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

Urinary biomarkers for amyotrophic lateral sclerosis: candidates, opportunities and considerations

Amyotrophic lateral sclerosis is a relentless neurodegenerative disease that is mostly fatal within 3-5 years and is diagnosed on evidence of progressive upper and lower motor neuron degeneration. Around 15% of those with amyotrophic lateral sclerosis also have frontotemporal degeneration, and gene mutations account for ∼10%. Amyotrophic lateral sclerosis is a variable heterogeneous disease, and it is becoming increasingly clear that numerous different disease processes culminate in the final degeneration of motor neurons. There is a profound need to clearly articulate and measure pathological process that occurs. Such information is needed to tailor treatments to individuals with amyotrophic lateral sclerosis according to an individual's pathological fingerprint. For new candidate therapies, there is also a need for methods to select patients according to expected treatment outcomes and measure the success, or not, of treatments. Biomarkers are essential tools to fulfil these needs, and urine is a rich source for candidate biofluid biomarkers. This review will describe promising candidate urinary biomarkers of amyotrophic lateral sclerosis and other possible urinary candidates in future areas of investigation as well as the limitations of urinary biomarkers.

Interplay of Metallome and Metabolome in Amyotrophic Lateral Sclerosis: A Study on Cerebrospinal Fluid of Patients Carrying Disease-Related Gene Mutations

Amyotrophic lateral sclerosis (ALS) is a lethal progressive neurodegenerative disease, characterized by a loss of function of upper and lower motor neurons. This study aimed to explore probable pathological alterations occurring in individuals with ALS compared to neurologically healthy controls through the analysis of cerebrospinal fluid (CSF), a medium, which directly interacts with brain parenchyma. A total of 7 ALS patients with disease-associated mutations (ATXN2, C9ORF72, FUS, SOD1, and TARDBP) and 13 controls were included in the study. Multiple analytical approaches were employed, including metabolomic and metallomics profiling, as well as genetic screening, using CSF samples obtained from the brain compartment. Data analysis involved the application of multivariate statistical methods. Advanced hyphenated selenium and redox metal (iron, copper, and manganese) speciation techniques and nontargeted Fourier transform ion cyclotron resonance mass spectrometry-based metabolomics were used for data acquisition. Nontargeted metabolomics showed reduced steroids, including sex hormones; additionally, copper and manganese species were found to be the most relevant features for ALS patients. This indicates a potential alteration of sex hormone pathways in the ALS-affected brain, as reflected in the CSF.

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.

Integrated network pharmacology approach shows a potential role of Ginseng catechins and ginsenosides in modulating protein aggregation in Amyotrophic Lateral Sclerosis

Amyotrophic lateral Sclerosis is an incurable, progressive neurodegenerative motor neuron disease. The disease is characterized by protein aggregates. The symptoms include weakness, denervation of muscles, atrophy and progressive paralysis of bulbar and respiratory muscles and dysphagia. Various secondary metabolites are evaluated for their ability to improve symptoms in ALS. Ginseng has been traditionally used for treating several neurodegenerative diseases. Several studies using model systems have shown a potential role of Ginseng catechins and Ginsenosides in clearing protein aggregation associated with ALS. We focus on Network pharmacology approach to understand the effect of Ginseng catechins or ginsenosides on protein aggregation associated with ALS. A catechin/ginsenoside-protein interaction network was generated and the pathways obtained were compared with those obtained from transcriptomic datasets of ALS from GEO database. Knock out of MAPK14, AKT and GSK from Catechin and BACE 1 from ginsenoside modulated pathways inhibited protein aggregation. Catechins and ginsenosides have potential as therapeutic agents in the management of ALS.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03401-1.

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.

