Metabolomic investigations in cerebrospinal fluid of Parkinson's disease

Unveiling Parkinson's disease through biomarker research: current insights and future prospects

Parkinson's disease (PD) is a neurodegenerative condition marked by the gradual depletion of dopaminergic neurons in the substantia nigra. Despite substantial strides in comprehending potential causative mechanisms, the validation of biomarkers with unequivocal evidence for routine clinical application remains elusive. Consequently, the diagnosis heavily relies on patients' clinical assessments and medical backgrounds. The imperative need for diagnostic and prognostic biomarkers arises due to the prevailing limitations of treatments, which predominantly address symptoms without modifying the disease course. This comprehensive review aims to elucidate the existing landscape of diagnostic and prognostic biomarkers for PD, drawing insights from contemporary literature.

Identification of metabolites reproducibly associated with Parkinson's Disease via meta-analysis and computational modelling

Many studies have reported metabolomic analysis of different bio-specimens from Parkinson's disease (PD) patients. However, inconsistencies in reported metabolite concentration changes make it difficult to draw conclusions as to the role of metabolism in the occurrence or development of Parkinson's disease. We reviewed the literature on metabolomic analysis of PD patients. From 74 studies that passed quality control metrics, 928 metabolites were identified with significant changes in PD patients, but only 190 were replicated with the same changes in more than one study. Of these metabolites, 60 exclusively increased, such as 3-methoxytyrosine and glycine, 54 exclusively decreased, such as pantothenic acid and caffeine, and 76 inconsistently changed in concentration in PD versus control subjects, such as ornithine and tyrosine. A genome-scale metabolic model of PD and corresponding metabolic map linking most of the replicated metabolites enabled a better understanding of the dysfunctional pathways of PD and the prediction of additional potential metabolic markers from pathways with consistent metabolite changes to target in future studies.

A crazy trio in Parkinson's disease: metabolism alteration, α-synuclein aggregation, and oxidative stress

Parkinson's disease (PD) is an aging-associated neurodegenerative disorder, characterized by the progressive loss of dopaminergic neurons in the pars compacta of the substantia nigra and the presence of Lewy bodies containing α-synuclein within these neurons. Oligomeric α-synuclein exerts neurotoxic effects through mitochondrial dysfunction, glial cell inflammatory response, lysosomal dysfunction and so on. α-synuclein aggregation, often accompanied by oxidative stress, is generally considered to be a key factor in PD pathology. At present, emerging evidences suggest that metabolism alteration is closely associated with α-synuclein aggregation and PD progression, and improvement of key molecules in metabolism might be potentially beneficial in PD treatment. In this review, we highlight the tripartite relationship among metabolic changes, α-synuclein aggregation, and oxidative stress in PD, and offer updated insights into the treatments of PD, aiming to deepen our understanding of PD pathogenesis and explore new therapeutic strategies for the disease.

Relationship among Parkinson's disease, constipation, microbes, and microbiological therapy

This comprehensive review elucidates the complex interplay between gut microbiota and constipation in Parkinson's disease (PD), a prevalent non-motor symptom contributing significantly to patients' morbidity. A marked alteration in the gut microbiota, predominantly an increase in the abundance of Proteobacteria and Bacteroidetes, is observed in PD-related constipation. Conventional treatments, although safe, have failed to effectively alleviate symptoms, thereby necessitating the development of novel therapeutic strategies. Microbiological interventions such as prebiotics, probiotics, and fecal microbiota transplantation (FMT) hold therapeutic potential. While prebiotics improve bowel movements, probiotics are effective in enhancing stool consistency and alleviating abdominal discomfort. FMT shows potential for significantly alleviating constipation symptoms by restoring gut microbiota balance in patients with PD. Despite promising developments, the causal relationship between changes in gut microbiota and PD-related constipation remains elusive, highlighting the need for further research in this expanding field.

Deciphering the complexes of zinc ions and hen egg white lysozyme: Instrumental analysis, molecular docking, and antimicrobial assessment

In the research presented in this manuscript, an intricate study has been carried out on the interaction of zinc ions with the hen egg white lysozyme (HEWL) protein. Utilizing a spectroscopic technique, the alterations that arise due to the binding of Zn2+ to the HEWL were scrutinized, underscoring the paramount significance of deprotonated carboxyl and thiol groups in the process of binding. The binding phenomena were substantiated using capillary electrophoresis integrated with inductively coupled plasma mass spectrometry (CE-ICP-MS). Further spectrometric assessments (MALDI-TOF MS and FT-ICR-MS) shed light on the direct interaction of zinc ions with the functional groups of the protein. Importantly, high-resolution FT-ICR-MS techniques elucidated the capability of a single protein molecule to bind to multiple zinc ions. The empirically derived spectroscopic data received additional confirmation via a molecular docking study of the Zn2+ binding process, which highlighted a substantial affinity between the predicted 3D model of zinc-lysozyme complexes. Predominantly, the interaction between the bound entities was observed at the cysteine residues. Lastly, the conducted antimicrobial tests revealed that the zinc-lysozyme complexes manifest an inhibitory effect against bacterial (E. coli and S. aureus) and yeast (C. albicans) strains.

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.

Metabolomics: An Emerging "Omics" Platform for Systems Biology and Its Implications for Huntington Disease Research

Huntington's disease (HD) is a progressive, fatal neurodegenerative disease characterized by motor, cognitive, and psychiatric symptoms. The precise mechanisms of HD progression are poorly understood; however, it is known that there is an expansion of the trinucleotide cytosine-adenine-guanine (CAG) repeat in the Huntingtin gene. Important new strategies are of paramount importance to identify early biomarkers with predictive value for intervening in disease progression at a stage when cellular dysfunction has not progressed irreversibly. Metabolomics is the study of global metabolite profiles in a system (cell, tissue, or organism) under certain conditions and is becoming an essential tool for the systemic characterization of metabolites to provide a snapshot of the functional and pathophysiological states of an organism and support disease diagnosis and biomarker discovery. This review briefly highlights the historical progress of metabolomic methodologies, followed by a more detailed review of the use of metabolomics in HD research to enable a greater understanding of the pathogenesis, its early prediction, and finally the main technical platforms in the field of metabolomics.

