Serum amino acid profile in patients with Parkinson's disease

Bioinformatics gene analysis for potential biomarkers and therapeutic targets of Parkinson's disease based on neutrophil extracellular traps

Introduction

Neutrophil extracellular traps (NETs) provide key innate immune mechanisms, and studies have shown innate immunity and adaptive immunity are directly linked to Parkinson's disease (PD) pathology. However, limited research has been conducted on NETs in the context of PD.

Methods

A differential analysis was implemented to acquire differentially expressed genes (DEGs) between PD and control as well as between high- and low-score groups determined by a gene set variation analysis (GSVA). Then, the genes within the critical module, obtained through a weighted gene co-expression network analysis (WGCNA), were intersected with the DEGs to identify the overlapping genes. Then, five kinds of algorithms in the protein-protein interaction (PPI) were performed to identify potential biomarkers. Subsequently, a nomogram for forecasting PD probability was created. An enrichment analysis and an immune infiltration analysis were performed on the identified biomarkers. qRT-PCR was performed to validate the expression trends of three biomarkers.

Results

We revealed 798 DEGs between PD and control groups as well as 168 DEGs between high- and low-score groups obtained by differential analyses. The pink module containing 926 genes was identified as the critical module. According to the intersection of these gene sets, a total of 43 overlapping genes were screened out. Furthermore, GPR78, CADM3, and CACNA1E were confirmed as biomarkers. Moreover, we found that biomarkers mainly participated in pathways, such as the 'hydrogen peroxide catabolic process', and 'cell cycle'; five kinds of differential immune cells between PD and control groups were identified. Finally, the qRT-PCR analysis demonstrated the up-regulation of GPR78, CADM3, and CACNA1E in the PD group.

Discussion

Our study authenticated GPR78, CADM3, and CACNA1E as the biomarkers associated with PD. These findings provide an original reference for the diagnosis and treatment of PD.

Multi-omics integration of scRNA-seq time series data predicts new intervention points for Parkinson's disease

Parkinson's disease (PD) is a complex neurodegenerative disorder without a cure. The onset of PD symptoms corresponds to 50% loss of midbrain dopaminergic (mDA) neurons, limiting early-stage understanding of PD. To shed light on early PD development, we study time series scRNA-seq datasets of mDA neurons obtained from patient-derived induced pluripotent stem cell differentiation. We develop a new data integration method based on Non-negative Matrix Tri-Factorization that integrates these datasets with molecular interaction networks, producing condition-specific "gene embeddings". By mining these embeddings, we predict 193 PD-related genes that are largely supported (49.7%) in the literature and are specific to the investigated PINK1 mutation. Enrichment analysis in Kyoto Encyclopedia of Genes and Genomes pathways highlights 10 PD-related molecular mechanisms perturbed during early PD development. Finally, investigating the top 20 prioritized genes reveals 12 previously unrecognized genes associated with PD that represent interesting drug targets.

Nontargeted metabolomics reveals sequential changes in amino acid and ferroptosis-related metabolism in Parkinson's disease

Parkinson's disease (PD) is inseparable from metabolic disorders but lacks assessment of specific metabolite alteration. To explore the sequential metabolic changes in PD progression, we evenly divided 78 C57BL/6 mice (10 weeks) into six groups (one control group and five experimental groups) and collected the hippocampus tissue of mice after treating with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine, and probenecid (twice a week) at five periods (1, 2, 3, 4, and 5 weeks) for metabolome analysis. Our study identified 567 differentially abundant metabolites (DAMs) (total 4348 metabolites). Compared with controls, 145, 146, 171, 208, and 213 DAMs were obtained from the five experimental groups, respectively. Notably, 40 shared DAMs were present in five experimental groups, of which 22 shared DAMs formed a new metabolic network based on amino acid metabolism. Compared with group W3, 84 DAMs were identified in group W5, including 12 unique DAMs. DAMs in different stages of PD were significantly enriched in amino acid metabolism pathway, lipid metabolism pathway, and ferroptosis pathway. l-Glutamine, spermidine, and l-tryptophan were the key hubs in the whole metabolic process of PD. N-Formyl-l-methionine gradually increased in abundance with PD progression, whereas 5-methylcytosine gradually decreased. The study emphasized the sequential changes in DAMs in PD progression, stimulating subsequent studies.

Blood D-serine levels correlate with aging and dopaminergic treatment in Parkinson's disease

We recently described increased D- and L-serine concentrations in the striatum of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-treated monkeys, the post-mortem caudate-putamen of human Parkinson's disease (PD) brains and the cerebrospinal fluid (CSF) of de novo living PD patients. However, data regarding blood D- and L-serine levels in PD are scarce. Here, we investigated whether the serum profile of D- and L-serine, as well as the other glutamate N-methyl-D-aspartate ionotropic receptor (NMDAR)-related amino acids, (i) differs between PD patients and healthy controls (HC) and (ii) correlates with clinical-demographic features and levodopa equivalent daily dose (LEDD) in PD. Eighty-three consecutive PD patients and forty-one HC were enrolled. PD cohort underwent an extensive clinical characterization. Serum levels of D- and L-serine, L-glutamate, L-glutamine, L-aspartate, L-asparagine and glycine were determined using High Performance Liquid Chromatography. In age- and sex-adjusted analyses, no differences emerged in the serum levels of D-serine, L-serine and other NMDAR-related amino acids between PD and HC. However, we found that D-serine and D-/Total serine ratio positively correlated with age in PD but not in HC, and also with PD age at onset. Moreover, we found that higher LEDD correlated with lower levels of D-serine and the other excitatory amino acids. Following these results, the addition of LEDD as covariate in the analyses disclosed a selective significant increase of D-serine in PD compared to HC (Δ ≈ 38%). Overall, these findings suggest that serum D-serine and D-/Total serine may represent a valuable biochemical signature of PD.

Rubusoside mitigates neuroinflammation and cellular apoptosis in Parkinson's disease, and alters gut microbiota and metabolite composition

BACKGROUND

Parkinson's disease (PD) is a neurodegenerative condition characterized by the progressive loss of dopaminergic neurons within the substantia nigra. Neuroinflammation plays a pivotal role in the pathogenesis of PD, involving the activation of microglia cells, heightened production of proinflammatory cytokines, and perturbations in the composition of the gut microbiota. Rubusoside (Ru), the principal steviol bisglucoside present in Rubus chingii var. suavissimus (S.K.Lee) L.T.Lu (Rosaceae), has been documented for its anti-inflammatory properties in diverse disease models. Nonetheless, there is an imperative need to comprehensively assess and elucidate the protective and anti-inflammatory attributes of Ru concerning PD, as well as to uncover the underlying mechanism involved.

OBJECTIVE

The aim of this study is to evaluate the neuroprotective and anti-inflammatory effects of Ru on PD and investigate its potential mechanisms associated with microbes.

RESEARCH DESIGN AND METHODS

We pre-treated mice and cell lines with Ru in order to simulate the progression of PD and the neuroinflammatory state. The mouse model was induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), SN4741 cells were induced by 1-methyl-4-phenylpyridine (mpp+), and BV-2 cells were induced by lipopolysaccharide (LPS). We assessed the impact of Ru on motor function, neuroinflammation, neuron apoptosis, the composition of gut microbes, and their metabolites.

RESULTS

Ru treatment reduces the release of pro-inflammatory mediators by inhibiting microglia activation. It also prevents neuronal apoptosis, thereby safeguarding dopaminergic neurons and ameliorating motor dysfunction. Furthermore, it induces alterations in the fecal microbiota composition and metabolites profile in PD mice. In vitro experiments have demonstrated that Ru inhibits neuronal apoptosis in SN4741 cells induced by mpp+, suppresses the production of pro-inflammatory mediators, and activates the c-Jun N-terminal kinase (JNK), mitogen-activated protein kinase (p38 MAPK), and nuclear factor kappa-B (NF-κB) signaling pathways.

CONCLUSION

Ru exhibits inhibitory effects on the MPTP-induced PD model by mitigating neuroinflammation and neuronal apoptosis while also inducing changes in the gut microbiota and metabolite composition.

