Multi-omic evaluation of metabolic alterations in multiple sclerosis identifies shifts in aromatic amino acid metabolism

A diet-dependent host metabolite shapes the gut microbiota to protect from autoimmunity

Diet can protect from autoimmune disease; however, whether diet acts via the host and/or microbiome remains unclear. Here, we use a ketogenic diet (KD) as a model to dissect these complex interactions. A KD rescued the experimental autoimmune encephalomyelitis (EAE) mouse model of multiple sclerosis in a microbiota-dependent fashion. Dietary supplementation with a single KD-dependent host metabolite (β-hydroxybutyrate, βHB) rescued EAE whereas transgenic mice unable to produce βHB in the intestine developed more severe disease. Transplantation of the βHB-shaped gut microbiota was protective. Lactobacillus sequence variants were associated with decreased T helper 17 (Th17) cell activation in vitro . Finally, we isolated a L. murinus strain that protected from EAE, which was phenocopied by the Lactobacillus metabolite indole lactic acid. Thus, diet alters the immunomodulatory potential of the gut microbiota by shifting host metabolism, emphasizing the utility of taking a more integrative approach to study diet-host-microbiome interactions.

Metabolomics of Multiple Sclerosis Lesions Demonstrates Lipid Changes Linked to Alterations in Transcriptomics-Based Cellular Profiles

BACKGROUND AND OBJECTIVES

People with multiple sclerosis (MS) have a dysregulated circulating metabolome, but the metabolome of MS brain lesions has not been studied. The aims of this study were to identify differences in the brain tissue metabolome in MS compared with controls and to assess its association with the cellular profile of corresponding tissue.

METHODS

MS tissues included samples from the edge and core of chronic active or inactive lesions and periplaque white matter (WM). Control specimens were obtained from normal WM. Metabolomic analysis was performed using mass-spectrometry coupled with liquid/gas chromatography and subsequently integrated with single-nucleus RNA-sequencing data by correlating metabolite abundances with relative cell counts, as well as individual genes using Multiomics Factor Analysis (MOFA).

RESULTS

Seventeen samples from 5 people with secondary progressive MS and 8 samples from 6 controls underwent metabolomic profiling identifying 783 metabolites. MS lesions had higher levels of sphingosines (false discovery rate-adjusted p-value[q] = 2.88E-05) and sphingomyelins and ceramides (q = 2.15E-07), but lower nucleotide (q = 0.05), energy (q = 0.001), lysophospholipid (q = 1.86E-07), and monoacylglycerol (q = 0.04) metabolite levels compared with control WM. Periplaque WM had elevated sphingomyelins and ceramides (q = 0.05) and decreased energy metabolites (q = 0.01) and lysophospholipids (q = 0.05) compared with control WM. Sphingolipids and membrane lipid metabolites were positively correlated with astrocyte and immune cell abundances and negatively correlated with oligodendrocytes. On the other hand, long-chain fatty acid, endocannabinoid, and monoacylglycerol pathways were negatively correlated with astrocyte and immune cell populations and positively correlated with oligodendrocytes. MOFA demonstrated associations between differentially expressed metabolites and genes involved in myelination and lipid biosynthesis.

DISCUSSION

MS lesions and perilesional WM demonstrated a significantly altered metabolome compared with control WM. Many of the altered metabolites were associated with altered cellular composition and gene expression, indicating an important role of lipid metabolism in chronic neuroinflammation in MS.

The role of the "gut microbiota-mitochondria" crosstalk in the pathogenesis of multiple sclerosis

Multiple Sclerosis (MS) is a neurologic autoimmune disease whose exact pathophysiologic mechanisms remain to be elucidated. Recent studies have shown that the onset and progression of MS are associated with dysbiosis of the gut microbiota. Similarly, a large body of evidence suggests that mitochondrial dysfunction may also have a significant impact on the development of MS. Endosymbiotic theory has found that human mitochondria are microbial in origin and share similar biological characteristics with the gut microbiota. Therefore, gut microbiota and mitochondrial function crosstalk are relevant in the development of MS. However, the relationship between gut microbiota and mitochondrial function in the development of MS is not fully understood. Therefore, by synthesizing previous relevant literature, this paper focuses on the changes in gut microbiota and metabolite composition in the development of MS and the possible mechanisms of the crosstalk between gut microbiota and mitochondrial function in the progression of MS, to provide new therapeutic approaches for the prevention or reduction of MS based on this crosstalk.