Plasma metabolites of aromatic amino acids associate with clinical severity and gut microbiota of Parkinson's disease

Gut microbial proteolytic metabolism has been reportedly altered in Parkinson's disease (PD). However, the circulating aromatic amino acids (AAA) described in PD are inconsistent. Here we aimed to investigate plasma AAA profiles in a large cohort of PD patients, and examine their correlations with clinical severity and gut microbiota changes. We enrolled 500 participants including 250 PD patients and 250 neurologically normal controls. Plasma metabolites were measured using liquid chromatography mass spectrometry. Faecal samples were newly collected from 154 PD patients for microbiota shotgun metagenomic sequencing combined with data derived from 96 PD patients reported before. Data were collected regarding diet, medications, and motor and non-motor symptoms of PD. Compared to controls, PD patients had higher plasma AAA levels, including phenylacetylglutamine (PAGln), p-cresol sulfate (Pcs), p-cresol glucuronide (Pcg), and indoxyl sulfate (IS). Multivariable linear regression analyses, with adjustment for age, sex, and medications, revealed that the plasma levels of PAGln (coefficient 4.49, 95% CI 0.40-8.58, P = 0.032) and Pcg (coefficient 1.79, 95% CI 0.07-3.52, P = 0.042) positively correlated with motor symptom severity but not cognitive function. After correcting for abovementioned potential confounders, these AAA metabolites were also associated with the occurrence of constipation in PD patients (all P < 0.05). Furthermore, plasma levels of AAA metabolites were correlated with the abundance of specific gut microbiota species, including Bacteroides sp. CF01-10NS, Bacteroides vulgatus, and Clostridium sp. AF50-3. In conclusion, elevated plasma AAA metabolite levels correlated with disease characteristics in PD, suggesting that upregulated proteolytic metabolism may contribute to the pathophysiology of PD.

Exploring the interplay between metabolomics and genetics in Parkinson's disease: Insights from ongoing research and future avenues

Parkinson's disease (PD) is a widespread neurodegenerative disorder, whose complex aetiology remains under construction. While rare variants have been associated with the monogenic PD form, most PD cases are influenced by multiple genetic and environmental aspects. Nonetheless, the pathophysiological pathways and molecular networks involved in monogenic/idiopathic PD overlap, and genetic variants are decisive in elucidating the convergent underlying mechanisms of PD. In this scenario, metabolomics has furnished a dynamic and systematic picture of the synergy between the genetic background and environmental influences that impact PD, making it a valuable tool for investigating PD-related metabolic dysfunctions. In this review, we performed a brief overview of metabolomics current research in PD, focusing on significant metabolic alterations observed in idiopathic PD from different biofluids and strata and exploring how they relate to genetic factors associated with monogenic PD. Dysregulated amino acid metabolism, lipid metabolism, and oxidative stress are the critical metabolic pathways implicated in both genetic and idiopathic PD. By merging metabolomics and genetics data, it is possible to distinguish metabolic signatures of specific genetic backgrounds and to pinpoint subgroups of PD patients who could derive personalized therapeutic benefits. This approach holds great promise for advancing PD research and developing innovative, cost-effective treatments.

Anti-inflammatory effects of myristic acid mediated by the NF-κB pathway in lipopolysaccharide-induced BV-2 microglial cells

Parkinson's disease (PD) is a serious neurodegenerative disorder wherein changes in metabolites related to lipids, glutathione, and energy metabolism occur. Currently, metabolite changes in PD have been reported, yet their role in the prognosis of disease remains poorly understood. Functional metabolites can be used to diagnose diseases, especially PD, and can exert neuroprotective effects. This study used a PD animal model and a lipopolysaccharide (LPS)-mediated inflammatory response model (using the BV-2 mouse microglial cell line) to identify functional metabolites that can identify important metabolic disorders during PD, and comprehensively evaluated their profiles using a metabolomics-based approach. Our results showed that co-treatment with myristic acid and heptadecanoic acid downregulated the expression of interleukin (IL)-1β, IL-6, and tumor necrosis factor-α in BV-2 cells. Additionally, myristic acid and 10 μM heptadecanoic acid significantly inhibited the LPS-induced inflammatory response through the nuclear factor-κB pathway in BV-2 microglial cells, which provides a potential approach for PD treatment. Myristic acid and heptadecanoic acid were the active metabolites found by active metabolomics technology, but at present, there is no research report about their function for PD treatment, and our findings offer a novel research strategy for PD diagnosis and treatment.

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

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

More than meets the eye in Parkinson's disease and other synucleinopathies: from proteinopathy to lipidopathy

The accumulation of proteinaceous inclusions in the brain is a common feature among neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease (PD), and dementia with Lewy bodies (DLB). The main neuropathological hallmark of PD and DLB are inclusions, known as Lewy bodies (LBs), enriched not only in α-synuclein (aSyn), but also in lipid species, organelles, membranes, and even nucleic acids. Furthermore, several genetic risk factors for PD are mutations in genes involved in lipid metabolism, such as GBA1, VSP35, or PINK1. Thus, it is not surprising that mechanisms that have been implicated in PD, such as inflammation, altered intracellular and vesicular trafficking, mitochondrial dysfunction, and alterations in the protein degradation systems, may be also directly or indirectly connected through lipid homeostasis. In this review, we highlight and discuss the recent evidence that suggests lipid biology as important drivers of PD, and which require renovated attention by neuropathologists. Particularly, we address the implication of lipids in aSyn accumulation and in the spreading of aSyn pathology, in mitochondrial dysfunction, and in ER stress. Together, this suggests we should broaden the view of PD not only as a proteinopathy but also as a lipidopathy.

Mitochondrial Bioenergy in Neurodegenerative Disease: Huntington and Parkinson

Strong evidence suggests a correlation between degeneration and mitochondrial deficiency. Typical cases of degeneration can be observed in physiological phenomena (i.e., ageing) as well as in neurological neurodegenerative diseases and cancer. All these pathologies have the dyshomeostasis of mitochondrial bioenergy as a common denominator. Neurodegenerative diseases show bioenergetic imbalances in their pathogenesis or progression. Huntington's chorea and Parkinson's disease are both neurodegenerative diseases, but while Huntington's disease is genetic and progressive with early manifestation and severe penetrance, Parkinson's disease is a pathology with multifactorial aspects. Indeed, there are different types of Parkinson/Parkinsonism. Many forms are early-onset diseases linked to gene mutations, while others could be idiopathic, appear in young adults, or be post-injury senescence conditions. Although Huntington's is defined as a hyperkinetic disorder, Parkinson's is a hypokinetic disorder. However, they both share a lot of similarities, such as neuronal excitability, the loss of striatal function, psychiatric comorbidity, etc. In this review, we will describe the start and development of both diseases in relation to mitochondrial dysfunction. These dysfunctions act on energy metabolism and reduce the vitality of neurons in many different brain areas.

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other “omic” techniques might be required.

Diagnostic metabolomic profiling of Parkinson's disease biospecimens

BACKGROUND

Reliable and sensitive biomarkers are needed for enhancing and predicting Parkinson's disease (PD) diagnosis.

