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]

[What are the applications of biomarkers in ALS today?]

Numerous biomarkers studies in ALS used targeted and non-targeted approaches, to help for the diagnosis, the prognosis or to identify new pathophysiological ways. The emerging approaches such as "omics" studies are very promising, but the practical and technical limits do not enable their optimization. Even if some biomarkers such as cystatin C or glutamate are highlighted in ALS, to date, no biomarker is currently used in routine practice. Diffusion-based neuroimaging has emerged as a tool to identify the involvement of the central neuron, but a recent meta-analysis shows a poor sensitivity and specificity. Spinal cord imaging has the advantage of simultaneoulsy investigating both the corticospinal tract and the peripheral motor neurons in the anterior horns of the spinal cord. Its interest to provide biomarkers in ALS is illustrated by recent studies that used a multiparametric approach. The limits of biomarkers studies are principally based on small cohorts, involving a control population who does not allow to assess specificity. The discrepancies between the biomarkers identified in the different studies are based on a strong heterogeneity of the disease and a lack of standardization of the research methodology, including the step of the validation of these molecules in independent cohorts. The perspectives in biomarker research in ALS imply the combination of analytical methods, human abilities and harmonization of the strategies.

A plural role for lipids in motor neuron diseases: energy, signaling and structure

Motor neuron diseases (MNDs) are characterized by selective death of motor neurons and include mainly adult-onset amyotrophic lateral sclerosis (ALS) and spinal muscular atrophy (SMA). Neurodegeneration is not the single pathogenic event occurring during disease progression. There are multiple lines of evidence for the existence of defects in lipid metabolism at peripheral level. For instance, hypermetabolism is well characterized in ALS, and dyslipidemia correlates with better prognosis in patients. Lipid metabolism plays also a role in other MNDs. In SMA, misuse of lipids as energetic nutrients is described in patients and in related animal models. The composition of structural lipids in the central nervous system is modified, with repercussion on membrane fluidity and on cell signaling mediated by bioactive lipids. Here, we review the main epidemiologic and mechanistic findings that link alterations of lipid metabolism and motor neuron degeneration, and we discuss the rationale of targeting these modifications for therapeutic management of MNDs.

Mechanisms, models and biomarkers in amyotrophic lateral sclerosis

The last 30 years have seen a major advance in the understanding of the clinical and pathological heterogeneity of amyotrophic lateral sclerosis (ALS), and its overlap with frontotemporal dementia. Multiple, seemingly disparate biochemical pathways converge on a common clinical syndrome characterized by progressive loss of upper and lower motor neurons. Pathogenic themes in ALS include excitotoxicity, oxidative stress, mitochondrial dysfunction, neuroinflammation, altered energy metabolism, and most recently RNA mis-processing. The transgenic rodent, overexpressing mutant superoxide dismutase-1, is now only one of several models of ALS pathogenesis. The nematode, fruit fly and zebrafish all offer fresh insight, and the development of induced pluripotent stem cell-derived motor neurons holds promise for the screening of candidate therapeutics. The lack of useful biomarkers in ALS contributes to diagnostic delay, and the inability to stratify patients by prognosis may be an important factor in the failure of therapeutic trials. Biomarkers sensitive to disease activity might lessen reliance on clinical measures and survival as trial endpoints and reduce study length. Emerging proteomic markers of neuronal loss and glial activity in cerebrospinal fluid, a cortical signature derived from advanced structural and functional MRI, and the development of more sensitive measurements of lower motor neuron physiology are leading a new phase of biomarker-driven therapeutic discovery.

Advances in cellular models to explore the pathophysiology of amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS), the most common adult-onset motor neuron disorder, is fatal for most patients less than 3 years from when the first symptoms appear. The aetiologies for sporadic and most familial forms of ALS are unknown, but genetic factors are increasingly recognized as causal in a subset of patients. Studies of disease physiology suggest roles for oxidative stress, glutamate-mediated excitotoxicity or protein aggregation; how these pathways interact in the complex pathophysiology of ALS awaits elucidation. Cellular models are being used to examine disease mechanisms. Recent advances include the availability of expanded cell types, from neuronal or glial cell culture to motoneuron-astrocyte co-culture genetically or environmentally modified. Cell culture experiments confirmed the central role of glial cells in ALS. The recent adaptation of induced pluripotent stem cells (iPSC) for ALS modeling could allow a broader perspective and is expected to generate new hypotheses, related particularly to mechanisms underlying genetic factors. Cellular models have provided meaningful advances in the understanding of ALS, but, to date, complete characterization of in vitro models is only partially described. Consensus on methodological approaches, strategies for validation and techniques that allow rapid adaptation to new genetic or environmental influences is needed. In this article, we review the principal cellular models being employed in ALS and highlight their contribution to the understanding of disease mechanisms. We conclude with recommendations on means to enhance the robustness and generalizability of the different concepts for experimental ALS.