Blood metabolomic and transcriptomic signatures stratify patient subgroups in multiple sclerosis according to disease severity

There are no blood-based biomarkers distinguishing patients with relapsing-remitting (RRMS) from secondary progressive multiple sclerosis (SPMS) although evidence supports metabolomic changes according to MS disease severity. Here machine learning analysis of serum metabolomic data stratified patients with RRMS from SPMS with high accuracy and a putative score was developed that stratified MS patient subsets. The top differentially expressed metabolites between SPMS versus patients with RRMS included lipids and fatty acids, metabolites enriched in pathways related to cellular respiration, notably, elevated lactate and glutamine (gluconeogenesis-related) and acetoacetate and bOHbutyrate (ketone bodies), and reduced alanine and pyruvate (glycolysis-related). Serum metabolomic changes were recapitulated in the whole blood transcriptome, whereby differentially expressed genes were also enriched in cellular respiration pathways in patients with SPMS. The final gene-metabolite interaction network demonstrated a potential metabolic shift from glycolysis toward increased gluconeogenesis and ketogenesis in SPMS, indicating metabolic stress which may trigger stress response pathways and subsequent neurodegeneration.

Bile acid metabolites predict multiple sclerosis progression and supplementation is safe in progressive disease

Background

Bile acid metabolism is altered in multiple sclerosis (MS) and tauroursodeoxycholic acid (TUDCA) supplementation ameliorated disease in mouse models of MS.

Methods

Global metabolomics was performed in an observational cohort of people with MS followed by pathway analysis to examine relationships between baseline metabolite levels and subsequent brain and retinal atrophy. A double-blind, placebo-controlled trial, was completed in people with progressive MS (PMS), randomized to receive either TUDCA (2g daily) or placebo for 16 weeks. Participants were followed with serial clinical and laboratory assessments. Primary outcomes were safety and tolerability of TUDCA, and exploratory outcomes included changes in clinical, laboratory and gut microbiome parameters.

Results

In the observational cohort, higher primary bile acid levels at baseline predicted slower whole brain, brain substructure and specific retinal layer atrophy. In the clinical trial, 47 participants were included in our analyses (21 in placebo arm, 26 in TUDCA arm). Adverse events did not significantly differ between arms (p=0.77). The TUDCA arm demonstrated increased serum levels of multiple bile acids. No significant differences were noted in clinical or fluid biomarker outcomes. Central memory CD4+ and Th1/17 cells decreased, while CD4+ naïve cells increased in the TUDCA arm compared to placebo. Changes in the composition and function of gut microbiota were also noted in the TUDCA arm compared to placebo.

Conclusion

Bile acid metabolism in MS is linked with brain and retinal atrophy. TUDCA supplementation in PMS is safe, tolerable and has measurable biological effects that warrant further evaluation in larger trials with a longer treatment duration.

Myeloid cell-associated aromatic amino acid metabolism facilitates CNS myelin regeneration