A Review from a Clinical Perspective: Recent Advances in Biosensors for the Detection of L-Amino Acids

The field of biosensors is filled with reports and designs of various sensors, with the vast majority focusing on glucose sensing. However, in addition to glucose, there are many other important analytes that are worth investigating as well. In particular, L-amino acids appear as important diagnostic markers for a number of conditions. However, the progress in L-amino acid detection and the development of biosensors for L-amino acids are still somewhat insufficient. In recent years, the need to determine L-amino acids from clinical samples has risen. More clinical data appear to demonstrate that abnormal concentrations of L-amino acids are related to various clinical conditions such as inherited metabolic disorders, dyslipidemia, type 2 diabetes, muscle damage, etc. However, to this day, the diagnostic potential of L-amino acids is not yet fully established. Most likely, this is because of the difficulties in measuring L-amino acids, especially in human blood. In this review article, we extensively investigate the 'overlooked' L-amino acids. We review typical levels of amino acids present in human blood and broadly survey the importance of L-amino acids in most common conditions which can be monitored or diagnosed from changes in L-amino acids present in human blood. We also provide an overview of recent biosensors for L-amino acid monitoring and their advantages and disadvantages, with some other alternative methods for L-amino acid quantification, and finally we outline future perspectives related to the development of biosensing devices for L-amino acid monitoring.

Untargeted serum metabolomics reveals novel metabolite associations and disruptions in amino acid and lipid metabolism in Parkinson's disease

BACKGROUND

Untargeted high-resolution metabolomic profiling provides simultaneous measurement of thousands of metabolites. Metabolic networks based on these data can help uncover disease-related perturbations across interconnected pathways.

OBJECTIVE

Identify metabolic disturbances associated with Parkinson's disease (PD) in two population-based studies using untargeted metabolomics.

METHODS

We performed a metabolome-wide association study (MWAS) of PD using serum-based untargeted metabolomics data derived from liquid chromatography with high-resolution mass spectrometry (LC-HRMS) using two distinct population-based case-control populations. We also combined our results with a previous publication of 34 metabolites linked to PD in a large-scale, untargeted MWAS to assess external validation.

RESULTS

LC-HRMS detected 4,762 metabolites for analysis (HILIC: 2716 metabolites; C18: 2046 metabolites). We identified 296 features associated with PD at FDR<0.05, 134 having a log2 fold change (FC) beyond ±0.5 (228 beyond ±0.25). Of these, 104 were independently associated with PD in both discovery and replication studies at p<0.05 (170 at p<0.10), while 27 were associated with levodopa-equivalent dose among the PD patients. Intriguingly, among the externally validated features were the microbial-related metabolites, p-cresol glucuronide (FC=2.52, 95% CI=1.67, 3.81, FDR=7.8e-04) and p-cresol sulfate. P-cresol glucuronide was also associated with motor symptoms among patients. Additional externally validated metabolites associated with PD include phenylacetyl-L-glutamine, trigonelline, kynurenine, biliverdin, and pantothenic acid. Novel associations include the anti-inflammatory metabolite itaconate (FC=0.79, 95% CI=0.73, 0.86; FDR=2.17E-06) and cysteine-S-sulfate (FC=1.56, 95% CI=1.39, 1.75; FDR=3.43E-11). Seventeen pathways were enriched, including several related to amino acid and lipid metabolism.

CONCLUSIONS

Our results revealed PD-associated metabolites, confirming several previous observations, including for p-cresol glucuronide, and newly implicating interesting metabolites, such as itaconate. Our data also suggests metabolic disturbances in amino acid and lipid metabolism and inflammatory processes in PD.

Omics data integration suggests a potential idiopathic Parkinson's disease signature

The vast majority of Parkinson's disease cases are idiopathic. Unclear etiology and multifactorial nature complicate the comprehension of disease pathogenesis. Identification of early transcriptomic and metabolic alterations consistent across different idiopathic Parkinson's disease (IPD) patients might reveal the potential basis of increased dopaminergic neuron vulnerability and primary disease mechanisms. In this study, we combine systems biology and data integration approaches to identify differences in transcriptomic and metabolic signatures between IPD patient and healthy individual-derived midbrain neural precursor cells. Characterization of gene expression and metabolic modeling reveal pyruvate, several amino acid and lipid metabolism as the most dysregulated metabolic pathways in IPD neural precursors. Furthermore, we show that IPD neural precursors endure mitochondrial metabolism impairment and a reduced total NAD pool. Accordingly, we show that treatment with NAD precursors increases ATP yield hence demonstrating a potential to rescue early IPD-associated metabolic changes.

Orchestration of a blood-derived and ADARB1-centred network in Alzheimer's and Parkinson's disease

The peripheral immune system is thought to influence the pathogenesis of the central nervous system in Alzheimer's disease (AD) and Parkinson's disease (PD). This study aimed to investigate the characteristics of peripheral leukocytes in AD and PD by comprehensively analyzing the transcriptomic and metabolic features in the blood (NCONTROL = 15; NAD = 11; NPD = 13). The study found an ADARB1-centered module that was associated with diagnosis, phenethylamine, and glutamate. The module consisted of ADARB1, a vital RNA-editing enzyme, LINC02960, and 109 miRNAs. The study also predicted that the ADARB1 and involved regulators were targeted by miRNAs in the ADARB1 module. The integrated analysis of transcriptome and metabolic panel revealed a central role of ADARB1, miR-199b-5p, miR-26a, miR-450b-5p, miR-34c-5p, glutamate and phenethylamine in the regulatory relationships. The study highlights a set of synergetic non-coding RNA related to ADARB1 in the blood ecosystem of AD and PD with dynamic glutamate and phenethylamine, providing new insights into the pathogenesis of these diseases.

Serum amino acid profiles in patients with myasthenia gravis

Myasthenia gravis (MG) is an autoimmune disease characterized by weakness and rapid fatigue. Diagnostic methods used for myasthenia gravis are not conclusive and satisfactory, therefore it is necessary to develop reliable tools to help diagnose myasthenia gravis as early as possible. The aim of the study was to use HPLC-MS in conjunction with multivariate statistical analyses to investigate changes in the amino acid metabolic profiles between myasthenia gravis patients compared and controls. In addition, the effect of treatment regimens and myasthenia gravis type, on the observed changes in amino acid metabolic profiles were assessed. Serum levels of 29 amino acids were determined in 2 groups of individuals-28 patients with myasthenia gravis and 53 control subjects (CS). The results of our study indicate that serum levels of several amino acids in patients with myasthenia gravis changed significantly compared to the control group. Statistical analysis revealed differences between amino acids concentration in patients with different therapeutic scheme. In conclusion, amino acids may be involved in mechanisms underlying myasthenia gravis pathogenesis as well as may be potential biomarkers in MG patients diagnosis. However, considering the multifactorial, heterogenous and complex nature of this disease, validation on a larger study sample in further research is required before application into diagnostic practice.

Astrocytes Differentiated from LRRK2-I1371V Parkinson's-Disease-Induced Pluripotent Stem Cells Exhibit Similar Yield but Cell-Intrinsic Dysfunction in Glutamate Uptake and Metabolism, ATP Generation, and Nrf2-Mediated Glutathione Machinery

Owing to the presence of multiple enzymatic domains, LRRK2 has been associated with a diverse set of cellular functions and signaling pathways. It also has several pathological mutant-variants, and their incidences show ethnicity biases and drug-response differences with expression in dopaminergic-neurons and astrocytes. Here, we aimed to assess the cell-intrinsic effect of the LRRK2-I1371V mutant variant, prevalent in East Asian populations, on astrocyte yield and biology, involving Nrf2-mediated glutathione machinery, glutamate uptake and metabolism, and ATP generation in astrocytes derived from LRRK2-I1371V PD patient iPSCs and independently confirmed in LRRK2-I1371V-overexpressed U87 cells. Astrocyte yield (GFAP-immunopositive) was comparable between LRRK2-I1371V and healthy control (HC) populations; however, the astrocytic capability to mitigate oxidative stress in terms of glutathione content was significantly reduced in the mutant astrocytes, along with a reduction in the gene expression of the enzymes involved in glutathione machinery and nuclear factor erythroid 2-related factor 2 (Nrf2) expression. Simultaneously, a significant decrease in glutamate uptake was observed in LRRK2-I1371V astrocytes, with lower gene expression of glutamate transporters SLC1A2 and SLC1A3. The reduction in the protein expression of SLC1A2 was also directly confirmed. Enzymes catalyzing the generation of γ glutamyl cysteine (precursor of glutathione) from glutamate and the metabolism of glutamate to enter the Krebs cycle (α-ketoglutaric acid) were impaired, with significantly lower ATP generation in LRRK2-I1371V astrocytes. De novo glutamine synthesis via the conversion of glutamate to glutamine was also affected, indicating glutamate metabolism disorder. Our data demonstrate for the first time that the mutation in the LRRK2-I1371V allele causes significant astrocytic dysfunction with respect to Nrf2-mediated antioxidant machinery, AT -generation, and glutamate metabolism, even with comparable astrocyte yields.

