EAE: Experimental Autoimmune Encephalitis; MS: Multiple Sclerosis; CNS: Central Nervous System; RR: Relapsing Remitting; FDR: False Discovery Rate; KEGG: Kyoto Encyclopedia of Genes and Genomics; MBP: Myelin Basic Protein; MOG: Myelin Oligodendrocyte Glycoprotein; PLP: Proteolipod Protein; CFA: Complete Freund’s Adjuvant; Th: T Helper; TNFα: Tumor Necrosis Factor Alpha; IL: Interleukin; BBB: Blood Brain Barrier; IDO: Indoleamine 2,3-Dioxygenase; UPLC/MS/MS: Ultrahigh Performance Liquid Chromatography/Mass Spectroscopy; GC/MS: Gas Chromatography/ Mass Spectroscopy; PCA: Principal Component Analysis; FFA: Free Fatty Acid; LCFAs: Long-Chain Fatty Acids; Iacra : Indoleacrylic Acid; FXR: Farnesoid X Receptor; PGE2: Prostaglandin E2; PPARs: Peroxisome Proliferator-Activated Receptors; LA: Linoleic Acid; NO: Nitric Oxide; PLS-DA: Partial Least Squares Discriminant Analysis

Multiple sclerosis (MS) is a chronic inflammatory and demyelinating disease of the central nervous system (CNS). The hypothesis, that MS is an autoimmune disease comes mainly from studies of an animal model for demyelination called experimental autoimmune encephalomyelitis (EAE) [1-3]. EAE can be induced in various inbred animal strains by inoculation of whole myelin or defined myelin proteins/peptides such as myelin basic protein (MBP), myelin oligodendrocyte glycoprotein (MOG), and proteolipod protein(PLP) in complete Freund’s adjuvant (CFA) [1-3]. The two most widely used EAE models are the MOG_35-55 induced chronic progressive EAE (C-EAE) in B6 mice and the PLP_139-151 induced relapsing remitting (RR-EAE) EAE in SJL mice.

Elegant studies in murine/rodent EAE models have documented that encephalitogenic T cells are CD4⁺, T helper (Th1)-type cells secreting TNF-α/β and IFNγ [4-6]. However recent studies have indicated that a new T cell phenotype Th17 secreting IL-17, IL-17F, IL-21, IL-22 and IL-23 might also play an important role in the immuno-pathogenesis of EAE [7]. Thus current hypothesis of EAE indicates that both Th1 and Th17 cytokines play an important role in the immunopathogenesis of EAE. These encephalitogenic CD4⁺ T cells traffic to CNS by crossing the leaky BBB (blood brain barrier) and initiate an inflammatory cascade, which ultimately leads to demyelination and possible axonal loss. To be efficacious as a therapeutic agent for EAE/MS, a drug should modulate directly or indirectly: i) Th1/Th17 pathway; ii) trafficking of inflammatory cells to CNS; and (iii) integrity of BBB. At the molecular level, a number of metabolites are generated inside and outside of the cells, which can directly or indirectly regulate immune response, and modulate inflammation and demyelination in CNS. Recent studies support this argument, as number of metabolites such as indoleamine 2,3-dioxygenase (IDO) [8], tryptophan, glucose and pyruvate have been shown to directly regulate CD4 T cells, macrophages and DC response [9-11].

Metabolomics focuses on global exploration of endogenous small molecule metabolites as the end products of cellular processes in the biological system, including cell, tissue, organ or organism [12,13]. Therefore, metabolic profiling can provide a window to the instantaneous as well as long term physiological or pathological changes as a supplement to the transcriptomic and proteomic profiling for the systematic and functional study of living organisms [14,15]. It has been used successfully in identifying novel clinical biomarkers and therapeutic targets, especially in cancer [16,17]. Recent reports have implicated the importance of metabolomics in the possible identification of biomarkers in neurological disorders including Alzheimer’s disease [18,19], Parkinson’s disease [20], and EAE using CSF and urine [21-23].

Here, we describe the first comprehensive analysis of plasma metabolites, using the PLP_139-151 induced RR-EAE model of MS, which mimics human RR-MS closely. This study can be used as a surrogate for future studies to identify metabolites in the plasma of MS patients. We identified a 44 metabolite signature corresponding to various metabolite classes including lipids, amino acids, xenobiotics and carbohydrates that distinguishes the chronic phase of EAE disease from the non-disease state. Development of a non-invasive technique to measure disease severity quantitatively will greatly benefit the clinical and the scientific community and speed-up the drug development for MS patients.

Animals

Female SJL/J mice were purchased from Jackson Laboratories and housed in the pathogen-free animal facility of Mayo Clinic, Rochester, MN, according to the animal protocols approved by the Animal Care and Use Committee of Mayo Clinic.