Regulation of myeloid cell activity is critical for successful myelin regeneration (remyelination) in demyelinating diseases, such as multiple sclerosis (MS). Here, we show aromatic alpha-keto acids (AKAs) generated from the amino acid oxidase, interleukin-4 induced 1 (IL4I1), promote efficient remyelination in mouse models of MS. During remyelination, myeloid cells upregulated the expression of IL4I1. Conditionally knocking out IL4I1 in myeloid cells impaired remyelination efficiency. Mice lacking IL4I1 expression exhibited a reduction in the AKAs, phenylpyruvate, indole-3-pyruvate, and 4-hydroxyphenylpyruvate, in remyelinating lesions. Decreased AKA levels were also observed in people with MS, particularly in the progressive phase when remyelination is impaired. Oral administration of AKAs modulated myeloid cell-associated inflammation, promoted oligodendrocyte maturation, and enhanced remyelination in mice with focal demyelinated lesions. Transcriptomic analysis revealed AKA treatment induced a shift in metabolic pathways in myeloid cells and upregulated aryl hydrocarbon receptor activity in lesions. Our results suggest myeloid cell-associated aromatic amino acid metabolism via IL4I1 produces AKAs in demyelinated lesions to enable efficient remyelination. Increasing AKA levels or targeting related pathways may serve as a strategy to facilitate the regeneration of myelin in inflammatory demyelinating conditions.

Immuno-Responsive Gene-1: A mitochondrial gene regulates pathogenic Th17 in CNS autoimmunity mouse model

Pathogenic Th17 cells are crucial to CNS autoimmune diseases like multiple sclerosis (MS), though their control by endogenous mechanisms is unknown. RNAseq analysis of brain glial cells identified immuno-responsive gene 1 (Irg1), a mitochondrial-related enzyme-coding gene, as one of the highly upregulated gene under inflammatory conditions which were further validated in the spinal cord of animals with experimental autoimmune encephalomyelitis (EAE), an animal model of MS. Moreover, Irg1 mRNA and protein levels in myeloid, CD4, and B cells were higher in the EAE group, raising questions about its function in CNS autoimmunity. We observed that Irg1 knockout (KO) mice exhibited severe EAE disease and greater mononuclear cell infiltration, including triple-positive CD4 cells expressing IL17a, GM-CSF, and IFNγ. Lack of Irg1 in macrophages led to higher levels of Class II expression and polarized myelin primed CD4 cells into pathogenic Th17 cells through the NLRP3/IL1β axis. Our findings show that Irg1 in macrophages plays an important role in the formation of pathogenic Th17 cells, emphasizing its potential as a therapy for autoimmune diseases, including MS.

High-Protein Supplementation and Neuromuscular Electric Stimulation after Aneurysmal Subarachnoid Hemorrhage Increases Systemic Amino Acid and Oxidative Metabolism: A Plasma Metabolomics Approach

Background The INSPIRE randomized clinical trial demonstrated that a high protein diet (HPRO) combined with neuromuscular electrical stimulation (NMES) attenuates muscle atrophy and may improve functional outcomes after aSAH. Using an untargeted metabolomics approach, we sought to identify specific metabolites mediating these effects. Methods Blood samples were collected from subjects on admission prior to randomization to either standard of care (SOC; N=12) or HPRO+NMES (N=12) and at 7 days as part of the INSPIRE protocol. Untargeted metabolomics were performed for each plasma sample. Paired fold changes were calculated for each metabolite among subjects in the HPRO+NMES group at baseline and 7 days after intervention. Changes in metabolites from baseline to 7 days were compared for the HPRO+NMES and SOC groups. Sparse partial least squared discriminant analysis (sPLS-DA) identified metabolites discriminating each group. Pearson's correlation coefficients were calculated between each metabolite and total protein per day, nitrogen balance, and muscle volume Multivariable models were developed to determine associations between each metabolite and muscle volume. Results A total of 18 unique metabolites were identified including pre and post treatment and differentiating SOC vs HPRO+NMES. Of these, 9 had significant positive correlations with protein intake: N-acetylserine (ρ=0.61, P =1.56x10 -3 ), N-acetylleucine (ρ=0.58, P =2.97x10 -3 ), β-hydroxyisovaleroylcarnitine (ρ=0.53, P =8.35x10 -3 ), tiglyl carnitine (ρ=0.48, P =0.0168), N-acetylisoleucine (ρ=0.48, P =0.0183), N-acetylthreonine (ρ=0.47, P =0.0218), N-acetylkynurenine (ρ=0.45, P =0.0263), N-acetylvaline (ρ=0.44, P =0.0306), and urea (ρ=0.43, P =0.0381). In multivariable regression models, N-acetylleucine was significantly associated with preserved temporalis [OR 1.08 (95%CI 1.01, 1.16)] and quadricep [OR 1.08 (95%CI 1.02, 1.15)] muscle volume. Quinolinate was also significantly associated with preserved temporalis [OR 1.05 (95%CI 1.01, 1.09)] and quadricep [OR 1.04 (95%CI 1.00, 1.07)] muscle volume. N-acetylserine, N-acetylcitrulline, and b-hydroxyisovaleroylcarnitine were also associated with preserved temporalis or quadricep volume. Conclusions Metabolites defining the HPRO+NMES intervention mainly consisted of amino acid derivatives. These metabolites had strong correlations with protein intake and were associated with preserved muscle volume.

