1H-NMR-based metabolomic profiling of CSF in early amyotrophic lateral sclerosis

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Practical Aspects of NMR-Based Metabolomics

While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for >40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.

Metabolomics identifies shared lipid pathways in independent amyotrophic lateral sclerosis cohorts

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease lacking effective treatments. This is due, in part, to a complex and incompletely understood pathophysiology. To shed light, we conducted untargeted metabolomics on plasma from two independent cross-sectional ALS cohorts versus control participants to identify recurrent dysregulated metabolic pathways. Untargeted metabolomics was performed on plasma from two ALS cohorts (cohort 1, n = 125; cohort 2, n = 225) and healthy controls (cohort 1, n = 71; cohort 2, n = 104). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon, adjusted logistic regression and partial least squares-discriminant analysis, while group lasso explored sub-pathway level differences. Adjustment parameters included age, sex and body mass index. Metabolomics pathway enrichment analysis was performed on metabolites selected using the above methods. Additionally, we conducted a sex sensitivity analysis due to sex imbalance in the cohort 2 control arm. Finally, a data-driven approach, differential network enrichment analysis (DNEA), was performed on a combined dataset to further identify important ALS metabolic pathways. Cohort 2 ALS participants were slightly older than the controls (64.0 versus 62.0 years, P = 0.009). Cohort 2 controls were over-represented in females (68%, P < 0.001). The most concordant cohort 1 and 2 pathways centred heavily on lipid sub-pathways, including complex and signalling lipid species and metabolic intermediates. There were differences in sub-pathways that were enriched in ALS females versus males, including in lipid sub-pathways. Finally, DNEA of the merged metabolite dataset of both ALS and control cohorts identified nine significant subnetworks; three centred on lipids and two encompassed a range of sub-pathways. In our analysis, we saw consistent and important shared metabolic sub-pathways in both ALS cohorts, particularly in lipids, further supporting their importance as ALS pathomechanisms and therapeutics targets.

Fatty acids derived from the probiotic Lacticaseibacillus rhamnosus HA-114 suppress age-dependent neurodegeneration

The human microbiota is believed to influence health. Microbiome dysbiosis may be linked to neurological conditions like Alzheimer's disease, amyotrophic lateral sclerosis, and Huntington's disease. We report the ability of a probiotic bacterial strain in halting neurodegeneration phenotypes. We show that Lacticaseibacillus rhamnosus HA-114 is neuroprotective in C. elegans models of amyotrophic lateral sclerosis and Huntington's disease. Our results show that neuroprotection from L. rhamnosus HA-114 is unique from other L. rhamnosus strains and resides in its fatty acid content. Neuroprotection by L. rhamnosus HA-114 requires acdh-1/ACADSB, kat-1/ACAT1 and elo-6/ELOVL3/6, which are associated with fatty acid metabolism and mitochondrial β-oxidation. Our data suggest that disrupted lipid metabolism contributes to neurodegeneration and that dietary intervention with L. rhamnosus HA-114 restores lipid homeostasis and energy balance through mitochondrial β-oxidation. Our findings encourage the exploration of L. rhamnosus HA-114 derived interventions to modify the progression of neurodegenerative diseases.

Central and peripheral regulations mediated by short-chain fatty acids on energy homeostasis

The human gut microbiota influences obesity, insulin resistance, and the subsequent development of type 2 diabetes (T2D). The gut microbiota digests and ferments nutrients resulting in the production of short-chain fatty acids (SCFAs), which generate various beneficial metabolic effects on energy and glucose homeostasis. However, their roles in the central nervous system (CNS)-mediated outputs on the metabolism have only been minimally studied. Here, we explore what is known and future directions that may be worth exploring in this emerging area. Specifically, we searched studies or data in English by using PubMed, Google Scholar, and the Human Metabolome Database. Studies were filtered by time from 1978 to March 2022. As a result, 195 studies, 53 reviews, 1 website, and 1 book were included. One hundred and sixty-five of 195 studies describe the production and metabolism of SCFAs or the effects of SCFAs on energy homeostasis, glucose balance, and mental diseases through the gut-brain axis or directly by a central pathway. Thirty of 195 studies show that inappropriate metabolism and excessive of SCFAs are metabolically detrimental. Most studies suggest that SCFAs exert beneficial metabolic effects by acting as the energy substrate in the TCA cycle, regulating the hormones related to satiety regulation and insulin secretion, and modulating immune cells and microglia. These functions have been linked with AMPK signaling, GPCRs-dependent pathways, and inhibition of histone deacetylases (HDACs). However, the studies focusing on the central effects of SCFAs are still limited. The mechanisms by which central SCFAs regulate appetite, energy expenditure, and blood glucose during different physiological conditions warrant further investigation.

NMR based metabolic profiling of patients with potential celiac disease elucidating early biochemical changes of gluten-sensitivity: A pilot Study

BACKGROUND

The patients with positive celiac disease (CeD) specific serology, but no evidence of intestinal inflammation are defined as potential celiac disease (PCeD) patients. About one-third of PCeD patients develop intestinal inflammation over time. The present study investigated the metabolome of small intestinal biopsies, blood plasma, and urine of patients with PCeD to understand the biochemical changes underlying the CeD.

METHODS

The metabolic profiles of small intestinal biopsies, blood plasma, and urine of patients with PCeD (n=7) were compared with CeD (n=64) and controls (n=15) [disease controls (DC) and healthy controls (HC)] using ¹H NMR spectroscopy.

RESULTS

The intestinal mucosa of PCeD showed lower levels of histidine, glycine, tyrosine, and tryptophan compared to DC. Altered levels of 6 metabolites (glucose, acetate, acetoacetate, β-hydroxybutyrate, pyruvate, arginine) in blood plasma and two metabolites (succinate and aminohippurate) in urine were observed in PCeD compared to HC. The PLS-DA model built on the concentration of blood plasma showed separate clustering for PCeD and CeD patients.

CONCLUSION

Altered metabolic profile of PCeD suggested that gluten intolerance was evident at the metabolic level before the intestinal damage. Altered energy metabolism and lower cytoprotective activity (histidine, glycine, arginine) indicated vulnerability to develop intestinal inflammation in PCeD over time. Our study may provide an insight into early biochemical processes of the progression of PCeD to CeD.