OBJECTIVE

To investigate comprehensive metabolomic profiling of biochemicals in CSF and serum for determining diagnostic biomarkers of PD.

METHODS

Fifty subjects, symptomatic with PD for ≥5 years, were matched to 50 healthy controls (HCs). We used ultrahigh-performance liquid chromatography linked to tandem mass spectrometry (UHPLC-MS/MS) for measuring relative concentrations of ≤1.5 kDalton biochemicals. A reference library created from authentic standards facilitated chemical identifications. Analytes underwent univariate analysis for PD association, with false discovery rate-adjusted p-value (≤0.05) determinations. Multivariate analysis (for identifying a panel of biochemicals discriminating PD from HCs) used several biostatistical methods, including logistic LASSO regression.

RESULTS

Comparing PD and HCs, strong differentiation was achieved from CSF but not serum specimens. With univariate analysis, 21 CSF compounds exhibited significant differential concentrations. Logistic LASSO regression led to selection of 23 biochemicals (11 shared with those determined by the univariate analysis). The selected compounds, as a group, distinguished PD from HCs, with Area-Under-the-Receiver-Operating-Characteristic (ROC) curve of 0.897. With optimal cutoff, logistic LASSO achieved 100% sensitivity and 96% specificity (and positive and negative predictive values of 96% and 100%). Ten-fold cross-validation gave 84% sensitivity and 82% specificity (and 82% positive and 84% negative predictive values). From the logistic LASSO-chosen regression model, 2 polyamine metabolites (N-acetylcadaverine and N-acetylputrescine) were chosen and had the highest fold-changes in comparing PD to HCs. Another chosen biochemical, acisoga (N-(3-acetamidopropyl)pyrrolidine-2-one), also is a polyamine metabolism derivative.

CONCLUSIONS

UHPLC-MS/MS assays provided a metabolomic signature highly predictive of PD. These findings provide further evidence for involvement of polyamine pathways in the neurodegeneration of PD.

A Metabolic Signature of Hereditary Transthyretin Amyloidosis: A Pilot Study

Hereditary transthyretin amyloidosis is the most common form of hereditary amyloidosis, with an autosomal dominant inheritance and a variable penetrance. ATTRv amyloidosis can present as a progressive, axonal sensory autonomic and motor neuropathy or as an infiltrative cardiomyopathy. The definition of biomarkers for the early diagnosis of ATTRv is particularly important in the current era of emerging treatments. In this sense, metabolomics could be an instrument able to provide metabolic profiles with their related metabolic pathways, and we would propose them as possible fluid biomarkers. The aim of this study is to identify altered metabolites (free fatty acids and amino acids) in subjects with a confirmed pathogenic TTR variant. Out of the studied total free fatty acids and amino acids, the serum values of palmitic acid are significantly lower in the ATTRv patients compared to the recruited healthy subjects. The metabolic remodeling identified in this neurogenetic disorder could be the manifestation of pathophysiological processes of the disease, such as mitochondrial dysfunction and neuroinflammation, and contribute to explaining some of its clinical manifestations.

Microbiome and Metabolome Insights into the Role of the Gastrointestinal-Brain Axis in Parkinson's and Alzheimer's Disease: Unveiling Potential Therapeutic Targets

Neurodegenerative diseases such as Parkinson's (PD) and Alzheimer's disease (AD), the prevalence of which is rapidly rising due to an aging world population and westernization of lifestyles, are expected to put a strong socioeconomic burden on health systems worldwide. Clinical trials of therapies against PD and AD have only shown limited success so far. Therefore, research has extended its scope to a systems medicine point of view, with a particular focus on the gastrointestinal-brain axis as a potential main actor in disease development and progression. Microbiome and metabolome studies have already revealed important insights into disease mechanisms. Both the microbiome and metabolome can be easily manipulated by dietary and lifestyle interventions, and might thus offer novel, readily available therapeutic options to prevent the onset as well as the progression of PD and AD. This review summarizes our current knowledge on the interplay between microbiota, metabolites, and neurodegeneration along the gastrointestinal-brain axis. We further illustrate state-of-the art methods of microbiome and metabolome research as well as metabolic modeling that facilitate the identification of disease pathomechanisms. We conclude with therapeutic options to modulate microbiome composition to prevent or delay neurodegeneration and illustrate potential future research directions to fight PD and AD.

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.

Gut microenvironmental changes as a potential trigger in Parkinson's disease through the gut-brain axis

Parkinson's disease (PD) is the second most common neurodegenerative disease attributed to the synergistic effects of genetic risk and environmental stimuli. Although PD is characterized by motor dysfunction resulting from intraneuronal alpha-synuclein accumulations, termed Lewy bodies, and dopaminergic neuronal degeneration in the substantia nigra, multiple systems are involved in the disease process, resulting in heterogenous clinical presentation and progression. Genetic predisposition to PD regarding aberrant immune responses, abnormal protein aggregation, autophagolysosomal impairment, and mitochondrial dysfunction leads to vulnerable neurons that are sensitive to environmental triggers and, together, result in neuronal degeneration. Neuropathology studies have shown that, at least in some patients, Lewy bodies start from the enteric nervous system and then spread to the central dopaminergic neurons through the gut-brain axis, suggesting the contribution of an altered gut microenvironment in the pathogenesis of PD. A plethora of evidence has revealed different gut microbiomes and gut metabolites in patients with PD compared to unaffected controls. Chronic gut inflammation and impaired intestinal barrier integrity have been observed in human PD patients and mouse models of PD. These observations led to the hypothesis that an altered gut microenvironment is a potential trigger of the PD process in a genetically susceptible host. In this review, we will discuss the complex interplay between genetic factors and gut microenvironmental changes contributing to PD pathogenesis.

Graph Properties of Mass-Difference Networks for Profiling and Discrimination in Untargeted Metabolomics

Untargeted metabolomics seeks to identify and quantify most metabolites in a biological system. In general, metabolomics results are represented by numerical matrices containing data that represent the intensities of the detected variables. These matrices are subsequently analyzed by methods that seek to extract significant biological information from the data. In mass spectrometry-based metabolomics, if mass is detected with sufficient accuracy, below 1 ppm, it is possible to derive mass-difference networks, which have spectral features as nodes and chemical changes as edges. These networks have previously been used as means to assist formula annotation and to rank the importance of chemical transformations. In this work, we propose a novel role for such networks in untargeted metabolomics data analysis: we demonstrate that their properties as graphs can also be used as signatures for metabolic profiling and class discrimination. For several benchmark examples, we computed six graph properties and we found that the degree profile was consistently the property that allowed for the best performance of several clustering and classification methods, reaching levels that are competitive with the performance using intensity data matrices and traditional pretreatment procedures. Furthermore, we propose two new metrics for the ranking of chemical transformations derived from network properties, which can be applied to sample comparison or clustering. These metrics illustrate how the graph properties of mass-difference networks can highlight the aspects of the information contained in data that are complementary to the information extracted from intensity-based data analysis.