Insight into Early Diagnosis of Multiple Sclerosis by Targeting Prognostic Biomarkers

Multiple sclerosis (MS) is a central nervous system (CNS) immune-mediated disease that mainly strikes young adults and leaves them disabled. MS is an autoimmune illness that causes the immune system to attack the brain and spinal cord. The myelin sheaths, which insulate the nerve fibers, are harmed by our own immune cells, and this interferes with brain signal transmission. Numbness, tingling, mood swings, memory problems, exhaustion, agony, vision problems, and/or paralysis are just a few of the symptoms. Despite technological advancements and significant research efforts in recent years, diagnosing MS can still be difficult. Each patient's MS is distinct due to a heterogeneous and complex pathophysiology with diverse types of disease courses. There is a pressing need to identify markers that will allow for more rapid and accurate diagnosis and prognosis assessments to choose the best course of treatment for each MS patient. The cerebrospinal fluid (CSF) is an excellent source of particular indicators associated with MS pathology. CSF contains molecules that represent pathological processes such as inflammation, cellular damage, and loss of blood-brain barrier integrity. Oligoclonal bands, neurofilaments, MS-specific miRNA, lncRNA, IgG-index, and anti-aquaporin 4 antibodies are all clinically utilised indicators for CSF in MS diagnosis. In recent years, a slew of new possible biomarkers have been presented. In this review, we look at what we know about CSF molecular markers and how they can aid in the diagnosis and differentiation of different MS forms and treatment options, and monitoring and predicting disease progression, therapy response, and consequences during such opportunistic infections.

Metabolomics of blood reveals age-dependent pathways in Parkinson’s Disease

Background

Parkinson’s Disease (PD) is the second most frequent degenerative disorder, the risk of which increases with age. A preclinical PD diagnostic test does not exist. We identify PD blood metabolites and metabolic pathways significantly correlated with age to develop personalized age-dependent PD blood biomarkers.

Results

We found 33 metabolites producing a receiver operating characteristic (ROC) area under the curve (AUC) value of 97%. PCA revealed that they belong to three pathways with distinct age-dependent behavior: glycine, threonine and serine metabolism correlates with age only in PD patients; unsaturated fatty acids biosynthesis correlates with age only in a healthy control group; and, finally, tryptophan metabolism characterizes PD but does not correlate with age.

Conclusions

The targeted analysis of the blood metabolome proposed in this paper allowed to find specific age-related metabolites and metabolic pathways. The model offers a promising set of blood biomarkers for a personalized age-dependent approach to the early PD diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13578-022-00831-5.

Plasma Amino Acids in Horses Suffering from Pituitary Pars Intermedia Dysfunction

Pituitary pars intermedia dysfunction is one of the most common diseases of aged horses and ponies. In Parkinson's disease, which is, similar to PPID, a disease that involves oxidative damage to dopaminergic pathways but with different clinical signs, alterations to the serum amino acid profile have been reported. To examine changes in the plasma amino acid profile in horses with PPID, EDTA plasma of horses that were presented for various reasons that required laboratory examinations of blood anticoagulated with EDTA was collected. With this plasma, the basal ACTH concentration as well as the amino acid profile was determined. Horses were considered PPID patients if the ACTH concentration was ≥ 100 pg/mL, i.e., they would be considered affected at any time. Horses were defined as non-PPID (nPPID) patients if the ACTH concentration was below 30 pg/mL. Horses receiving pergolide with ACTH ≤ 30 pg/mL were allocated to the group PPIDrr (PPID, ACTH in reference range) and horses receiving pergolide with ACTH ≥ 100 pg/mL to the group PPIDarr (PPID, ACTH above reference range). In total, 93 horses were examined, including 88 horses at the clinic and 5 horses at a private practice. Of these, 53 horses fulfilled the inclusion criteria (ACTH ≤ 30 pg/mL or ACTH ≥ 100 pg/mL). A total of 25 horses were diagnosed as nPPID, 20 as PPID, 5 as PPIDrr, and 3 as PPIDarr. Arginine was significantly higher in PPIDrr than in PPID and nPPID, asparagine was significantly higher in PPID, PPIDrr, and PPIDarr than in nPPID, citrulline was significantly higher in PPIDrr than in nPPID and PPID, cysteine was significantly lower in PPIDrr than in PPID, nPPID, and PPIDarr, and glutamine was significantly higher in PPID and PPIDarr than in nPPID. Especially, asparagine, citrulline, and glutamine may be potential diagnostic markers and may offer interesting approaches for research regarding amino supplementation in PPID.

Plasma Metabolic Disturbances in Parkinson's Disease Patients

Plasma from patients with Parkinson's disease (PD) is a valuable source of information indicating altered metabolites associated with the risk or progression of the disease. Neurotoxicity of dopaminergic neurons, which is triggered by aggregation of α-synuclein, is the main pathogenic feature of PD. However, a growing body of scientific reports indicates that metabolic changes may precede and directly contribute to neurodegeneration. Identification and characterization of the abnormal metabolic pattern in patients' plasma are therefore crucial for the search for potential PD biomarkers. The aims of the present study were (1) to identify metabolic alterations in plasma metabolome in subjects with PD as compared with the controls; (2) to find new potential markers, some correlations among them; (3) to identify metabolic pathways relevant to the pathophysiology of PD. Plasma samples from patients with PD (n = 25) and control group (n = 12) were collected and the gas chromatography-time-of-flight-mass spectrometry GC-TOFMS-based metabolomics approach was used to evaluate the metabolic changes based on the identified 14 metabolites with significantly altered levels using univariate and multivariate statistical analysis. The panel, including 6 metabolites (L-3-methoxytyrosine, aconitic acid, L-methionine, 13-docosenamide, hippuric acid, 9,12-octadecadienoic acid), was identified to discriminate PD from controls with the area under the curve (AUC) of 0.975, with an accuracy of 92%. We also used statistical criteria to identify the significantly altered level of metabolites. The metabolic pathways involved were associated with linoleic acid metabolism, mitochondrial electron transport chain, glycerolipid metabolism, and bile acid biosynthesis. These abnormal metabolic changes in the plasma of patients with PD were mainly related to the amino acid metabolism, TCA cycle metabolism, and mitochondrial function.

Serum Metabolomics of Benign Essential Blepharospasm Using Liquid Chromatography and Orbitrap Mass Spectrometry

Background

Benign essential blepharospasm (BEB) is a form of focal dystonia that causes excessive involuntary spasms of the eyelids. Currently, the pathogenesis of BEB remains unclear. This study is aimed at investigating the serum metabolites profiles in patients with BEB and healthy control and to identify the mechanism and biomarkers of this disease.

Methods

30 patients with BEB and 33 healthy controls were recruited for this study. We conducted the quantitative and nontargeted metabolomics analysis of the serum samples from 63 subjects by using liquid chromatography and Orbitrap mass spectrometry (LC-Orbitrap MS). Multivariate statistical analysis was performed to detect and identify different metabolites between the two groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and receiver operating characteristic (ROC) curve analysis of the altered metabolites were performed.

Results

A total of 134 metabolites were found and identified. The metabolites belonged to several metabolic pathways including phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arginine biosynthesis, linoleic acid metabolism, tryptophan metabolism, aminoacyl-tRNA biosynthesis, sphingolipid metabolism, glycosphingolipid biosynthesis, leucine and isoleucine biosynthesis, and vitamin B6 metabolism. Eight metabolites were identified as the potential biomarkers.

Conclusions

These results demonstrated that serum metabolic profiling of BEB patients was significantly different from healthy controls based on LC-Orbitrap MS. Besides, metabolomics might provide useful information for a better understanding of BEB.

Amino acids profile in children with acute brucellosis

BACKGROUND

Many new cases of brucella infections are seen in Turkey every year, especially in March, April, and May, due to the consumption of local unpasteurized cheese. Amino acids profiles have not been studied in brucellosis so far.

INTRODUCTION

The amino acid profiles may be affected by infectious diseases. Our study aims to evaluate the plasma amino acid profile in the progression of acute brucellosis.