Altered Metabolic Profiles of the Plasma of Patients with Amyotrophic Lateral Sclerosis

Currently, there is no objective biomarker to indicate disease progression and monitor therapeutic effects for amyotrophic lateral sclerosis (ALS). This study aimed to identify plasma biomarkers for ALS using a targeted metabolomics approach. Plasma levels of 185 metabolites in 36 ALS patients and 36 age- and sex-matched normal controls (NCs) were quantified using an assay combining liquid chromatography with tandem mass spectrometry and direct flow injection. Identified candidates were correlated with the scores of the revised ALS Functional Rating Scale (ALSFRS-r). Support vector machine (SVM) learning applied to selected metabolites was used to differentiate ALS and NC subjects. Forty-four metabolites differed significantly between ALS and NC subjects. Significant correlations with ALSFRS-r score were seen in 23 metabolites. Six of them showing potential to distinguish ALS from NC-asymmetric dimethylarginine (area under the curve (AUC): 0.829), creatinine (AUC: 0.803), methionine (AUC: 0.767), PC-acyl-alkyl C34:2 (AUC: 0.808), C34:2 (AUC: 0.763), and PC-acyl-acyl C42:2 (AUC: 0.751)-were selected for machine learning. The SVM algorithm using selected metabolites achieved good performance, with an AUC of 0.945. In conclusion, our findings indicate that a panel of metabolites were correlated with disease severity of ALS, which could be potential biomarkers for monitoring ALS progression and therapeutic effects.

Gh BF, Taherkhani A, Rostami-Nejad M, Asri N, Haidari MH. Screening of Altered Metabolites and Metabolic Pathways in Celiac Disease Using NMR Spectroscopy

BACKGROUND

Celiac disease (CeD) is an autoimmune intestinal disorder caused by gluten protein consumption in genetically predisposed individuals. As biopsy sampling is an invasive procedure, finding novel noninvasive serological markers for screening of at-risk CeD population is a priority. Metabolomics is helpful in monitoring metabolite changes in body fluids and tissues. In the present study, we evaluated serum metabolite levels of CeD patients relative to healthy controls with the aim of introducing new biomarkers for population screening.

METHOD

We compared the serum metabolic profile of CeD patients (n = 42) and healthy controls (n = 22) using NMR spectroscopy and multivariate analysis.

RESULT

25 metabolites were identified by serum metabolic profiling. Levels of 3-hydroxyisobutyric acid and isobutyrate showed significant differences in CeD patients' samples compared with healthy controls (p < 0.05). According to pathway analysis, our data demonstrated that changes in nine metabolic pathways were significantly disrupted/affected in patients with CeD. These enriched pathways are involved in aminoacyl-tRNA biosynthesis; primary bile acid biosynthesis; nitrogen metabolism; glutamine and glutamate metabolism; valine, leucine, and isoleucine biosynthesis and degradation; taurine and hypotaurine metabolism; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and arginine biosynthesis.

CONCLUSION

In summary, our results demonstrated that changes in the serum level of 25 metabolites may be useful in distinguishing CeD patients from healthy controls, which have the potential to be considered candidate biomarkers of CeD.

Nutrient Effects on Motor Neurons and the Risk of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is an incurable chronic progressive neurodegenerative disease with the progressive degeneration of motor neurons in the motor cortex and lower motor neurons in the spinal cord and the brain stem. The etiology and pathogenesis of ALS are being actively studied, but there is still no single concept. The study of ALS risk factors can help to understand the mechanism of this disease development and, possibly, slow down the rate of its progression in patients and also reduce the risk of its development in people with a predisposition toward familial ALS. The interest of researchers and clinicians in the protective role of nutrients in the development of ALS has been increasing in recent years. However, the role of some of them is not well-understood or disputed. The objective of this review is to analyze studies on the role of nutrients as environmental factors affecting the risk of developing ALS and the rate of motor neuron degeneration progression.

METHODS

We searched the PubMed, Springer, Clinical keys, Google Scholar, and E-Library databases for publications using keywords and their combinations. We analyzed all the available studies published in 2010-2020.

DISCUSSION

We analyzed 39 studies, including randomized clinical trials, clinical cases, and meta-analyses, involving ALS patients and studies on animal models of ALS. This review demonstrated that the following vitamins are the most significant protectors of ALS development: vitamin B12, vitamin E > vitamin C > vitamin B1, vitamin B9 > vitamin D > vitamin B2, vitamin B6 > vitamin A, and vitamin B7. In addition, this review indicates that the role of foods with a high content of cholesterol, polyunsaturated fatty acids, urates, and purines plays a big part in ALS development.

CONCLUSION

The inclusion of vitamins and a ketogenic diet in disease-modifying ALS therapy can reduce the progression rate of motor neuron degeneration and slow the rate of disease progression, but the approach to nutrient selection must be personalized. The roles of vitamins C, D, and B7 as ALS protectors need further study.

Radicava/Edaravone Findings in Biomarkers From Amyotrophic Lateral Sclerosis (REFINE-ALS): Protocol and Study Design

Objectives

To identify putative biomarkers that may serve as quantifiable, biological, nonclinical measures of the pharmacodynamic effect of edaravone in amyotrophic lateral sclerosis (ALS) and to report real-world treatment outcomes.

Methods

This is a prospective, observational, longitudinal, multicenter (up to 40 sites) US study (Clinicaltrials.gov; NCT04259255) with at least 200 patients with ALS who will receive edaravone for 24 weeks (6 cycles; Food and Drug Administration-approved regimen). All participants must either be treatment naive for edaravone or be more than 1 month without receiving any edaravone dose before screening. Biomarker quantification and other assessments will be performed at baseline (before cycle 1) and during cycles 1, 3, and 6. Selected biomarkers of oxidative stress, inflammation, neuronal injury and death, and muscle injury, as well as biomarker discovery panels (EpiSwitch and SOMAscan), will be evaluated and, when feasible, compared with biobanked samples. Clinical efficacy assessments will include the ALS Functional Rating Scale-Revised, King's clinical staging, ALS Assessment Questionnaire-40, Appel ALS Score (Rating Scale), slow vital capacity, hand-held dynamometry and grip strength, and time to specified states of disease progression or death. DNA samples will also be collected for potential genomic evaluation. The predicted rates of progression and survival, and their potential correlations with biomarkers, will be evaluated. Adverse events related to the study will be reported.

Results

The study is estimated to be completed in 2022 with an interim analysis planned.

Conclusions

Findings may help to further the understanding of the pharmacodynamic effect of edaravone, including changes in biomarkers, in response to treatment.

ALSUntangled #62: vitamin C

Vitamin C is one of the most common supplements taken by people with ALS. As an antioxidant, it has a plausible mechanism for slowing disease progression and there are some flawed pre-clinical studies and case reports suggesting benefit. However, a small human trial showed no benefit. Given this negative trial, we do not currently advise vitamin C as an ALS treatment.

