Metabolomic analysis of serum by (1) H NMR spectroscopy in amyotrophic lateral sclerosis. Clin Chim Acta. 2010;411:563-567. [PMID: 20096678 DOI: 10.1016/j.cca.2010.01.016]

Disturbances in Muscle Energy Metabolism in Patients with Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neuromuscular disease type of motor neuron disorder characterized by degeneration of the upper and lower motor neurons resulting in dysfunction of the somatic muscles of the body. The ALS condition is manifested in progressive skeletal muscle atrophy and spasticity. It leads to death, mostly due to respiratory failure. Within the pathophysiology of the disease, muscle energy metabolism seems to be an important part. In our study, we used blood plasma from 25 patients with ALS diagnosed by definitive El Escorial criteria according to ALSFR-R (Revised Amyotrophic Lateral Sclerosis Functional Rating Scale) criteria and 25 age and sex-matched subjects. Aside from standard clinical biochemical parameters, we used the NMR (nuclear magnetic resonance) metabolomics approach to determine relative plasma levels of metabolites. We observed a decrease in total protein level in blood; however, despite accelerated skeletal muscle catabolism characteristic for ALS patients, we did not detect changes in plasma levels of essential amino acids. When focused on alterations in energy metabolism within muscle, compromised creatine uptake was accompanied by decreased plasma creatinine. We did not observe changes in plasma levels of BCAAs (branched chain amino acids; leucine, isoleucine, valine); however, the observed decrease in plasma levels of all three BCKAs (branched chain alpha-keto acids derived from BCAAs) suggests enhanced utilization of BCKAs as energy substrate. Glutamine, found to be increased in blood plasma in ALS patients, besides serving for ammonia detoxification, could also be considered a potential TCA (tricarboxylic acid) cycle contributor in times of decreased pyruvate utilization. When analyzing the data by using a cross-validated Random Forest algorithm, it finished with an AUC of 0.92, oob error of 8%, and an MCC (Matthew's correlation coefficient) of 0.84 when relative plasma levels of metabolites were used as input variables. Although the discriminatory power of the system used was promising, additional features are needed to create a robust discriminatory model.

Mitochondria: A Promising Convergent Target for the Treatment of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease characterized by the progressive loss of motor neurons, for which current treatment options are limited. Recent studies have shed light on the role of mitochondria in ALS pathogenesis, making them an attractive therapeutic intervention target. This review contains a very comprehensive critical description of the involvement of mitochondria and mitochondria-mediated mechanisms in ALS. The review covers several key areas related to mitochondria in ALS, including impaired mitochondrial function, mitochondrial bioenergetics, reactive oxygen species, metabolic processes and energy metabolism, mitochondrial dynamics, turnover, autophagy and mitophagy, impaired mitochondrial transport, and apoptosis. This review also highlights preclinical and clinical studies that have investigated various mitochondria-targeted therapies for ALS treatment. These include strategies to improve mitochondrial function, such as the use of dichloroacetate, ketogenic and high-fat diets, acetyl-carnitine, and mitochondria-targeted antioxidants. Additionally, antiapoptotic agents, like the mPTP-targeting agents minocycline and rasagiline, are discussed. The paper aims to contribute to the identification of effective mitochondria-targeted therapies for ALS treatment by synthesizing the current understanding of the role of mitochondria in ALS pathogenesis and reviewing potential convergent therapeutic interventions. The complex interplay between mitochondria and the pathogenic mechanisms of ALS holds promise for the development of novel treatment strategies to combat this devastating disease.

