Sylvie Mavel

Metabolomics in cerebrospinal fluid of patients with amyotrophic lateral sclerosis: an untargeted approach via high-resolution mass spectrometry.

Amyotrophic lateral sclerosis (ALS) is characterized by the absence of reliable diagnostic biomarkers. The aim of the study was to (i) devise an untargeted metabolomics methodology that reliably compares cerebrospinal fluid (CSF) from ALS patients and controls by liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS); (ii) ascertain a metabolic signature of ALS by use of the LC-HRMS platform; (iii) identify metabolites for use as diagnostic or pathophysiologic markers. We developed a method to analyze CSF components by UPLC coupled with a Q-Exactive mass spectrometer that uses electrospray ionization. Metabolomic profiles were created from the CSF obtained at diagnosis from ALS patients and patients with other neurological conditions. We performed multivariate analyses (OPLS-DA) and univariate analyses to assess the contribution of individual metabolites as well as compounds identified in other studies. Sixty-six CSF samples from ALS patients and 128 from controls were analyzed. Metabolome analysis correctly predicted the diagnosis of ALS in more than 80% of cases. OPLS-DA identified four features that discriminated diagnostic group (p < 0.004). Our data demonstrate that untargeted metabolomics with LC-HRMS is a robust procedure to generate a specific metabolic profile for ALS from CSF and could be an important aid to the development of biomarkers for the disease.

Influence of 2-substituent on the activity of imidazo[1,2-a] pyridine derivatives against human cytomegalovirus.

The synthesis of various 2-substituted imidazo[1,2-a]pyridine bearing a thioether side chain in position 3 was reported. The new compounds were characterized by 1H and 13C NMR spectra. A conformational study was obtained by X-ray crystallographic analysis for 2-biphen-4-ylimidazopyridine 7. The antiviral activity against human cytomegalovirus (HCMV) was investigated. It was strongly influenced by the nature of C-2 substituent.

1H–13C NMR-based urine metabolic profiling in autism spectrum disorders

Autism Spectrum Disorders (ASD) are a group of developmental disorders caused by environmental and genetic factors. Diagnosis is based on behavioral and developmental signs detected before 3 years of age with no reliable biological marker. The purpose of this study was to evaluate the potential use of a 2D NMR-based approach to express the global biochemical signature of autistic individuals compared to normal controls. This technique has greater spectral resolution than to 1D (1)H NMR spectroscopy, which is limited by overlapping signals. The urinary metabolic profiles of 30 autistic and 28 matched healthy children were obtained using a (1)H-(13)C NMR-based approach. The data acquired were processed by multivariate orthogonal partial least-squares discriminant analysis (OPLS-DA). Some discriminating metabolites were identified: β-alanine, glycine, taurine and succinate concentrations were significatively higher, and creatine and 3-methylhistidine concentrations were lower in autistic children than in controls. We also noted differences in several other metabolites that were unidentified but characterized by a cross peak correlation in (1)H-(13)C HSQC. Statistical models of (1)H and (1)H-(13)C analyses were compared and only 2D spectra allowed the characterization of statistically relevant changes [R(2)Y(cum)=0.78 and Q(2)(cum)=0.60] in the low abundance metabolites. This method has the potential to contribute to the diagnosis of neurodevelopment disorders but needs to be validated on larger cohorts and on other developmental disorders to define its specificity.

Metabolomics Study of Urine in Autism Spectrum Disorders Using a Multiplatform Analytical Methodology

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with no clinical biomarker. The aims of this study were to characterize a metabolic signature of ASD and to evaluate multiplatform analytical methodologies in order to develop predictive tools for diagnosis and disease follow-up. Urine samples were analyzed using (1)H and (1)H-(13)C NMR-based approaches and LC-HRMS-based approaches (ESI+ and ESI- on HILIC and C18 chromatography columns). Data tables obtained from the six analytical modalities on a training set of 46 urine samples (22 autistic children and 24 controls) were processed by multivariate analysis (orthogonal partial least-squares discriminant analysis, OPLS-DA). The predictions from each of these OPLS-DA models were then evaluated using a prediction set of 16 samples (8 autistic children and 8 controls) and receiver operating characteristic curves. Thereafter, a data fusion block-scaling OPLS-DA model was generated from the 6 best models obtained for each modality. This fused OPLS-DA model showed an enhanced performance (R(2)Y(cum) = 0.88, Q(2)(cum) = 0.75) compared to each analytical modality model, as well as a better predictive capacity (AUC = 0.91, p-value = 0.006). Metabolites that are most significantly different between autistic and control children (p < 0.05) are indoxyl sulfate, N-α-acetyl-l-arginine, methyl guanidine, and phenylacetylglutamine. This multimodality approach has the potential to contribute to find robust biomarkers and characterize a metabolic phenotype of the ASD population.

Synthesis of imidazo[2,1-a]phthalazines, potential inhibitors of p38 MAP kinase. Prediction of binding affinities of protein ligands.