METHODS

Plasma amino acid profile was performed by an 8045 LC-MS / MS device (Shimadzu 8045, Japan) using JASEM amino acid kit.

RESULTS

Analysis of 45 amino acid profiles was made and results profiles showed significant differences in concentrations and types of amino acids in brucella patients. We observed a significant difference in terms of alanine, arginine, aspartic acid, glutamine, glutamic acid, glycine, isoleucine, ornithine, phenylalanine, proline, tyrosine, valine, alpha-aminoadipic acid, alpha-amino-pimelic acid, argininosuccinic acid, gamma-aminobutyric acid, thiaproline, 1-methylhistidine, 3-methylhistidine, hydroxylysine, hydroxyproline, cystine, serotonin, ethanolamine, and taurine (p-value <0.05 for each). No significant differences were determined regarding asparagine, citrulline, histidine, leucine, alloisoleucine, lysine, methionine, serine, threonine, tryptophan, anserine, alpha aminobutyric acid, beta aminoisobutyric acid, beta-alanine, cystathionine, histamine, and 5-oh-trp (p-value >0.05 for all).

CONCLUSION

Patients with brucellosis have a specific profile of amino acids which may reflect sequelae of pathological and metabolic biochemical changes in the disease process due to the growth of Brucella spp. in the human body leading to an imbalance of amino acid levels.

Interactions between gut microbiota and Parkinson's disease: The role of microbiota-derived amino acid metabolism

Non-motor symptoms (NMS) of Parkinson's disease (PD), such as constipation, sleep disorders, and olfactory deficits, may emerge up to 20 years earlier than motor symptoms. A series of evidence indicates that the pathology of PD may occur from the gastrointestinal tract to the brain. Numerous studies support that the gut microbiota communicates with the brain through the immune system, special amino acid metabolism, and the nervous system in PD. Recently, there is growing recognition that the gut microbiota plays a vital role in the modulation of multiple neurochemical pathways via the “gut microbiota-brain axis” (GMBA). Many gut microbiota metabolites, such as fatty acids, amino acids, and bile acids, convey signaling functions as they mediate the crosstalk between gut microbiota and host physiology. Amino acids' abundance and species alteration, including glutamate and tryptophan, may disturb the signaling transmission between nerve cells and disrupt the normal basal ganglia function in PD. Specific amino acids and their receptors are considered new potential targets for ameliorating PD. The present study aimed to systematically summarize all available evidence on the gut microbiota-derived amino acid metabolism alterations associated with PD.

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

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

Pesticides Exposure-Induced Changes in Brain Metabolome: Implications in the Pathogenesis of Neurodegenerative Disorders

Pesticides have been used in agriculture, public health programs, and pharmaceuticals for many decades. Though pesticides primarily target pests by affecting their nervous system and causing other lethal effects, these chemical entities also exert toxic effects in inadvertently exposed humans through inhalation or ingestion. Mounting pieces of evidence from cellular, animal, and clinical studies indicate that pesticide-exposed models display metabolite alterations of pathways involved in neurodegenerative diseases. Hence, identifying common key metabolites/metabolic pathways between pesticide-induced metabolic reprogramming and neurodegenerative diseases is necessary to understand the etiology of pesticides in the rise of neurodegenerative disorders. The present review provides an overview of specific metabolic pathways, including tryptophan metabolism, glutathione metabolism, dopamine metabolism, energy metabolism, mitochondrial dysfunction, fatty acids, and lipid metabolism that are specifically altered in response to pesticides. Furthermore, we discuss how these metabolite alterations are linked to the pathogenesis of neurodegenerative diseases and to identify novel biomarkers for targeted therapeutic approaches.

Extraction of Reduced Infrared Biomarker Signatures for the Stratification of Patients Affected by Parkinson’s Disease: An Untargeted Metabolomic Approach

An untargeted Fourier transform infrared (FTIR) metabolomic approach was employed to study metabolic changes and disarrangements, recorded as infrared signatures, in Parkinson’s disease (PD). Herein, the principal aim was to propose an efficient sequential classification strategy based on SELECT-LDA, which enabled optimal stratification of three main categories: PD patients from subjects with Alzheimer’s disease (AD) and healthy controls (HC). Moreover, sub-categories, such as PD at the early stage (PDI) from PD in the advanced stage (PDD), and PDD vs. AD, were stratified. Every classification step with selected wavenumbers achieved 90.11% to 100% correct assignment rates in classification and internal validation. Therefore, selected metabolic signatures from new patients could be used as input features for screening and diagnostic purposes.

Trafficking of the glutamate transporter is impaired in LRRK2-related Parkinson's disease

The Excitatory Amino Acid Transporter 2 (EAAT2) accounts for 80% of brain glutamate clearance and is mainly expressed in astrocytic perisynaptic processes. EAAT2 function is finely regulated by endocytic events, recycling to the plasma membrane and degradation. Noteworthy, deficits in EAAT2 have been associated with neuronal excitotoxicity and neurodegeneration. In this study, we show that EAAT2 trafficking is impaired by the leucine-rich repeat kinase 2 (LRRK2) pathogenic variant G2019S, a common cause of late-onset familial Parkinson’s disease (PD). In LRRK2 G2019S human brains and experimental animal models, EAAT2 protein levels are significantly decreased, which is associated with elevated gliosis. The decreased expression of the transporter correlates with its reduced functionality in mouse LRRK2 G2019S purified astrocytic terminals and in Xenopus laevis oocytes expressing human LRRK2 G2019S. In LRRK2 G2019S knock-in mouse brain, the correct surface localization of the endogenous transporter is impaired, resulting in its interaction with a plethora of endo-vesicular proteins. Mechanistically, we report that pathogenic LRRK2 kinase activity delays the recycling of the transporter to the plasma membrane via Rabs inactivation, causing its intracellular re-localization and degradation. Taken together, our results demonstrate that pathogenic LRRK2 interferes with the physiology of EAAT2, pointing to extracellular glutamate overload as a possible contributor to neurodegeneration in PD.

Glycation modulates glutamatergic signaling and exacerbates Parkinson's disease-like phenotypes

Alpha-synuclein (aSyn) is a central player in the pathogenesis of synucleinopathies due to its accumulation in typical protein aggregates in the brain. However, it is still unclear how it contributes to neurodegeneration. Type-2 diabetes mellitus is a risk factor for Parkinson's disease (PD). Interestingly, a common molecular alteration among these disorders is the age-associated increase in protein glycation. We hypothesized that glycation-induced neuronal dysfunction is a contributing factor in synucleinopathies. Here, we dissected the impact of methylglyoxal (MGO, a glycating agent) in mice overexpressing aSyn in the brain. We found that MGO-glycation potentiates motor, cognitive, olfactory, and colonic dysfunction in aSyn transgenic (Thy1-aSyn) mice that received a single dose of MGO via intracerebroventricular injection. aSyn accumulates in the midbrain, striatum, and prefrontal cortex, and protein glycation is increased in the cerebellum and midbrain. SWATH mass spectrometry analysis, used to quantify changes in the brain proteome, revealed that MGO mainly increase glutamatergic-associated proteins in the midbrain (NMDA, AMPA, glutaminase, VGLUT and EAAT1), but not in the prefrontal cortex, where it mainly affects the electron transport chain. The glycated proteins in the midbrain of MGO-injected Thy1-aSyn mice strongly correlate with PD and dopaminergic pathways. Overall, we demonstrated that MGO-induced glycation accelerates PD-like sensorimotor and cognitive alterations and suggest that the increase of glutamatergic signaling may underly these events. Our study sheds new light into the enhanced vulnerability of the midbrain in PD-related synaptic dysfunction and suggests that glycation suppressors and anti-glutamatergic drugs may hold promise as disease-modifying therapies for synucleinopathies.