GC/MS and LC/MS serum metabolomic analysis of Chinese LN patients

China, being a densely populated nation, faces a substantial economic burden due to a high incidence of lupus nephritis (LN) cases. The concealed onset of LN has resulted in many individuals have missed the optimal timing for treatment. The aim of the research is to study the serum metabolomics of Chinese LN patients using gas chromatography (GC)/mass spectrometry (MS) and liquid chromatography (LC)/MS to identify potential diagnostic markers. Fifty LN patients and fifty normal controls, matched for Body Mass Index (BMI) and age, were selected. Serum analysis was conducted using GC/MS and LC/MS, followed by multivariate statistical analysis. Various multidimensional analyses, including principal component analysis, partial least squares discrimination analysis, and orthogonal partial least squares discrimination analysis, along with one-dimensional analyses such as t-tests, were performed. Metabolites with variable importance in projection value > 1 and a p-value < 0.05 were considered critical biomarkers for LN. Furthermore, identified biomarkers delineated relevant metabolic pathways, and a metabolic pathway map was obtained from the database. Forty-one metabolites were identified as potential LN biomarkers, primarily associated with immune regulation, energy metabolism, intestinal microbial metabolism, renal damage, and oxidative stress. The potential for diagnosing LN and other diseases through metabolomics is demonstrated. Future research should explore larger sample sizes, metabolomic comparisons across different diseases and health states, and integration of metabolomics with clinical diagnostics. Such studies will enhance the understanding of metabolomics in medical diagnosis and provide robust support for its practical application.

Exploring the role of cerebrospinal fluid as analyte in neurologic disorders

The cerebrospinal fluid (CSF) is a clear ultrafiltrate of blood that envelopes and protects the central nervous system while regulating neuronal function through the maintenance of interstitial fluid homeostasis in the brain. Due to its anatomic location and physiological functions, the CSF can provide a reliable source of biomarkers for the diagnosis and treatment monitoring of different neurological diseases, including neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and primary and secondary brain malignancies. The incorporation of CSF biomarkers into the drug discovery and development can improve the efficiency of drug development and increase the chances of success. This review aims to consolidate the current use of CSF biomarkers in clinical practice and explore future perspectives for the field.

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.

Target Metabolites to Slow Down Progression of Amyotrophic Lateral Sclerosis in Mice

Microbial metabolites affect the neuron system and muscle cell functions. Amyotrophic lateral sclerosis (ALS) is a multifactorial neuromuscular disease. Our previous study has demonstrated elevated intestinal inflammation and dysfunction of the microbiome in patients with ALS and an ALS mouse model (human-SOD1^G93A transgenic mice). However, the metabolites in ALS progression are unknown. Using an unbiased global metabolomic measurement and targeted measurement, we investigated the longitudinal changes of fecal metabolites in SOD1^G93A mice over the course of 13 weeks. We further compared the changes of metabolites and inflammatory response in age-matched wild-type (WT) and SOD1^G93A mice treated with the bacterial product butyrate. We found changes in carbohydrate levels, amino acid metabolism, and the formation of gamma-glutamyl amino acids. Shifts in several microbially contributed catabolites of aromatic amino acids agree with butyrate-induced changes in the composition of the gut microbiome. Declines in gamma-glutamyl amino acids in feces may stem from differential expression of gamma-glutamyltransferase (GGT) in response to butyrate administration. Due to the signaling nature of amino acid-derived metabolites, these changes indicate changes in inflammation, e.g., histamine, and contribute to differences in systemic levels of neurotransmitters, e.g., γ-Aminobutyric acid (GABA) and glutamate. Butyrate treatment was able to restore some of the healthy metabolites in ALS mice. Moreover, microglia in the spinal cord were measured by IBA1 staining. Butyrate treatment significantly suppressed the IBA1 level in the SOD1^G93A mice. Serum IL-17 and LPS were significantly reduced in the butyrate-treated SOD1^G93A mice. We have demonstrated an inter-organ communications link among microbial metabolites, neuroactive metabolites from the gut, and inflammation in ALS progression. The study supports the potential to use metabolites as ALS hallmarks and for treatment.

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.