Some CSF Kynurenine Pathway Intermediates Associated with Disease Evolution in Amyotrophic Lateral Sclerosis

The aim of this study was to evaluate the kynurenine pathway (KP) and amino acids profile, using mass spectrometry, in the cerebrospinal fluid (CSF) of 42 amyotrophic lateral sclerosis (ALS) patients at the diagnosis and 40 controls to detect early disorders of these pathways. Diagnostic and predictive ability (based on weight loss, forced vital capacity, ALS Functional Rating Scale-Revised evolution over 12 months, and survival time) of these metabolites were evaluated using univariate followed by supervised multivariate analysis. The multivariate model between ALS and controls was not significant but highlighted some KP metabolites (kynurenine (KYN), kynurenic acid (KYNA), 3-Hydroxynurenine (3-HK)/KYNA ratio), and amino acids (Lysine, asparagine) as involved in the discrimination between groups (accuracy 62%). It revealed a probable KP impairment toward neurotoxicity in ALS patients and in bulbar forms. Regarding the prognostic effect of metabolites, 12 were commonly discriminant for at least 3 of 4 disease evolution criteria. This investigation was crucial as it did not show significant changes in CSF concentrations of amino acids and KP intermediates in early ALS evolution. However, trends of KP modifications suggest further exploration. The unclear kinetics of neuroinflammation linked to KP support the interest in exploring these pathways during disease evolution through a longitudinal strategy.

Application of a bioinformatic pipeline to RNA-seq data identifies novel viruslike sequence in human blood

Numerous reports have suggested that infectious agents could play a role in neurodegenerative diseases, but specific etiological agents have not been convincingly demonstrated. To search for candidate agents in an unbiased fashion, we have developed a bioinformatic pipeline that identifies microbial sequences in mammalian RNA-seq data, including sequences with no significant nucleotide similarity hits in GenBank. Effectiveness of the pipeline was tested using publicly available RNA-seq data and in a reconstruction experiment using synthetic data. We then applied this pipeline to a novel RNA-seq dataset generated from a cohort of 120 samples from amyotrophic lateral sclerosis patients and controls, and identified sequences corresponding to known bacteria and viruses, as well as novel virus-like sequences. The presence of these novel virus-like sequences, which were identified in subsets of both patients and controls, were confirmed by quantitative RT-PCR. We believe this pipeline will be a useful tool for the identification of potential etiological agents in the many RNA-seq datasets currently being generated.

Importance of lipids for upper motor neuron health and disease

Building evidence reveals the importance of maintaining lipid homeostasis for the health and function of neurons, and upper motor neurons (UMNs) are no exception. UMNs are critically important for the initiation and modulation of voluntary movement as they are responsible for conveying cerebral cortex' input to spinal cord targets. To maintain their unique cytoarchitecture with a prominent apical dendrite and a very long axon, UMNs require a stable cell membrane, a lipid bilayer. Lipids can act as building blocks for many biomolecules, and they also contribute to the production of energy. Therefore, UMNs require sustained control over the production, utilization and homeostasis of lipids. Perturbations of lipid homeostasis lead to UMN vulnerability and progressive degeneration in diseases such as hereditary spastic paraplegia (HSP) and primary lateral sclerosis (PLS). Here, we discuss the importance of lipids, especially for UMNs.

Untargeted metabolomics yields insight into ALS disease mechanisms

OBJECTIVE

To identify dysregulated metabolic pathways in amyotrophic lateral sclerosis (ALS) versus control participants through untargeted metabolomics.

METHODS

Untargeted metabolomics was performed on plasma from ALS participants (n=125) around 6.8 months after diagnosis and healthy controls (n=71). Individual differential metabolites in ALS cases versus controls were assessed by Wilcoxon rank-sum tests, adjusted logistic regression and partial least squares-discriminant analysis (PLS-DA), while group lasso explored sub-pathway-level differences. Adjustment parameters included sex, age and body mass index (BMI). Metabolomics pathway enrichment analysis was performed on metabolites selected by the above methods. Finally, machine learning classification algorithms applied to group lasso-selected metabolites were evaluated for classifying case status.

RESULTS

There were no group differences in sex, age and BMI. Significant metabolites selected were 303 by Wilcoxon, 300 by logistic regression, 295 by PLS-DA and 259 by group lasso, corresponding to 11, 13, 12 and 22 enriched sub-pathways, respectively. 'Benzoate metabolism', 'ceramides', 'creatine metabolism', 'fatty acid metabolism (acyl carnitine, polyunsaturated)' and 'hexosylceramides' sub-pathways were enriched by all methods, and 'sphingomyelins' by all but Wilcoxon, indicating these pathways significantly associate with ALS. Finally, machine learning prediction of ALS cases using group lasso-selected metabolites achieved the best performance by regularised logistic regression with elastic net regularisation, with an area under the curve of 0.98 and specificity of 83%.

CONCLUSION

In our analysis, ALS led to significant metabolic pathway alterations, which had correlations to known ALS pathomechanisms in the basic and clinical literature, and may represent important targets for future ALS therapeutics.

Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders

There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.

The role of lipids in the central nervous system and their pathological implications in amyotrophic lateral sclerosis

Lipids play an important role in the central nervous system (CNS). They contribute to the structural integrity and physical characteristics of cell and organelle membranes, act as bioactive signalling molecules, and are utilised as fuel sources for mitochondrial metabolism. The intricate homeostatic mechanisms underpinning lipid handling and metabolism across two major CNS cell types; neurons and astrocytes, are integral for cellular health and maintenance. Here, we explore the various roles of lipids in these two cell types. Given that changes in lipid metabolism have been identified in a number of neurodegenerative diseases, we also discuss changes in lipid handling and utilisation in the context of amyotrophic lateral sclerosis (ALS), in order to identify key cellular processes affected by the disease, and inform future areas of research.

Defining novel functions for cerebrospinal fluid in ALS pathophysiology

Despite the considerable progress made towards understanding ALS pathophysiology, several key features of ALS remain unexplained, from its aetiology to its epidemiological aspects. The glymphatic system, which has recently been recognised as a major clearance pathway for the brain, has received considerable attention in several neurological conditions, particularly Alzheimer's disease. Its significance in ALS has, however, been little addressed. This perspective article therefore aims to assess the possibility of CSF contribution in ALS by considering various lines of evidence, including the abnormal composition of ALS-CSF, its toxicity and the evidence for impaired CSF dynamics in ALS patients. We also describe a potential role for CSF circulation in determining disease spread as well as the importance of CSF dynamics in ALS neurotherapeutics. We propose that a CSF model could potentially offer additional avenues to explore currently unexplained features of ALS, ultimately leading to new treatment options for people with ALS.

