal individuals appears to be essential for reliable interpretation of biomarker discovery studies for CNS disorders because such results may be influenced by natural inter-individual variations. Therefore, proteins and metabolites with high variation between individuals ought to be assessed with caution as candidate biomarkers because at least part of the difference observed between the diseased individuals and the controls will not be caused by the disease, but rather by the natural biological variation between individuals.

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

We sought to evaluate the diagnostic accuracy of metabolomic biomarker profiles in neurological conditions (idiopathic intracranial hypertension (IIH), multiple sclerosis (MS) and cerebrovascular disease (CVD) compared to controls with either no neurological disease or mixed neurological diseases). Spectra of CSF (n = 87) and serum (n = 72) were acquired using (1)H NMR spectroscopy. Multivariate pattern recognition analysis was used to identify disease-specific metabolite biomarker profiles. The metabolite profiles were then used to predict the diagnosis of a second cohort of patients (n = 25). CSF metabolite profiles were able to predict diagnosis with a sensitivity and specificity of 80% for both IIH and MS. The CVD serum metabolite profile was 75% sensitive and specific. On analysing the second patient cohort, the established metabolite biomarker profiles generated from the first cohort showed moderate ability to segregate patients with IIH and MS (sensitivity:specificity of 63:75% and 67:75%, respectively). These findings suggest that NMR spectroscopic metabolic profiling of CSF and serum can identify differences between IIH, MS, CVD and mixed neurological diseases. Metabolomics may, therefore, have the potential to be developed into a clinically useful diagnostic tool. The identification of disease-unique metabolites may also impart information on disease pathology.

Challenges in applying chemometrics to LC–MS-based global metabolite profile data

Metabolite profiling can provide insights into the metabolic status of complex living systems through the non-targeted analysis of metabolites in any biological sample. Metabolite profiling is complementary to genomics, transcriptomics and proteomics, and its applications span epidemiology, disease diagnosis, nutrition, pharmaceutical research, and toxicology. Metabolic phenotypes are a reflection of an organism’s environment, lifestyle, diet, gut microfloral composition and are also influenced by genetic factors, with important implications in genome-wide-association studies. Specialized analytical platforms, such as NMR spectroscopy and MS, are required to interrogate such metabolic complexity. The increased sophistication of such techniques has lead to a demand for improved data analysis approaches, including preprocessing and advanced chemometric techniques. This article discusses data generation, preprocessing, multivariate analysis and data interpretation for LC-MS-based metabolite profiling, focusing on challenges encountered and potential solutions.

Metabolomics: moving to the clinic

Assessment of a biological system by means of global and non-targeted metabolite profiling--metabolomics or metabonomics--provides the investigator with molecular information that is close to the phenotype in question in the sense that metabolites are an ultimate product of gene, mRNA, and protein activity. Over the last few years, there has been a rapidly growing number of metabolomics applications aimed at finding biomarkers which could assist diagnosis, provide therapy guidance, and evaluate response to therapy for particular diseases. Also, within the fields of drug discovery, drug toxicology, and personalized pharmacology, metabolomics is emerging as a powerful tool. This review seeks to update the reader on analytical strategies, biomarker findings, and implications of metabolomics for the clinic. Particular attention is paid to recent biomarkers found related to neurological, cardiovascular, and cancer diseases. Moreover, the impact of metabolomics in the drug discovery and development process is examined.

Cerebrospinal fluid evidence of increased extra-mitochondrial glucose metabolism implicates mitochondrial dysfunction in multiple sclerosis disease progression

In contrast to relapse, the mechanisms of multiple sclerosis (MS) disease progression are less understood and appear not to be exclusively inflammatory in nature. In this pilot study we investigated the relationship between disturbed CNS energy metabolism and MS disease progression. We tested the hypothesis that cerebrospinal fluid (CSF) concentrations of sorbitol, fructose, and lactate, all metabolites of extra-mitochondrial glucose metabolism, would be elevated in secondary progressive (SP) MS patients and would be associated with worsening neurologic disability. We measured metabolite concentrations by gas chromatographic/mass spectrometric and enzymatic methods in archived CSF samples from 85 MS patients [31 relapsing-remitting (RR) and 54 SP patients] and 18 healthy controls. We found that concentrations of all three metabolites, but not concentrations of glucose or myoinositol, were significantly increased in CSF from SP and, to a lesser degree, RR patients, compared to controls. Furthermore, CSF concentrations of sorbitol and fructose (polyol pathway metabolites), but not lactate (anaerobic glycolysis metabolite), correlated positively and significantly with Expanded Disability Status Scale (EDSS) score, an index of neurologic disability in MS patients. We conclude that extra-mitochondrial glucose metabolism is increased in MS patients and is associated with disease progression evidenced by increasing EDSS score. As extra-mitochondrial glucose metabolism increases with impaired mitochondrial metabolism of glucose, these findings implicate mitochondrial dysfunction in the pathogenesis of MS disease progression. CSF metabolic profiling may be useful in clarifying the role of mitochondrial pathology in progression and in targeting and monitoring therapies for disease progression that aim to preserve or boost mitochondrial glucose metabolism.

Systems biology approaches for the study of multiple sclerosis

Multiple sclerosis (MS) is a progressive neurological disease caused by an autoimmune attack to the central nervous system (CNS). MS is thought to result from a complex interaction between genetic and environmental factors. In this review we analyze the contribution of genomics, trancriptomics and proteomics in delineating these factors, as well as their utility for the monitoring of disease progression, the identification of new targets for therapeutic intervention and the early detection of individuals at risk.