Peptide and reagents

Murine myelin proteolipid protein (PLP_139-151; (HSLGKWLGHPDKF)) was synthesized at Mayo peptide core facility. Complete Freund’s adjuvant (CFA) and mycobacterium tuberculosis (MT) lyophilized powder was purchased from DIFCO Laboratories (Michigan, USA).

EAE induction and recall response

SJL mice (10-12 wk old) were immunized on day 0 by subcutaneous (SC) injections in the flank region with total 200 μl of emulsion containing PLP_139-151 peptide (100 μg/mouse), along with killed Mycobacterium tuberculosis H37Ra (400 μg). One set of mice were injected with CFA without PLP_139-151 peptide named as healthy. Clinical disease was monitored daily in a blinded fashion by measuring paralysis according to the conventional grading system: 0, no disease; 1, complete loss of tail tonicity; 2, partial hind limb paralysis (uneven gate of hind limb); 3, complete hind limb paralysis; 4, complete hind and forelimb paralysis; 5, moribund or dead. On day 45 (chronic phase of disease), cells (2×10⁶/ml) isolated from lymph nodes of myelin PLP_139-151-immunized mice were cultured in the presence or absence of PLP_139-151 (20 μg/ml). Cell proliferation and the production of various cytokines (IFNγ and IL17) were examined as described before [24]. On the same day, blood was drawn from both groups to isolate plasma for metabolomics analysis.

Histology of the brain

Following perfusion with Trump’s fixative, we made two coronal cuts in the intact brain at the time of removal from the skull (one section through the optic chiasm and a second section through the infundibulum). As a guide, we used the Atlas of the Mouse Brain and Spinal Cord corresponding to sections 220 and 350, page 664. These yielded three blocks that were embedded in paraffin to allow for systematic analysis of the pathology of the cortex, corpus callosum, hippocampus, brain stem, striatum, and cerebellum. The resulting slides were stained with hematoxylin and eosin (H&E) and assigned pathological scores to the different areas ofthe brain without knowledge of experimental group. We used a four-point scale to grade each area of the brain: 0, no pathology; 1, no tissue destruction but only minimal inflammation; 2, early tissue destruction (loss of architecture) and moderate inflammation; 3, definite tissue destruction (demyelination, parenchymal damage, cell death, neurophagia, neuronal vacuolation); and 4, necrosis (complete loss of all tissue elements with associated cellular debris). We assessed and graded meningeal inflammation as follows: 0, no inflammation; 1, one cell layer of inflammation; 2, two cell layers of inflammation; 3, three cell layers of inflammation; 4, four or more cell layers of inflammation. The area with maximal tissue damage was used for assessment of each brain region.

Spinal cord pathology

We anesthetized mice with sodium pentobarbital and perfused them intracardially with Trump’s fixative (phosphate-buffered 4% formaldehyde/1% glutaraldehyde, pH 7.4). We cut the removed spinal cords into 1 mm blocks with every third block postfixed and stained with osmium tetroxide and embedded in glycol methacrylate plastic (Polysciences, Warrington, PA). Ten to twelve spinal cord sections were stained with cresyl violet/erichrome stain to visualize the myelin sheaths and inflammatory infiltrates. Each quadrant from every crosssection from each mouse was graded for the presence or absence of gray matter disease, meningeal inflammation, and demyelination. The score was expressed as the percentage of spinal cord quadrants examined with the pathological abnormality. A maximum score of 100 indicated a particular pathological abnormality in every quadrant of all spinal cord sections of a given mouse. All grading was performed on coded sections without knowledge of the experimental group.

Axon counts

Four sections of the mid-thoracic area were embedded in araldite plastic and stained with p-phenyldiamine. An Olympus Provis AX70 microscope that was fitted with a DP70 digital camera and a 60x oilimmersion objective was used to capture six sample areas of normalappearing white matter containing a relative absence of demyelination from each cross section, according to the sampling scheme as previously reported [25]. Approximately 400,000 μm² of white matter was sampled from each mouse. Absolute myelinated axon numbers were calculated as previously reported [26]. Data were represented as the absolute number of all axons sampled per mid-thoracic spinal cord section. Data were analyzed without knowledge of experimental groups. All numbers were averaged per group.

Metabolite analysis

Metabolomic profiling analysis was performed by Metabolon Inc. (Durham, NC) as previously described [17,27-29].

Sample accessioning

Each sample received was accessioned into the Metabolon LIMS system and was assigned by the LIMS a unique identifier that was associated with the original source identifier only. This identifier was used to track all sample handling, tasks, results etc. The samples (and all derived aliquots) were tracked by the LIMS system. All portions of any sample were automatically assigned their own unique identifiers by the LIMS when a new task is created; the relationship of these samples is also tracked. All samples were maintained at -80° C until processed.