Biological and neuroimaging biomarkers for amyotrophic lateral sclerosis: 2013 and beyond

SUMMARY Amyotrophic lateral sclerosis is an idiopathic, incurable neurodegenerative disease that is fatal for most patients in less than 3 years from the time weakness first appears. Alongside identification of etiologies and stronger neuroprotective agents, the development of biomarkers is a main research priority. Since the original description, diagnosis and progression measurement in amyotrophic lateral sclerosis has been clinical. The time from symptom onset to diagnosis is usually more than a year, and clinical research studies utilize clinical end points that have low sensitivity. Few eligible patients and inefficient trials mean that just one or a few new therapies can be tested each year. Biological markers are needed not only to improve the sensitivity of clinical assessments, but also to better examine disease pathophysiology in vivo.

Serum analysis by 1H nuclear magnetic resonance spectroscopy: a new tool for distinguishing neuromyelitis optica from multiple sclerosis

BACKGROUND

Neuromyelitis optica (NMO) and multiple sclerosis (MS), two inflammatory demyelinating diseases, are characterized by different therapeutic strategies. Currently, the only biological diagnostic tool available to distinguish NMO from MS is the specific serum autoantibody that targets aquaporin 4, but its sensitivity is low.

OBJECTIVE

To assess the diagnostic accuracy of metabolomic biomarker profiles in these two neurological conditions, compared to control patients.

METHODS

We acquired serum spectra (47 MS, 44 NMO and 42 controls) using proton nuclear magnetic resonance ((1)H-NMR) spectroscopy. We used multivariate pattern recognition analysis to identify disease-specific metabolic profiles.

RESULTS

The (1)H-NMR spectroscopic analysis evidenced two metabolites, originating probably from astrocytes, scyllo-inositol and acetate, as promising serum biomarkers of MS and NMO, respectively. In 87.8% of MS patients, scyllo-inositol increased 0.15 to 3-fold, compared to controls and in 74.3% of NMO patients, acetate increased 0.4 to 7-fold, compared to controls. Using these two metabolites simultaneously, we can discriminate MS versus NMO patients (sensitivity, 94.3%; specificity, 90.2%).

CONCLUSION

This study demonstrates the potential of (1)H-NMR spectroscopy of serum as a novel, promising analytical tool to discriminate populations of patients affected by NMO or MS.

Biomarker Discovery and Translation in Metabolomics

The multifaceted field of metabolomics has witnessed exponential growth in both methods development and applications. Owing to the urgent need, a significant fraction of research investigations in the field is focused on understanding, diagnosing and preventing human diseases; hence, the field of biomedicine has been the major beneficiary of metabolomics research. A large body of literature now documents the discovery of numerous potential biomarkers and provides greater insights into pathogeneses of numerous human diseases. A sizable number of findings have been tested for translational applications focusing on disease diagnostics ranging from early detection, to therapy prediction and prognosis, monitoring treatment and recurrence detection, as well as the important area of therapeutic target discovery. Current advances in analytical technologies promise quantitation of biomarkers from even small amounts of bio-specimens using non-invasive or minimally invasive approaches, and facilitate high-throughput analysis required for real time applications in clinical settings. Nevertheless, a number of challenges exist that have thus far delayed the translation of a majority of promising biomarker discoveries to the clinic. This article presents advances in the field of metabolomics with emphasis on biomarker discovery and translational efforts, highlighting the current status, challenges and future directions.