Plasma branched-chain and aromatic amino acids correlate with the gut microbiota and severity of Parkinson's disease

Disturbances of circulating amino acids have been demonstrated in patients with Parkinson’s disease (PD). However, there have been no consistent results for branched-chain amino acids (BCAAs) and aromatic amino acids (AAAs), and related factors have not been explored. We aimed to explore plasma BCAA and AAA profiles in PD patients, and identify their correlations with clinical characteristics and the gut microbiota. Plasma BCAA (leucine, isoleucine, and valine) and AAA (tyrosine and phenylalanine) levels were measured in 106 PD patients and 114 controls. Fecal samples were collected from PD patients for microbiota sequencing and functional analysis. We found that plasma BCAAs and tyrosine were decreased in PD patients. BCAAs and AAAs were correlated with clinical characteristics and microbial taxa, and, in particular, they were negatively correlated with the Hoehn and Yahr stage. Compared with early PD patients, BCAA and AAA levels were even lower, and microbial composition was altered in advanced PD patients. Predictive functional analysis indicated that predicted genes numbers involved in BCAA biosynthesis were lower in advanced PD patients. What’s more, the fecal abundances of critical genes (ilvB, ilvC, ilvD, and ilvN) involved in BCAA biosynthesis were reduced and fecal BCAA concentrations were lower in advanced PD patients. In conclusion, the disturbances of plasma BCAAs and AAAs in PD patients may be related to the gut microbiota and exacerbated with PD severity. The microbial amino acid metabolism may serve as a potential mechanistic link.

A Multi-Scale Computational Model of Levodopa-Induced Toxicity in Parkinson's Disease

Parkinson's disease (PD) is caused by the progressive loss of dopaminergic cells in substantia nigra pars compacta (SNc). The root cause of this cell loss in PD is still not decisively elucidated. A recent line of thinking has traced the cause of PD neurodegeneration to metabolic deficiency. Levodopa (L-DOPA), a precursor of dopamine, used as a symptom-relieving treatment for PD, leads to positive and negative outcomes. Several researchers inferred that L-DOPA might be harmful to SNc cells due to oxidative stress. The role of L-DOPA in the course of the PD pathogenesis is still debatable. We hypothesize that energy deficiency can lead to L-DOPA-induced toxicity in two ways: by promoting dopamine-induced oxidative stress and by exacerbating excitotoxicity in SNc. We present a systems-level computational model of SNc-striatum, which will help us understand the mechanism behind neurodegeneration postulated above and provide insights into developing disease-modifying therapeutics. It was observed that SNc terminals are more vulnerable to energy deficiency than SNc somas. During L-DOPA therapy, it was observed that higher L-DOPA dosage results in increased loss of terminals in SNc. It was also observed that co-administration of L-DOPA and glutathione (antioxidant) evades L-DOPA-induced toxicity in SNc neurons. Our proposed model of the SNc-striatum system is the first of its kind, where SNc neurons were modeled at a biophysical level, and striatal neurons were modeled at a spiking level. We show that our proposed model was able to capture L-DOPA-induced toxicity in SNc, caused by energy deficiency.

Modifying the diet and gut microbiota to prevent and manage neurodegenerative diseases

The global prevalence of Alzheimer's disease and Parkinson's disease is steadily increasing due to the aging population. The lack of effective drugs against these neurodegenerative disorders makes it imperative to identify new strategies for their prevention and treatment. Recent studies have revealed that harnessing the power of the gut microbiota through modification of diet may be a valuable approach for reducing the risk, modulating the symptoms, and ameliorating the pathophysiological aspects of neurodegenerative diseases. Consuming specific dietary components can alter the prevalence of bacterial communities within the gut to a healthy enterotype, which can influence the production of beneficial metabolites by microbiota. This article focuses on several dietary components, which have been demonstrated to affect the gut microbiota-brain axis and therefore could lead to attenuation of specific pathological processes in neurodegenerative diseases. Published evidence indicates that fermented foods, including kefir, and foods that are high in bioactive polyphenols and complex carbohydrates, such as grapes, pomegranates, and seaweed, may be effective at reducing neuroinflammation, oxidative stress, neurotransmitter dysfunction, and neuronal death associated with Alzheimer's and Parkinson's diseases. Even though experimental evidence supporting the protective properties of the above dietary components in these diseases is emerging, it is evident that further human clinical studies are required to conclusively establish the benefits of any suggested dietary interventions. The translational potential of such research is illustrated by the clinical success of the recently developed Alzheimer's drug, GV-971, which is a seaweed derivative that works by modulating the gut microbiota-brain axis.

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

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

Metabolic Alterations in a Drosophila Model of Parkinson's Disease Based on DJ-1 Deficiency

Parkinson’s disease (PD) is the second-most common neurodegenerative disorder, whose physiopathology is still unclear. Moreover, there is an urgent need to discover new biomarkers and therapeutic targets to facilitate its diagnosis and treatment. Previous studies performed in PD models and samples from PD patients already demonstrated that metabolic alterations are associated with this disease. In this context, the aim of this study is to provide a better understanding of metabolic disturbances underlying PD pathogenesis. To achieve this goal, we used a Drosophila PD model based on inactivation of the DJ-1β gene (ortholog of human DJ-1). Metabolomic analyses were performed in 1-day-old and 15-day-old DJ-1β mutants and control flies using ¹H nuclear magnetic resonance spectroscopy, combined with expression and enzymatic activity assays of proteins implicated in altered pathways. Our results showed that the PD model flies exhibited protein metabolism alterations, a shift fromthe tricarboxylic acid cycle to glycolytic pathway to obtain ATP, together with an increase in the expression of some urea cycle enzymes. Thus, these metabolic changes could contribute to PD pathogenesis and might constitute possible therapeutic targets and/or biomarkers for this disease.

Serum fractalkine and 3-nitrotyrosine levels correlate with disease severity in Parkinson's disease: a pilot study

Parkinson's disease (PD) and Parkinsonian syndromes; Progressive supranuclear palsy (PSP), and Multiple system atrophy (MSA) are debilitating neurodegenerative disorders. Fractalkine is a chemokine involved in neuroinflammation, whereas, 3-nitrotyrosine (3-NT) is a marker of early neurodegenerative cellular-damage. We measured Fractalkine and 3-NT levels in the serum of these patients to examine the neuroinflammation hypothesis and also to decipher the propensity of these biologics to be used as early (5 years from onset) biochemical markers in neurodegenerative Parkinsonism. The diagnoses of PD, PSP and MSA were performed as per the respective clinical criteria. 21 PD, 9 PSP and 8 MSA patients along with controls participated in this study. Serum concentrations of Fractalkine and 3-NT were measured by ELISA. Fractalkine levels were increased in PD, PSP and MSA cohorts in comparison with controls with p < 0.001, p < 0.05 and p < 0.05 respectively. Levels of 3-NT also showed elevation in PD (p < 0.01) vs. controls. However, Pearson plot showed that Fractalkine levels were high in the patients with unified Parkinson's disease rating scale (UPDRS) part III motor score of 1, meaning slight disability, but gradually dropped in patients with motor score of 4, which is a measure of severe motor disability. This negative correlation (- .565, p < .0.01) also accentuates the neuroprotectant/anti-inflammatory nature of Fractalkine in PD. Continuous rise of 3-NT in PD, positively correlating (.512, p < 0.05) with worsening motor symptoms points to deleterious consequences of nitrosative stress. To our knowledge, this is the first report providing evidence that serum Fractalkine and 3-NT have early diagnostic/prognostic significance as PD biomarkers.

Plasma Metabolite Markers of Parkinson's Disease and Atypical Parkinsonism

Differentiating between Parkinson’s disease (PD) and the atypical Parkinsonian disorders of multiple system atrophy (MSA) and progressive supranuclear palsy (PSP) is difficult clinically due to overlapping symptomatology, especially at early disease stages. Consequently, there is a need to identify metabolic markers for these diseases and to develop them into viable biomarkers. In the present investigation, solution nuclear magnetic resonance and mass spectrometry metabolomics were used to quantitatively characterize the plasma metabolomes (a total of 167 metabolites) of a cohort of 94 individuals comprising 34 PD, 12 MSA, and 17 PSP patients, as well as 31 control subjects. The distinct and statistically significant differences observed in the metabolite concentrations of the different disease and control groups enabled the identification of potential plasma metabolite markers of each disorder and enabled the differentiation between the disorders. These group-specific differences further implicate disturbances in specific metabolic pathways. The two metabolites, formic acid and succinate, were altered similarly in all three disease groups when compared to the control group, where a reduced level of formic acid suggested an effect on pyruvate metabolism, methane metabolism, and/or the kynurenine pathway, and an increased succinate level suggested an effect on the citric acid cycle and mitochondrial dysfunction.