Abnormalities in metabolic pathways in celiac disease investigated by the metabolic profiling of small intestinal mucosa, blood plasma and urine by NMR spectroscopy

Celiac disease (CeD) is an autoimmune enteropathy caused by gluten intake in genetically predisposed individuals. We investigated the metabolism of CeD by metabolic profiling of intestinal mucosa, blood plasma and urine using NMR spectroscopy and multivariate analysis. The metabolic profile of the small intestinal mucosa was compared between patients with CeD (n = 64) and disease controls (DCs, n = 30). The blood plasma and urinary metabolomes of CeD patients were compared with healthy controls (HCs, n = 39). Twelve metabolites (proline (Pro), arginine (Arg), glycine (Gly), histidine (His), glutamate (Glu), aspartate, tryptophan (Trp), fumarate, formate, succinate (Succ), glycerophosphocholine (GPC) and allantoin (Alln)) of intestinal mucosa differentiated CeD from controls. The metabolome of blood plasma with 18 metabolites (Pro, Arg, Gly, alanine, Glu, glutamine, glucose (Glc), lactate (Lac), acetate (Ace), acetoacetate (AcAc), β-hydroxybutyrate (β-OHB), pyruvate (Pyr), Succ, citrate (Cit), choline (Cho), creatine (Cr), phosphocreatine (PCr) and creatinine) and 9 metabolites of urine (Pro, Trp, β-OHB, Pyr, Succ, N-methylnicotinamide (NMN), aminohippurate (AHA), indoxyl sulfate (IS) and Alln) distinguished CeD from HCs. Our data demonstrated changes in nine metabolic pathways. The altered metabolites were associated with increased oxidative stress (Alln), impaired healing and repair mechanisms (Pro, Arg), compromised anti-inflammatory and cytoprotective processes (Gly, His, NMN), altered energy metabolism (Glc, Lac, β-OHB, Ace, AcAc, Pyr, Succ, Cit, Cho, Cr and PCr), impaired membrane metabolism (GPC and Cho) and intestinal dysbiosis (AHA and IS). An orthogonal partial least square discriminant analysis model provided clear differentiation between patients with CeD and controls in all three specimens. A classification model built by combining the distinguishing metabolites of blood plasma and urine samples gave an AUC of 0.99 with 97.7% sensitivity, 93.3% specificity and a predictive accuracy of 95.1%, which was higher than for the models built separately using small intestinal mucosa, blood plasma and urine. In conclusion, a panel of metabolic biomarkers in intestinal biopsies, plasma and urine samples has potential to differentiate CeD from controls and may complement traditional tests to improve the diagnosis of CeD.

Pursuing Experimental Reproducibility: An Efficient Protocol for the Preparation of Cerebrospinal Fluid Samples for NMR-based Metabolomics and Analysis of Sample Degradation

NMR-based metabolomics investigations of human biofluids offer great potential to uncover new biomarkers. In contrast to protocols for sample collection and biobanking, procedures for sample preparation prior to NMR measurements are still heterogeneous, thus compromising the comparability of the resulting data. Herein, we present results of an investigation of the handling of cerebrospinal fluid (CSF) samples for NMR metabolomics research. Origins of commonly observed problems when conducting NMR experiments on this type of sample are addressed, and suitable experimental conditions in terms of sample preparation and pH control are discussed. Sample stability was assessed by monitoring the degradation of CSF samples by NMR, hereby identifying metabolite candidates, which are potentially affected by sample storage. A protocol was devised yielding consistent spectroscopic data as well as achieving overall sample stability for robust analysis. We present easy to adopt standard operating procedures with the aim to establish a shared sample handling strategy that facilitates and promotes inter-laboratory comparison, and the analysis of sample degradation provides new insights into sample stability.

Therapeutic alternative of the ketogenic Mediterranean diet to improve mitochondrial activity in Amyotrophic Lateral Sclerosis (ALS): A Comprehensive Review

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease which is pathogenically based on the mitochondrial alteration of motor neurons, causing progressive neuron death. While ALS is characterized by enormous oxidative stress, the Mediterranean diet has been seen to have high antioxidant power. Therefore, the aim of this study is to determine how the Mediterranean diet can improve mitochondrial activity, establishing the specific nutrients and, in addition, observing the pathogenic mechanisms related to the disease that would achieve this improvement. To this end, a comprehensive review of the literature was performed using PubMed. KBs have been observed to have a neuroprotective effect to improve energy balance, increasing survival and the number of motor neurons. This ketogenesis can be achieved after following a Mediterranean diet which is associated with great benefits in other neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and ALS. These benefits are due to the high antioxidant power especially based on polyphenols contained mainly in olive oil, wine, nuts, or berries. In short, KBs could be considered as a promising option to treat ALS, representing an alternative source to glucose in motor neurons by providing neuroprotection. In addition, treatment results can be improved as ketogenesis can be achieved (increase in KBs) by following a Mediterranean diet, thanks to the high antioxidant properties which, at the same time, would improve the high oxidative stress that characterizes the disease.

Transcriptomics and Metabolomics in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease involving progressive and selective loss of motor neurons, muscle weakness, paralysis and death. The pathogenesis of ALS is not clearly understood, while reliable prognostic markers have not been identified to detect symptoms at earlier time points. The rapid development of microarray technology offers great potential for simultaneous analysis of the transcriptional expression of thousands of genes, aiming to determine novel candidate targets for efficient treatment. Additionally, metabolomics, as a high-throughput approach, is gaining significant attention in ALS research providing an opportunity to develop predictive biomarkers that may be utilized as indicators of clinical symptoms of ALS. In this review, recent evidences from gene expression profiling studies in ALS are illustrated in order to examine molecular signatures related to the disease's pathogenesis and potential discovery of therapeutic targets. Moreover, potent challenges are presented regarding the utilization of the metabolomics approach as a diagnostic tool in context with distinctive biomarkers' identification.

Existing and Emerging Metabolomic Tools for ALS Research

Growing evidence suggests that aberrant energy metabolism could play an important role in the pathogenesis of amyotrophic lateral sclerosis (ALS). Despite this, studies applying advanced technologies to investigate energy metabolism in ALS remain scarce. The rapidly growing field of metabolomics offers exciting new possibilities for ALS research. Here, we review existing and emerging metabolomic tools that could be used to further investigate the role of metabolism in ALS. A better understanding of the metabolic state of motor neurons and their surrounding cells could hopefully result in novel therapeutic strategies.

