Urinary and Plasma Metabolomics Identify the Distinct Metabolic Profile of Disease State in Chronic Mouse Model of Multiple Sclerosis

Metabolomic profiling of childhood medulloblastoma: contributions and relevance to diagnosis and molecular subtyping

The incidence of brain tumors among children is second only to acute lymphoblastic leukemia, but the mortality rate of brain tumors has exceeded that of leukemia, making it the most common cause of death among children. Medulloblastoma (MB) is the most common type of brain tumor among children. Malignant brain tumors have strong invasion and metastasis capabilities, can spread through cerebrospinal fluid, and have a high mortality rate. In 2010, the World Health Organization first divided MB into four molecular subtypes based on molecular markers: WNT, Sonic hedgehog (SHH), Group 3, and Group 4. MB is a highly heterogeneous tumor. Different molecular subtypes of MB have significantly different clinical, pathological, and molecular characteristics. The prognosis of MB varies significantly among patients with different subtypes of this cancer. Thus, it is needed to study new diagnostic and therapeutic strategies. Metabolomics is an advanced analytical technology that uses various spectroscopic, electrochemical, and data analysis technologies to study and analyze the body's metabolites. By detecting changes in metabolite types and quantities in different types of samples, it can sensitively discover the physiological and pathological changes in the body. It has great potential for clinical application and personalized medicine. It is promising and can help develop personalized treatment strategies based on the metabolic profiles of individuals. It can unravel the unique metabolic profiles of MB, which may revolutionize our understanding of the disease and improve patients' outcomes.

Development of an LC-HRMS non-targeted method for comprehensive profiling of the exposome of nicotine and tobacco product users - A showcase for cigarette smokers

The global prevalence of electronic cigarettes, heated tobacco products, and other smokeless alternatives has grown significantly in the last ten years. These products have been suggested as combustion-free alternatives for conventional tobacco products like cigarettes, aiming to reduce the negative health impacts associated with smoking. However, the impact of those products on the health and safety of the general population are still unclear, as the absolute exposure from those products has not been thoroughly studied, yet. In this project, a non-targeted LC-HRMS method was developed comprising four different analytical modes for the investigation of the exposure profile in urine of the product users. The method is characterized by its high sensitivity and reproducibility, as shown during method validation. As a proof of concept, we first applied this method to detect significant differences in biomarkers of exposure (BoEs) between smokers and non-smokers. We observed a total of 171 BoEs significantly elevated in smokers, including several well-known biomarkers of smoke exposure like nicotine and its metabolites, mercapturic acid derivatives, and phenolic compounds. Some of the detected biomarkers are present at low ng/mL concentrations in urine, proving the high sensitivity needed for a holistic exploration of the exposome. Moreover, we were able to identify BoEs that have not been reported previously for smoking, such as 2,6-dimethoxyphenol and 7-methyl-1-naphthol glucuronide.

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

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

Increased serum phenylalanine/tyrosine ratio associated with the psychiatric symptom of anti-NMDAR encephalitis

Background

Encephalitis associated with antibodies against the N-methyl-D-aspartate receptor (NMDAR) results in a distinctive neuro-psychiatric syndrome. It has been reported that the serum phenylalanine-tyrosine (Phe/Tyr) ratio increases during infection. However, the connection between phenylalanine-tyrosine metabolism and psychiatric symptoms remains unclear.

Methods

We enrolled 24 individuals with anti-NMDAR encephalitis and 18 individuals with non-inflammatory neurological diseases (OND). Chromatography was used to measure serum levels of phenylalanine and tyrosine. Serum and cerebrospinal fluid (CSF) TNF-α levels were obtained from the clinical database. The modified Rankin Scale (mRS) score and Glasgow Coma Scale (GCS) score were recorded during the acute phase. The area under the curve (AUC) of the receiver operating characteristic curve was used to assess prediction efficacy.

Results

In NMDAR patients, levels of serum Phe and the ratio of serum Phe/Tyr were higher compared to OND patients. The serum Phe/Tyr ratio was also elevated in NMDAR patients with psychiatric syndrome. Furthermore, serum Phe and Tyr levels were correlated with inflammatory indexes.

Conclusion

The serum Phe/Tyr ratio is elevated in NMDAR patients with psychiatric syndrome and is associated with severity. Therefore, the serum Phe/Tyr ratio may serve as a potential prognostic biomarker.