Metabolomics as a Crucial Tool to Develop New Therapeutic Strategies for Neurodegenerative Diseases

Neurodegenerative diseases (NDs), such as Alzheimer’s (AD), Parkinson’s (PD), and amyotrophic lateral sclerosis (ALS), share common pathological mechanisms, including metabolism alterations. However, their specific neuronal cell types affected and molecular biomarkers suggest that there are both common and specific alterations regarding metabolite levels. In this review, we were interested in identifying metabolite alterations that have been reported in preclinical models of NDs and that have also been documented as altered in NDs patients. Such alterations could represent interesting targets for the development of targeted therapy. Importantly, the translation of such findings from preclinical to clinical studies is primordial for the study of possible therapeutic agents. We found that N-acetyl-aspartate (NAA), myo-inositol, and glutamate are commonly altered in the three NDs investigated here. We also found other metabolites commonly altered in both AD and PD. In this review, we discuss the studies reporting such alterations and the possible pathological mechanism underlying them. Finally, we discuss clinical trials that have attempted to develop treatments targeting such alterations. We conclude that the treatment combination of both common and differential alterations would increase the chances of patients having access to efficient treatments for each ND.

The Metabolomic Profile in Amyotrophic Lateral Sclerosis Changes According to the Progression of the Disease: An Exploratory Study

Amyotrophic lateral sclerosis (ALS) is a multifactorial neurodegenerative pathology of the upper or lower motor neuron. Evaluation of ALS progression is based on clinical outcomes considering the impairment of body sites. ALS has been extensively investigated in the pathogenetic mechanisms and the clinical profile; however, no molecular biomarkers are used as diagnostic criteria to establish the ALS pathological staging. Using the source-reconstructed magnetoencephalography (MEG) approach, we demonstrated that global brain hyperconnectivity is associated with early and advanced clinical ALS stages. Using nuclear magnetic resonance (¹H-NMR) and high resolution mass spectrometry (HRMS) spectroscopy, here we studied the metabolomic profile of ALS patients' sera characterized by different stages of disease progression-namely early and advanced. Multivariate statistical analysis of the data integrated with the network analysis indicates that metabolites related to energy deficit, abnormal concentrations of neurotoxic metabolites and metabolites related to neurotransmitter production are pathognomonic of ALS in the advanced stage. Furthermore, analysis of the lipidomic profile indicates that advanced ALS patients report significant alteration of phosphocholine (PCs), lysophosphatidylcholine (LPCs), and sphingomyelin (SMs) metabolism, consistent with the exigency of lipid remodeling to repair advanced neuronal degeneration and inflammation.

Metabolic Profile and Pathological Alterations in the Muscle of Patients with Early-Stage Amyotrophic Lateral Sclerosis

Diverse biomarkers and pathological alterations have been found in muscle of patients with Amyotrophic lateral sclerosis (ALS), but the relation between such alterations and dysfunction in energetic metabolism remains to be investigated. We established the metabolome of muscle and serum of ALS patients and correlated these findings with the clinical status and pathological alterations observed in the muscle. We obtained data from 20 controls and 17 ALS patients (disease duration: 9.4 ± 6.8 months). Multivariate metabolomics analysis identified a distinct serum metabolome for ALS compared to controls (p-CV-ANOVA < 0.035) and revealed an excellent discriminant profile for muscle metabolome (p-CV-ANOVA < 0.0012). Citramalate was discriminant for both muscle and serum. High lauroylcarnitine levels in muscle were associated with low Forced Vital Capacity. Transcriptomics analysis of key antioxidant enzymes showed an upregulation of SOD3 (p = 0.0017) and GLRX2(1) (p = 0.0022) in ALS muscle. Analysis of mitochondrial enzymatic activity in muscle revealed higher complex II/CS (p = 0.04) and lower LDH (p = 0.03) activity in ALS than in controls. Our study showed, for the first time, a global dysfunction in the muscle of early-stage ALS patients. Furthermore, we identified novel metabolites to be employed as biomarkers for diagnosis and prognosis of ALS patients.