C9orf72 expansion within astrocytes reduces metabolic flexibility in amyotrophic lateral sclerosis

It is important to understand how the disease process affects the metabolic pathways in amyotrophic lateral sclerosis and whether these pathways can be manipulated to ameliorate disease progression. To analyse the basis of the metabolic defect in amyotrophic lateral sclerosis we used a phenotypic metabolic profiling approach. Using fibroblasts and reprogrammed induced astrocytes from C9orf72 and sporadic amyotrophic lateral sclerosis cases we measured the production rate of reduced nicotinamide adenine dinucleotides (NADH) from 91 potential energy substrates simultaneously. Our screening approach identified that C9orf72 and sporadic amyotrophic lateral sclerosis induced astrocytes have distinct metabolic profiles compared to controls and displayed a loss of metabolic flexibility that was not observed in fibroblast models. This loss of metabolic flexibility, involving defects in adenosine, fructose and glycogen metabolism, as well as disruptions in the membrane transport of mitochondrial specific energy substrates, contributed to increased starvation induced toxicity in C9orf72 induced astrocytes. A reduction in glycogen metabolism was attributed to loss of glycogen phosphorylase and phosphoglucomutase at the protein level in both C9orf72 induced astrocytes and induced neurons. In addition, we found alterations in the levels of fructose metabolism enzymes and a reduction in the methylglyoxal removal enzyme GLO1 in both C9orf72 and sporadic models of disease. Our data show that metabolic flexibility is important in the CNS in times of bioenergetic stress.

Prognostic analysis of amyotrophic lateral sclerosis based on clinical features and plasma surface-enhanced Raman spectroscopy

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with a wide range of survival times. We aimed to explore prognostic factors related to short survival based on clinical features and plasma metabolic signatures using surface-enhanced Raman spectroscopy (SERS). One hundred and thirty-eight sporadic ALS cases were enrolled serially, including 62 for the short-duration group (≤3 years) and 76 for the long-duration group (>3 years). Multivariate analysis showed that an older age of onset (>60 years; odds ratio [OR] = 3.98, 95% CI: 1.09-14.53), lower body mass index (BMI) (<18.5; OR = 6.80, 95% CI: 1.36-33.92), and lower ALSFRS-R score (<35; OR = 6.03, 95% CI: 1.42-25.63) were associated with higher odds of tracheotomy or death, while a higher uric acid (UA) level showed a protective effect (>356.36 μmol/L; OR = 0.19, 95% CI: 0.05-0.73). SERS analysis showed significant differences between the two groups, and pathway analysis highlighted five main metabolic pathways, including metabolisms of glutathione, pyrimidine, phenylalanine, galactose, and phenylalanine-tyrosine-tryptophan biosynthesis. In conclusion, age of onset, BMI, ALSFRS-R score and UA, together with dysregulation of glucose, amino acid, nucleic acid, and antioxidant metabolism contributed to disease progression, and are therefore potential therapeutic targets for ALS.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

Metabolic and Stress Response Changes Precede Disease Onset in the Spinal Cord of Mutant SOD1 ALS Mice

Many Amyotrophic Lateral Sclerosis (ALS) patients experience hypermetabolism, or an increase in measured vs. calculated metabolic rate. The cause of hypermetabolism and the effects on neuronal metabolism in ALS are currently unknown, but the efficacy of dietary interventions shows promise for metabolism as an ALS therapeutic target. The goal of this study is to measure changes in metabolic pathways as a function of disease progression in spinal cords of the SOD1^G93A mouse model of ALS. We conducted a comprehensive assessment of protein expression for metabolic pathways, antioxidants, chaperones, and proteases in lumbar spinal cord from male SOD1^G93A mice at pre-onset, onset, and end-stages of the disease using targeted proteomic analysis. These results reveal that protein content of metabolic proteins including proteins involved in glycolysis, β-oxidation, and mitochondrial metabolism is altered in SOD1^G93A mouse spinal cord well before disease onset. The changes in mitochondrial metabolism proteins are associated with decreased maximal respiration and glycolytic flux in SOD1^G93A dermal fibroblasts and increased hydrogen peroxide and lipid hydroperoxide production in mitochondria from sciatic nerve and gastrocnemius muscle fibers at end stage of disease. Consistent with redox dysregulation, expression of the glutathione antioxidant system is decreased, and peroxiredoxins and catalase expression are increased. In addition, stress response proteases and chaperones, including those involved in the mitochondrial unfolded protein response (UPR^mt), are induced before disease onset. In summary, we report that metabolic and stress response changes occur in SOD1^G93A lumbar spinal cord before motor symptom onset, and are primarily caused by SOD1^G93A expression and do not vary greatly as a function of disease course.

A Systematic Review of Suggested Molecular Strata, Biomarkers and Their Tissue Sources in ALS

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is an incurable neurodegenerative condition, characterized by the loss of upper and lower motor neurons. It affects 1–1.8/100,000 individuals worldwide, and the number of cases is projected to increase as the population ages. Thus, there is an urgent need to identify both therapeutic targets and disease-specific biomarkers–biomarkers that would be useful to diagnose and stratify patients into different sub-groups for therapeutic strategies, as well as biomarkers to follow the efficacy of any treatment tested during clinical trials. There is a lack of knowledge about pathogenesis and many hypotheses. Numerous “omics” studies have been conducted on ALS in the past decade to identify a disease-signature in tissues and circulating biomarkers. The first goal of the present review was to group the molecular pathways that have been implicated in monogenic forms of ALS, to enable the description of patient strata corresponding to each pathway grouping. This strategy allowed us to suggest 14 strata, each potentially targetable by different pharmacological strategies. The second goal of this review was to identify diagnostic/prognostic biomarker candidates consistently observed across the literature. For this purpose, we explore previous biomarker-relevant “omics” studies of ALS and summarize their findings, focusing on potential circulating biomarker candidates. We systematically review 118 papers on biomarkers published during the last decade. Several candidate markers were consistently shared across the results of different studies in either cerebrospinal fluid (CSF) or blood (leukocyte or serum/plasma). Although these candidates still need to be validated in a systematic manner, we suggest the use of combinations of biomarkers that would likely reflect the “health status” of different tissues, including motor neuron health (e.g., pNFH and NF-L, cystatin C, Transthyretin), inflammation status (e.g., MCP-1, miR451), muscle health (miR-338-3p, miR-206) and metabolism (homocysteine, glutamate, cholesterol). In light of these studies and because ALS is increasingly perceived as a multi-system disease, the identification of a panel of biomarkers that accurately reflect features of pathology is a priority, not only for diagnostic purposes but also for prognostic or predictive applications.