Extracellular Purine Metabolism-Potential Target in Multiple Sclerosis

The purinergic signaling system comprises a complex network of extracellular purines and purine-metabolizing ectoenzymes, nucleotide and nucleoside receptors, ATP release channels, and nucleoside transporters. Because of its immunomodulatory function, this system is critically involved in the pathogenesis of multiple sclerosis (MS) and its best-characterized animal model, experimental autoimmune encephalomyelitis (EAE). MS is a chronic neuroinflammatory demyelinating and neurodegenerative disease with autoimmune etiology and great heterogeneity, mostly affecting young adults and leading to permanent disability. In MS/EAE, alterations were detected in almost all components of the purinergic signaling system in both peripheral immune cells and central nervous system (CNS) glial cells, which play an important role in the pathogenesis of the disease. A decrease in extracellular ATP levels and an increase in its downstream metabolites, particularly adenosine and inosine, were frequently observed at MS, indicating a shift in metabolism toward an anti-inflammatory environment. Accordingly, upregulation of the major ectonucleotidase tandem CD39/CD73 was detected in the blood cells and CNS of relapsing-remitting MS patients. Based on the postulated role of A2A receptors in the transition from acute to chronic neuroinflammation, the association of variants of the adenosine deaminase gene with the severity of MS, and the beneficial effects of inosine treatment in EAE, the adenosinergic system emerged as a promising target in neuroinflammation. More recently, several publications have identified ADP-dependent P2Y12 receptors and the major extracellular ADP producing enzyme nucleoside triphosphate diphosphohydrolase 2 (NTPDase2) as novel potential targets in MS.

System-based integrated metabolomics and microRNA analysis identifies potential molecular alterations in human X-linked cerebral adrenoleukodystrophy brain

X-linked adrenoleukodystrophy is a severe demyelinating neurodegenerative disease mainly affecting males. The severe cerebral adrenoleukodystrophy (cALD) phenotype has a poor prognosis and underlying mechanism of onset and progression of neuropathology remains poorly understood. In this study we aim to integrate metabolomic and microRNA (miRNA) datasets to identify variances associated with cALD. Postmortem brain tissue samples from five healthy controls (CTL) and five cALD patients were utilized in this study. White matter from ALD patients was obtained from normal-appearing areas, away from lesions (NLA) and from the periphery of lesions- plaque shadow (PLS). Metabolomics was performed by gas chromatography coupled with time-of-flight mass spectrometry and miRNA expression analysis was performed by next generation sequencing (RNAseq). Principal component analysis revealed that among the three sample groups (CTL, NLA and PLS) there were 19 miRNA, including several novel miRNA, of which 17 were increased with disease severity and 2 were decreased. Untargeted metabolomics revealed 13 metabolites with disease severity-related patterns with 7 increased and 6 decreased with disease severity. Ingenuity pathway analysis of differentially altered metabolites and miRNA comparing CTL with NLA and NLA with PLS, identified several hubs of metabolite and signaling molecules and their upstream regulation by miRNA. The transomic approach to map the crosstalk between miRNA and metabolomics suggests involvement of specific molecular and metabolic pathways in cALD and offers opportunity to understand the complex underlying mechanism of disease severity in cALD.

Early urinary candidate biomarkers and clinical outcomes of intervention in a rat model of experimental autoimmune encephalomyelitis

Multiple sclerosis is a chronic autoimmune demyelinating disease of the central nervous system and is difficult to diagnose in early stages. Without homeostatic control, urine was reported to have the ability to accumulate early changes in the body. We expect that urinary proteome can reflect early changes in the nervous system. The early urinary proteome changes in a most employed multiple sclerosis rat model (experimental autoimmune encephalomyelitis) were analysed to explore early urinary candidate biomarkers, and early treatment of methylprednisolone was used to evaluate the therapeutic effect. Twenty-five urinary proteins were altered at day 7 when there were no clinical symptoms and obvious histological changes. Fourteen were reported to be differently expressed in the serum/cerebrospinal fluid/brain tissues of multiple sclerosis patients or animals such as angiotensinogen and matrix metallopeptidase 8. Functional analysis showed that the dysregulated proteins were associated with asparagine degradation, neuroinflammation and lipid metabolism. After the early treatment of methylprednisolone, the incidence of encephalomyelitis in the intervention group was only 1/13. This study demonstrates that urine may be a good source of biomarkers for the early detection of multiple sclerosis. These findings may provide important information for early diagnosis and intervention of multiple sclerosis in the future.