Changes in the Gut Microbiome and Predicted Functional Metabolic Effects in an Australian Parkinson's Disease Cohort

Background: There has been increasing recognition of the importance of the gut microbiome in Parkinson's disease (PD), but the influence of geographic location has received little attention. The present study characterized the gut microbiota and associated changes in host metabolic pathways in an Australian cohort of people with PD (PwP). Methods: The study involved recruitment and assessment of 87 PwP from multiple Movement Disorders Clinics in Australia and 47 healthy controls. Illumina sequencing of the V3 and V4 regions of the 16S rRNA gene was used to distinguish inter-cohort differences in gut microbiota; KEGG analysis was subsequently performed to predict functional changes in host metabolic pathways. Results: The current findings identified significant differences in relative abundance and diversity of microbial operational taxonomic units (OTUs), and specific bacterial taxa between PwP and control groups. Alpha diversity was significantly reduced in PwP when compared to controls. Differences were found in two phyla (Synergistetes and Proteobacteria; both increased in PwP), and five genera (Colidextribacter, Intestinibacter, Kineothrix, Agathobaculum, and Roseburia; all decreased in PwP). Within the PD cohort, there was no association identified between microbial composition and gender, constipation or use of gastrointestinal medication. Furthermore, KEGG analysis identified 15 upregulated and 11 downregulated metabolic pathways which were predicted to be significantly altered in PwP. Conclusion: This study provides the first comprehensive characterization of the gut microbiome and predicted functional metabolic effects in a southern hemisphere PD population, further exploring the possible mechanisms whereby the gut microbiota may exert their influence on this disease, and providing evidence for the incorporation of such data in future individualized therapeutic strategies.

A six-metabolite panel as potential blood-based biomarkers for Parkinson's disease

Characterisation and diagnosis of idiopathic Parkinson's disease (iPD) is a current challenge that hampers both clinical assessment and clinical trial development with the potential inclusion of non-PD cases. Here, we used a targeted mass spectrometry approach to quantify 38 metabolites extracted from the serum of 231 individuals. This cohort is currently one of the largest metabolomic studies including iPD patients, drug-naïve iPD, healthy controls and patients with Alzheimer's disease as a disease-specific control group. We identified six metabolites (3-hydroxykynurenine, aspartate, beta-alanine, homoserine, ornithine (Orn) and tyrosine) that are significantly altered between iPD patients and control participants. A multivariate model to predict iPD from controls had an area under the curve (AUC) of 0.905, with an accuracy of 86.2%. This panel of metabolites may serve as a potential prognostic or diagnostic assay for clinical trial prescreening, or for aiding in diagnosing pathological disease in the clinic.

Alterations of gut microbiota and metabolome with Parkinson's disease

Gut microbiota and amino acids that are one of their metabolites play important roles in the mechanism of pathology of Parkinson's disease (PD). It has been reported that the level of amino acids in vivo participate in neurodegeneration by regulating adaptive immune response, while the current researches on alteration of amino acids in gut microbiota are still insufficient. We hypothesized that alterations in gut microbiota might be accompanied by altered concentrations of amino acids, leading to the occurrence of PD. In this study, we collected stool samples from PD and healthy controls to analyse fecal microbiome and targeted metabolome by 16S ribosomal RNA (16S rRNA) gene sequencing and gas chromatography coupled to mass spectrometry (GC-MS). At the genus level, there was a greater abundance of Alistipes, Rikenellaceae_RC9_gut_group, Bifidobacterium, Parabacteroides, while Faecalibacterium was decreased in fecal samples from PD patients. Moreover, fecal branched chain amino acids (BCAAs) and aromatic amino acids concentrations were significantly reduced in PD patients compared to controls. Our study not only finds the abundance of certain gut microbiota in PD,but also reveals that it is related to BCAAs and aromatic amino acids. These findings are beneficial to identifying new therapeutic targets for PD by regulating diet and/or gut microbiota.

Plasma amino acids in patients with essential tremor

Essential tremor (ET) is one of the most common movement disorders. However, there are currently no accepted biomarkers for ET. This report suggested that concentration of plasma glutamic acid, aspartic acid, and taurine could be biomarkers for ET.

Direct detection of inorganic ions and underivatized amino acids in seconds using high-speed capillary electrophoresis coupled with back-scatter interferometry

High speed capillary electrophoresis (HSCE) combined with refractive index (RI) detection is developed for the rapid separation and detection of inorganic ions and amino acids. A mixture of three inorganic ions (K⁺, Na⁺, Li⁺) and eight amino acids (Lys, Arg, Ala, Gly, Val, Thr, Trp, Asp) are detected using back scatter interferometry (BSI), without the need for chemical modifications or contrast. A thin-walled separation capillary (50 μm i.d. by 80 μm o.d.) helps mitigate Joule heating at the high field strengths required for rapid separations. This, combined with a short 8 cm length-to-detector (10 cm total length), enables separations on the seconds time scale. Using a background electrolyte (BGE) of 4 M acetic acid (pH 1.6) and a field strength of 900 V cm^-1, all 11 analytes are separated in less than 40 s. Moreover, peaks in the BSI signal arising from the sample injection and EOF, enable electrophoretic mobilities to readily be obtained from apparent mobilities. This leads to excellent repeatability, with analyte electrophoretic mobilities varying from 0.39 to 1.56 % RSD over eight consecutive separations. The universal detection of inorganic ions and amino acids without prior chemical modification or additives in the BGE is an advantage of refractive index detection. A disadvantage arises from modest detection limits. Here, however, we show that submicromolar detection is possible with careful thermostatting of the thin separation capillary. A series of electropherograms are used to quantify arginine concentrations from 700 nM to 500 μM, using 50 μM Li⁺ as an internal standard. The resulting calibration curve leads to a calculated LOD of 376 nM and a LOQ of 1.76 μM. Diagnostically relevant amino acid panels are also separated, illustrating the potential for future applications in neurodegenerative and metabolic disease diagnostics. HSCE combined with BSI detection, therefore, is shown to be a rapid, sensitive, and universal approach for analyzing sample mixtures.

Serum amino acid profiles in patients with mild cognitive impairment and in patients with mild dementia or moderate dementia

Neurodegenerative disorders are one of the greatest global challenges for social and health care in the twenty-first century. Nowadays, determination of cerebrospinal fluid biomarkers for early diagnosis is served by a complex sample preparation procedure with limited diagnostic accuracy. Furthermore, neuroimaging methods are expensive, time-consuming and are not readily available for use as a complimentary and common screening method. Recently, researchers have shown an increased interest in the identification and characterization of new blood biomarkers of dementia to minimize the limitations associated with the current methods of biomarker determination. Amino acids play many important roles in the central nervous system, acting as neuromodulators, neurotransmitters and regulators of energy metabolism. The aim of this study was to evaluate if serum amino acid levels change along the continuum from no cognitive impairment to moderate dementia, and to identify putative biomarkers for early diagnosis of neurodegenerative diseases. Serum levels of 16 amino acids were determined in 3 groups of patients-22 with mild cognitive impairment, 45 with mild dementia and 28 with moderate dementia-by high-performance liquid chromatography (HPLC) with fluorescence detection using AccQ Tag column (Waters). The most exciting result is the significantly elevated concentration of arginine in patients with both stages of dementia as compared to mild cognitive impairment individuals. Recent accumulating evidence suggests the implication of changed arginine metabolism in the pathogenesis of neurodegenerative diseases. We conclude that amino acids profiling might be helpful in searching for biomarkers of neurogenerative diseases. In the present study, we discovered that arginine in plasma may have a putative diagnostic value for dementia.

Gut microbiota and metabolome distinctive features in Parkinson disease: Focus on levodopa and levodopa-carbidopa intrajejunal gel

BACKGROUND AND PURPOSE

Recent data suggest that imbalances in the composition of the gut microbiota (GM) could exacerbate the progression of Parkinson disease (PD). The effects of levodopa (LD) have been poorly assessed, and those of LD-carbidopa intestinal gel (LCIG) have not been evaluated so far. The aim of this study was to identify the effect of LD and LCIG, in particular, on the GM and metabolome.

METHODS

Fecal DNA samples from 107 patients with a clinical diagnosis of PD were analyzed by next-generation sequencing of the V3 and V4 regions of the 16S rRNA gene. PD patients were classified in different groups: patients on LCIG (LCIG group, n = 38) and on LD (LD group, n = 46). We also included a group of patients (n = 23) without antiparkinsonian medicaments (Naïve group). Fecal metabolic extracts were evaluated by gas chromatography mass spectrometry.