Sample preparation

Samples were prepared using the automated MicroLab STAR^® system from Hamilton Company. A recovery standard was added prior to the first step in the extraction process for QC purposes. Sample preparation was conducted using aqueous methanol extraction process to remove the protein fraction while allowing maximum recovery of small molecules. The resulting extract was divided into four fractions: one for analysis by UPLC/MS/MS (positive mode), one for UPLC/MS/ MS (negative mode), one for GC/MS, and one for backup. Samples were placed briefly on a TurboVap^® (Zymark) to remove the organic solvent. Each sample was then frozen and dried under vacuum. Samples were then prepared for the appropriate instrument, either UPLC/MS/MS or GC/MS.

Ultrahigh performance liquid chromatography/Mass Spectroscopy (UPLC/MS/MS)

The LC/MS portion of the platform was based on a Waters ACQUITY ultra-performance liquid chromatography (UPLC) and a Thermo-Finnigan linear trap quadrupole (LTQ) mass spectrometer, which consisted of an electrospray ionization (ESI) source and linear ion-trap (LIT) mass analyzer. The sample extract was dried then reconstituted in acidic or basic LC-compatible solvents, each of which contained 8 or more injection standards at fixed concentrations to ensure injection and chromatographic consistency. One aliquot was analyzed using acidic positive ion optimized conditions and the other using basic negative ion optimized conditions in two independent injections using separate dedicated columns. Extracts reconstituted in acidic conditions were gradient eluted using water and methanol containing 0.1% formic acid, while the basic extracts, which also used water/methanol, contained 6.5 mM Ammonium Bicarbonate. The MS analysis alternated between MS and data-dependent MS2 scans using dynamic exclusion. Raw data files are archived and extracted as described below.

Gas chromatography/Mass Spectroscopy (GC/MS)

The samples destined for GC/MS analysis were re-dried under vacuum desiccation for a minimum of 24 hours prior to being derivatized under dried nitrogen using bistrimethyl-silyltriflouroacetamide( BSTFA). The GC column was 5% phenyl and the temperature ramp was from 40° to 300°C in a 16 minute period. Samples were analyzed on a Thermo-Finnigan Trace DSQ fast-scanning single-quadrupole mass spectrometer using electron impact ionization. The instrument was tuned and calibrated for mass resolution and mass accuracy on a daily basis. The information output from the raw data files was automatically extracted as discussed below.

Quality assurance/QC

For QA/QC purposes, additional samples were included with each day’s analysis. These samples included extracts of a pool of well-characterized human plasma, extracts of a pool created from a small aliquot of the experimental samples, and process blanks. QC samples were spaced evenly among the injections and all experimental samples were randomly distributed throughout the run. A selection of QC compounds was added to every sample for chromatographic alignment, including those under test. These compounds were carefully chosen so as not to interfere with the measurement of the endogenous compounds.

Data extraction and compound identification

Raw data were extracted, peak-identified and QC processed using Metabolon’s hardware and software. These systems are built on a webservice platform utilizing Microsoft’s NET technologies, which run on high-performance application servers and fiber-channel storage arrays in clusters to provide active failover and load-balancing [30]. Compounds were identified by comparison to library entries of purified standards or recurrent unknown entities. Metabolon maintains a library based on authenticated standards that contains the retention time/index (RI), mass to charge ratio (m/z), and chromatographic data (including MS/MS spectral data) on all molecules present in the library. Furthermore, biochemical identifications are based on three criteria: retention index within a narrow RI window of the proposed identification, nominal mass match to the library ± 0.2 amu, and the MS/MS forward and reverse scores between the experimental data and authentic standards. The MS/MS scores are based on a comparison of the ions present in the experimental spectrum to the ions present in the library spectrum. While there may be similarities between these molecules based on one of these factors, the use of all three data points can be utilized to distinguish and differentiate biochemicals. More than 2400 commercially available purified standard compounds have been acquired and registered into LIMS for distribution to both the LC and GC platforms for determination of their analytical characteristics.