Plasma taurine is an axonal excitability-translatable biomarker for amyotrophic lateral sclerosis

Although various body fluid biomarkers for amyotrophic lateral sclerosis (ALS) have been reported, no biomarkers specifically reflecting abnormalities in axonal excitability indices have currently been established. Capillary electrophoresis time-of-flight mass spectrometry and liquid chromatography time-of-flight mass spectrometry were used to perform a comprehensive metabolome analysis of plasma from seven ALS patients and 20 controls, and correlation analysis with disease phenotypes was then performed in 22 other ALS patients. Additionally, electrophysiological studies of motor nerve axonal excitability were performed in all ALS patients. In the ALS and control groups, levels of various metabolites directly associated with skeletal muscle metabolism, such as those involved in fatty acid β-oxidation and the creatine pathway, were detected. Receiver operating characteristic curve analysis of the top four metabolites (ribose-5-phosphate, N6-acetyllysine, dyphylline, 3-methoxytyrosine) showed high diagnostic accuracy (area under the curve = 0.971) in the ALS group compared with the control group. Furthermore, hierarchical cluster analysis revealed that taurine levels were correlated with the strength-duration time constant, an axonal excitability indicator established to predict survival. No significant effects of diabetes mellitus and treatment (Riluzole and Edaravone) on this relationship were detected in the study. Therefore, plasma taurine is a potential novel axonal excitability-translatable biomarker for ALS.

Advances in Proteomic and Metabolomic Profiling of Neurodegenerative Diseases

Proteomics and metabolomics are two emerging fields that hold promise to shine light on the molecular mechanisms causing neurodegenerative diseases. Research in this area may reveal and quantify specific metabolites and proteins that can be targeted by therapeutic interventions intended at halting or reversing the neurodegenerative process. This review aims at providing a general overview on the current status of proteomic and metabolomic profiling in neurodegenerative diseases. We focus on the most common neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. We discuss the relevance of state-of-the-art metabolomics and proteomics approaches and their potential for biomarker discovery. We critically review advancements made so far, highlighting how metabolomics and proteomics may have a significant impact in future therapeutic and biomarker development. Finally, we further outline technologies used so far as well as challenges and limitations, placing the current information in a future-facing context.

Systems Biology to Address Unmet Medical Needs in Neurological Disorders

Neurological diseases are highly prevalent and constitute a significant cause of mortality and disability. Neurological disorders encompass a heterogeneous group of neurodegenerative conditions, broadly characterized by injury to the peripheral and/or central nervous system. Although the etiology of neurological diseases varies greatly, they share several characteristics, such as heterogeneity of clinical presentation, non-cell autonomous nature, and diversity of cellular, subcellular, and molecular pathways. Systems biology has emerged as a valuable platform for addressing the challenges of studying heterogeneous neurological diseases. Systems biology has manifold applications to address unmet medical needs for neurological illness, including integrating and correlating different large datasets covering the transcriptome, epigenome, proteome, and metabolome associated with a specific condition. This is particularly useful for disentangling the heterogeneity and complexity of neurological conditions. Hence, systems biology can help in uncovering pathophysiology to develop novel therapeutic targets and assessing the impact of known treatments on disease progression. Additionally, systems biology can identify early diagnostic biomarkers, to help diagnose neurological disease preceded by a long subclinical phase, as well as define the exposome, the collection of environmental toxicants that increase risk of certain neurological diseases. In addition to these current applications, there are numerous potential emergent uses, such as precision medicine.

Behavioral, Hormonal, Inflammatory, and Metabolic Effects Associated with FGF21-Pathway Activation in an ALS Mouse Model