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.

A Set of Reliable Samples for the Study of Biomarkers for the Early Diagnosis of Parkinson's Disease

Background

Parkinson's disease (PD) is a progressive neurodegenerative disorder, diagnosed according to the clinical criteria that occur in already advanced stages of PD. The definition of biomarkers for the early diagnosis of PD represents a challenge that might improve treatment and avoid complications in this disease. Therefore, we propose a set of reliable samples for the identification of altered metabolites to find potential prognostic biomarkers for early PD.

Methods

This case–control study included plasma samples of 12 patients with PD and 21 control subjects, from the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC)-Navarra cohort, part of the EPIC-Spain study. All the case samples were provided by healthy volunteers who were followed-up for 15.9 (±4.1) years and developed PD disease later on, after the sample collection. Liquid chromatography coupled to tandem mass spectrometry was used for the analysis of samples.

Results

Out of 40 that were selected and studied due to their involvement in established cases of PD, seven significantly different metabolites between PD cases and healthy control subjects were obtained in this study (benzoic acid, palmitic acid, oleic acid, stearic acid, myo-inositol, sorbitol, and quinolinic acid). These metabolites are related to mitochondrial dysfunction, the oxidative stress, and the mechanisms of energy production.

Conclusion

We propose the samples from the EPIC study as reliable and invaluable samples for the search of early biomarkers of PD. Likewise, this study might also be a starting point in the establishment of a well-founded panel of metabolites that can be used for the early detection of this disease.

Predictive Modeling of Alzheimer's and Parkinson's Disease Using Metabolomic and Lipidomic Profiles from Cerebrospinal Fluid

In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer's disease (AD), Parkinson's disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies.

GAIT-GM integrative cross-omics analyses reveal cholinergic defects in a C. elegans model of Parkinson's disease

Parkinson’s disease (PD) is a disabling neurodegenerative disorder in which multiple cell types, including dopaminergic and cholinergic neurons, are affected. The mechanisms of neurodegeneration in PD are not fully understood, limiting the development of therapies directed at disease-relevant molecular targets. C. elegans is a genetically tractable model system that can be used to disentangle disease mechanisms in complex diseases such as PD. Such mechanisms can be studied combining high-throughput molecular profiling technologies such as transcriptomics and metabolomics. However, the integrative analysis of multi-omics data in order to unravel disease mechanisms is a challenging task without advanced bioinformatics training. Galaxy, a widely-used resource for enabling bioinformatics analysis by the broad scientific community, has poor representation of multi-omics integration pipelines. We present the integrative analysis of gene expression and metabolite levels of a C. elegans PD model using GAIT-GM, a new Galaxy tool for multi-omics data analysis. Using GAIT-GM, we discovered an association between branched-chain amino acid metabolism and cholinergic neurons in the C. elegans PD model. An independent follow-up experiment uncovered cholinergic neurodegeneration in the C. elegans model that is consistent with cholinergic cell loss observed in PD. GAIT-GM is an easy to use Galaxy-based tool for generating novel testable hypotheses of disease mechanisms involving gene-metabolite relationships.

Update on CSF Biomarkers in Parkinson's Disease

Progress in developing disease-modifying therapies in Parkinson’s disease (PD) can only be achieved through reliable objective markers that help to identify subjects at risk. This includes an early and accurate diagnosis as well as continuous monitoring of disease progression and therapy response. Although PD diagnosis still relies mainly on clinical features, encouragingly, advances in biomarker discovery have been made. The cerebrospinal fluid (CSF) is a biofluid of particular interest to study biomarkers since it is closest to the brain structures and therefore could serve as an ideal source to reflect ongoing pathologic processes. According to the key pathophysiological mechanisms, the CSF status of α-synuclein species, markers of amyloid and tau pathology, neurofilament light chain, lysosomal enzymes and markers of neuroinflammation provide promising preliminary results as candidate biomarkers. Untargeted approaches in the field of metabolomics provide insights into novel and interconnected biological pathways. Markers based on genetic forms of PD can contribute to identifying subgroups suitable for gene-targeted treatment strategies that might also be transferable to sporadic PD. Further validation analyses in large PD cohort studies will identify the CSF biomarker or biomarker combinations with the best value for clinical and research purposes.

Cerebrospinal Fluid Metabolome in Parkinson's Disease and Multiple System Atrophy

Parkinson’s disease (PD) and multiple system atrophy (MSA) belong to the neurodegenerative group of synucleinopathies; differential diagnosis between PD and MSA is difficult, especially at early stages, owing to their clinical and biological similarities. Thus, there is a pressing need to identify metabolic biomarkers for these diseases. The metabolic profile of the cerebrospinal fluid (CSF) is reported to be altered in PD and MSA; however, the altered metabolites remain unclear. We created a single network with altered metabolites in PD and MSA based on the literature and assessed biological functions, including metabolic disorders of the nervous system, inflammation, concentration of ATP, and neurological disorder, through bioinformatics methods. Our in-silico prediction-based metabolic networks are consistent with Parkinsonism events. Although metabolomics approaches provide a more quantitative understanding of biochemical events underlying the symptoms of PD and MSA, limitations persist in covering molecules related to neurodegenerative disease pathways. Thus, omics data, such as proteomics and microRNA, help understand the altered metabolomes mechanism. In particular, integrated omics and machine learning approaches will be helpful to elucidate the pathological mechanisms of PD and MSA. This review discusses the altered metabolites between PD and MSA in the CSF and omics approaches to discover diagnostic biomarkers.