Based upon molecular modeling, the pharmacophore of potential inhibitors of p38 MAPK (mitogen‐activated protein kinases) is discussed and the predictive binding affinities are calculated. Syntheses of original diarylimidazo[2, 1‐a]phthalazines obtained by Suzuki coupling are described.

Untargeted 1H-NMR metabolomics in CSF Toward a diagnostic biomarker for motor neuron disease

Objectives: To develop a CSF metabolomics signature for motor neuron disease (MND) using 1H-NMR spectroscopy and to evaluate the predictive value of the profile in a separate cohort. Methods: We collected CSF from patients with MND and controls and analyzed the samples using 1H-NMR spectroscopy. We divided the total patient sample in a 4:1 ratio into a training cohort and a test cohort. First, a metabolomics signature was created by statistical modeling in the training cohort, and then the analyses tested the predictive value of the signature in the test cohort. We conducted 10 independent trials for each step. Finally, we identified the compounds that contributed most consistently to the metabolome profile. Results: Analysis of CSF from 95 patients and 86 controls identified a diagnostic profile for MND (R2X > 22%, R2Y > 93%, Q2 > 66%). The best model selected the correct diagnosis with mean probability of 99.31% in the training cohort. The profile discriminated between diagnostic groups with 78.9% sensitivity and 76.5% specificity in the test cohort. Metabolites linked to pathophysiologic pathways in MND (i.e., threonine, histidine, and molecules related to the metabolism of branched amino acids) were among the discriminant compounds. Conclusion: CSF metabolomics using 1H-NMR spectroscopy can detect a reproducible metabolic signature for MND with reasonable performance. To our knowledge, this is the first metabolomics study that shows that a validation in separate cohorts is feasible. These data should be considered in future biomarker studies. Classification of evidence: This study provides Class III evidence that CSF metabolomics accurately distinguishes MNDs from other neurologic diseases.

3D QSAR study, synthesis, and in vitro evaluation of (+)-5-FBVM as potential PET radioligand for the vesicular acetylcholine transporter (VAChT)

Located in presynaptic cholinergic nerve terminals, the vesicular acetylcholine transporter (VAChT) represents a potential target for quantitative visualization of early degeneration of cholinergic neurons in Alzheimers disease using PET. Benzovesamicol derivatives are proposed as radioligands for this purpose. We report QSAR studies of vesamicol and benzovesamicol derivatives taking into account the stereoselectivity of the VAChT binding site. Use of different data sets and different models in this study revealed that both enantiomers of 5-fluoro-3-(4-phenyl-piperidin-1-yl)-1,2,3,4-tetrahydro-naphthalen-2-ol (5-FBVM) are promising candidates, with predicted VAChT affinities between 6.1 and 0.05 nM. The synthesis of enantiopure (R,R)- and (S,S)-5-FBVM and their corresponding triazene precursors for future radiofluorination is reported. Both enantiomers exhibited high in vitro affinity for VAChT [(+)-5-FBVM: K(i)=6.95 nM and (-)-5-FBVM: K(i)=3.68 nM] and were selective for σ(2) receptors (∼70-fold), only (+)-5-FBVM is selective for σ(1) receptors (∼fivefold). These initial results suggest that (+)-(S,S)-5-FBVM warrants further investigation as a potential radioligand for in vivo PET imaging of cholinergic nerve terminals.

NSC-34 Motor Neuron-Like Cells Are Unsuitable as Experimental Model for Glutamate-Mediated Excitotoxicity

Glutamate-induced excitotoxicity is a major contributor to motor neuron degeneration in the pathogenesis of amyotrophic lateral sclerosis (ALS). The spinal cord × Neuroblastoma hybrid cell line (NSC-34) is often used as a bona fide cellular model to investigate the physiopathological mechanisms of ALS. However, the physiological response of NSC-34 to glutamate remains insufficiently described. In this study, we evaluated the relevance of differentiated NSC-34 (NSC-34D) as an in vitro model for glutamate excitotoxicity studies. NSC-34D showed morphological and physiological properties of motor neuron-like cells and expressed glutamate receptor subunits GluA1–4, GluN1 and GluN2A/D. Despite these diverse characteristics, no specific effect of glutamate was observed on cultured NSC-34D survival and morphology, in contrast to what has been described in primary culture of motor neurons (MN). Moreover, a small non sustained increase in the concentration of intracellular calcium was observed in NSC-34D after exposure to glutamate compared to primary MN. Our findings, together with the inability to obtain cultures containing only differentiated cells, suggest that the motor neuron-like NSC-34 cell line is not a suitable in vitro model to study glutamate-induced excitotoxicity. We suggest that the use of primary cultures of MN is more suitable than NSC-34 cell line to explore the pathogenesis of glutamate-mediated excitotoxicity at the cellular level in ALS and other motor neuron diseases.

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

Biomarkers in amyotrophic lateral sclerosis: combining metabolomic and clinical parameters to define disease progression

The objectives of this study were to define the metabolomic profile of cerebrospinal fluid in amyotrophic lateral sclerosis (ALS) patients, to model outcome through combined clinical and metabolomic parameters and independently to validate predictive models.