Statistical calculation

Metabolites with missing intensity scores, indicating low levels of the metabolite in the sample, were imputed with a small number (half of the minimum value for the study). Principal component analysis was used to detect outlying samples. PLS-DA was used for assessment of separability of the samples. T-tests, allowing unequal variance, were used to compare changes in mean expression per metabolite between the control and disease groups. Boxplots of t-statistics depict changes in metabolites of similar molecule type or function. Those with p<0.05 were included in a heat map using metabolite-level normalized data. Samples were clustered by complete linkage on Pearson’s correlation, rows are ordered by direction of change and then molecule type. Boxplots of metabolite intensity per group were also drawn for each significantly changed metabolite. A z-score plot was drawn with the z-scores based on the mean and standard deviation of the control samples per metabolite. KEGG pathway analysis (http://www.genome.jp/kegg) of 80 Homo sapiens associated pathways considered both statistical enrichment of changed intensity using the GlobalTest [31] and the impact of metabolite changes based on the pathway topology using the relative betweeness centrality measure [32]. Metabolites were mapped to the KEGG pathways using Human Metabolome Databse (HMDB; www.hmdb.ca/) number; n=228 were retained. Statistical analyses were conducted with “R” http://cran.r-project.org/, except for the PCA, PLS-DA, and pathway analysis which were conducted with “MetaboAnalyst 2.0” (http://www.metaboanalyst.ca/ [33,34]) and using log-transformed data.

Characterization of the clinical pathological state of EAE in SJL mice

The goal of this study was to profile the metabolic changes in plasma associated with clinical pathological state in experimental autoimmune encephalitis (EAE), a well-characterized animal model of multiple sclerosis (MS). For this, we induced EAE in SJL mice using PLP_139-151 peptide as described before [24]. Mice exhibited two episodes of relapsing and remitting, followed by the chronic phase of the disease (Figure 1A). At the chronic phase of disease (day 45), plasma was isolated for metabolomic profile and the spinal cords were collected and processed for CNS pathology recording inflammation, demyelination and axonal loss. The lymph nodes (LN) were processed for recall response to identify the relationship between altered metabolic changes, clinical pathology and immune response in SJL mice with EAE. Pathological analysis of CNS tissue showed that EAE group displayed inflammation and demyelination, as expected (Figures 1B and 1C). We further counted the absolute number of axons in the normal-appearing white matter at T6 which provided a global representation of the axon loss from multiple, randomly distributed demyelinated lesions throughout the spinal cord. There were 26% fewer axons in untreated EAE group compared to the healthy group (p<0.001) (Figure 1D). On performing recall response using LN cells, we observed production of pro-inflammatory cytokines (IFNγ and IL17) (Figure 1E). Overall, these set of data characterize the clinical and pathological state of EAE in SJL mice obtained at day 45 of disease induction.

Figure 1: Characterization of clinical pathological state of EAE in RR mouse model. A. EAE was induced in SJL mice using PLP_139-151 peptide emulsified in CFA and clinical score was recorded daily (n=10). The healthy group was given CFA without peptide. Arrow represents the day when tissues/plasma were harvested for analysis. B-C. Percentage of spinal cord quadrants containing spinal cord white matter inflammation and demyelination (mean ± SD; n=5). D. Absolute number of axons counted in six areas of a mid-thoracic spinal cord section. P<0.01 and P<0.001 compared to healthy group. E. Recall response in cells isolated from lymph nodes, stimulated with 20 μg of PLP_139-151 for 72 h. Cell supernatant was used for measuring the levels of IFNγ and IL17 by ELISA (n=4).

Alteration of metabolites in plasma of EAE mice are linked to various metabolic pathways

In search of circulating metabolites as biomarkers of EAE disease, we profiled the global metabolome using liquid and gas chromatography coupled with mass spectrometry to identify the relative levels of metabolites in plasma of EAE diseased mice versus healthy control mice. Evaluation of untargeted metabolomic profiling of plasma from EAE and healthy SJL mice detected 282 known metabolites (Supplementary Table 1). One control sample was found to be an outlier dominating the first principal component in a PCA (Supplementary Figure 1) and was excluded from further analysis. PLS-DA revealed a clear separation between EAE and healthy groups, indicating presence of unique metabolite profiles for the EAE and healthy mice group (Figure 2A). We have depicted the EAE profile (red) relative to that of healthy mice (blue) in a Z score plot (Figure 2B), where each point represents a metabolite intensity measure (rows) normalized by the mean and standard deviation of the healthy samples. Positive points represent up-regulation whereas negative points represent down regulation of the particular metabolite in the EAE mice. Metabolites are arranged by class and then by subclass. Two-sample t-tests per metabolite identified biochemicals with significantly different average intensity between the experimental groups. We found that 44 out of the 282 (15%) metabolites were differentially altered (P<0.05 with FDR<0.23), indicating a robust alteration in the circulating metabolomic profile during disease. Among the perturbed metabolites, 32 were up regulated in EAE plasma whereas 12 were down regulated.