Power of metabolomics in diagnosis and biomarker discovery of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the commonest primary hepatic malignancy and the third most common cause of cancer-related death worldwide. Incidence remains highest in the developing world and is steadily increasing across the developed world. Current diagnostic modalities, of ultrasound and α-fetoprotein, are expensive and lack sensitivity in tumor detection. Because of its asymptomatic nature, HCC is usually diagnosed at late and advanced stages, for which there are no effective therapies. Thus, biomarkers for early detection and molecular targets for treating HCC are urgently needed. Emerging high-throughput metabolomics technologies have been widely applied, aiming at the discovery of candidate biomarkers for cancer staging, prediction of recurrence and prognosis, and treatment selection. Metabolic profiles, which are affected by many physiological and pathological processes, may provide further insight into the metabolic consequences of this severe liver disease. Small-molecule metabolites have an important role in biological systems and represent attractive candidates to understand HCC phenotypes. The power of metabolomics allows an unparalleled opportunity to query the molecular mechanisms of HCC. This technique-driven review aims to demystify the metabolomics pathway, while also illustrating the potential of this technique, with recent examples of its application in HCC.

Amyotrophic Lateral Sclerosis and Metabolomics: Clinical Implication and Therapeutic Approach

Amyotrophic lateral sclerosis (ALS) is one of the most common motor neurodegenerative disorders, primarily affecting upper and lower motor neurons in the brain, brainstem, and spinal cord, resulting in paralysis due to muscle weakness and atrophy. The majority of patients die within 3-5 years of symptom onset as a consequence of respiratory failure. Due to relatively fast progression of the disease, early diagnosis is essential. Metabolomics offer a unique opportunity to understand the spatiotemporal metabolic crosstalks through the assessment of body fluids and tissue. So far, one of the most challenging issues related to ALS is to understand the variation of metabolites in body fluids and CNS with the progression of disease. In this paper we will review the changes in metabolic profile in response to disease progression condition and also see the therapeutic implication of various drugs in ALS patients.

Early prognostic markers for fatal fulminant hepatic failure cases with viral hepatitis: proton nuclear magnetic resonance spectroscopic studies of serum

BACKGROUND

Fulminant hepatic failure is associated with liver metabolic derangements which could have fatal consequences. The aim of the present study is to identify serum markers for early prediction of the outcome.

METHODS

Proton nuclear magnetic resonance spectroscopic studies of serum of fulminant hepatic failure patients due to viral hepatitis with grade II/III of encephalopathy (twenty-four: ten prospective and fourteen retrospective) and twenty-five controls were undertaken. Of the twenty-four patients, fifteen survived with medical management alone while nine had fatal outcome.

RESULTS

The results demonstrated significantly elevated indices of amino acids (alanine, lysine, glutamine, histidine, tyrosine, phenylalanine and 1,2-propanediol) in fatal cases compared to survivors and controls. Principal component analysis showed clear separation of fatal and surviving cases. Liver function parameters were significantly deranged in patients but they failed to provide early significant differences between surviving and fatal cases. Compared to model for end-stage liver disease scores, principal component analysis appear to be better as an early prognostic indicator. Biochemical mapping of pathways suggested interruptions in amino acid metabolism and urea cycle.

CONCLUSIONS

Proton nuclear magnetic resonance studies of serum have the potential of rapidly identifying patients with irreversible fulminant hepatic failure requiring liver transplantation as life saving option.

Comparison of the metabolic profiling of hepatitis B virus-infected cirrhosis and alcoholic cirrhosis patients by using (1) H NMR-based metabonomics

AIM

  The aims of the present study were to depict the serum metabolic characteristics of hepatitis B virus (HBV)-infected cirrhosis and alcoholic cirrhosis patients, and to find the specific serum biomarkers associated with the diseases.

METHODS

  A pilot metabolic profiling study was conducted using three groups: HBV-infected cirrhosis patients (n = 21), alcoholic cirrhosis patients (n = 20) and healthy controls (n = 20). (1) H nuclear magnetic resonance (NMR)-based metabonomics was used to obtain the serum metabolic profiles of the samples. The acquired data were processed by multivariate principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA). The discriminatory metabolites between HBV-infected cirrhosis and alcoholic cirrhosis were further validated by classical biochemical assays.

RESULTS

  The OPLS-DA model was capable of distinguishing between HBV-infected and alcoholic cirrhosis patients. Five metabolites, creatine, acetoacetate, isobutyrate, glutamine and glutamate, were identified as the most influential factors to compare HBV-infected cirrhosis and alcoholic cirrhosis. The validation tests showed that the changes of the five metabolites were well coincident with the results of NMR.