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.

Molecular systems biology approaches to investigate mechanisms of gut-brain communication in neurological diseases

BACKGROUND

Whilst the incidence of neurological diseases is increasing worldwide, treatment remains mostly limited to symptom management. The gut-brain axis, which encompasses the communication routes between microbiota, gut and brain, has emerged as a crucial area of investigation for identifying new preventive and therapeutic targets in neurological disease.

METHODS

Due to the inter-organ, systemic nature of the gut-brain axis, together with the multitude of biomolecules and microbial species involved, molecular systems biology approaches are required to accurately investigate the mechanisms of gut-brain communication. High-throughput omics profiling, together with computational methodologies such as dimensionality reduction or clustering, machine learning, network inference and genome-scale metabolic models, allows novel biomarkers to be discovered and elucidates mechanistic insights.

RESULTS

In this review, the general concepts of experimental and computational methodologies for gut-brain axis research are introduced and their applications are discussed, mainly in human cohorts. Important aspects are further highlighted concerning rational study design, sampling procedures and data modalities relevant for gut-brain communication, strengths and limitations of methodological approaches and some future perspectives.

CONCLUSION

Multi-omics analyses, together with advanced data mining, are essential to functionally characterize the gut-brain axis and put forward novel preventive or therapeutic strategies in neurological disease.

Multiple Sclerosis-Associated Gut Microbiome in the Israeli Diverse Populations: Associations with Ethnicity, Gender, Disability Status, Vitamin D Levels, and Mediterranean Diet

Microbiome dysbiosis is increasingly being recognized as implicated in immune-mediated disorders including multiple sclerosis (MS). The microbiome is modulated by genetic and environmental factors including lifestyle, diet, and drug intake. This study aimed to characterize the MS-associated gut microbiome in the Israeli populations and to identify associations with demographic, dietary, and clinical features. The microbiota from 57 treatment-naive patients with MS (PwMS) and 43 age- and gender-matched healthy controls (HCs) was sequenced and abundance compared. Associations between differential microbes with demographic or clinical characteristics, as well as diet and nutrient intake, were assessed. While there was no difference in α- or β-diversity of the microbiome, we identified 40 microbes from different taxonomic levels that differ in abundance between PwMS and HCs, including Barnesiella, Collinsella, Egerthella, Mitsuokella, Olsenella Romboutsia, and Succinivibrio, all enhanced in PwMS, while several members of Lacnospira were reduced. Additional MS-differential microbes specific to ethnicity were identified. Several MS-specific microbial patterns were associated with gender, vitamin D level, Mediterranean diet, nutrient intake, or disability status. Thus, PwMS have altered microbiota composition, with distinctive patterns related to geographic locations and population. Microbiome dysbiosis seem to be implicated in disease progression, gender-related differences, and vitamin D-mediated immunological effects recognized in MS. Dietary interventions may be beneficial in restoring a "healthy microbiota" as part of applying comprehensive personalized therapeutic strategies for PwMS.

Several serum lipid metabolites are associated with relapse risk in pediatric-onset multiple sclerosis

BACKGROUND

The circulating metabolome is altered in multiple sclerosis (MS), but its prognostic capabilities have not been extensively explored. Lipid metabolites might be of particular interest due to their multiple roles in the brain, as they can serve as structural components, energy sources, and bioactive molecules. Gaining a deeper understanding of the disease may be possible by examining the lipid metabolism in the periphery, which serves as the primary source of lipids for the brain.