Metabolite and lipoprotein profiles reveal sex-related oxidative stress imbalance in de novo drug-naive Parkinson's disease patients

Parkinson’s disease (PD) is the neurological disorder showing the greatest rise in prevalence from 1990 to 2016. Despite clinical definition criteria and a tremendous effort to develop objective biomarkers, precise diagnosis of PD is still unavailable at early stage. In recent years, an increasing number of studies have used omic methods to unveil the molecular basis of PD, providing a detailed characterization of potentially pathological alterations in various biological specimens. Metabolomics could provide useful insights to deepen our knowledge of PD aetiopathogenesis, to identify signatures that distinguish groups of patients and uncover responsive biomarkers of PD that may be significant in early detection and in tracking the disease progression and drug treatment efficacy. The present work is the first large metabolomic study based on nuclear magnetic resonance (NMR) with an independent validation cohort aiming at the serum characterization of de novo drug-naive PD patients. Here, NMR is applied to sera from large training and independent validation cohorts of German subjects. Multivariate and univariate approaches are used to infer metabolic differences that characterize the metabolite and the lipoprotein profiles of newly diagnosed de novo drug-naive PD patients also in relation to the biological sex of the subjects in the study, evidencing a more pronounced fingerprint of the pathology in male patients. The presence of a validation cohort allowed us to confirm altered levels of acetone and cholesterol in male PD patients. By comparing the metabolites and lipoproteins levels among de novo drug-naive PD patients, age- and sex-matched healthy controls, and a group of advanced PD patients, we detected several descriptors of stronger oxidative stress.

Neurodegenerative Disorders of Alzheimer, Parkinsonism, Amyotrophic Lateral Sclerosis and Multiple Sclerosis: An Early Diagnostic Approach for Precision Treatment

Neurodegenerative diseases (NDs) are characterised by progressive dysfunction of synapses, neurons, glial cells and their networks. Neurodegenerative diseases can be classified according to primary clinical features (e.g., dementia, parkinsonism, or motor neuron disease), anatomic distribution of neurodegeneration (e.g., frontotemporal degenerations, extrapyramidal disorders, or spinocerebellar degenerations), or principal molecular abnormalities. The most common neurodegenerative disorders are amyloidosis, tauopathies, a-synucleinopathy, and TAR DNA-binding protein 43 (TDP-43) proteopathy. The protein abnormalities in these disorders have abnormal conformational properties along with altered cellular mechanisms, and they exhibit motor deficit, mitochondrial malfunction, dysfunctions in autophagic-lysosomal pathways, synaptic toxicity, and more emerging mechanisms such as the roles of stress granule pathways and liquid-phase transitions. Finally, for each ND, microglial cells have been reported to be implicated in neurodegeneration, in particular, because the microglial responses can shift from neuroprotective to a deleterious role. Growing experimental evidence suggests that abnormal protein conformers act as seed material for oligomerization, spreading from cell to cell through anatomically connected neuronal pathways, which may in part explain the specific anatomical patterns observed in brain autopsy sample. In this review, we mention the human pathology of select neurodegenerative disorders, focusing on how neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis) represent a great healthcare problem worldwide and are becoming prevalent because of the increasing aged population. Despite many studies have focused on their etiopathology, the exact cause of these diseases is still largely unknown and until now with the only available option of symptomatic treatments. In this review, we aim to report the systematic and clinically correlated potential biomarker candidates. Although future studies are necessary for their use in early detection and progression in humans affected by NDs, the promising results obtained by several groups leads us to this idea that biomarkers could be used to design a potential therapeutic approach and preclinical clinical trials for the treatments of NDs.

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.

Metabolomics of neurological disorders in India

Metabolomics is the comprehensive study of the metabolome and its alterations within biological fluids and tissues. Over the years, applications of metabolomics have been explored in several areas, including personalised medicine in diseases, metabolome-wide association studies (MWAS), pharmacometabolomics and in combination with other branches of omics such as proteomics, transcriptomics and genomics. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the major analytical techniques widely employed in metabolomics. In addition, MS is coupled with chromatography techniques like gas chromatography (GC) and liquid chromatography (LC) to separate metabolites before analysis. These analytical techniques have made possible identification and quantification of large numbers of metabolites, encompassing characterization of diseases and facilitating a systematic and rational therapeutic strategy based on metabolic patterns. In recent years, the metabolomics approach has been used to obtain a deeper insight into the underlying biochemistry of neurodegenerative disorders and the discovery of biomarkers of clinical implications. The current review mainly focuses on an Indian perspective of metabolomics for the identification of metabolites and metabolic alterations serving as potential diagnostic biomarkers for neurological diseases including acute spinal cord injury, amyotrophic lateral sclerosis, tethered cord syndrome, spina bifida, stroke, Parkinson's disease, glioblastoma and neurological disorders with inborn errors of metabolism.