Figure 2: Metabolomics profiling of plasma distinguishes EAE from healthy group. A. Partial least squares discriminant analysis (PLS-DA) score plot of the metabolic profile of plasma isolated from the EAE and healthy groups shows clear separation. This indicates different metabolic profiles of the plasma extricates in the groups. B. Pie chart of the percentage of changed metabolites by major metabolic super-pathway. C. Z-score plot of the changed metabolites in plasma of EAE (red) compared to healthy group (blue). D. A heatmap drawn with the altered metabolites (P<0.05 with FDR<0.23) arranged on the basis relative change (up/ down) and then by super pathway. C: control healthy; D: EAE diseased mice. Samples are ordered by hierarchical clustering. Red and green indicate increased and decreased levels, respectively.

Of these 44 altered compounds, ~47% belonged to the lipid class including lysolipids, bile acids, sterols, medium/long chain fatty acids, fatty acid and fatty acid metabolism, and inositol metabolism. The rest of the compounds represent amino acids, xenobiotics, cofactor and vitamins, and carbohydrates with one nucleotide and one energy class molecule (Figure 2C, Tables 1 and 2). To visualize the relationship between the 44 altered metabolites, a heatmap was generated with the metabolites arranged on the basis of relative change (up/down) and then by super pathway and samples ordered by hierarchical clustering (Figure 2D). Though the metabolites in this heatmap were selected based on average intensity differences, it is reassuring to see that these metabolites show enough distinct changes to separate the two diagnostic groups.

Table 1: Up-regulated metabolites in plasma of EAE compared to healthy group .

Table 2: Down-regulated metabolites in plasma of EAE compared to healthy group.

The most striking alteration was observed in a system-wide increase in plasma free fatty acid (FFA) levels, predominantly in the mediumchain and long-chain fatty acids (LCFAs) in the plasma of EAE group (Figure 3A). The increase in FFAs could be due to higher lipolysis or break down of membrane lipids. Lipolysis from adipose tissue and liver could also potentially be a significant source for the observed increase in plasma FFA levels. Our interpretation of higher lipolysis due to adipose tissue is supported by a recent metabolic flexibility study in MS patients, where higher lipolytic activity in adipose tissue was observed in MS patients compared to healthy [35]. Although no significant change was found in choline levels in plasma of the EAE group compared to healthy, a decreasing trend was observed. Presently, we do not have an explanation for this observation as choline serves several cellular functions including being the major head group for membrane lipid (phosphatidylcholine) especially the myelin sheath. The levels of many detected lysolipids increased with EAE disease, suggesting a possible increase in membrane breakdown and offering one possible scenario for the observed increase in the plasma FFA. The role of phospholipases in MS and EAE is well documented and they have been shown to be elevated during disease [36,37]. An elevated level of myo-inositol (MI) was found in EAE which is an organic osmolyte and a purported glial marker [38]. Changes in MI levels have been associated with onset of cognitive decline in neuroinflammatory conditions including MS [39,40]. Disease induction was also associated with changes in glycolysis (3-phosphoglycerate), TCA (alpha-ketogluterate) and glycemic control (higher levels of 1,2-AG) and histidine metabolism (Figures 3D,3F and 5). Primarily, EAE disease induction brought a system-wide increase in FFA levels. The increase in plasma FFA levels could result from multiple processes including but not limited to lipolysis, membrane breakdown and dietary uptake. Without supporting information from other tissues, it is difficult to pinpoint the source(s) of this observed increase in plasma FFAs.

Figure 3: Box plots of various metabolite classes altered in EAE. Significantly altered metabolite intensities are shown as box plots grouped by class: lipid (i), xenobiotics (ii), amino acids (iii), carbohydrates (iv), cofactors and vitamins (v), energy (vi) and nucleotide (vii). Medians are represented by horizontal bars, boxes span the interquartile range (IQR) and whiskers extend to extreme data points within 1.5 times IQR. Outliers plotted as open circles lie outside 1.5 times the IQR. Blue and red box plots represent healthy and EAE group, respectively. *P<0.05; **P<0.01; ***P<0.001 compared to healthy group. Abbreviation used for following lysolipids: 1-arachidoyl GC: 1--arachidoylglycerophosphocholine; 1-eicosadienoyl GC: 1- eicosadienoylglycerophosphocholine; 1-linoleoyl GE: 1- linoleoylglycerophosphoethanolamine; 1-oleoyl GE: 1-oleoylglycerophosphoethanolamine; 1-palmitoyl GE: 1- palmitoylplasmenylethanolamine; 1-palmitoylplasmenyl E: 1-palmitoylplasmenylethanolamine.

Acylcarnitines, a marker of incomplete fatty acid β-oxidation, have been reported in metabolic disorders including diabetes, cardiovascular and mitochondrial diseases, were also elevated in EAE plasma [41,42]. In animal models of metabolic disorders, its increased levels have been linked to mitochondrial overload under metabolic stress [43,44]. Recent studies are implicating mitochondrial dysfunction as one of the causes of axonal dysfunction in MS [45,46].