Metabolomics toward personalized medicine

Metabolomics, which is the metabolites profiling in biological matrices, is a key tool for biomarker discovery and personalized medicine and has great potential to elucidate the ultimate product of the genomic processes. Over the last decade, metabolomics studies have identified several relevant biomarkers involved in complex clinical phenotypes using diverse biological systems. Most diseases result in signature metabolic profiles that reflect the sums of external and internal cellular activities. Metabolomics has a major role in clinical practice as it represents >95% of the workload in clinical laboratories worldwide. Many of these metabolites require different analytical platforms, such as Nuclear Magnetic Resonance (NMR), Mass Spectrometry (MS), and Ultra Performance Liquid Chromatography (UPLC), while many clinically relevant metabolites are still not routinely amenable to detection using currently available assays. Combining metabolomics with genomics, transcriptomics, and proteomics studies will result in a significantly improved understanding of the disease mechanisms and the pathophysiology of the target clinical phenotype. This comprehensive approach will represent a major step forward toward providing precision medical care, in which individual is accounted for variability in genes, environment, and personal lifestyle. In this review, we compare and evaluate the metabolomics strategies and studies that focus on the discovery of biomarkers that have "personalized" diagnostic, prognostic, and therapeutic value, validated for monitoring disease progression and responses to various management regimens.

Biomarkers in Motor Neuron Disease: A State of the Art Review

Motor neuron disease can be viewed as an umbrella term describing a heterogeneous group of conditions, all of which are relentlessly progressive and ultimately fatal. The average life expectancy is 2 years, but with a broad range of months to decades. Biomarker research deepens disease understanding through exploration of pathophysiological mechanisms which, in turn, highlights targets for novel therapies. It also allows differentiation of the disease population into sub-groups, which serves two general purposes: (a) provides clinicians with information to better guide their patients in terms of disease progression, and (b) guides clinical trial design so that an intervention may be shown to be effective if population variation is controlled for. Biomarkers also have the potential to provide monitoring during clinical trials to ensure target engagement. This review highlights biomarkers that have emerged from the fields of systemic measurements including biochemistry (blood, cerebrospinal fluid, and urine analysis); imaging and electrophysiology, and gives examples of how a combinatorial approach may yield the best results. We emphasize the importance of systematic sample collection and analysis, and the need to correlate biomarker findings with detailed phenotype and genotype data.

Prediagnostic plasma metabolomics and the risk of amyotrophic lateral sclerosis

OBJECTIVE

To identify prediagnostic plasma metabolomic biomarkers associated with amyotrophic lateral sclerosis (ALS).

METHODS

We conducted a global metabolomic study using a nested case-control study design within 5 prospective cohorts and identified 275 individuals who developed ALS during follow-up. We profiled plasma metabolites using liquid chromatography-mass spectrometry and identified 404 known metabolites. We used conditional logistic regression to evaluate the associations between metabolites and ALS risk. Further, we used machine learning analyses to determine whether the prediagnostic metabolomic profile could discriminate ALS cases from controls.

RESULTS

A total of 31 out of 404 identified metabolites were associated with ALS risk (p < 0.05). We observed inverse associations (n = 27) with plasma levels of diacylglycerides and triacylglycerides, urate, purine nucleosides, and some organic acids and derivatives, while we found positive associations for a cholesteryl ester, 2 phosphatidylcholines, and a sphingomyelin. The number of significant associations increased to 67 (63 inverse) in analyses restricted to cases with blood samples collected within 5 years of onset. None of these associations remained significant after multiple comparison adjustment. Further, we were not able to reliably distinguish individuals who became cases from controls based on their metabolomic profile using partial least squares discriminant analysis, elastic net regression, random forest, support vector machine, or weighted correlation network analyses.

CONCLUSIONS

Although the metabolomic profile in blood samples collected years before ALS diagnosis did not reliably separate presymptomatic ALS cases from controls, our results suggest that ALS is preceded by a broad, but poorly defined, metabolic dysregulation years before the disease onset.

Biomarkers of Metabolism in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by the deterioration of motor neurons. However, this complex disease extends beyond the boundaries of the central nervous system, with metabolic alterations being observed at the systemic and cellular level. While the number of studies that assess the role and impact of metabolic perturbations in ALS is rapidly increasing, the use of metabolism biomarkers in ALS remains largely underinvestigated. In this review, we discuss current and potential metabolism biomarkers in the context of ALS. Of those for which data does exist, there is limited insight provided by individual markers, with specificity for disease, and lack of reproducibility and efficacy in informing prognosis being the largest drawbacks. However, given the array of metabolic markers available, the potential exists for a panel of metabolism biomarkers, which may complement other current biomarkers (including neurophysiology, imaging, as well as CSF, blood and urine markers) to overturn these limitations and give rise to new diagnostic and prognostic indicators.

Metabolomics Biomarkers: A Strategy Toward Therapeutics Improvement in ALS

Biomarkers research in amyotrophic lateral sclerosis (ALS) holds the promise of improving ALS diagnosis, follow-up of patients, and clinical trials outcomes. Metabolomics have a big impact on biomarkers identification. In this mini-review, we provide the main findings of metabolomics studies in ALS and discuss the most relevant therapeutics attempts that targeted some prominent alterations found in ALS, like glutamate excitotoxicity, oxidative stress, alterations in energetic metabolism, and creatinine levels. Metabolomics studies have reported putative diagnosis or prognosis biomarkers, but discrepancies among these studies did not allow validation of metabolic biomarkers for clinical use in ALS. In this context, we wonder whether metabolomics knowledge could improve ALS therapeutics. As metabolomics identify specific metabolic pathways modified by disease progression and/or treatment, we support that adjuvant or combined treatment should be used to rescue these pathways, creating a new perspective for ALS treatment. Some ongoing clinical trials are already trying to target these pathways. As clinical trials in ALS have been disappointing and considering the heterogeneity of the disease presentation, we support the application of a pharmacometabolomic approach to evaluate the individual response to drug treatments and their side effects, enabling the development of personalized treatments for ALS. We suggest that the best strategy to apply metabolomics for ALS therapeutics progress is to establish a metabolic signature for ALS patients in order to improve the knowledge of patient metabotypes, to choose the most adequate pharmacological treatment, and to follow the drug response and side effects, based on metabolomics biomarkers.

Personalized Medicine and Molecular Interaction Networks in Amyotrophic Lateral Sclerosis (ALS): Current Knowledge

Multiple genes and mechanisms of pathophysiology have been implicated in amyotrophic lateral sclerosis (ALS), suggesting it is a complex systemic disease. With this in mind, applying personalized medicine (PM) approaches to tailor treatment pipelines for ALS patients may be necessary. The modelling and analysis of molecular interaction networks could represent valuable resources in defining ALS-associated pathways and discovering novel therapeutic targets. Here we review existing omics datasets and analytical approaches, in order to consider how molecular interaction networks could improve our understanding of the molecular pathophysiology of this fatal neuromuscular disorder.