Metabolomics detects clinically silent neuroinflammatory lesions earlier than neurofilament-light chain in a focal multiple sclerosis animal model

Background

Despite widespread searches, there are currently no validated biofluid markers for the detection of subclinical neuroinflammation in multiple sclerosis (MS). The dynamic nature of human metabolism in response to changes in homeostasis, as measured by metabolomics, may allow early identification of clinically silent neuroinflammation. Using the delayed-type hypersensitivity (DTH) MS rat model, we investigated the serum and cerebrospinal fluid (CSF) metabolomics profiles and neurofilament-light chain (NfL) levels, as a putative marker of neuroaxonal damage, arising from focal, clinically silent neuroinflammatory brain lesions and their discriminatory abilities to distinguish DTH animals from controls.

Methods

¹H nuclear magnetic resonance (NMR) spectroscopy metabolomics and NfL measurements were performed on serum and CSF at days 12, 28 and 60 after DTH lesion initiation. Supervised multivariate analyses were used to determine metabolomics differences between DTH animals and controls. Immunohistochemistry was used to assess the extent of neuroinflammation and tissue damage.

Results

Serum and CSF metabolomics perturbations were detectable in DTH animals (vs. controls) at all time points, with the greatest change occurring at the earliest time point (day 12) when the neuroinflammatory response was most intense (mean predictive accuracy [SD]—serum: 80.6 [10.7]%, p < 0.0001; CSF: 69.3 [13.5]%, p < 0.0001). The top discriminatory metabolites at day 12 (serum: allantoin, cytidine; CSF: glutamine, glucose) were all reduced in DTH animals compared to controls, and correlated with histological markers of neuroinflammation, particularly astrogliosis (Pearson coefficient, r—allantoin: r = − 0.562, p = 0.004; glutamine: r = − 0.528, p = 0.008). Serum and CSF NfL levels did not distinguish DTH animals from controls at day 12, rather, significant differences were observed at day 28 (mean [SEM]—serum: 38.5 [4.8] vs. 17.4 [2.6] pg/mL, p = 0.002; CSF: 1312.0 [379.1] vs. 475.8 [74.7] pg/mL, p = 0.027). Neither serum nor CSF NfL levels correlated with markers of neuroinflammation; serum NfL did, however, correlate strongly with axonal loss (r = 0.641, p = 0.001), but CSF NfL did not (p = 0.137).

Conclusions

While NfL levels were elevated later in the pathogenesis of the DTH lesion, serum and CSF metabolomics were able to detect early, clinically silent neuroinflammation and are likely to present sensitive biomarkers for the assessment of subclinical disease activity in patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02614-8.

How Microbiota-Derived Metabolites Link the Gut to the Brain during Neuroinflammation

Microbiota-derived metabolites are important molecules connecting the gut to the brain. Over the last decade, several studies have highlighted the importance of gut-derived metabolites in the development of multiple sclerosis (MS). Indeed, microbiota-derived metabolites modulate the immune system and affect demyelination. Here, we discuss the current knowledge about microbiota-derived metabolites implications in MS and in different mouse models of neuroinflammation. We focus on the main families of microbial metabolites that play a role during neuroinflammation. A better understanding of the role of those metabolites may lead to new therapeutical avenues to treat neuroinflammatory diseases targeting the gut–brain axis.

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.

Blood-based untargeted metabolomics in relapsing-remitting multiple sclerosis revealed the testable therapeutic target

Metabolic aberrations impact the pathogenesis of multiple sclerosis (MS) and possibly can provide clues for new treatment strategies. Using untargeted metabolomics, we measured serum metabolites from 35 patients with relapsing-remitting multiple sclerosis (RRMS) and 14 healthy age-matched controls. Of 632 known metabolites detected, 60 were significantly altered in RRMS. Bioinformatics analysis identified an altered metabotype in patients with RRMS, represented by four changed metabolic pathways of glycerophospholipid, citrate cycle, sphingolipid, and pyruvate metabolism. Interestingly, the common upstream metabolic pathway feeding these four pathways is the glycolysis pathway. Real-time bioenergetic analysis of the patient-derived peripheral blood mononuclear cells showed enhanced glycolysis, supporting the altered metabolic state of immune cells. Experimental autoimmune encephalomyelitis mice treated with the glycolytic inhibitor 2-deoxy-D-glucose ameliorated the disease progression and inhibited the disease pathology significantly by promoting the antiinflammatory phenotype of monocytes/macrophage in the central nervous system. Our study provided a proof of principle for how a blood-based metabolomic approach using patient samples could lead to the identification of a therapeutic target for developing potential therapy.

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.