Multi-Omics Approach to Elucidate Cerebrospinal Fluid Changes in Dogs with Intervertebral Disc Herniation

Herniation of the intervertebral disc (IVDH) is the most common cause of neurological and intervertebral disc degeneration-related diseases. Since the disc starts to degenerate before it can be observed by currently available diagnostic methods, there is an urgent need for novel diagnostic approaches. To identify molecular networks and pathways which may play important roles in intervertebral disc herniation, as well as to reveal the potential features which could be useful for monitoring disease progression and prognosis, multi-omics profiling, including high-resolution liquid chromatography-mass spectrometry (LC-MS)-based metabolomics and tandem mass tag (TMT)-based proteomics was performed. Cerebrospinal fluid of nine dogs with IVDH and six healthy controls were used for the analyses, and an additional five IVDH samples were used for proteomic data validation. Furthermore, multi-omics data were integrated to decipher a complex interaction between individual omics layers, leading to an improved prediction model. Together with metabolic pathways related to amino acids and lipid metabolism and coagulation cascades, our integromics prediction model identified the key features in IVDH, namely the proteins follistatin Like 1 (FSTL1), secretogranin V (SCG5), nucleobindin 1 (NUCB1), calcitonin re-ceptor-stimulating peptide 2 precursor (CRSP2) and the metabolites N-acetyl-D-glucosamine and adenine, involved in neuropathic pain, myelination, and neurotransmission and inflammatory response, respectively. Their clinical application is to be further investigated. The utilization of a novel integrative interdisciplinary approach may provide new opportunities to apply innovative diagnostic and monitoring methods as well as improve treatment strategies and personalized care for patients with degenerative spinal disorders.

The neuromicrobiology of Parkinson's disease: A unifying theory

Recent evidence confirms that PD is indeed a multifactorial disease with different aetiologies and prodromal symptomatology that likely depend on the initial trigger. New players with important roles as triggers, facilitators and aggravators of the PD neurodegenerative process have re-emerged in the last few years, the microbes. Having evolved in association with humans for ages, microbes and their products are now seen as fundamental regulators of human physiology with disturbances in their balance being increasingly accepted to have a relevant impact on the progression of disease in general and on PD in particular. In this review, we comprehensively address early studies that have directly or indirectly linked bacteria or other infectious agents to the onset and progression of PD, from the earliest suspects to the most recent culprits, the gut microbiota. The quest for effective treatments to arrest PD progression must inevitably address the different interactions between microbiota and human cells, and naturally consider the gut-brain axis. The comprehensive characterization of such mechanisms will help design innovative bacteriotherapeutic approaches to selectively shape the gut microbiota profile ultimately to halt PD progression. The present review describes our current understanding of the role of microorganisms and their endosymbiotic relatives, the mitochondria, in inducing, facilitating, or aggravating PD pathogenesis.

Substantively Lowered Levels of Pantothenic Acid (Vitamin B5) in Several Regions of the Human Brain in Parkinson's Disease Dementia

Pantothenic acid (vitamin B5) is an essential trace nutrient required for the synthesis of coenzyme A (CoA). It has previously been shown that pantothenic acid is significantly decreased in multiple brain regions in both Alzheimer's disease (ADD) and Huntington's disease (HD). The current investigation aimed to determine whether similar changes are also present in cases of Parkinson's disease dementia (PDD), another age-related neurodegenerative condition, and whether such perturbations might occur in similar regions in these apparently different diseases. Brain tissue was obtained from nine confirmed cases of PDD and nine controls with a post-mortem delay of 26 h or less. Tissues were acquired from nine regions that show high, moderate, or low levels of neurodegeneration in PDD: the cerebellum, motor cortex, primary visual cortex, hippocampus, substantia nigra, middle temporal gyrus, medulla oblongata, cingulate gyrus, and pons. A targeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to quantify pantothenic acid in these tissues. Pantothenic acid was significantly decreased in the cerebellum (p = 0.008), substantia nigra (p = 0.02), and medulla (p = 0.008) of PDD cases. These findings mirror the significant decreases in the cerebellum of both ADD and HD cases, as well as the substantia nigra, putamen, middle frontal gyrus, and entorhinal cortex of HD cases, and motor cortex, primary visual cortex, hippocampus, middle temporal gyrus, cingulate gyrus, and entorhinal cortex of ADD cases. Taken together, these observations indicate a common but regionally selective disruption of pantothenic acid levels across PDD, ADD, and HD.

Identification of potential serum metabolic biomarkers for patient with keratoconus using untargeted metabolomics approach

This study aimed to investigate the metabolite differences between patients with keratoconus and control subjects and identify potential serum biomarkers for keratoconus using a non-targeted metabolomics approach. Venous blood samples were obtained from patients with keratoconus (n = 20) as well as from age-, gender- and race-matched control subjects (n = 20). Metabolites extracted from serum were separated and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometer. Processing of raw data and analysis of the data files was performed using Agilent Mass Hunter Qualitative software. The identified metabolites were subjected to a principal component and hierarchical cluster analysis. Appropriate statistical tests were used to analyze the metabolomic profiling data. Together, the analysis revealed that the dehydroepiandrosterone sulfate from the steroidal hormone synthesis pathway was significantly upregulated in patients with keratoconus (p < 0.05). Also, a combination of eicosanoids from the arachidonic acid pathway, mainly prostaglandin F2α, prostaglandin A2, 16,16-dimethyl prostaglandin E2, and 5-hydroxyeicosatetraenoic acid were collectively up-regulated as a group in keratoconus patients (p < 0.05). On the other hand, glycerophospholipid PS(17:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)) was found to be significantly upregulated in the metabolomics profiles of control subjects (p < 0.05). The differently regulated metabolites provide insights into the pathophysiology of keratoconus and could potentially be used as biomarkers for keratoconus to aid in screening for individuals at risk hence, enabling early diagnosis and timely monitoring of disease.

Simultaneous Quantification and Speciation of Trace Metals in Paired Serum and CSF Samples by Size Exclusion Chromatography-Inductively Coupled Plasma-Dynamic Reaction Cell-Mass Spectrometry (SEC-DRC-ICP-MS)

BACKGROUND

Transition metals play a crucial role in brain metabolism: since they exist in different oxidation states they are involved in ROS generation, but they are also co-factors of enzymes in cellular energy metabolism or oxidative defense.

METHODS

Paired serum and cerebrospinal fluid (CSF) samples were analyzed for iron, zinc, copper and manganese as well as for speciation using SEC-ICP-DRC-MS. Brain extracts from Mn-exposed rats were additionally analyzed with SEC-ICP-DRC-MS.

RESULTS

The concentration patterns of transition metal size fractions were correlated between serum and CSF: Total element concentrations were significantly lower in CSF. Fe-ferritin was decreased in CSF whereas a LMW Fe fraction was relatively increased. The 400-600 kDa Zn fraction and the Cu-ceruloplasmin fraction were decreased in CSF, by contrast the 40-80 kDa fraction, containing Cu- and Zn-albumin, relatively increased. For manganese, the α-2-macroglobulin fraction showed significantly lower concentration in CSF, whereas the citrate Mn fraction was enriched. Results from the rat brain extracts supported the findings from human paired serum and CSF samples.

CONCLUSIONS

Transition metals are strictly controlled at neural barriers (NB) of neurologic healthy patients. High molecular weight species are down-concentrated along NB, however, the Mn-citrate fraction seems to be less controlled, which may be problematic under environmental load.