We found elevated levels of various metabolites categorized under xenobiotics class (Figure 3B), which are normally not synthesized in the body, but can be metabolized by the micro-biome of the distal gut, and their elevated levels can be observed in biological fluids under normal or pathological state. The most dramatically increased xenobiotic metabolites observed in the plasma of EAE were equolsulphate and homostachydrine. While, no biological role has been identified for these two metabolites, a recent study reported that equolsulphate was observed in the plasma of conventional mice but not in the plasma of germ-free mice [47], suggesting a significant interplay between resident bacterial and mammalian metabolism. Homostachydrine has been reported in citrus genus plants [48], but with no biological activity defined. Stachydrine was significantly elevated in plasma of EAE, which was recently shown to activate Th17/Th1 by reducing Th2/Treg in RU486 induced mouse model [49]. This observation agrees with the identified higher levels of stachydrine, increased inflammation and severity in SJL mice with EAE (Figure 1). Benzoate (benzoic acid) a monocarboxylate, is used as a food preservative and is also used for the treatment of hyperammonemia [50]. It has been shown to have anti-inflammatory properties, and reduced microglial and astroglial inflammatory responses and EAE disease progression [51,52]. Its metabolism occurs exclusively by conjugation with glycine to form hippurate. It is a mammalian-microbial co-metabolite and a normal constituent of the endogenous urinary metabolite profile. Its excretion has been reported in various disease conditions including obesity, diabetes, gastrointestinal diseases, impaired renal function and psychological disorders [53]. We observed significantly higher level of both benzoate and hippurate in the plasma of EAE afflicted mice. Strong evidence for the pivotal role of the gut microbiota in the generation of hippurate [54] further suggesting the alteration of gut microbiome during disease, which may be responsible for altered levels of xenobiotics in plasma of EAE group. Indoleacrylate (indoleacrylic acid; IAcrA), a metabolite of tryptophan pathway, is highly reactive and conjugates with glycine to form indolylacryloylglycine (IAG), which is excreted in urine. The only significantly decreased xenobiotic found in EAE plasma was glycolate (glycolic acid), which is considered a major precursor of oxalate in hepatocytes.

We observed elevated levels of two metabolites, alpha-tocopherol (vitamin E) and salicylate in plasma (Figures 3B and 3E), known to have anti-inflammatory and protective effect against inflammation. Alpha-tocopherol exhibits anti-oxidant and anti-inflammatory properties. Alpha-tocopherol was shown to be significantly increased during clinical attack in EAE [55], however, its levels were found to be reduced in MS patients [56], which is dissimilar from our finding. Salicylate is a well known inhibitor of cyclooxygenase and has been shown to attenuate EAE disease progression and inflammation [57]. Trigoneline, an alkaloid and coffee constituent, was elevated in the plasma of EAE (Figure 3E). It has been reported to have anti-diabetic property [58]. Higher levels of these compounds found in the plasma of EAE could be a self-protective mechanism up regulated during disease against the inflammatory cascades.

To get a holistic view of the metabolic alterations occurring in the plasma of EAE mice we conducted pathway analysis of the biochemical pathways of the Kyoto Encyclopedia of Genes and Genomics (KEGG, http://genome.jp/kegg). We considered both concerted changes in metabolite intensity within the pathway (GlobalTest) [31] and alterations of high impact (i.e. at major junctions in the pathway), and found that a number of pathways were significantly altered (Figure 4A). We selected six pathways based on p values and high impact factor (Figure 4B). Pathways found to be altered based on the Global Test included primary bile acid biosynthesis, taurine and hypotaurine metabolism, tryptophan and histidine metabolism. Linoleic acid and D-arginine and D-orinithine metabolism pathways had altered metabolites with high impact. These pathways are highly integrated as shown in Figure 5, suggesting that perturbation of certain central metabolites could have impact on multiple metabolic pathways. While some of these metabolite changes could easily be developed as biomarkers of the disease, the key to translating metabolomics into therapeutics would require figuring out the central altered metabolic pathway(s).

Figure 4: Metabolites altered in EAE compared to healthy group map to multiple biosynthetic pathways. A. Each of 80 KEGG pathways plotted according to Global Test p-value (vertical axis, intensity of color) and impact factor (horizontal axis, size of circle). B. Statistics for pathways with major change based on the p value (pathways 1-4) or on high impact (pathways 5-6).

Figure 5: Perturbation of metabolic pathways in EAE compared to healthy group. Altered pathways summarized from KEGG and SMPDB reference pathways. Red nodes represent significantly altered metabolites (n=8 EAE and n=6 healthy; p<0.05, FDR<0.23).