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.

Molecular and Cellular Mechanisms Affected in ALS

Amyotrophic lateral sclerosis (ALS) is a terminal late-onset condition characterized by the loss of upper and lower motor neurons. Mutations in more than 30 genes are associated to the disease, but these explain only ~20% of cases. The molecular functions of these genes implicate a wide range of cellular processes in ALS pathology, a cohesive understanding of which may provide clues to common molecular mechanisms across both familial (inherited) and sporadic cases and could be key to the development of effective therapeutic approaches. Here, the different pathways that have been investigated in ALS are summarized, discussing in detail: mitochondrial dysfunction, oxidative stress, axonal transport dysregulation, glutamate excitotoxicity, endosomal and vesicular transport impairment, impaired protein homeostasis, and aberrant RNA metabolism. This review considers the mechanistic roles of ALS-associated genes in pathology, viewed through the prism of shared molecular pathways.

Metabolomics markers in Neurology: current knowledge and future perspectives for therapeutic targeting

INTRODUCTION

Metabolomics is an emerging approach providing new insights into the metabolic changes and underlying mechanisms involved in the pathogenesis of neurological disorders.

AREAS COVERED

Here, the authors present an overview of the current knowledge of metabolic profiling (metabolomics) to provide critical insight on the role of biochemical markers and metabolic alterations in neurological diseases.

EXPERT OPINION

Elucidation of characteristic metabolic alterations in neurological disorders is crucial for a better understanding of their pathogenesis, and for identifying potential biomarkers and drug targets. Nevertheless, discrepancies in diagnostic criteria, sample handling protocols, and analytical methods still affect the generalizability of current study results.

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.

Extracellular RNAs as Biomarkers of Sporadic Amyotrophic Lateral Sclerosis and Other Neurodegenerative Diseases

Recent progress in the research for underlying mechanisms in neurodegenerative diseases, including Alzheimer disease (AD), Parkinson disease (PD), and amyotrophic lateral sclerosis (ALS) has led to the development of potentially effective treatment, and hence increased the need for useful biomarkers that may enable early diagnosis and therapeutic monitoring. The deposition of abnormal proteins is a pathological hallmark of neurodegenerative diseases, including β-amyloid in AD, α-synuclein in PD, and the transactive response DNA/RNA binding protein of 43kDa (TDP-43) in ALS. Furthermore, progression of the disease process accompanies the spreading of abnormal proteins. Extracellular proteins and RNAs, including mRNA, micro RNA, and circular RNA, which are present as a composite of exosomes or other forms, play a role in cell–cell communication, and the role of extracellular molecules in the cell-to-cell spreading of pathological processes in neurodegenerative diseases is now in the spotlight. Therefore, extracellular proteins and RNAs are considered potential biomarkers of neurodegenerative diseases, in particular ALS, in which RNA dysregulation has been shown to be involved in the pathogenesis. Here, we review extracellular proteins and RNAs that have been scrutinized as potential biomarkers of neurodegenerative diseases, and discuss the possibility of extracellular RNAs as diagnostic and therapeutic monitoring biomarkers of sporadic ALS.

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.

Stratification of cancer and diabetes based on circulating levels of formate and glucose

BACKGROUND

Serum and urine metabolites have been investigated for their use as cancer biomarkers. The specificity of candidate metabolites can be limited by the impact of other disorders on metabolite levels. In particular, the increasing incidence of obesity could become a significant confounding factor.