In amyotrophic lateral sclerosis (ALS), motor neuron degeneration occurs simultaneously with systemic metabolic dysfunction and neuro-inflammation. The fibroblast growth factor 21 (FGF21) plays an important role in the regulation of both phenomena and is a major hormone of energetic homeostasis. In this study, we aimed to determine the relevance of FGF21 pathway stimulation in a male mouse model of ALS (mutated SOD1-G93A mice) by using a pharmacological agonist of FGF21, R1Mab1. Mice (SOD1-WT and mutant SOD1-G93A) were treated with R1Mab1 or vehicle. Longitudinal data about clinical status (motor function, body weight) and biological parameters (including hormonal, immunological, and metabolomics profiles) were collected from the first symptoms to euthanasia at week 20. Multivariate models were performed to identify the main parameters associated with R1Mab1 treatment and to link them with clinical status, and metabolic pathways involving the discriminant metabolites were also determined. A beneficial clinical effect of R1Mab1 was revealed on slow rotarod (p = 0.032), despite a significant decrease in body weight of ALS mice (p < 0.001). We observed a decrease in serum TNF-α, MCP-1, and insulin levels (p = 0.0059, p = 0.003, and p = 0.01, respectively). At 16 weeks, metabolomics analyses revealed a clear discrimination (CV-ANOVA = 0.0086) according to the treatment and the most discriminant pathways, including sphingolipid metabolism, butanoate metabolism, pantothenate and CoA biosynthesis, and the metabolism of amino acids like tyrosine, arginine, proline, glycine, serine, alanine, aspartate, and glutamate. Mice treated with R1Mab1 had mildly higher performance on slow rotarod despite a decrease on body weight and could be linked with the anti-inflammatory effect of R1Mab1. These results indicate that FGF21 pathway is an interesting target in ALS, with a slight improvement in motor function combined with metabolic and anti-inflammatory effects.

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.

From Multi-Omics Approaches to Precision Medicine in Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a devastating and fatal neurodegenerative disorder, caused by the degeneration of upper and lower motor neurons for which there is no truly effective cure. The lack of successful treatments can be well explained by the complex and heterogeneous nature of ALS, with patients displaying widely distinct clinical features and progression patterns, and distinct molecular mechanisms underlying the phenotypic heterogeneity. Thus, stratifying ALS patients into consistent and clinically relevant subgroups can be of great value for the development of new precision diagnostics and targeted therapeutics for ALS patients. In the last years, the use and integration of high-throughput "omics" approaches have dramatically changed our thinking about ALS, improving our understanding of the complex molecular architecture of ALS, distinguishing distinct patient subtypes and providing a rational foundation for the discovery of biomarkers and new individualized treatments. In this review, we discuss the most significant contributions of omics technologies in unraveling the biological heterogeneity of ALS, highlighting how these approaches are revealing diagnostic, prognostic and therapeutic targets for future personalized interventions.

Is There a Role for Vitamin D in Amyotrophic Lateral Sclerosis? A Systematic Review and Meta-Analysis

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative condition characterized by the progressive loss of motor neurons. Patients usually die 3–5 years after diagnosis from respiratory failure. Several studies investigated the role of vitamin D as a biomarker or a therapeutic option for ALS patients. To clarify the scientific evidence, we performed a systematic review and different meta-analyses regarding the potential role of vitamin D in ALS.

Methods: We performed a systematic review of clinical trials, cohorts, and case–control studies retrieved from PubMed, EMBASE, and Cochrane databases reporting vitamin D levels as a putative biomarker for ALS diagnosis or prognosis or the effect of vitamin D supplementation in ALS patients. Whenever possible, data were pooled using a random-effects model, with an assessment of heterogeneity.

Results: Out of 2,996 articles retrieved, we finally included 13 research articles, 12 observational studies (50% prospective), and 1 clinical trial. We found that ALS patients had slightly lower levels of vitamin D than controls (mean difference −6 ng/ml, 95% CI [−10.8; −1.3]), but important confounding factors were not considered in the studies analyzed. We found no relationship between vitamin D levels and ALS functional rate score—revised (ALSFRS-R), with highly heterogeneous results. Discordant results were reported in three studies regarding survival. Finally, five studies reported the effects of vitamin D supplementation with discordant results. Two of them showed a small improvement, whereas two others showed a deleterious effect on ALSFRS-R. One very small clinical trial with important methodological limitations showed some improvement in ALSFRS-R with high doses of vitamin D compared with normal doses.