Prognostic biomarkers of Parkinson's disease in the Spanish EPIC cohort: a multiplatform metabolomics approach

The lack of knowledge about the onset and progression of Parkinson's disease (PD) hampers its early diagnosis and treatment. Metabolomics might shed light on the PD imprint seeking a broader view of the biochemical remodeling induced by this disease in an early and pre-symptomatic stage and unveiling potential biomarkers. To achieve this goal, we took advantage of the great potential of the European Prospective Study on Nutrition and Cancer (EPIC) cohort to apply metabolomics searching for early diagnostic PD markers. This cohort consisted of healthy volunteers that were followed for around 15 years until June 2011 to ascertain incident PD. For this untargeted metabolomics-based study, baseline preclinical plasma samples of 39 randomly selected individuals that developed PD (Pre-PD group) and the corresponding control group were analyzed using a multiplatform approach. Data were statistically analyzed and exposed alterations in 33 metabolites levels, including significantly lower levels of free fatty acids (FFAs) in the preclinical samples from PD subjects. These results were then validated by adopting a targeted HPLC-QqQ-MS approach. After integrating all the metabolites affected, our finding revealed alterations in FFAs metabolism, mitochondrial dysfunction, oxidative stress, and gut-brain axis dysregulation long before the development of PD hallmarks. Although the biological purpose of these events is still unknown, the remodeled metabolic pathways highlighted in this work might be considered worthy prognostic biomarkers of early prodromal PD. The findings revealed by this work are of inestimable value since this is the first study conducted with samples collected many years before the disease development.

Cerebrospinal fluid metabolomics: detection of neuroinflammation in human central nervous system disease

The high morbidity and mortality of neuroinflammatory diseases drives significant interest in understanding the underlying mechanisms involved in the innate and adaptive immune response of the central nervous system (CNS). Diagnostic biomarkers are important to define treatable neuroinflammation. Metabolomics is a rapidly evolving research area offering novel insights into metabolic pathways, and elucidation of reliable metabolites as biomarkers for diseases. This review focuses on the emerging literature regarding the detection of neuroinflammation using cerebrospinal fluid (CSF) metabolomics in human cohort studies. Studies of classic neuroinflammatory disorders such as encephalitis, CNS infection and multiple sclerosis confirm the utility of CSF metabolomics. Additionally, studies in neurodegeneration and neuropsychiatry support the emerging potential of CSF metabolomics to detect neuroinflammation in common CNS diseases such as Alzheimer's disease and depression. We demonstrate metabolites in the tryptophan-kynurenine pathway, nitric oxide pathway, neopterin and major lipid species show moderately consistent ability to differentiate patients with neuroinflammation from controls. Integration of CSF metabolomics into clinical practice is warranted to improve recognition and treatment of neuroinflammation.

Total Content of Piperidine Analysis in Artane by RP-HPLC Using Pre-Column Derivatization with 4-Toluene Sulfonyl Chloride

A simple, sensitive and accurate reversed-phase high-performance liquid chromatography (RP-HPLC) method was established for the determination of piperidine and piperidine hydrochloride in artane, using pre-column derivatization with 4-toluenesulfonyl chloride. The RP-HPLC method was carried out on a Inertsil C18 column (250 × 4.6 mm I.D.) maintained at 30°C. The mobile phase consisted of water with 0.1% phosphoric acid (phase A) and acetonitrile (phase B) (32:68, V:V) at a flow rate of 1.0 mL/min. Linearity of piperidine was found in the range of 0.44-53.33 μg/mL with R2 = 0.9996. The limit of detection was estimated to be 0.15 μg/mL, and the limit of quantitation was 0.44 μg/mL. The average recovery was 101.82% with relative standard deviations of 0.6% at three spiked levels. The developed method using HPLC-ultraviolet system was a rapid tool for routine analysis of piperidine in the bulk form with good accuracy.

Alpha-Synuclein as a Biomarker of Parkinson's Disease: Good, but Not Good Enough

Parkinson's disease (PD) is the second most common neurodegenerative disorder of the elderly, presenting primarily with symptoms of motor impairment. The disease is diagnosed most commonly by clinical examination with a great degree of accuracy in specialized centers. However, in some cases, non-classical presentations occur when it may be difficult to distinguish the disease from other types of degenerative or non-degenerative movement disorders with overlapping symptoms. The diagnostic difficulty may also arise in patients at the early stage of PD. Thus, a biomarker could help clinicians circumvent such problems and help them monitor the improvement in disease pathology during anti-parkinsonian drug trials. This review first provides a brief overview of PD, emphasizing, in the process, the important role of α-synuclein in the pathogenesis of the disease. Various attempts made by the researchers to develop imaging, genetic, and various biochemical biomarkers for PD are then briefly reviewed to point out the absence of a definitive biomarker for this disorder. In view of the overwhelming importance of α-synuclein in the pathogenesis, a detailed analysis is then made of various studies to establish the biomarker potential of this protein in PD; these studies measured total α-synuclein, oligomeric, and post-translationally modified forms of α-synuclein in cerebrospinal fluid, blood (plasma, serum, erythrocytes, and circulating neuron-specific extracellular vesicles) and saliva in combination with certain other proteins. Multiple studies also examined the accumulation of α-synuclein in various forms in PD in the neural elements in the gut, submandibular glands, skin, and the retina. The measurements of the levels of certain forms of α-synuclein in some of these body fluids or their components or peripheral tissues hold a significant promise in establishing α-synuclein as a definitive biomarker for PD. However, many methodological issues related to detection and quantification of α-synuclein have to be resolved, and larger cross-sectional and follow-up studies with controls and patients of PD, parkinsonian disorders, and non-parkinsonian movement disorders are to be undertaken.

Emerging role of metabolomics in protein conformational disorders

Introduction: Metabolomics focuses on interactions among different metabolites associated with various cellular functions in cells, tissues, and organs. In recent years, metabolomics has emerged as a powerful tool to identify perturbed metabolites, pathways influenced by the environment, for protein conformational diseases (PCDs) and also offers wide clinical application.Area Covered: This review provides a brief overview of recent advances in metabolomics as applied to identify metabolic variations in PCDs, such as Alzheimer's disease, Parkinson's disease, Huntington's disease, prion disease, and cardiac amyloidosis. The 'PubMed' and 'Google Scholar' database search methods have been used to screen the published reports with key search terms: metabolomics, biomarkers, and protein conformational disorders.Expert opinion: Metabolomics is the large-scale study of metabolites and is deemed to overwhelm other omics. It plays a crucial role in finding variations in diseases due to protein conformational changes. However, many PCDs are yet to be identified. Metabolomics is still an emerging field; there is a need for new high-resolution analytical techniques and more studies need to be carried out to generate new information.