METHODS

Here we developed a multinomial classifier for the stratification of cancer, obesity and healthy phenotypes based on circulating glucose and formate levels. We quantified the classifier performance from the retrospective analysis of samples from breast cancer, lung cancer, obese individuals and healthy controls.

RESULTS

We discovered that circulating formate levels are significantly lower in breast and lung cancer patients than in healthy controls. However, the performance of a cancer classifier based on formate levels alone is limited because obese patients also have low serum formate levels. By introducing a multinomial classifier based on circulating glucose and formate levels, we were able to improve the classifier performance, reaching a true positive rate of 79% with a false positive rate of 8%.

CONCLUSIONS

Circulating formate is reduced in HER2+ breast cancer, non-small cell lung cancer and highly obese patients relative to healthy controls. Further studies are required to determine the relevance of these observations in other cancer types and diseases.

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.

Biomarkers in Neurodegenerative Diseases

The past decade has seen tremendous efforts in biomarker discovery and validation for neurodegenerative diseases. The source and type of biomarkers has continued to grow for central nervous system diseases, from biofluid-based biomarkers (blood or cerebrospinal fluid (CSF)), to nucleic acids, tissue, and imaging. While DNA remains a predominant biomarker used to identify familial forms of neurodegenerative diseases, various types of RNA have more recently been linked to familial and sporadic forms of neurodegenerative diseases during the past few years. Imaging approaches continue to evolve and are making major contributions to target engagement and early diagnostic biomarkers. Incorporation of biomarkers into drug development and clinical trials for neurodegenerative diseases promises to aid in the development and demonstration of target engagement and drug efficacy for neurologic disorders. This review will focus on recent advancements in developing biomarkers for clinical utility in Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

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.

Prospective serum metabolomic profile of prostate cancer by size and extent of primary tumor

Two recent investigations found serum lipid and energy metabolites related to aggressive prostate cancer up to 20 years prior to diagnosis. To elucidate whether those metabolomic profiles represent etiologic or tumor biomarker signals, we prospectively examined serum metabolites of prostate cancer cases by size and extent of primary tumors in a nested case-control analysis in the ATBC Study cohort that compared cases diagnosed with T2 (n = 71), T3 (n = 51), or T4 (n = 15) disease to controls (n = 200). Time from fasting serum collection to diagnosis averaged 10 years (range 1-20). LC/MS-GC/MS identified 625 known compounds, and logistic regression estimated odds ratios (ORs) associated with one-standard deviation differences in log-metabolites. N-acetyl-3-methylhistidine, 3-methylhistidine and 2'-deoxyuridine were elevated in men with T2 cancers compared to controls (ORs = 1.38-1.79; 0.0002 ≤ p ≤ 0.01). By contrast, four lipid metabolites were inversely associated with T3 tumors: oleoyl-linoleoyl-glycerophosphoinositol (GPI), palmitoyl-linoleoyl-GPI, cholate, and inositol 1-phosphate (ORs = 0.49-0.60; 0.000017 ≤ p ≤ 0.003). Secondary bile acid lipids, sex steroids and caffeine-related xanthine metabolites were elevated, while two Krebs cycle metabolites were decreased, in men diagnosed with T4 cancers. Men with T2, T3, and T4 prostate cancer primaries exhibit qualitatively different metabolite profiles years in advance of diagnosis that may represent etiologic factors, molecular patterns reflective of distinct primary tumors, or a combination of both.

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.

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.

Metabolomic Profiling of Serum Retinol in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study