Major pathways with concerted alterations during EAE disease

Primary bile acid biosynthesis metabolism: Bile acids are steroids found predominately in the bile of mammals and their main function is to facilitate the formation of micelles to promote processing of fat. Both primary and secondary circulatory bile acid levels (Deoxycholate, Taurodeoxycholate and alpha-muricholate) were decreased in the EAE group, which could either be due to a more efficient uptake of bile acids from enterohepatic circulation or decreased synthesis in the liver. Bile acid precursor, cholesterol was found to be increased during disease, which is a known risk factor for several diseases including atherosclerosis, possibly suggesting a decrease in hepatic bile acid synthesis. Alternatively, it could also indicate an increase in cholesterol synthesis in response to EAE disease. Changes in bile acid levels could affect dietary lipid absorption. Increase in cholesterol levels in plasma in EAE has been previously reported [59], however, no conclusive reports are available indicating a relationship between higher cholesterol and MS incidence in patients. Under normal conditions, the most abundant bile acids are chenodeoxycholic acid (45%) and cholic acid (31%), referred to as primary bile acids. Before they are secreted from lumen, they are conjugated with amino acids glycine or taurine and called glycoconjugates and tauroconjugates, respectively. In human and rat, both conjugates are present, however, in mouse, only tauroconjugates are formed. We found decreased levels of deoxycholate in plasma, which may reflect that gut bacteria may be not able to efficiently modify primary bile acids (cholate) into secondary bile acids (deoxycholate). Decreased level of deoxycholate is reflected in lower levels of taurocdeoxycholate observed in diseased mice (Figures 3A and 5). Alpha-mucholic acid was also decreased in plasma of EAE group; however, taurocholic acid and taurochenodeoxycholic acids were unaffected compared to healthy group. Deoxycholic acid is reported to activate farnesoid X receptor (FXR) [60], which is a nuclear receptor controlling genes of various pathways including bile acid synthesis, cholesterol, glycolysis, glyconeogenesis and fatty acid oxidation [61]. Moreover, activation of FXR shows anti-inflammatory property in inflammatory models [62,63], raising the question whether decreased levels of anti-inflammatory bile acids could be one of the factors contributing towards the severity of disease in EAE.

Tryptophan metabolism: Tryptophan metabolism is critical for two important biosynthetic pathways; 1: generation of neurotransmitter 5-hydroxytryptamin (serotonin) by tryptophan 5-hydroxylkase, and 2: the formation of kynurenine derivatives and NAD. Serotonin is a major neurotransmitter in the enteric nervous system (ENS) as well as in CNS. A portion of serotonin is further converted to melatonin, affecting sleep pattern. Although we did not observe any changes in the levels of tryptophan and serotonin, the level of kynurenate (kynurenic acid) was significantly low in plasma of EAE, which is a metabolite of kynurenine. On the other hand, indolepropionate and indoleacrylate levels were found to be elevated in EAE, suggesting a disruption of tryptophan metabolism in EAE. Tryptophan catabolism is regulated by the balanced expression of indolamine 2,3-dioxygenase (IDO)/ tryptophanyl-tRNA-synthase (TTS). IDO is expressed in a variety of cells in CNS including macrophage/activated microglia during disease [64], and drives immune dysfunction by suppressing T cell proliferation, altering Th17/Treg balance and controlling EAE disease [8].

Taurine and hypotaurine metabolism: Taurine is a major constituent of bile and accounts for approximately 0.1% of total human body weight. Apart from the fundamental biological roles it plays in conjugation of bile acids, as an anti-oxidant, osmoregulation, membrane stabilization and calcium signaling, it also has immunomodulatory and neuroprotective effects [65]. Taurine and its metabolites inhibit T cell response and functions of antigen presenting cells, and thereby play an important role in maintaining the balance between the inflammatory response and the induction of an antigen specific immune response [66]. Our observation that taurine metabolism pathway is significantly altered is in accordance with previous published observations in EAE and MS CSF, where higher levels of taurine was also observed [23,67,68]. Our data reveals that this increase in taurine can also be determined in the plasma, without the need of CSF, and could be a potential biomarker.

Histidine metabolism: While histidine levels were found to be increased, one of its metabolites (also an antioxidant), anserine, showed a decreasing trend in the EAE group. Histamine, one of the metabolites in histidine metabolism, has been shown to play regulatory role in EAE by altering the permeability of the BBB and promoting CNS inflammation [69,70]. Its levels were reported to be significantly higher in CSF of MS patients [71]. Changes in histidine metabolism could potentially affect histamine levels.The biosynthesis of histidine is inherently linked to the nucleotide pathway through 5-phosphoribosyl- 1-pyrophsophate (PRPP) [72]. Circulatory nucleosides including N4- acetylcytidine were increased in EAE group compared to healthy group, possibly being generated from the increased degradation of synthesized RNA [73]. Anserine, which was significantly decreased in EAE plasma, is a di-peptide of beta-alanine and N-methyl-histidine. It is an antioxidant found in skeletal muscle and brain, and inhibits the catalysis of lipid oxidation. Another antioxidant, alpha-tocopherol was increased during EAE disease while no change was found in metabolites involved in the glutathione pathway. It is accepted that a critical balance between various anti-oxidants could tilt the severity of disease in EAE.