CONCLUSION

  NMR spectra combined with pattern recognition analysis techniques may provide a new way to explore the pathogenesis of HBV-infected and alcoholic cirrhosis patients.

Modulation of astrocytic mitochondrial function by dichloroacetate improves survival and motor performance in inherited amyotrophic lateral sclerosis

Mitochondrial dysfunction is one of the pathogenic mechanisms that lead to neurodegeneration in Amyotrophic Lateral Sclerosis (ALS). Astrocytes expressing the ALS-linked SOD1(G93A) mutation display a decreased mitochondrial respiratory capacity associated to phenotypic changes that cause them to induce motor neuron death. Astrocyte-mediated toxicity can be prevented by mitochondria-targeted antioxidants, indicating a critical role of mitochondria in the neurotoxic phenotype. However, it is presently unknown whether drugs currently used to stimulate mitochondrial metabolism can also modulate ALS progression. Here, we tested the disease-modifying effect of dichloroacetate (DCA), an orphan drug that improves the functional status of mitochondria through the stimulation of the pyruvate dehydrogenase complex activity (PDH). Applied to astrocyte cultures isolated from rats expressing the SOD1(G93A) mutation, DCA reduced phosphorylation of PDH and improved mitochondrial coupling as expressed by the respiratory control ratio (RCR). Notably, DCA completely prevented the toxicity of SOD1(G93A) astrocytes to motor neurons in coculture conditions. Chronic administration of DCA (500 mg/L) in the drinking water of mice expressing the SOD1(G93A) mutation increased survival by 2 weeks compared to untreated mice. Systemic DCA also normalized the reduced RCR value measured in lumbar spinal cord tissue of diseased SOD1(G93A) mice. A remarkable effect of DCA was the improvement of grip strength performance at the end stage of the disease, which correlated with a recovery of the neuromuscular junction area in extensor digitorum longus muscles. Systemic DCA also decreased astrocyte reactivity and prevented motor neuron loss in SOD1(G93A) mice. Taken together, our results indicate that improvement of the mitochondrial redox status by DCA leads to a disease-modifying effect, further supporting the therapeutic potential of mitochondria-targeted drugs in ALS.

1H NMR-based serum metabolic profiling in compensated and decompensated cirrhosis

AIM: To study the metabolic profiling of serum samples from compensated and decompensated cirrhosis patients.

METHODS: A pilot metabolic profiling study was conducted using three groups: compensated cirrhosis patients (n = 30), decompensated cirrhosis patients (n = 30) and healthy controls (n = 30). A ¹H nuclear magnetic resonance (NMR)-based metabonomics approach was used to obtain the serum metabolic profiles of the samples. The acquired data were processed by multivariate principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA).

RESULTS: The OPLS-DA model was capable of distinguishing between decompensated and compensated cirrhosis patients, with an R²Y of 0.784 and a Q²Y of 0.598. Twelve metabolites, such as pyruvate, phenylalanine and succinate, were identified as the most influential factors for the difference between the two groups. The validation of the diagnosis prediction showed that the accuracy of the OPLS-DA model was 85% (17/20).

CONCLUSION: ¹H NMR spectra combined with pattern recognition analysis techniques offer a new way to diagnose compensated and decompensated cirrhosis in the future.

A proton nuclear magnetic resonance-based metabonomics study of metabolic profiling in immunoglobulin a nephropathy

OBJECTIVES

Immunoglobulin A nephropathy is the most common cause of chronic renal failure among primary glomerulonephritis patients. The ability to diagnose immunoglobulin A nephropathy remains poor. However, renal biopsy is an inconvenient, invasive, and painful examination, and no reliable biomarkers have been developed for use in routine patient evaluations. The aims of the present study were to identify immunoglobulin A nephropathy patients, to identify useful biomarkers of immunoglobulin A nephropathy and to establish a human immunoglobulin A nephropathy metabolic profile.