OBJECTIVE

To determine if altered serum lipid metabolites are associated with the risk of relapse and disability in children with MS.

METHODS

We collected serum samples from 61 participants with pediatric-onset MS within 4 years of disease onset. Prospective longitudinal relapse data and cross-sectional disability measures (Expanded Disability Status Scale [EDSS]) were collected. Serum metabolomics was performed using untargeted liquid chromatography and mass spectrometry. Individual lipid metabolites were clustered into pre-defined pathways. The associations between clusters of metabolites and relapse rate and EDSS score were estimated utilizing negative binomial and linear regression models, respectively.

RESULTS

We found that serum acylcarnitines (relapse rate: normalized enrichment score [NES] = 2.1, q = 1.03E-04; EDSS: NES = 1.7, q = 0.02) and poly-unsaturated fatty acids (relapse rate: NES = 1.6, q = 0.047; EDSS: NES = 1.9, q = 0.005) were associated with higher relapse rates and EDSS, while serum phosphatidylethanolamines (relapse rate: NES = -2.3, q = 0.002; EDSS: NES = -2.1, q = 0.004), plasmalogens (relapse rate: NES = -2.5, q = 5.81E-04; EDSS: NES = -2.1, q = 0.004), and primary bile acid metabolites (relapse rate: NES = -2.0, q = 0.02; EDSS: NES = -1.9, q = 0.02) were associated with lower relapse rates and lower EDSS.

CONCLUSION

This study supports the role of some lipid metabolites in pediatric MS relapses and disability.

Profile and potential role of novel metabolite biomarkers, especially indoleacrylic acid, in pathogenesis of neuromyelitis optica spectrum disorders

Background: Neuromyelitis optica spectrum disorder (NMOSD) is an autoimmune central nervous system (CNS) inflammatory and demyelinating disorder that can lead to serious disability and mortality. Humoral fluid biomarkers with specific, convenient, and efficient profiles that could characterize and monitor disease activity or severity are very useful. We aimed to develop a sensitive and high-throughput liquid chromatography-tandem mass spectrometry (LC-MS)/MS-based analytical method for novel biomarkers finding in NMOSD patients and verified its function tentatively. Methods: Serum samples were collected from 47 NMOSD patients, 18 patients with other neurological disorders (ONDs), and 35 healthy controls (HC). Cerebrospinal fluid (CSF) samples were collected from 18 NMOSD and 17 OND patients. Three aromatic amino acids (phenylalanine, tyrosine, and tryptophan) and nine important metabolites that included phenylacetylglutamine (PAGln), indoleacrylic acid (IA), 3-indole acetic acid (IAA), 5-hydroxyindoleacetic acid (HIAA), hippuric acid (HA), I-3-carboxylic acid (I-3-CA), kynurenine (KYN), kynurenic acid (KYNA), and quinine (QUIN) were analyzed by using the liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method. The profile of IA was further analyzed, and its function was verified in an astrocyte injury model stimulated by NMO-IgG, which represents important events in NMOSD pathogenesis. Results: In the serum, tyrosine and some of the tryptophan metabolites IA and I-3-CA decreased, and HIAA increased significantly in NMOSD patients. The CSF levels of phenylalanine and tyrosine showed a significant increase exactly during the relapse stage, and IA in the CSF was also increased markedly during the relapse and remission phases. All conversion ratios had similar profiles with their level fluctuations. In addition, the serum IA levels negatively correlated with glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) levels in the serum of NMOSD patients were measured by using ultra-sensitive single-molecule arrays (Simoa). IA showed an anti-inflammatory effect in an in vitro astrocyte injury model. Conclusion: Our data suggest that essential aromatic amino acid tryptophan metabolites IA in the serum or CSF may serve as a novel promising biomarker to monitor and predict the activity and severity of NMOSD disease. Supplying or enhancing IA function can promote anti-inflammatory responses and may have therapeutic benefits.