Conclusions: Our review did not find evidence to support the role of vitamin D on ALS diagnosis, prognosis, or treatment. Most studies had important limitations, mostly regarding the risk of bias for not considering confounding factors. Vitamin D supplementation should be offered to ALS patients to avoid other health issues related to vitamin D deficiency, but there is not enough evidence to support the use of vitamin D as a therapy for ALS.

Understanding and managing metabolic dysfunction in Amyotrophic Lateral Sclerosis

INTRODUCTION

Amyotrophic Lateral Sclerosis (ALS) is a fatal motor neuron disease that leads to death after a median survival of 36 months. The development of an effective treatment has proven to be extremely difficult due to the inadequate understanding of the pathogenesis of ALS. Energy metabolism is thoroughly involved in the disease based on the discoveries of hypermetabolism, lipid/glucose metabolism, the tricarboxylic acid (TCA) cycle, and mitochondrial impairment.

AREA COVERED

Many perturbed metabolites within these processes have been identified as promising therapeutic targets. However, the therapeutic strategies targeting these pathways have failed to produce clinically significant results. The authors present in this review the metabolic disturbances observed in ALS and the derived-therapeutics.

EXPERT OPINION

The authors suggest that this is due to the insufficient knowledge of the relationship between the metabolic targets and the type of ALS of the patient, depending on genetic and environmental factors. We must improve our understanding of the pathological mechanisms and pay attention to the subtle hidden effects of changing diet, for example, and to use this strategy in addition to other drugs or to use metabolism status to determine subgroups of patients.

Amyotrophic Lateral Sclerosis: Current Status in Diagnostic Biomarkers

Amyotrophic lateral sclerosis (ALS) is a rare, neurodegenerative disease that affects the human motor system. ALS is a highly heterogeneous disease, depending on several causative factors. The heterogeneity of the disease is also reflected in the variation of the symptoms in ALS patients. The worldwide annual incidence of ALS is about 2.08 per 100,000 with uniform rates in Caucasian populations and lower rates in African, Asian, and Hispanic populations, while the number of individuals with ALS is expected to grow significantly between 2015 and 2040 with an estimated increase of 69% (Chio et al. 2013a; Arthur et al. 2016).

Vestibular evoked myogenic potentials (VEMP) captured in the forearm flexor muscles: a study of its feasibility and reference ranges

OBJECTIVE

To determine the central tendency measures and variability of vestibular evoked myogenic potential (VEMP) with regard to the latency and wave amplitude when potentials are captured from the flexor muscles of the forearm.

METHODS

Ten adult volunteers with normal hearing underwent examination of their forearm flexor muscles (right and left sides; 20 samples in total) for VEMP acquisition. To this end, 200 tone burst stimuli at a 500 Hz frequency and 95 dBnHL intensity were promediated.

RESULTS

No statistical differences were observed in VEMP responses acquired from the right and left forearm flexor muscles concerning P34 and N44 latencies (p=0.32 and 0.90, respectively). The mean latency obtained for the P34 wave component was 34.9 ms (±2.6), with a lower limit equal to 29.3 and an upper limit equal to 40.4 ms. The average latency of the N44 wave component was 43.6 ms (±2.1), with a lower limit of 39.1 ms and an upper limit of 48.1 ms. The results were consistent and had low variability, and showed an average asymmetry index of 15.4 (±10.7). These findings indicate that potentials may be investigated in different age groups and in specific clinical populations, such as pathologies that may alter the neuronal transmission of the inferior vestibular pathway, especially when a longer portion is observed.

CONCLUSIONS

VEMP recording from forearm flexors is both feasible and stable, with latency reference ranges between 29.3 and 40.4 ms for P34, and 39.1 and 48.1 ms for N44.