METHODS

Serum samples were collected from immunoglobulin A nephropathy patients who were not using immunosuppressants. A pilot study was undertaken to determine disease-specific metabolite biomarker profiles in three groups: healthy controls (N = 23), low-risk patients in whom immunoglobulin A nephropathy was confirmed as grades I-II by renal biopsy (N = 23), and high-risk patients with nephropathies of grades IV-V (N = 12). Serum samples were analyzed using proton nuclear magnetic resonance spectroscopy and by applying multivariate pattern recognition analysis for disease classification.

RESULTS

Compared with the healthy controls, both the low-risk and high-risk patients had higher levels of phenylalanine, myo-Inositol, lactate, L6 lipids ( = CH-CH2-CH = O), L5 lipids (-CH2-C = O), and L3 lipids (-CH2-CH2-C = O) as well as lower levels of β -glucose, α-glucose, valine, tyrosine, phosphocholine, lysine, isoleucine, glycerolphosphocholine, glycine, glutamine, glutamate, alanine, acetate, 3-hydroxybutyrate, and 1-methylhistidine.

CONCLUSIONS

These metabolites investigated in this study may serve as potential biomarkers of immunoglobulin A nephropathy. Point scoring of pattern recognition analysis was able to distinguish immunoglobulin A nephropathy patients from healthy controls. However, there were no obvious differences between the low-risk and high-risk groups in our research. These results offer new, sensitive and specific, noninvasive approaches that may be of great benefit to immunoglobulin A nephropathy patients by enabling earlier diagnosis.

1H NMR-based metabolomic study of metabolic profiling for systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic inflammatory disease characterized by multi-system involvement, diverse clinical presentation, and alterations in circulating metabolites. In this study, a 1H NMR spectroscopy-based metabolomics approach was applied to establish a human SLE serum metabolic profile. Serum samples were obtained from patients with SLE ( n = 64), patients with rheumatoid arthritis (RA) ( n = 30) and healthy controls ( n = 35). The NOESYPR1D spectrum combined with multi-variate pattern recognition analysis was used to cluster the groups and establish a disease-specific metabolites phenotype. Principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) models were capable of distinguishing SLE or RA patients from healthy subjects. The OPLS-DA model was able to predict diagnosis of SLE with a sensitivity rate of 60.9% and a specificity rate of 97.1%. For diagnosing RA, the model has much higher sensitivity (96.7%) and specificity (91.4%). The SLE serum samples were characterized by reduced concentrations of valine, tyrosine, phenylalanine, lysine, isoleucine, histidine, glutamine, alanine, citrate, creatinine, creatine, pyruvate, high-density lipoprotein, cholesterol, glycerol, formate and increased concentrations of N-acetyl glycoprotein, very low-density lipoprotein and low-density lipoprotein in comparison with the control population. Theresults not only indicated that serum NMR-based metabolomic methods had sufficient sensitivity and specificity to distinguish SLE and RA from healthy controls, but also have the potential to be developed into a clinically useful diagnostic tool, and could also contribute to a further understanding of disease mechanisms.

Serum metabolic profiling and features of papillary thyroid carcinoma and nodular goiter

Thyroid carcinoma is a common endocrine malignancy worldwide, accounting for approximately 1% of all diagnosed cancers and about 91.5% of the malignancies of head and neck. However, differentiating malignant thyroid nodules from benign ones remains a diagnostic challenge. Thus, novel molecular markers that enable non-invasive diagnostics for malignant thyroid nodules are urgently needed. In the present study, a metabonomic investigation based on liquid chromatography-LTQ Orbitrap mass spectrometry was employed for serum metabolic profiling of 30 cases of papillary thyroid carcinomas (PTC), 80 cases of nodular goiters (benign thyroid nodules) and 30 cases of healthy controls. According to the results of multivariate statistical data analysis, the significantly changed metabolites among these three groups were defined. It was found that most of these metabolites decreased in the sera of both malignant and benign thyroid cases due to the increased metabolic rate, which is in accordance with clinical features. The major metabolic differences between benign and malignant nodules occurred in lipid metabolism. Especially, the content of 3-hydroxybutyric acid, an intermediate product of fatty acid metabolism, was much higher in the PTC group than that in the nodule goiter and control groups, indicating its potential as a diagnostic marker for PTC and nodular goiters. These results show that the serum metabolic profiling method is a powerful tool for distinguishing thyroid carcinoma from nodular goiter and healthy controls.

