NMR-based Metabonomics of Cerebrospinal Fluid Applied to Amyotrophic Lateral Sclerosis

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.

The Relationship between Gut Microbiome and Cognition in Older Australians

Ageing is associated with changes in biological processes, including reductions in cognitive functions and gut microbiome diversity. However, not much is known about the relationship between cognition and the microbiome with increasing age. Therefore, we examined the relationship between the gut microbiome and cognition in 69 healthy participants aged 60–75 years. The gut microbiome was analysed with the 16S rRNA sequencing method. The cognitive assessment included the Cognitive Drug Research computerised assessment battery, which produced five cognitive factors corresponding to ‘Quality of Episodic Secondary Memory’, ‘Quality of Working Memory’, ‘Continuity of Attention, ‘Speed of Memory’ and ‘Power of Concentration’. Multiple linear regression showed that the bacterial family Carnobacteriaceae explained 9% of the variance in predicting Quality of Episodic Secondary Memory. Alcaligenaceae and Clostridiaceae explained 15% of the variance in predicting Quality of Working Memory; Bacteroidaceae, Barnesiellaceae, Rikenellaceae and Gemellaceae explained 11% of the variance in Power of Concentration. The present study provides specific evidence of a relationship between specific families of bacteria and different domains of cognition.

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.

Changes in the metabolic profiles of the serum and putamen in Parkinson's disease patients - In vitro and in vivo NMR spectroscopy studies

The aim of this study was to investigate the relationship between serum metabolomic biomarkers and brain in vivo magnetic resonance spectroscopy (MRS) biomarkers in patients with Parkinson's disease (PD) as well as to investigate compound concentration changes by comparing the results with healthy control subjects. Univariate statistical analysis of the serum showed significant differences in the levels of phenylalanine, tyrosine, lysine, glutamine, glutamate, acetone, acetate, 3-hydroxybutyrate, and 1-monoacylglycerol (1-MAG) between the PD patient group and the control group. Orthogonal partial least squares discriminant analysis showed significantly different compound concentrations of acetate, 3-hydroxybutyrate, glutamine, tyrosine, 1-MAG and testosterone. In vivo MRS of the putamen showed significantly higher concentrations of glutamine/glutamate complex and glutamine in patients with PD in comparison to control subjects. Following disrupted metabolic pathways in patients with PD were identified: dopamine synthesis, steroid hormone biosynthesis, fatty acid biosynthesis, the synthesis and degradation of ketone bodies, the metabolism of pyruvate, arginine, proline, alanine, aspartate, glutamate, tyrosine and phenylalanine. The obtained results may indicate changes in neurotransmission, disturbances in energy production and an altered cell membrane structure.

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.

Glutamate, Glutamine and GABA Levels in Rat Brain Measured Using MRS, HPLC and NMR Methods in Study of Two Models of Autism

The disorders of the glutamatergic neurotransmission have been associated with pathogenesis of autism. In this study we evaluated the impact of the in vivo and ex vivo test methodology on measurements of levels of neurotransmitter amino acids in hippocampus of rats for valproic acid- (VPA) and thalidomide- (THAL) induced models of autism. The main goal was to compare the changes in concentrations of glutamate (Glu), glutamine (Gln) and GABA between both autistic groups and the control, measured in vivo and ex vivo in homogenates. The rat pups underwent three in vivo tests: ultrasonic vocalization (USV), magnetic resonance spectroscopy (MRS) and unilateral microdialysis of the hippocampus. Analyses of homogenates of rat hippocampus were performed using high-performance liquid chromatography (HPLC) and nuclear magnetic resonance (NMR) spectroscopy. For the statistical analysis, we performed univariate and multivariate tests. USV test, which is considered in rodents as an indicator of pathology similar to autism, showed decreased USV in VPA and THAL groups. In vivo MRS studies demonstrated increases of Glu content in male rat's hippocampus in VPA and THAL groups, while the microdialysis, which allows examination of the contents in the extracellular space, detected decreases in the basal level of Gln concentrations in VPA and THAL groups. Ex vivo HPLC studies showed that levels of Glu, Gln and GABA significantly increased in male rat's hippocampus in the VPA and THAL groups, while NMR studies showed increased levels of Gln and GABA in the VPA group. Collectively, these results are consistent with the hypothesis suggesting the role of the glutamatergic disturbances on the pathogenesis of autism. For all methods used, the values of measured changes were in the same direction. The orthogonal partial least square discriminant analysis confirmed that both animal models of autism tested here can be used to trace neurochemical changes in the brain.

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.