Systems Immunology Approaches to Metabolism

Over the last decade, immunometabolism has emerged as a novel interdisciplinary field of research and yielded significant fundamental insights into the regulation of immune responses. Multiple classical approaches to interrogate immunometabolism, including bulk metabolic profiling and analysis of metabolic regulator expression, paved the way to appreciating the physiological complexity of immunometabolic regulation in vivo. Studying immunometabolism at the systems level raised the need to transition towards the next-generation technology for metabolic profiling and analysis. Spatially resolved metabolic imaging and computational algorithms for multi-modal data integration are new approaches to connecting metabolism and immunity. In this review, we discuss recent studies that highlight the complex physiological interplay between immune responses and metabolism and give an overview of technological developments that bear the promise of capturing this complexity most directly and comprehensively.

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.

Seasonal Changes in Serum Metabolites in Multiple Sclerosis Relapse

Multiple sclerosis (MS) is a debilitating chronic disease of unknown etiology. There are limited treatment options due to an incomplete understanding of disease pathology. The disease is shown to have seasonal exacerbation of clinical symptoms. The mechanisms of such seasonal worsening of symptoms remains unknown. In this study, we applied targeted metabolomics analysis of serum samples using LC-MC/MC to determine seasonal changes in metabolites throughout the four seasons. We also analyzed seasonal serum cytokine alterations in patients with relapsed MS. For the first time, we can demonstrate seasonal changes in various metabolites in MS compared to the control. More metabolites were affected in MS in the fall season followed by spring, while summer MS was characterized by the smallest number of affected metabolites. Ceramides were activated in all seasons, suggesting their central role in the disease pathogenesis. Substantial changes in glucose metabolite levels were found in MS, indicating a potential shift to glycolysis. An increased serum level of quinolinic acid was demonstrated in winter MS. Histidine pathways were affected, suggesting their role in relapse of MS in the spring and fall. We also found that spring and fall seasons had a higher number of overlapping metabolites affected in MS. This could be explained by patients having a relapse of symptoms during these two seasons.

The Role of Gut Dysbiosis and Potential Approaches to Target the Gut Microbiota in Multiple Sclerosis

It has now been established that a perturbation in gut microbiome composition exists in multiple sclerosis (MS) and its interplay with the immune system and brain could potentially contribute to the development of the disease and influence its course. The effects of the gut microbiota on the disease may be mediated by direct interactions between bacteria and immune cells or through interactions of products of bacterial metabolism with immune and CNS cells. In this review article we summarize the ways in which the gut microbiome of people with MS differs from controls and how bacterial metabolites can potentially play a role in MS pathogenesis, and examine approaches to alter the composition of the gut microbiota potentially alleviating gut dysbiosis and impacting the course of MS.

Omics approaches to understanding the efficacy and safety of disease-modifying treatments in multiple sclerosis

From the perspective of precision medicine, the challenge for the future is to improve the accuracy of diagnosis, prognosis, and prediction of therapeutic responses through the identification of biomarkers. In this framework, the omics sciences (genomics, transcriptomics, proteomics, and metabolomics) and their combined use represent innovative approaches for the exploration of the complexity and heterogeneity of multiple sclerosis (MS). This review examines the evidence currently available on the application of omics sciences to MS, analyses the methods, their limitations, the samples used, and their characteristics, with a particular focus on biomarkers associated with the disease state, exposure to disease-modifying treatments (DMTs), and drug efficacies and safety profiles.