NPT520-34 improves neuropathology and motor deficits in a transgenic mouse model of Parkinson's disease

NPT520-34 is a clinical-stage, small molecule being developed for the treatment of Parkinson's disease and other neurodegenerative disorders. The therapeutic potential of NPT520-34 was first suggested by findings from cell-based assays of alpha-synuclein (ASYN) clearance. As reported here, NPT520-34 was subsequently evaluated for therapeutically relevant actions in a transgenic animal model of Parkinson's disease that overexpresses human ASYN and in an acute lipopolysaccharide (LPS)-challenge model using wild-type mice. Daily administration of NPT520-34 to mThy1-ASYN (Line 61) transgenic mice for one or three months resulted in reduced ASYN pathology, reduced expression of markers of neuroinflammation, and improvements in multiple indices of motor function. In an LPS-challenge model using wild-type mice, a single-dose of NPT520-34 reduced LPS-evoked increases in the expression of several pro-inflammatory cytokines in plasma. These findings demonstrate the beneficial effects of NPT520-34 on both inflammation and protein-pathology endpoints, with consequent improvements in motor function in an animal model of Parkinson's disease. These findings further suggest that NPT520-34 may have two complementary actions: (1) to increase the clearance of neurotoxic protein aggregates and (2) to directly attenuate inflammation. NPT520-34 treatment may thereby address two of the predominate underlying pathophysiological aspects of neurodegenerative disorders such as Parkinson's disease.

Identification of bioactive metabolites in human iPSC-derived dopaminergic neurons with PARK2 mutation: Altered mitochondrial and energy metabolism

PARK2 (parkin) mutations cause early-onset Parkinson's disease (PD). Parkin is an ubiquitin E3 ligase that participates in several cellular functions, including mitochondrial homeostasis. However, the specific metabolomic changes caused by parkin depletion remain unknown. Here, we used isogenic human induced pluripotent stem cells (iPSCs) with and without PARK2 knockout (KO) to investigate the effect of parkin loss of function by comparative metabolomics supplemented with ultrastructural and functional analyses. PARK2 KO neurons displayed increased tricarboxylic acid (TCA) cycle activity, perturbed mitochondrial ultrastructure, ATP depletion, and dysregulation of glycolysis and carnitine metabolism. These perturbations were combined with increased oxidative stress and a decreased anti-oxidative response. Key findings for PARK2 KO cells were confirmed using patient-specific iPSC-derived neurons. Overall, our data describe a unique metabolomic profile associated with parkin dysfunction and show that combining metabolomics with an iPSC-derived dopaminergic neuronal model of PD is a valuable approach to obtain novel insight into the disease pathogenesis.

Vesicle trafficking and lipid metabolism in synucleinopathy

The neuronal protein α-synuclein (αS) is central to the pathogenesis of Parkinson's disease and other progressive brain diseases such as Lewy body dementia and multiple system atrophy. These diseases, collectively referred to as 'synucleinopathies', have long been considered purely proteinopathies: diseases characterized by the misfolding of a protein into small and large aggregates mainly consisting of that protein (in this case: α-synuclein). However, recent morphological insights into Lewy bodies, the hallmark neuropathology of human synucleinopathies, suggests these lesions are also rich in vesicles and other membranous organelles. Moreover, αS physiology and pathology are both strongly associated with various aspects of intracellular vesicle trafficking and lipid biology. αS physiologically binds to synaptic and other small vesicles, and several functions of αS in regulating vesicle biology have been proposed. Familial PD-linked αS excess and missense mutations have been shown to impair vesicle trafficking and alter lipid homeostasis. On the other hand, vesicle trafficking and lipid-related genes have emerged as Parkinson's risk factors, suggesting a bidirectional relationship. The answer to the question "Does abnormal αS accumulation cause impaired vesicle trafficking and lipid dyshomeostasis or is αS aggregation the consequence of such impairments?" may be "Both". Here, we review current knowledge of the αS-lipid and αS-vesicle trafficking interplay, with a special focus on Parkinson's disease and Lewy body dementia.

Shared genetic etiology between Parkinson's disease and blood levels of specific lipids

Parkinson’s disease (PD) is characterized by the degeneration of dopaminergic neurons in the substantia nigra and the formation of Lewy bodies. The mechanisms underlying these molecular and cellular effects are largely unknown. Previously, based on genetic and other data, we built a molecular landscape of PD that highlighted a central role for lipids. To explore which lipid species may be involved in PD pathology, we used published genome-wide association study (GWAS) data to conduct polygenic risk score-based analyses to examine putative genetic sharing between PD and blood levels of 370 lipid species and lipid-related molecules. We found a shared genetic etiology between PD and blood levels of 25 lipids. We then used data from a much-extended GWAS of PD to try and corroborate our findings. Across both analyses, we found genetic overlap between PD and blood levels of eight lipid species, namely two polyunsaturated fatty acids (PUFA 20:3n3-n6 and 20:4n6), four triacylglycerols (TAG 44:1, 46:1, 46:2, and 48:0), phosphatidylcholine aa 32:3 (PC aa 32:3) and sphingomyelin 26:0 (SM 26:0). Analysis of the concordance—the agreement in genetic variant effect directions across two traits—revealed a significant negative concordance between PD and blood levels of the four triacylglycerols and PC aa 32:3 and a positive concordance between PD and blood levels of both PUFA and SM 26:0. Taken together, our analyses imply that genetic variants associated with PD modulate blood levels of a specific set of lipid species supporting a key role of these lipids in PD etiology.

The Role of Gut Bacterial Metabolites in Brain Development, Aging and Disease

In the last decade, emerging evidence has reported correlations between the gut microbiome and human health and disease, including those affecting the brain. We performed a systematic assessment of the available literature focusing on gut bacterial metabolites and their associations with diseases of the central nervous system (CNS). The bacterial metabolites short-chain fatty acids (SCFAs) as well as non-SCFAs like amino acid metabolites (AAMs) and bacterial amyloids are described in particular. We found significantly altered SCFA levels in patients with autism spectrum disorder (ASD), affective disorders, multiple sclerosis (MS) and Parkinson's disease (PD). Non-SCFAs yielded less significantly distinct changes in faecal levels of patients and healthy controls, with the majority of findings were derived from urinary and blood samples. Preclinical studies have implicated different bacterial metabolites with potentially beneficial as well as detrimental mechanisms in brain diseases. Examples include immunomodulation and changes in catecholamine production by histone deacetylase inhibition, anti-inflammatory effects through activity on the aryl hydrocarbon receptor and involvement in protein misfolding. Overall, our findings highlight the existence of altered bacterial metabolites in patients across various brain diseases, as well as potential neuroactive effects by which gut-derived SCFAs, p-cresol, indole derivatives and bacterial amyloids could impact disease development and progression. The findings summarized in this review could lead to further insights into the gut-brain-axis and thus into potential diagnostic, therapeutic or preventive strategies in brain diseases.