Astrocyte alterations in neurodegenerative pathologies and their modeling in human induced pluripotent stem cell platforms

Astrocytes are the most abundant cell type in the brain. They were long considered only as passive support for neuronal cells. However, recent data have revealed many active roles for these cells both in maintenance of the normal physiological homeostasis in the brain as well as in neurodegeneration and disease. Moreover, human astrocytes have been found to be much more complex than their rodent counterparts, and to date, astrocytes are known to actively participate in a multitude of processes such as neurotransmitter uptake and recycling, gliotransmitter release, neuroenergetics, inflammation, modulation of synaptic activity, ionic balance, maintenance of the blood-brain barrier, and many other crucial functions of the brain. This review focuses on the role of astrocytes in human neurodegenerative disease and the potential of the novel stem cell-based platforms in modeling astrocytic functions in health and in disease.

Are Circulating Cytokines Reliable Biomarkers for Amyotrophic Lateral Sclerosis?

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that has no effective treatment. The lack of any specific biomarker that can help in the diagnosis or prognosis of ALS has made the identification of biomarkers an urgent challenge. Multiple panels have shown alterations in levels of numerous cytokines in ALS, supporting the contribution of neuroinflammation to the progressive motor neuron loss. However, none of them is fully sensitive and specific enough to become a universal biomarker for ALS. This review gathers the numerous circulating cytokines that have been found dysregulated in both ALS animal models and patients. Particularly, it highlights the opposing results found in the literature to date, and points out another potential application of inflammatory cytokines as therapeutic targets.

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.

The Metabolome and Osteoarthritis: Possible Contributions to Symptoms and Pathology

Osteoarthritis (OA) is a progressive, deteriorative disease of articular joints. Although traditionally viewed as a local pathology, biomarker exploration has shown that systemic changes can be observed. These include changes to cytokines, microRNAs, and more recently, metabolites. The metabolome is the set of metabolites within a biological sample and includes circulating amino acids, lipids, and sugar moieties. Recent studies suggest that metabolites in the synovial fluid and blood could be used as biomarkers for OA incidence, prognosis, and response to therapy. However, based on clinical, demographic, and anthropometric factors, the local synovial joint and circulating metabolomes may be patient specific, with select subsets of metabolites contributing to OA disease. This review explores the contribution of the local and systemic metabolite changes to OA, and their potential impact on OA symptoms and disease pathogenesis.

A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression

There is an urgent and unmet need for accurate biomarkers in Amyotrophic Lateral Sclerosis. A pharmaco-metabolomics study was conducted using plasma samples from the TRO19622 (olesoxime) trial to assess the link between early metabolomic profiles and clinical outcomes. Patients included in this trial were randomized into either Group O receiving olesoxime (n = 38) or Group P receiving placebo (n = 36). The metabolomic profile was assessed at time-point one (V1) and 12 months (V12) after the initiation of the treatment. High performance liquid chromatography coupled with tandem mass spectrometry was used to quantify 188 metabolites (Biocrates® commercial kit). Multivariate analysis based on machine learning approaches (i.e. Biosigner algorithm) was performed. Metabolomic profiles at V1 and V12 and changes in metabolomic profiles between V1 and V12 accurately discriminated between Groups O and P (p<5×10–6), and identified glycine, kynurenine and citrulline/arginine as the best predictors of group membership. Changes in metabolomic profiles were closely linked to clinical progression, and correlated with glutamine levels in Group P and amino acids, lipids and spermidine levels in Group O. Multivariate models accurately predicted disease progression and highlighted the discriminant role of sphingomyelins (SM C22:3, SM C24:1, SM OH C22:2, SM C16:1). To predict SVC from SM C24:1 in group O and SVC from SM OH C22:2 and SM C16:1 in group P+O, we noted a median sensitivity between 67% and 100%, a specificity between 66.7 and 71.4%, a positive predictive value between 66 and 75% and a negative predictive value between 70% and 100% in the test sets. This proof-of-concept study demonstrates that the metabolomics has a role in evaluating the biological effect of an investigational drug and may be a candidate biomarker as a secondary outcome measure in clinical trials.

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.