Blood Metabolomics May Discriminate a Sub-Group of Patients with First Demyelinating Episode in the Context of RRMS with Increased Disability and MRI Characteristics Indicative of Poor Prognosis

Biomarker research across the health-to-disease continuum is being increasingly applied. We applied blood-based metabolomics in order to identify patient clusters with a first demyelinating episode, and explored the prognostic potential of the method by thoroughly characterizing each cluster in terms of clinical, laboratory and MRI markers of established prognostic potential for Multiple Sclerosis (MS). Recruitment consisted of 11 patients with Clinically Isolated Syndrome (CIS), 37 patients with a first demyelinating episode in the context of Relapsing-Remitting MS (RRMS) and 11 control participants. Blood-based metabolomics and hierarchical clustering analysis (HCL) were applied. Constructed OPLS-DA models illustrated a discrimination between patients with CIS and the controls (p = 0.0014), as well as between patients with RRMS and the controls (p = 1 × 10−5). Hierarchical clustering analysis (HCL) for patients with RRMS identified three clusters. RRMS-patients-cluster-3 exhibited higher mean cell numbers in the Cerebro-spinal Fluid (CSF) compared to patients with CIS (18.17 ± 6.3 vs. 1.09 ± 0.41, p = 0.004). Mean glucose CSF/serum ratio and infratentorial lesion burden significantly differed across CIS- and HCL-derived RRMS-patient clusters (F = 14.95, p < 0.001 and F = 6.087, p = 0.002, respectively), mainly due to increased mean values for patients with RRMS-cluster-3. HCL discriminated a cluster of patients with a first demyelinating episode in the context of RRMS with increased disability, laboratory findings linked with increased pathology burden and MRI markers of poor prognosis.

Lactobacillus reuteri tryptophan metabolism promotes host susceptibility to CNS autoimmunity

BACKGROUND

Dysregulation of gut microbiota-associated tryptophan metabolism has been observed in patients with multiple sclerosis. However, defining direct mechanistic links between this apparent metabolic rewiring and individual constituents of the gut microbiota remains challenging. We and others have previously shown that colonization with the gut commensal and putative probiotic species, Lactobacillus reuteri, unexpectedly enhances host susceptibility to experimental autoimmune encephalomyelitis (EAE), a murine model of multiple sclerosis. To identify underlying mechanisms, we characterized the genome of commensal L. reuteri isolates, coupled with in vitro and in vivo metabolomic profiling, modulation of dietary substrates, and gut microbiota manipulation.

RESULTS

The enzymes necessary to metabolize dietary tryptophan into immunomodulatory indole derivatives were enriched in the L. reuteri genomes, including araT, fldH, and amiE. Moreover, metabolite profiling of L. reuteri monocultures and serum of L. reuteri-colonized mice revealed a depletion of kynurenines and production of a wide array of known and novel tryptophan-derived aryl hydrocarbon receptor (AhR) agonists and antagonists, including indole acetate, indole-3-glyoxylic acid, tryptamine, p-cresol, and diverse imidazole derivatives. Functionally, dietary tryptophan was required for L. reuteri-dependent EAE exacerbation, while depletion of dietary tryptophan suppressed disease activity and inflammatory T cell responses in the CNS. Mechanistically, L. reuteri tryptophan-derived metabolites activated the AhR and enhanced T cell production of IL-17.

CONCLUSIONS

Our data suggests that tryptophan metabolism by gut commensals, such as the putative probiotic species L. reuteri, can unexpectedly enhance autoimmunity, inducing broad shifts in the metabolome and immunological repertoire. Video Abstract.

Current Understanding on the Genetic Basis of Key Metabolic Disorders: A Review

Simple Summary

Metabolic disorders (MD) are a challenge to healthcare systems; the emergence of the modern socio-economic system has led to a profound change in lifestyles in terms of dietary habits, exercise regimens, and behavior, all of which complement the genetic factors associated with MD. Diabetes Mellitus and Familial hypercholesterolemia are two of the 14 most widely researched MD, as they pose the greatest challenge to the public healthcare system and have an impact on productivity and the economy. Research findings have led to the development of new therapeutic molecules for the mitigation of MD as well as the invention of experimental strategies, which target the genes themselves via gene editing and RNA interference. Although these approaches may herald the emergence of a new toolbox to treat MD, the current therapeutic approaches still heavily depend on substrate reduction, dietary restrictions based on genetic factors, exercise, and the maintenance of good mental health. The development of orphan drugs for the less common MD such as Krabbe, Farber, Fabry, and Gaucher diseases, remains in its infancy, owing to the lack of investment in research and development, and this has driven the development of personalized therapeutics based on gene silencing and related technologies.