1H-NMR-based metabolic profiling identifies non-invasive diagnostic and predictive urinary fingerprints in 5q spinal muscular atrophy

Background

5q spinal muscular atrophy (SMA) is a disabling and life-limiting neuromuscular disease. In recent years, novel therapies have shown to improve clinical outcomes. Yet, the absence of reliable biomarkers renders clinical assessment and prognosis of possibly already affected newborns with a positive newborn screening result for SMA imprecise and difficult. Therapeutic decisions and stratification of individualized therapies remain challenging, especially in symptomatic children. The aim of this proof-of-concept and feasibility study was to explore the value of ¹H-nuclear magnetic resonance (NMR)-based metabolic profiling in identifying non-invasive diagnostic and prognostic urinary fingerprints in children and adolescents with SMA.

Results

Urine samples were collected from 29 treatment-naïve SMA patients (5 pre-symptomatic, 9 SMA 1, 8 SMA 2, 7 SMA 3), 18 patients with Duchenne muscular dystrophy (DMD) and 444 healthy controls. Using machine-learning algorithms, we propose a set of prediction models built on urinary fingerprints that showed potential diagnostic value in discriminating SMA patients from controls and DMD, as well as predictive properties in separating between SMA types, allowing predictions about phenotypic severity. Interestingly, preliminary results of the prediction models suggest additional value in determining biochemical onset of disease in pre-symptomatic infants with SMA identified by genetic newborn screening and furthermore as potential therapeutic monitoring tool.

Conclusions

This study provides preliminary evidence for the use of ¹H-NMR-based urinary metabolic profiling as diagnostic and prognostic biomarker in spinal muscular atrophy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-02075-x.

Identification of causal metabolites related to multiple autoimmune diseases

OBJECT

Observational studies provide evidence that metabolites may be involved in the development of autoimmune diseases (ADs), but whether it is causal is still unknown.

METHODS

Based on the large-scale GWAS summary statistics, two-sample Mendelian randomization (MR) was performed to evaluate the causal association between human serum metabolites and multiple ADs, which were inflammatory bowel disease (IBD), ulcerative Colitis (UC), crohn's disease (CD), rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), primary biliary cirrhosis (PBC) and primary sclerosing cholangitis (PSC). Comprehensive sensitive analysis was used to validate the robustness of MR results and multivariable MR analysis was conducted to avoid potential pleiotropic effect of other complex traits. Finally, metabolic pathway analysis was performed based on causal metabolites for each ad, respectively.

RESULTS

We identified 6 causal features of metabolite after Bonferroni adjustment, i.e. glycerol 2-phosphate for T1D, hexadecanedioate, phenylacetylglutamine and laurylcarnitine for RA, glycine and arachidonate (20:4n6) for CD. Then comprehensively sensitive analysis proved the robustness of the causal associations. We also observed some overlaps of metabolites among different ADs, indicating the similar mechanisms. After controlling for several common traits, multivariable MR analysis ruled out most of potential pleiotropic effects and validated the independence of identified metabolites. Additionally, a total of 6 metabolic pathways have been identified for different ADs.

CONCLUSIONS

This study provided novel insights into investigating causal role of serum metabolites in development of multiple ADs through a comprehensive genetic pathway.

Direct and indirect effects of microbiota-derived metabolites on neuroinflammation in multiple sclerosis

Multiple sclerosis (MS) and experimental autoimmune encephalomyelitis (EAE) are highly influenced by changes in the microbiota and of microbiota-derived metabolites, including short chain fatty acids, bile acids, and tryptophan derivatives. This review will discuss the effects of microbiota-derived metabolites on neuroinflammation driven by central nervous system-resident cells and peripheral immune cells, and their influence on outcomes of EAE and MS.

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

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

Metabolomic Profiling in Neuromyelitis Optica Spectrum Disorder Biomarker Discovery

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

Host and Microbial Tryptophan Metabolic Profiling in Multiple Sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that is associated with demyelination and neuronal loss. Over recent years, the immunological and neuronal effects of tryptophan (Trp) metabolites have been largely investigated, leading to the hypothesis that these compounds and the related enzymes are possibly involved in the pathophysiology of MS. Specifically, the kynurenine pathway of Trp metabolism is responsible for the synthesis of intermediate products with potential immunological and neuronal effects. More recently, Trp metabolites, originating also from the host microbiome, have been identified in MS, and it has been shown that they are differently regulated in MS patients. Here, we sought to discuss whether, in MS patients, a specific urinary signature of host/microbiome Trp metabolism can be potentially identified so as to select novel biomarkers and guide toward the identification of specific metabolic pathways as drug targets in MS.