Wildtype motoneurons, ALS-Linked SOD1 mutation and glutamate profoundly modify astrocyte metabolism and lactate shuttling

The selective degeneration of motoneuron that typifies amyotrophic lateral sclerosis (ALS) implicates non-cell-autonomous effects of astrocytes. However, mechanisms underlying astrocyte-mediated neurotoxicity remain largely unknown. According to the determinant role of astrocyte metabolism in supporting neuronal function, we propose to explore the metabolic status of astrocytes exposed to ALS-associated conditions. We found a significant metabolic dysregulation including purine, pyrimidine, lysine, and glycerophospholipid metabolism pathways in astrocytes expressing an ALS-causing mutated superoxide dismutase-1 (SOD1) when co-cultured with motoneurons. SOD1 astrocytes exposed to glutamate revealed a significant modification of the astrocyte metabolic fingerprint. More importantly, we observed that SOD1 mutation and glutamate impact the cellular shuttling of lactate between astrocytes and motoneurons with a decreased in extra- and intra-cellular lactate levels in astrocytes. Based on the emergent strategy of metabolomics, this work provides novel insight for understanding metabolic dysfunction of astrocytes in ALS conditions and opens the perspective of therapeutics targets through focusing on these metabolic pathways. GLIA 2017 GLIA 2017;65:592-605.

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.

Combined Metabolomics and Transcriptomics Approaches to Assess the IL-6 Blockade as a Therapeutic of ALS: Deleterious Alteration of Lipid Metabolism

In amyotrophic lateral sclerosis (ALS), motor neuron degeneration occurs simultaneously with systemic metabolic impairment and neuroinflammation. Playing an important role in the regulation of both phenomena, interleukin (IL)-6, a major cytokine of the inflammatory response has been proposed as a target for management of ALS. Although a pilot clinical trial provided promising results in humans, another recent preclinical study showed that knocking out the IL-6 gene in mice carrying ALS did not improve clinical outcome. In this study, we aimed to determine the relevance of the IL-6 pathway blockade in a mouse model of ALS by using a pharmacological antagonist of IL-6, a murine surrogate of tocilizumab, namely MR16-1. We analyzed the immunological and metabolic effects of IL-6 blockade by cytokine measurement, blood cell immunophenotyping, targeted metabolomics, and transcriptomics. A deleterious clinical effect of MR16-1 was revealed, with a speeding up of weight loss (p = 0.0041) and decreasing body weight (p < 0.05). A significant increase in regulatory T-cell count (p = 0.0268) and a decrease in C-X-C ligand-1 concentrations in plasma (p = 0.0479) were observed. Metabolomic and transcriptomic analyses revealed that MR16-1 mainly affected branched-chain amino acid, lipid, arginine, and proline metabolism. IL-6 blockade negatively affected body weight, despite a moderated anti-inflammatory effect. Metabolic effects of IL-6 were mild compared with metabolic disturbances observed in ALS, but a modification of lipid metabolism by therapy was identified. These results indicate that IL-6 blockade did not improve clinical outcome of a mutant superoxide dismutase 1 mouse model of ALS.

Further development of biomarkers in amyotrophic lateral sclerosis

INTRODUCTION

Amyotrophic lateral sclerosis (ALS) is an idiopathic neurodegenerative disease usually fatal in less than three years. Even if standard guidelines are available to diagnose ALS, the mean diagnosis delay is more than one year. In this context, biomarker discovery is a priority. Research has to focus on new diagnostic tools, based on combined explorations.

AREAS COVERED

In this review, we specifically focus on biology and imaging markers. We detail the innovative field of 'omics' approach and imaging and explain their limits to be useful in routine practice. We describe the most relevant biomarkers and suggest some perspectives for biomarker research. Expert commentary: The successive failures of clinical trials in ALS underline the need for new strategy based on innovative tools to stratify patients and to evaluate their responses to treatment. Biomarker data may be useful to improve the designs of clinical trials. Biomarkers are also needed to better investigate disease pathophysiology, to identify new therapeutic targets, and to improve the performance of clinical assessments for diagnosis and prognosis in the clinical setting. A consensus on the best management of neuroimaging and 'omics' methods is necessary and a systematic independent validation of findings may add robustness to future studies.