Tumor Metabolism and Neurocognition in CNS Lymphoma

BACKGROUND

The mechanistic basis for neurocognitive deficits in CNS lymphoma and other brain tumors is incompletely understood. We tested the hypothesis that tumor metabolism impairs neurotransmitter pathways and neurocognitive function.

METHODS

We performed serial cerebrospinal fluid (CSF) metabolomic analyses using liquid chromatography-electrospray tandem mass spectrometry to evaluate changes in the tumor microenvironment in 14 patients with recurrent CNS lymphoma, focusing on 18 metabolites involved in neurotransmission and bioenergetics. These were paired with serial mini-mental state examinations (MMSE) and MRI studies for tumor volumetric analyses. Patients were analyzed in the setting of the phase I trial of lenalidomide/rituximab. Associations were assessed by Pearson and Spearman correlation coefficient. Generalized estimating equation (gee) models were also established, adjusting for within-subject repeated measures.

RESULTS

Of 18 metabolites, elevated CSF lactate correlated most strongly with lower MMSE score (p<8E-8, rho=-0.67). High lactate was associated with lower GABA, higher glutamate/GABA ratio and dopamine. Conversely, high succinate correlated with higher MMSE score. Serial analysis demonstrated a reproducible, time-dependent, reciprocal correlation between changes in lactate and GABA concentrations. While high lactate and low GABA correlated with tumor contrast enhancing volume, they correlated more significantly with lower MMSE scores than tumor volumes.

CONCLUSIONS

We provide evidence that lactate production and Warburg metabolism may impact neurotransmitter dysregulation and neurocognition in CNS lymphomas. We identify novel metabolomic biomarkers that may be applied in future studies of neurocognition in CNS lymphomas. Elucidation of mechanistic interactions between lymphoma metabolism, neurotransmitter imbalance and neurocognition may promote interventions that preserve cognitive function.

Metabolomics of Cerebrospinal Fluid from Healthy Subjects Reveal Metabolites Associated with Ageing

To increase our understanding of age-related diseases affecting the central nervous system (CNS) it is important to understand the molecular processes of biological ageing. Metabolomics of cerebrospinal fluid (CSF) is a promising methodology to increase our understanding of naturally occurring processes of ageing of the brain and CNS that could be reflected in CSF. In the present study the CSF metabolomes of healthy subjects aged 30-74 years (n = 23) were studied using liquid chromatography high-resolution mass spectrometry (LC-HRMS), and investigated in relation to age. Ten metabolites were identified with high confidence as significantly associated with ageing, eight with increasing levels with ageing: isoleucine, acetylcarnitine, pipecolate, methionine, glutarylcarnitine, 5-hydroxytryptophan, ketoleucine, and hippurate; and two decreasing with ageing: methylthioadenosine and 3-methyladenine. To our knowledge, this is the first time the CSF metabolomes of healthy subjects are assessed in relation to ageing. The present study contributes to the field of ageing metabolomics by presenting a number of metabolites present in CSF with potential relevance for ageing and the results motivate further studies.

Advances of Mechanisms-Related Metabolomics in Parkinson's Disease

Parkinson's disease (PD) is a multifactorial disorder characterized by progressively debilitating dopaminergic neurodegeneration in the substantia nigra and the striatum, along with various metabolic dysfunctions and molecular abnormalities. Metabolomics is an emerging study and has been demonstrated to play important roles in describing complex human diseases by integrating endogenous and exogenous sources of alterations. Recently, an increasing amount of research has shown that metabolomics profiling holds great promise in providing unique insights into molecular pathogenesis and could be helpful in identifying candidate biomarkers for clinical detection and therapies of PD. In this review, we briefly summarize recent findings and analyze the application of molecular metabolomics in familial and sporadic PD from genetic mutations, mitochondrial dysfunction, and dysbacteriosis. We also review metabolic biomarkers to assess the functional stage and improve therapeutic strategies to postpone or hinder the disease progression.

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.

Metabolomics: An emerging potential approach to decipher critical illnesses

Critical illnesses contribute to the maximum morbidity and mortality of hospitalized patients. Acute respiratory distress syndrome (ARDS) and sepsis/septic shock are the two most common acute illnesses associated with intensive care unit (ICU) admission. Once triggered, both have an identical underlying mechanism, portrayed by inflammation and endothelial dysfunction. The diagnosis of ARDS is based on clinical findings, laboratory tests, and radiological imaging. Blood cultures remain the gold standard for the diagnosis of sepsis, with the limitation of time delay and low positive yield. A combination of biomarkers has been proposed to diagnose and prognosticate these acute disorders with strengths and limitations, but still, the gold standard has been elusive to clinicians. In this review article, we illustrate the potential of metabolomics to unravel biomarkers that can be clinically utilized as a rapid prognostic and diagnostic tool associated with specific patient populations (ARDS and sepsis/septic shock) based on the available scientific data.

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.

Characterization of Postprandial Effects on CSF Metabolomics: A Pilot Study with Parallel Comparison to Plasma

Cerebrospinal fluid (CSF) metabolites reflect biochemical diffusion/export from the brain and possibly serve as biomarkers related to brain disease severity, pathophysiology, and therapeutic efficacy/toxicity. Metabolomic studies using blood matrices have demonstrated interindividual and preanalytical variation of blood metabolites, whereas those of CSF metabolites remain unclear. In this study, we aimed to delineate the postprandial effects on CSF metabolites because fasting of patients with brain-related disorders is challenging. We collected pre- and postprandial (1.5, 3, and 6 h) plasma and CSF from nine healthy subjects. Using a mass-spectrometry-based global metabolomics approach, 150 and 130 hydrophilic metabolites and 263 and 340 lipids were detected in CSF and plasma, respectively. Principal component analysis of CSF hydrophilic metabolites and lipids primarily classified individual subjects at any time point, suggesting that the postprandial effects had a lower impact than interindividual variations on CSF metabolites. Individually, less than 10% of the CSF metabolites were putatively altered by postprandial effects (with either significant differences or over 2-fold changes, but not both) at any time point. Thus, global CSF metabolite levels are not directly associated with food intake, and except for several putatively altered CSF metabolites, postprandial effects are not a major concern when applying CSF metabolomics to screen biomarkers.