The role of retinol in the prevention of multifactorial chronic diseases remains uncertain, and there is sparse evidence regarding biological actions and pathways implicated in its effects on various outcomes. The aim is to investigate whether serum retinol in an un-supplemented state is associated with low molecular weight circulating metabolites. We performed a metabolomic analysis of 1,282 male smoker participants based on pre-supplementation fasting serum in the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study. We examined the association between 947 metabolites measured by ultra-high performance LC-MS/GC-MS and retinol concentration (from HPLC) using linear regression that estimated the difference in metabolite concentrations per unit difference in retinol concentration as standardized β-coefficients and standard errors (SE). We identified 63 metabolites associated with serum retinol below the Bonferroni-corrected P-value (p < 5.3 × 10^–5). The strongest signals were for N-acetyltryptophan (β = 0.27; SE = 0.032; p = 9.8 × 10⁻¹⁷), myo-inositol (β = 0.23; SE = 0.032; p = 9.8 × 10⁻¹³), and 1-palmitoylglycerophosphoethanolamine (β = 0.22; SE = 0.032; p = 3.2 × 10⁻¹²). Several chemical class pathways were strongly associated with retinol, including amino acids (p = 1.6 × 10⁻¹⁰), lipids (p = 3.3 × 10^–7), and cofactor/vitamin metabolites (3.3 × 10⁻⁷). The strongest sub-pathway association was for inositol metabolism (p = 2.0 × 10^–14). Serum retinol concentration is associated with circulating metabolites in various metabolic pathways, particularly lipids, amino acids, and cofactors/vitamins. These interrelationships may have relevance to the biological actions of retinol, including its role in carcinogenesis.

Metabolomic profiling in umbilical venous plasma reveals effects of dietary rumen-protected arginine or N-carbamylglutamate supplementation in nutrient-restricted Hu sheep during pregnancy

Maternal nutrient restriction during pregnancy is a major problem worldwide for human and animal production. Arginine (Arg) is critical to health, growth and reproduction. N-carbamylglutamate (NCG), a key enzyme in arginine synthesis, is not extensively degraded in rumen. The aim of this study was to investigate ameliorating effects of rumen-protected arginine (RP-Arg) and NCG supplementation on dietary in undernourished Hu sheep during gestation. From day 35 to 110 of gestation, 32 Hu ewes carrying twin foetuses were randomly divided into four groups: a control (CG) group (n = 8; fed 100% National Research Council (NRC) requirements for pregnant sheep), a nutrient-restricted (RG) group (n = 8; fed 50% NRC requirements, which included 50% mineral-vitamin mixture) and two treatment (Arg and NCG) groups (n = 8; fed 50% NRC requirements supplemented with 20 g/day RP-Arg or 5 g/day NCG, which included 50% mineral-vitamin mixture). The umbilical venous plasma samples of foetus were tested by ¹ H-nuclear magnetic resonance. Thirty-two differential metabolites were identified, indicating altered metabolic pathways of amino acid, carbohydrate and energy, lipids and oxidative stress metabolism among the four groups. Our results demonstrate that the beneficial effect of dietary RP-Arg and NCG supplementation on mammalian reproduction is associated with complex metabolic networks.

Fluid-Based Biomarkers for Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a highly heterogeneous disease with no effective treatment. Drug development has been hampered by the lack of biomarkers that aid in early diagnosis, demonstrate target engagement, monitor disease progression, and can serve as surrogate endpoints to assess the efficacy of treatments. Fluid-based biomarkers may potentially address these issues. An ideal biomarker should exhibit high specificity and sensitivity for distinguishing ALS from control (appropriate disease mimics and other neurologic diseases) populations and monitor disease progression within individual patients. Significant progress has been made using cerebrospinal fluid, serum, and plasma in the search for ALS biomarkers, with urine and saliva biomarkers still in earlier stages of development. A few of these biomarker candidates have demonstrated use in patient stratification, predicting disease course (fast vs slow progression) and severity, or have been used in preclinical and clinical applications. However, while ALS biomarker discovery has seen tremendous advancements in the last decade, validating biomarkers and moving them towards the clinic remains more elusive. In this review, we highlight biomarkers that are moving towards clinical utility and the challenges that remain in order to implement biomarkers at all stages of the ALS drug development process.

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.