Medium-Chain Fatty Acids, Beta-Hydroxybutyric Acid and Genetic Modulation of the Carnitine Shuttle Are Protective in a Drosophila Model of ALS Based on TDP-43

ALS patients exhibit dyslipidemia, hypermetabolism and weight loss; in addition, cellular energetics deficits have been detected prior to denervation. Although evidence that metabolism is altered in ALS is compelling, the mechanisms underlying metabolic dysregulation and the contribution of altered metabolic pathways to disease remain poorly understood. Here we use a Drosophila model of ALS based on TDP-43 that recapitulates hallmark features of the disease including locomotor dysfunction and reduced lifespan. We performed a global, unbiased metabolomic profiling of larvae expressing TDP-43 (wild-type, TDP^WT or disease-associated mutant, TDP^G298S) and identified several lipid metabolism associated alterations. Among these, we found a significant increase in carnitine conjugated long-chain fatty acids and a significant decrease in carnitine, acetyl-carnitine and beta-hydroxybutyrate, a ketone precursor. Taken together these data suggest a deficit in the function of the carnitine shuttle and reduced lipid beta oxidation. To test this possibility we used a combined genetic and dietary approach in Drosophila. Our findings indicate that components of the carnitine shuttle are misexpressed in the context of TDP-43 proteinopathy and that genetic modulation of CPT1 or CPT2 expression, two core components of the carnitine shuttle, mitigates TDP-43 dependent locomotor dysfunction, in a variant dependent manner. In addition, feeding medium-chain fatty acids or beta-hydroxybutyrate improves locomotor function, consistent with the notion that bypassing the carnitine shuttle deficit is neuroprotective. Taken together, our findings highlight the potential contribution of the carnitine shuttle and lipid beta oxidation in ALS and suggest strategies for therapeutic intervention based on restoring lipid metabolism in motor neurons.

Neuronal Lipid Metabolism: Multiple Pathways Driving Functional Outcomes in Health and Disease

Lipids are a fundamental class of organic molecules implicated in a wide range of biological processes related to their structural diversity, and based on this can be broadly classified into five categories; fatty acids, triacylglycerols (TAGs), phospholipids, sterol lipids and sphingolipids. Different lipid classes play major roles in neuronal cell populations; they can be used as energy substrates, act as building blocks for cellular structural machinery, serve as bioactive molecules, or a combination of each. In amyotrophic lateral sclerosis (ALS), dysfunctions in lipid metabolism and function have been identified as potential drivers of pathogenesis. In particular, aberrant lipid metabolism is proposed to underlie denervation of neuromuscular junctions, mitochondrial dysfunction, excitotoxicity, impaired neuronal transport, cytoskeletal defects, inflammation and reduced neurotransmitter release. Here we review current knowledge of the roles of lipid metabolism and function in the CNS and discuss how modulating these pathways may offer novel therapeutic options for treating ALS.

Thallium stimulates ethanol production in immortalized hippocampal neurons

Lactate and ethanol (EtOH) were determined in cell culture medium (CCM) of immortalized hippocampal neurons (HN9.10e cell line) before and after incubation with Thallium (Tl). This cell line is a reliable, in vitro model of one of the most vulnerable regions of central nervous system. Cells were incubated for 48 h with three different single Tl doses: 1, 10, 100 μg/L (corresponding to 4.9, 49 and 490 nM, respectively). After 48 h, neurons were "reperfused" with fresh CCM every 24/48 h until 7 days after the treatment and the removed CCM was collected and analysed. Confocal microscopy was employed to observe morphological changes. EtOH was determined by head space-solid phase microextraction -gas chromatography -mass spectrometry (HS-SPME-GCMS), lactate by RP-HPLC with UV detection. Tl exposure had significant effects on neuronal growth rate and morphology. The damage degree was dose-dependent. In not exposed cells, EtOH concentration was 0.18 ± 0.013 mM, which represents about 5% of lactate concentration (3.4 ± 0.10 mM). After Tl exposure lactate and EtOH increased. In CCM of 100 and 10 μg/L Tl-treated cells, lactate increased 24 h after reperfusion up to 2 and 3.3 times the control value, respectively. In CCM of 10 and 100 μg/L Tl-treated cells 24 h after reperfusion, EtOH increased up to 0.3 and 0.58 mmol/L. respectively. These results are consistent with significant alterations in energy metabolism, despite the low doses of Tl employed and the relatively short incubation time.

Metabolic Biomarkers and Neurodegeneration: A Pathway Enrichment Analysis of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis

Neurodegenerative diseases such as Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS) lack robust diagnostics and prognostic biomarkers. Metabolomics is a postgenomics field that offers fresh insights for biomarkers of common complex as well as rare diseases. Using data on metabolite-disease associations published in the previous decade (2006-2016) in PubMed, ScienceDirect, Scopus, and Web of Science, we identified 101 metabolites as putative biomarkers for these three neurodegenerative diseases. Notably, uric acid, choline, creatine, L-glutamine, alanine, creatinine, and N-acetyl-L-aspartate were the shared metabolite signatures among the three diseases. The disease-metabolite-pathway associations pointed out the importance of membrane transport (through ATP binding cassette transporters), particularly of arginine and proline amino acids in all three neurodegenerative diseases. When disease-specific and common metabolic pathways were queried by using the pathway enrichment analyses, we found that alanine, aspartate, glutamate, and purine metabolism might act as alternative pathways to overcome inadequate glucose supply and energy crisis in neurodegeneration. These observations underscore the importance of metabolite-based biomarker research in deciphering the elusive pathophysiology of neurodegenerative diseases. Future research investments in metabolomics of complex diseases might provide new insights on AD, PD, and ALS that continue to place a significant burden on global health.

Metabolomics As a Tool for the Characterization of Drug-Resistant Epilepsy

Purpose

Drug resistance is a critical issue in the treatment of epilepsy, contributing to clinical emergencies and increasing both serious social and economic burdens on the health system. The wide variety of potential drug combinations followed by often failed consecutive attempts to match drugs to an individual patient may mean that this treatment stage may last for years with suboptimal benefit to the patient. Given these challenges, it is valuable to explore the availability of new methodologies able to shorten the period of determining a rationale pharmacologic treatment. Metabolomics could provide such a tool to investigate possible markers of drug resistance in subjects with epilepsy.

Methods

Blood samples were collected from (1) controls (C) (n = 35), (2) patients with epilepsy “responder” (R) (n = 18), and (3) patients with epilepsy “non-responder” (NR) (n = 17) to the drug therapy. The samples were analyzed using nuclear magnetic resonance spectroscopy, followed by multivariate statistical analysis.