RESULTS

The multivariate analysis showed a significantly higher abundance in the LCIG group of Enterobacteriaceae, Escherichia, and Serratia compared to the LD group. Compared to the Naïve group, the univariate analysis showed a reduction of Blautia and Lachnospirae in the LD group. Moreover, an increase of Proteobacteria, Enterobacteriaceae, and a reduction of Firmicutes, Lachnospiraceae, and Blautia was found in the LCIG group. No significant difference was found in the multivariate analysis of these comparisons. The LD group and LCIG group were associated with a metabolic profile linked to gut inflammation.

CONCLUSIONS

Our results suggest that LD, and mostly LCIG, might significantly influence the microbiota composition and host/bacteria metabolism, acting as stressors in precipitating a specific inflammatory intestinal microenvironment, potentially related to the PD state and progression.

Metabolic profiling reveals dysregulated lipid metabolism and potential biomarkers associated with the development and progression of Fragile X-Associated Tremor/Ataxia Syndrome (FXTAS)

Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a neurodegenerative disorder associated with the FMR1 premutation. It is currently unknown when, and if, individual premutation carriers will develop FXTAS. Thus, with the aim of identifying biomarkers for early diagnosis, development, and progression of FXTAS, we performed global metabolomic profiling of premutation carriers (PM) who, as part of an ongoing longitudinal study, emerged into two distinct categories: those who developed symptoms of FXTAS (converters, CON) at subsequent visits and those who did not (non-converters, NCON) and we compared to age-matched healthy controls (HC). We assessed CGG repeat allele size by Southern Blot and PCR analysis. Metabolomic profile was obtained by ultra-performance liquid chromatography, accurate mass spectrometer, and an Orbitrap mass analyzer. In this study we found 47 metabolites were significantly dysregulated between HC and the premutation groups (PM). Importantly, we identified 24 metabolites that showed significant changes in expression in the CON as compared to the NCON both at V1 and V2, and 70 metabolites in CON as compared to NCON but only at V2. These findings suggest the potential role of the identified metabolites as biomarkers for early diagnosis and for FXTAS disease progression, respectively. Interestingly, the majority of the identified metabolites were lipids, followed by amino acids. To our knowledge, this the first report of longitudinal metabolic profiling and identification of unique biomarkers of FXTAS. The lipid metabolism and specifically the sub pathways involved in mitochondrial bioenergetics, as observed in other neurodegenerative disorders, are significantly altered in FXTAS.

Amino Acid Levels as Potential Biomarker of Elderly Patients with Dementia

Dementia is a clinical syndrome characterized by cognitive impairment, in which there is disturbance of multiple higher cortical functions. The primary risk factor of dementia is old age, and due to significant changes in the worldwide demographic structure, the prevalence of cognitive impairment is increasing dramatically with aging populations in most countries. Alzheimer's disease is the predominant and leading cause of dementia. The aim of this study was to evaluate the modifications of amino acids that characterize the initial stages of dementia to help our understanding of the complex and multifactorial pathogenesis of neurodegenerative disorders. A total of 123 participants were divided into two groups: healthy elderly subjects and patients with mild or moderate dementia. The results of this study indicate that the serum levels of three amino acids were changed significantly in patients with dementia, in relation to the subjects without dementia. In particular, we observed differences in concentrations for serine, arginine and isoleucine (all of them were significantly increased in patients with dementia, compared with the control group). Our results suggest that the metabolisms of some amino acids seem be changed in patients with dementia. We conclude that amino acid profiling might be helpful for the better understanding of biochemical and metabolic changes related to the pathogenesis and progression of dementia. However, considering the multifactorial, heterogenous and complex nature of this disease, validation with a greater study sample in further research is required.

Gut Microbiota and Metabolome Alterations Associated with Parkinson's Disease

To our knowledge, this is one of the few studies thus far that correlates the composition of the gut microbiota with the direct analysis of fecal metabolites in patients with Parkinson’s disease. Overall, our data highlight microbiota modifications correlated with numerous fecal metabolites. This suggests that Parkinson’s disease is associated with gut dysregulation that involves a synergistic relationship between gut microbes and several bacterial metabolites favoring altered homeostasis. Interestingly, a reduction of short-chain fatty acid (SCFA)-producing bacteria influenced the shape of the metabolomics profile, affecting several metabolites with potential protective effects in the Parkinson group. On the other hand, the extensive impact that intestinal dysbiosis has at the level of numerous metabolic pathways could encourage the identification of specific biomarkers for the diagnosis and treatment of Parkinson’s disease, also in light of the effect that specific drugs have on the composition of the intestinal microbiota.

Parkinson’s disease is a neurodegenerative disorder characterized by the accumulation of intracellular aggregates of misfolded alpha-synuclein along the cerebral axis. Several studies report the association between intestinal dysbiosis and Parkinson’s disease, although a cause-effect relationship remains to be established. Herein, the gut microbiota composition of 64 Italian patients with Parkinson’s disease and 51 controls was determined using a next-generation sequencing approach. A real metagenomics shape based on gas chromatography-mass spectrometry was also investigated. The most significant changes within the Parkinson’s disease group highlighted a reduction in bacterial taxa, which are linked to anti-inflammatory/neuroprotective effects, particularly in the Lachnospiraceae family and key members, such as Butyrivibrio, Pseudobutyrivibrio, Coprococcus, and Blautia. The direct evaluation of fecal metabolites revealed changes in several classes of metabolites. Changes were seen in lipids (linoleic acid, oleic acid, succinic acid, and sebacic acid), vitamins (pantothenic acid and nicotinic acid), amino acids (isoleucine, leucine, phenylalanine, glutamic acid, and pyroglutamic acid) and other organic compounds (cadaverine, ethanolamine, and hydroxy propionic acid). Most modified metabolites strongly correlated with the abundance of members belonging to the Lachnospiraceae family, suggesting that these gut bacteria correlate with altered metabolism rates in Parkinson’s disease.

IMPORTANCE To our knowledge, this is one of the few studies thus far that correlates the composition of the gut microbiota with the direct analysis of fecal metabolites in patients with Parkinson’s disease. Overall, our data highlight microbiota modifications correlated with numerous fecal metabolites. This suggests that Parkinson’s disease is associated with gut dysregulation that involves a synergistic relationship between gut microbes and several bacterial metabolites favoring altered homeostasis. Interestingly, a reduction of short-chain fatty acid (SCFA)-producing bacteria influenced the shape of the metabolomics profile, affecting several metabolites with potential protective effects in the Parkinson group. On the other hand, the extensive impact that intestinal dysbiosis has at the level of numerous metabolic pathways could encourage the identification of specific biomarkers for the diagnosis and treatment of Parkinson’s disease, also in light of the effect that specific drugs have on the composition of the intestinal microbiota.

Metabolomics Fingerprint Induced by the Intranigral Inoculation of Exogenous Human Alpha-Synuclein Oligomers in a Rat Model of Parkinson's Disease

Parkinson’s disease (PD) is considered a synucleinopathy because of the intraneuronal accumulation of aggregated α-synuclein (αSyn). Recent evidence points to soluble αSyn-oligomers (αSynO) as the main cytotoxic species responsible for cell death. Given the pivotal role of αSyn in PD, αSyn-based models are crucial for the investigation of toxic mechanisms and the identification of new therapeutic targets in PD. By using a metabolomics approach, we evaluated the metabolic profile of brain and serum samples of rats infused unilaterally with preformed human αSynOs (HαSynOs), or vehicle, into the substantia nigra pars compacta (SNpc). Three months postinfusion, the striatum was dissected for striatal dopamine (DA) measurements via High Pressure Liquid Chromatography (HPLC) analysis and mesencephalon and serum samples were collected for the evaluation of metabolite content via gas chromatography mass spectrometry analysis. Multivariate, univariate and correlation statistics were applied. A 40% decrease of DA content was measured in the HαSynO-infused striatum as compared to the contralateral and the vehicle-infused striata. Decreased levels of dehydroascorbic acid, myo-inositol, and glycine, and increased levels of threonine, were found in the mesencephalon, while increased contents of fructose and mannose, and a decrease in glycine and urea, were found in the serum of HαSynO-infused rats. The significant correlation between DA and metabolite content indicated that metabolic variations reflected the nigrostriatal degeneration. Collectively, the metabolomic fingerprint of HαSynO-infused rats points to an increase of oxidative stress markers, in line with PD neuropathology, and provides hints for potential biomarkers of PD.