Amyotrophic lateral sclerosis and denervation alter sphingolipids and up-regulate glucosylceramide synthase

Amyotrophic lateral sclerosis (ALS) is a fatal adult-onset disease characterized by upper and lower motor neuron degeneration, muscle wasting and paralysis. Growing evidence suggests a link between changes in lipid metabolism and ALS. Here, we used UPLC/TOF-MS to survey the lipidome in SOD1(G86R) mice, a model of ALS. Significant changes in lipid expression were evident in spinal cord and skeletal muscle before overt neuropathology. In silico analysis also revealed appreciable changes in sphingolipids including ceramides and glucosylceramides (GlcCer). HPLC analysis showed increased amounts of GlcCer and downstream glycosphingolipids (GSLs) in SOD1(G86R) muscle compared with wild-type littermates. Glucosylceramide synthase (GCS), the enzyme responsible for GlcCer biosynthesis, was up-regulated in muscle of SOD1(G86R) mice and ALS patients, and in muscle of wild-type mice after surgically induced denervation. Conversely, inhibition of GCS in wild-type mice, following transient peripheral nerve injury, reversed the overexpression of genes in muscle involved in oxidative metabolism and delayed motor recovery. GCS inhibition in SOD1(G86R) mice also affected the expression of metabolic genes and induced a loss of muscle strength and morphological deterioration of the motor endplates. These findings suggest that GSLs may play a critical role in ALS muscle pathology and could lead to the identification of new therapeutic targets.

The longitudinal cerebrospinal fluid metabolomic profile of amyotrophic lateral sclerosis

Neurochemical biomarkers are urgently sought in ALS. Metabolomic analysis of cerebrospinal fluid (CSF) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy is a highly sensitive method capable of revealing nervous system cellular pathology. The (1)H-NMR CSF metabolomic signature of ALS was sought in a longitudinal cohort. Six-monthly serial collection was performed in ALS patients across a range of clinical sub-types (n = 41) for up to two years, and in healthy controls at a single time-point (n = 14). A multivariate statistical approach, partial least squares discriminant analysis, was used to determine differences between the NMR spectra from patients and controls. Significantly predictive models were found using those patients with at least one year's interval between recruitment and the second sample. Glucose, lactate, citric acid and, unexpectedly, ethanol were the discriminating metabolites elevated in ALS. It is concluded that (1)H-NMR captured the CSF metabolomic signature associated with derangements in cellular energy utilization connected with ALS, and was most prominent in comparisons using patients with longer disease duration. The specific metabolites identified support the concept of a hypercatabolic state, possibly involving mitochondrial dysfunction specifically. Endogenous ethanol in the CSF may be an unrecognized novel marker of neuronal tissue injury in ALS.

Use of biomarkers in ALS drug development and clinical trials

The past decade has seen a dramatic increase in the discovery of candidate biomarkers for ALS. These biomarkers typically can either differentiate ALS from control subjects or predict disease course (slow versus fast progression). At the same time, late-stage clinical trials for ALS have failed to generate improved drug treatments for ALS patients. Incorporation of biomarkers into the ALS drug development pipeline and the use of biologic and/or imaging biomarkers in early- and late-stage ALS clinical trials have been absent and only recently pursued in early-phase clinical trials. Further clinical research studies are needed to validate biomarkers for disease progression and develop biomarkers that can help determine that a drug has reached its target within the central nervous system. In this review we summarize recent progress in biomarkers across ALS model systems and patient population, and highlight continued research directions for biomarkers that stratify the patient population to enrich for patients that may best respond to a drug candidate, monitor disease progression and track drug responses in clinical trials. It is crucial that we further develop and validate ALS biomarkers and incorporate these biomarkers into the ALS drug development process. This article is part of a Special Issue entitled ALS complex pathogenesis.

Metabolic Profiling and Phenotyping of Central Nervous System Diseases: Metabolites Bring Insights into Brain Dysfunctions

Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis

BACKGROUND

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients.

RESULTS

Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS.

CONCLUSION

DRSA provides a complementary method for improving the predictive performance of the multivariate data analysis usually used in metabolomics. This method could help in the identification of metabolites involved in disease pathogenesis. Interestingly, these different strategies mostly identified the same metabolites as being discriminant. The selection of strong decision rules with high value of Bayesian confirmation provides useful information about relevant condition-decision relationships not otherwise revealed in metabolomics data.