The autophagic tumor stroma model of cancer: Role of oxidative stress and ketone production in fueling tumor cell metabolism

A loss of stromal Cav-1 in the tumor fibroblast compartment is associated with early tumor recurrence, lymph-node metastasis, and tamoxifen-resistance, resulting in poor clinical outcome in breast cancer patients. Here, we have used Cav-1 (-/-) null mice as a pre-clinical model for this "lethal tumor micro-environment." Metabolic profiling of Cav-1 (-/-) mammary fat pads revealed the upregulation of numerous metabolites (nearly 100), indicative of a major catabolic phenotype. Our results are consistent with the induction of oxidative stress, mitochondrial dysfunction, and autophagy/mitophagy. The two most prominent metabolites that emerged from this analysis were ADMA (asymmetric dimethyl arginine) and BHB (beta-hydroxybutyrate; a ketone body), which are markers of oxidative stress and mitochondrial dysfunction, respectively. Transcriptional profiling of Cav-1 (-/-) stromal cells and human tumor stroma from breast cancer patients directly supported an association with oxidative stress, mitochondrial dysfunction, and autophagy/mitophagy, as well as ADMA and ketone production. MircoRNA profiling of Cav-1 (-/-) stromal cells revealed the upregulation of two key cancer-related miR's, namely miR-31 and miR-34c. Consistent with our metabolic findings, these miR's are associated with oxidative stress (miR-34c) or activation of the hypoxic response/HIF1a (miR-31), which is sufficient to drive authophagy/mitophagy. Thus, via an unbiased comprehensive analysis of a lethal tumor micro-environment, we have identified a number of candidate biomarkers (ADMA, ketones, and miR-31/34c) that could be used to identify high-risk cancer patients at diagnosis, for treatment stratification and/or for evaluating therapeutic efficacy during anti-cancer therapy. We propose that the levels of these key biomarkers (ADMA, ketones/BHB, miR-31, and miR-34c) could be (1) assayed using serum or plasma from cancer patients, or (2) performed directly on excised tumor tissue. Importantly, induction of oxidative stress and autophagy/mitophagy in the tumor stromal compartment provides a means by which epithelial cancer cells can directly "feed off" of stromal-derived essential nutrients, chemical building blocks (amino acids, nucleotides), and energy-rich metabolites (glutamine, pyruvate, ketones/BHB), driving tumor progression and metastasis. Essentially, aggressive cancer cells are "eating" the cancer-associated fibroblasts via autophagy/mitophagy in the tumor micro-environment. Lastly, we discuss that this "Autophagic Tumor Stroma Model of Cancer Metabolism" provides a viable solution to the "Autophagy Paradox" in cancer etiology and chemo-therapy.

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

Background

Pathophysiological mechanisms involved in amyotrophic lateral sclerosis (ALS) are complex and none has identified reliable markers useful in routine patient evaluation. The aim of this study was to analyze the CSF of patients with ALS by ¹H NMR (Nuclear Magnetic Resonance) spectroscopy in order to identify biomarkers in the early stages of the disease, and to evaluate the biochemical factors involved in ALS.

Methodology

CSF samples were collected from patients with ALS at the time of diagnosis and from patients without neurodegenerative diseases. One and two-dimensional ¹H NMR analyses were performed and metabolites were quantified by the ERETIC method. We compared the concentrations of CSF metabolites between both groups. Finally, we performed principal component (PCA) and discriminant analyses.

Principal Findings

Fifty CSF samples from ALS patients and 44 from controls were analyzed. We quantified 17 metabolites including amino-acids, organic acids, and ketone bodies. Quantitative analysis revealed significantly lower acetate concentrations (p = 0.0002) in ALS patients compared to controls. Concentration of acetone trended higher (p = 0.015), and those of pyruvate (p = 0.002) and ascorbate (p = 0.003) were higher in the ALS group. PCA demonstrated that the pattern of analyzed metabolites discriminated between groups. Discriminant analysis using an algorithm of 17 metabolites revealed that patients were accurately classified 81.6% of the time.

Conclusion/Significance

CSF screening by NMR spectroscopy could be a useful, simple and low cost tool to improve the early diagnosis of ALS. The results indicate a perturbation of glucose metabolism, and the need to further explore cerebral energetic metabolism.