Key findings

A different metabolic profile based on metabolomics analysis of the serum was observed between C and patients with epilepsy and also between R and NR patients. It was possible to identify the discriminant metabolites for the three classes under investigation. Serum from patients with epilepsy were characterized by increased levels of 3-OH-butyrate, 2-OH-valerate, 2-OH-butyrate, acetoacetate, acetone, acetate, choline, alanine, glutamate, scyllo-inositol (C < R < NR), and decreased concentration of glucose, lactate, and citrate compared to C (C > R > NR).

Significance

In conclusion, metabolomics may represent an important tool for discovery of differences between subjects affected by epilepsy responding or resistant to therapies and for the study of its pathophysiology, optimizing the therapeutic resources and the quality of life of patients.

Does Vitamin C Influence Neurodegenerative Diseases and Psychiatric Disorders?

Vitamin C (Vit C) is considered to be a vital antioxidant molecule in the brain. Intracellular Vit C helps maintain integrity and function of several processes in the central nervous system (CNS), including neuronal maturation and differentiation, myelin formation, synthesis of catecholamine, modulation of neurotransmission and antioxidant protection. The importance of Vit C for CNS function has been proven by the fact that targeted deletion of the sodium-vitamin C co-transporter in mice results in widespread cerebral hemorrhage and death on post-natal day one. Since neurological diseases are characterized by increased free radical generation and the highest concentrations of Vit C in the body are found in the brain and neuroendocrine tissues, it is suggested that Vit C may change the course of neurological diseases and display potential therapeutic roles. The aim of this review is to update the current state of knowledge of the role of vitamin C on neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis and amyotrophic sclerosis, as well as psychiatric disorders including depression, anxiety and schizophrenia. The particular attention is attributed to understanding of the mechanisms underlying possible therapeutic properties of ascorbic acid in the presented disorders.

MicroRNA Metabolism and Dysregulation in Amyotrophic Lateral Sclerosis

MicroRNAs (miRNAs) are a subset of endogenous, small, non-coding RNA molecules involved in the post-transcriptional regulation of eukaryotic gene expression. Dysregulation in miRNA-related pathways in the central nervous system (CNS) is associated with severe neuronal injury and cell death, which can lead to the development of neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS). ALS is a fatal adult onset disease characterized by the selective loss of upper and lower motor neurons. While the pathogenesis of ALS is still largely unknown, familial ALS forms linked to TAR DNA-binding protein 43 (TDP-43) and fused in sarcoma (FUS) gene mutations, as well as sporadic forms, display changes in several steps of RNA metabolism, including miRNA processing. Here, we review the current knowledge about miRNA metabolism and biological functions and their crucial role in ALS pathogenesis with an in-depth analysis on different pathways. A more precise understanding of miRNA involvement in ALS could be useful not only to elucidate their role in the disease etiopathogenesis but also to investigate their potential as disease biomarkers and novel therapeutic targets.

Defective cholesterol metabolism in amyotrophic lateral sclerosis

As neurons die, cholesterol is released in the central nervous system (CNS); hence, this sterol and its metabolites may represent a biomarker of neurodegeneration, including in amyotrophic lateral sclerosis (ALS), in which altered cholesterol levels have been linked to prognosis. More than 40 different sterols were quantified in serum and cerebrospinal fluid (CSF) from ALS patients and healthy controls. In CSF, the concentration of cholesterol was found to be elevated in ALS samples. When CSF metabolite levels were normalized to cholesterol, the cholesterol metabolite 3β,7α-dihydroxycholest-5-en-26-oic acid, along with its precursor 3β-hydroxycholest-5-en-26-oic acid and product 7α-hydroxy-3-oxocholest-4-en-26-oic acid, were reduced in concentration, whereas metabolites known to be imported from the circulation into the CNS were not found to differ in concentration between groups. Analysis of serum revealed that (25R)26-hydroxycholesterol, the immediate precursor of 3β-hydroxycholest-5-en-26-oic acid, was reduced in concentration in ALS patients compared with controls. We conclude that the acidic branch of bile acid biosynthesis, known to be operative in-part in the brain, is defective in ALS, leading to a failure of the CNS to remove excess cholesterol, which may be toxic to neuronal cells, compounded by a reduction in neuroprotective 3β,7α-dihydroxycholest-5-en-26-oic acid.

Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs.

Disruption of TCA Cycle and Glutamate Metabolism Identified by Metabolomics in an In Vitro Model of Amyotrophic Lateral Sclerosis

This study aims to develop a cellular metabolomics model that reproduces the pathophysiological conditions found in amyotrophic lateral sclerosis in order to improve knowledge of disease physiology. We used a co-culture model combining the motor neuron-like cell line NSC-34 and the astrocyte clone C8-D1A, with each over-expressing wild-type or G93C mutant human SOD1, to examine amyotrophic lateral sclerosis (ALS) physiology. We focused on the effects of mutant human SOD1 as well as oxidative stress induced by menadione on intracellular metabolism using a metabolomics approach through gas chromatography coupled with mass spectrometry (GC-MS) analysis. Preliminary non-supervised analysis by Principal Component Analysis (PCA) revealed that cell type, genetic environment, and time of culture influenced the metabolomics profiles. Supervised analysis using orthogonal partial least squares discriminant analysis (OPLS-DA) on data from intracellular metabolomics profiles of SOD1^G93C co-cultures produced metabolites involved in glutamate metabolism and the tricarboxylic acid cycle (TCA) cycle. This study revealed the feasibility of using a metabolomics approach in a cellular model of ALS. We identified potential disruption of the TCA cycle and glutamate metabolism under oxidative stress, which is consistent with prior research in the disease. Analysis of metabolic alterations in an in vitro model is a novel approach to investigation of disease physiology.

The strengths and weaknesses of NMR spectroscopy and mass spectrometry with particular focus on metabolomics research

Mass spectrometry (MS) and nuclear magnetic resonance (NMR) have evolved as the most common techniques in metabolomics studies, and each brings its own advantages and limitations. Unlike MS spectrometry, NMR spectroscopy is quantitative and does not require extra steps for sample preparation, such as separation or derivatization. Although the sensitivity of NMR spectroscopy has increased enormously and improvements continue to emerge steadily, this remains a weak point for NMR compared with MS. MS-based metabolomics provides an excellent approach that can offer a combined sensitivity and selectivity platform for metabolomics research. Moreover, different MS approaches such as different ionization techniques and mass analyzer technology can be used in order to increase the number of metabolites that can be detected. In this chapter, the advantages, limitations, strengths, and weaknesses of NMR and MS as tools applicable to metabolomics research are highlighted.