Major pathways affected by alterations of high impact molecules during EAE disease

Linoleic acid metabolism: Linoleic acid (LA) is a member of the essential fatty acids called omega-6 fatty acids. LA is a precursor of eicosanoids, which have pro- and anti-inflammatory effect in vitro and in vivo. Its levels were found to be low in MS patients [74,75], suggesting the perturbation of this pathway during disease. Clinical trials in MS patients revealed that treatment with LA reduced the severity and duration of relapses at all levels of disability and duration of illness at entry to the trials [76]. Recently, a randomised, double-blind, placebocontrolled proof-of-concept clinical trial using novel oral nutraceutical formula of omega-3 and omega-6 fatty acids with vitamins (PLP10) in relapsing remitting multiple sclerosis showed a significant reduction in annualized relapse rate and the risk of sustained disability progression without any reported serious adverse events [77]. Moreover, oral feeding of LA has been reported to attenuate EAE disease progression associated with an increase in cell membrane long chain omega-6 fatty acids, production of prostaglandin E2 (PGE2) and the expression of TGFβ1 in mice [78] and guinea pigs [79]. Omega-3 and omega-6 PUFAs modulate transcription via interactions with peroxisome proliferatoractivated receptors (PPARs), which increase fatty acid oxidation and suppress lipogenesis and control inflammation by repressing various transcription factors including NFκB, NFAT, AP-1 and STATs [80,81]. These reports support that linoleic metabolism pathway is affected during EAE/MS disease and restoring omega-6 fatty acid levels may have beneficial effect in EAE and MS patients.

D-Arginine and D-ornithine pathway: This pathway described the general conversion of D-amino acids to oxo-amino acids by D-amino acid oxidase. D-amino acids can be found in some bacteria or may spontaneously form via isomerase/mutase reactions. D-arginine converted to L-arginine, which is the main substrate for nitric oxide (NO) synthesis during inflammation in EAE and MS. Overexpression of iNOS in the infiltrated macrophages and resident microglia/astrocytes leads to intense production of NO in the CNS [82]. The role of NO in EAE and MS is elusive. Although arginine level was not altered in plasma in EAE, citrulline levels were decreased significantly. Citrullline can be derived from multiple sources including from arginine via NOS or from ornithine via catabolism of proline and glutamine/glutamate. During inflammation in EAE, NOS in immune cells used arginine as a substrate producing NO as aninflammatory mediator and citrulline as a byproduct. In contrast, citrulline levels were significantly low in plasma during EAE. The most plausible explanation is that citrulline is extracted from circulation by proximal tubules of kidney, converted to arginine and returned to circulation, resulting in unaffected arginine levels in plasma of EAE.

Altogether, using untargeted metabolomics profiling, this study provides a better understanding of metabolic abnormalities in RR EAE mouse model at chronic phase of the disease. We identified 44 metabolite signature discriminating EAE from the healthy group that correlated with the clinical pathology of the disease. These metabolites pertaining to six identified pathways are highly integrated and participate in anti-and pro-inflammatory responses in body (Figure 5). Balance between these pathways possibly decides the outcome of the disease. We do realize that by limiting analysis to one time point, we may have missed earlier metabolic changes that may serve as early biomarker(s) in the mouse model. Earlier time points and other tissues will be subjected to metabolic profiling in the future to provide more insights into the mechanisms related to EAE disease. We appreciate that the in depth mechanistic studies with specific metabolite(s) and/ or pathways are required to judge the true contribution or effect on the disease process. However, we believe this is the first step in appreciating the milieu of metabolic changes associated with the EAE/MS disease process. In conclusion, the plasma metabolomics possesses great potential in biomarker discovery and in investigation of the underlying metabolic mechanisms for EAE/MS. Moreover, these findings clearly suggest that creation of new treatment paradigms targeting and modulating these metabolic pathways in their entirety, rather than single protein or pathway (for example immunomodulation), might be necessary for controlling and treating demyelinating disease in humans.

The authors have no financial conflict of interest.

This investigation was mainly supported by grants (RG3810-A-1 and RG4311A4/4) from the National Multiple Sclerosis Society and 5R21NS65928 NIH to SG.