Cerebrospinal and blood levels of amino acids as potential biomarkers for Parkinson's disease: review and meta-analysis

BACKGROUND AND PURPOSE

The present systematic review and meta-analysis aims to establish the possible value of cerebrospinal fluid (CSF) and serum/plasma levels of amino acids as markers of Parkinson's disease (PD).

METHODS

This is a review of four databases (PubMed, Embase, MEDLINE and Web of Science - Core Collection) from 1966 to 14 March 2020, with identification of references of interest for the topic. The meta-analysis of eligible studies was done using R software package meta, following the PRISMA and MOOSE guidelines.

RESULTS

Compared with age- and sex-matched controls, PD patients showed decreased CSF levels of glutamate and taurine and increased CSF levels of tyrosine; decreased serum/plasma levels of aspartate, serine, tryptophan and lysine, and increased serum/plasma proline and homocysteine levels.

CONCLUSION

Despite the limitations of this study due to the important variability of results between different series, our findings suggest the value of CSF or serum/plasma levels of several amino acids in the discrimination of PD patients from healthy subjects, related to the levels of some amino acids.

Identification of potential urine biomarkers in idiopathic parkinson's disease using NMR

INTRODUCTION

Parkinson's disease (PD) is the most common neurodegenerative disease caused by the loss of dopamine chemicals resulting in urinary incontinence, gastrointestinal dysfunction, gait impairment and mitochondrial dysfunction. Study investigated urinary metabolic profiles of patients with idiopathic PD as compared to healthy controls (HC) to identify the potential biomarkers.

METHODS

Urine samples were collected from 100 PD subjects and 50 HC using standard protocol. Metabolomic analyses were performed using high resolution nuclear magnetic resonance (NMR) spectroscopy. The integral values of 17 significant metabolites were estimated and concentration values were calculated, which were subjected to univariate and multivariate statistical analysis.

RESULTS

We found significantly increased levels of ornithine, phenylalanine, isoleucine, β-hydroxybutyrate, tyrosine and succinate in the urine of patients with PD in comparison with HC. These metabolites exhibited area under the curve greater than 0.60 on ROC curve analysis. We also observed a significant association between succinate concentration and UPDRS motor scores of PD.

DISCUSSION

Metabolic pathway alterations were observed in aromatic amino acid metabolism, ketone bodies synthesis, branched chain amino acid metabolism and ornithine metabolism. Comprehensive metabolomic profiling revealed variations in urinary signatures associated with severity of idiopathic PD. This profiling relies on non-invasive sampling and is complementary to existing clinical modalities.

Biofluid Markers for Prodromal Parkinson's Disease: Evidence From a Catecholaminergic Perspective

Parkinson's disease (PD) is the most frequent of all Lewy body diseases, a family of progressive neurodegenerative disorders characterized by intra-neuronal cytoplasmic inclusions of α-synuclein. Its most defining features are bradykinesia, tremor, rigidity and postural instability. By the time PD manifests with motor signs, 70% of dopaminergic midbrain neurons are lost, and the disease is already in the middle or late stage. However, there are various non-motor symptoms occurring up to 20 years before the actual parkinsonism that are closely associated with profound deficiency of myocardial noradrenaline content and peripheral sympathetic denervation, as evidenced by neuroimaging experiments in recent years. Additionally, there is an inherent autotoxicity of catecholamines in the neuronal cells in which they are produced, forming toxic catecholaldehyde intermediates that make α-synuclein prone to aggregation, initiating a cascade of events that ultimately leads to neuronal death. The etiopathogenesis of PD and related synucleinopathies thus may well be a prototypical example of a catecholamine-regulated neurodegeneration, given that the synucleinopathy in PD spreads in synergy with central and peripheral catecholaminergic dysfunction from the earliest phases onward. That is why catecholamines and their metabolites, precursors, or derivatives in cerebrospinal fluid or plasma could be of particular interest as biomarkers for prodromal and de novo PD. Because there is great demand for such markers, this mini-review summarizes all catecholamine-related studies to date, in addition to providing profound neurochemical evidence on a systemic and cellular level to further emphasize this hypothesis and with emphasis on extracellular vesicles as a novel diagnostic and therapeutic incentive.

Glutamate-induced excitotoxicity in Parkinson's disease: The role of glial cells

Glutamate is the major excitatory neurotransmitter in the central nervous system. Glutamate transmission efficiency depends on the correct functionality and expression of a plethora of receptors and transporters, located both on neurons and glial cells. Of note, glutamate reuptake by dedicated transporters prevents its accumulation at the synapse as well as non-physiological spillover. Indeed, extracellular glutamate increase causes aberrant synaptic signaling leading to neuronal excitotoxicity and death. Moreover, extrasynaptic glutamate diffusion is strongly associated with glia reaction and neuroinflammation. Glutamate-induced excitotoxicity is mainly linked to an impaired ability of glial cells to reuptake and respond to glutamate, then this is considered a common hallmark in many neurodegenerative diseases, including Parkinson's disease (PD). In this review, we discuss the function of astrocytes and microglia in glutamate homeostasis, focusing on how glial dysfunction causes glutamate-induced excitotoxicity leading to neurodegeneration in PD.

A novel multi-marker discovery approach identifies new serum biomarkers for Parkinson's disease in older people: an EXosomes in PArkiNson Disease (EXPAND) ancillary study

Dopaminergic nigrostriatal denervation and widespread intracellular α-synuclein accumulation are neuropathologic hallmarks of Parkinson's disease (PD). A constellation of peripheral processes, including metabolic and inflammatory changes, are thought to contribute to neurodegeneration. In the present study, we sought to obtain insight into the multifaceted pathophysiology of PD through the application of a multi-marker discovery approach. Fifty older adults aged 70+, 20 with PD and 30 age-matched controls were enrolled as part of the EXosomes in PArkiNson Disease (EXPAND) study. A panel of 68 circulating mediators of inflammation, neurogenesis and neural plasticity, and amino acid metabolism was assayed. Biomarker selection was accomplished through sequential and orthogonalized covariance selection (SO-CovSel), a multi-platform regression method developed to handle highly correlated variables organized in multi-block datasets. The SO-CovSel model with the best prediction ability using the smallest number of variables was built with seven biomolecules. The model allowed correct classification of 94.2 ± 3.1% participants with PD and 100% controls. The biomarker profile of older adults with PD was defined by higher circulating levels of interleukin (IL) 8, macrophage inflammatory protein (MIP)-1β, phosphoethanolamine, and proline, and by lower concentrations of citrulline, IL9, and MIP-1α. Our innovative approach allowed identifying and evaluating the classification performance of a set of potential biomarkers for PD in older adults. Future studies are warranted to establish whether these biomolecules could serve as biomarkers for PD as well as unveil new targets for interventions.

Quantitative metabolomics of saliva using proton NMR spectroscopy in patients with Parkinson's disease and healthy controls

INTRODUCTION

Parkinson's disease (PD) is a multisystem disorder of unknown etiology, highlights a broad array of symptoms and pathological features influencing organs throughout the body. The metabolic profile of saliva in patients with PD may be influenced by malabsorption in the gastroenteric tract, neurodegeneration, and mitochondrial dysfunction. In the present study, we apply a powerful NMR metabolomics approach for biomarker identification in PD using saliva, a non-invasive bio-fluid.

METHODS

Metabolic profiling of saliva were studied in patients with PD (n = 76) and healthy controls (HC, n = 37) were analyzed and differentiated PD from HC. A total of 40 metabolites including aromatic amino acids, short-chain fatty acids, branched chain amino acids, taurine, and N-acetylglutamate were identified. Spectral binned data and concentration of metabolites were estimated for analysis.

RESULTS

Increased concentration of phenylalanine, tyrosine, histidine, glycine, acetoacetate, taurine, TMAO, GABA, N-acetylglutamate, acetoin, acetate, alanine, fucose, propionate, isoleucine, and valine were observed in PD as compared to HC. Further, subgroup analysis among early PD, advanced PD, and HC groups, revealed increased metabolite concentration in early PD group as compared to advanced PD and HC group.

DISCUSSION

Analysis revealed potential biomarkers and their involvement in amino acid metabolism, energy metabolism, neurotransmitters metabolism, and microflora system. Patients with early PD exhibited higher metabolite concentration as compared to advanced PD group which might be associated with dopaminergic treatment.

CONCLUSION

The results of our data indicate that patients with PD might be characterized by metabolic imbalances like gut microflora system, energy metabolites, and neurotransmitters which may contribute to the PD pathogenesis.