Abstract

Advances in data acquisition via high resolution genomic, transcriptomic, proteomic and metabolomic platforms have driven the discovery of the underlying factors associated with metabolic disorders (MD) and led to interventions that target the underlying genetic causes as well as lifestyle changes and dietary regulation. The review focuses on fourteen of the most widely studied inherited MD, which are familial hypercholesterolemia, Gaucher disease, Hunter syndrome, Krabbe disease, Maple syrup urine disease, Metachromatic leukodystrophy, Mitochondrial encephalopathy lactic acidosis stroke-like episodes (MELAS), Niemann-Pick disease, Phenylketonuria (PKU), Porphyria, Tay-Sachs disease, Wilson’s disease, Familial hypertriglyceridemia (F-HTG) and Galactosemia based on genome wide association studies, epigenetic factors, transcript regulation, post-translational genetic modifications and biomarker discovery through metabolomic studies. We will delve into the current approaches being undertaken to analyze metadata using bioinformatic approaches and the emerging interventions using genome editing platforms as applied to animal models.

Metabolomics Profiling of Vitamin D Status in Relation to Dyslipidemia

Vitamin D deficiency is a global disorder associated with several chronic illnesses including dyslipidemia and metabolic syndrome. The impact of this association with both dyslipidemia and vitamin D deficiency on metabolomics profile is not yet fully understood. This study analyses the metabolomics and lipidomic signatures in relation to vitamin D status and dyslipidemia. Metabolomics data were collected from Qatar Biobank database and categorized into four groups based on vitamin D and dyslipidemia status. Metabolomics multivariate analysis was performed using the orthogonal partial least square discriminate analysis (OPLS-DA) whilst linear models were used to assess the per-metabolite association with each of the four dyslipidemia/vitamin D combination groups. Our results indicate a high prevalence of vitamin D deficiency among the younger age group, while dyslipidemia was more prominent in the older group. A significant alteration of metabolomics profile was observed among the dyslipidemic and vitamin D deficient individuals in comparison with control groups. These modifications reflected changes in some key pathways including ceramides, diacylglycerols, hemosylceramides, lysophospholipids, phosphatidylcholines, phosphatidylethanol amines, and sphingomyelins. Vitamin D deficiency and dyslipidemia have a deep impact on sphingomyelins profile. The modifications were noted at the level of ceramides and are likely to propagate through downstream pathways.

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.

Current and Future Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a debilitating autoimmune disorder. Currently, there is a lack of effective treatment for the progressive form of MS, partly due to insensitive readout for neurodegeneration. The recent development of sensitive assays for neurofilament light chain (NfL) has made it a potential new biomarker in predicting MS disease activity and progression, providing an additional readout in clinical trials. However, NfL is elevated in other neurodegenerative disorders besides MS, and, furthermore, it is also confounded by age, body mass index (BMI), and blood volume. Additionally, there is considerable overlap in the range of serum NfL (sNfL) levels compared to healthy controls. These confounders demonstrate the limitations of using solely NfL as a marker to monitor disease activity in MS patients. Other blood and cerebrospinal fluid (CSF) biomarkers of axonal damage, neuronal damage, glial dysfunction, demyelination, and inflammation have been studied as actionable biomarkers for MS and have provided insight into the pathology underlying the disease process of MS. However, these other biomarkers may be plagued with similar issues as NfL. Using biomarkers of a bioinformatic approach that includes cellular studies, micro-RNAs (miRNAs), extracellular vesicles (EVs), metabolomics, metabolites and the microbiome may prove to be useful in developing a more comprehensive panel that addresses the limitations of using a single biomarker. Therefore, more research with recent technological and statistical approaches is needed to identify novel and useful diagnostic and prognostic biomarker tools in MS.

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.

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.