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

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 machine learning algorithm based on circulating metabolic biomarkers offers improved predictions of neurological diseases

BACKGROUND AND AIMS

A machine learning algorithm based on circulating metabolic biomarkers for the predictions of neurological diseases (NLDs) is lacking. To develop a machine learning algorithm to compare the performance of a metabolic biomarker-based model with that of a clinical model based on conventional risk factors for predicting three NLDs: dementia, Parkinson's disease (PD), and Alzheimer's disease (AD).

MATERIALS AND METHODS

The eXtreme Gradient Boosting (XGBoost) algorithm was used to construct a metabolic biomarker-based model (metabolic model), a clinical risk factor-based model (clinical model), and a combined model for the prediction of the three NLDs. Risk discrimination (c-statistic), net reclassification improvement (NRI) index, and integrated discrimination improvement (IDI) index values were determined for each model.

RESULTS

The results indicate that incorporation of metabolic biomarkers into the clinical model afforded a model with improved performance in the prediction of dementia, AD, and PD, as demonstrated by NRI values of 0.159 (0.039-0.279), 0.113 (0.005-0.176), and 0.201 (-0.021-0.423), respectively; and IDI values of 0.098 (0.073-0.122), 0.070 (0.049-0.090), and 0.085 (0.068-0.101), respectively.

CONCLUSION

The performance of the model based on circulating NMR spectroscopy-detected metabolic biomarkers was better than that of the clinical model in the prediction of dementia, AD, and PD.

Relationship Between Short-chain Fatty Acids and Parkinson's Disease: A Review from Pathology to Clinic

Parkinson's disease (PD) is a complicated neurodegenerative disease, characterized by the accumulation of α-synuclein (α-syn) in Lewy bodies and neurites, and massive loss of midbrain dopamine neurons. Increasing evidence suggests that gut microbiota and microbial metabolites are involved in the development of PD. Among these, short-chain fatty acids (SCFAs), the most abundant microbial metabolites, have been proven to play a key role in brain-gut communication. In this review, we analyze the role of SCFAs in the pathology of PD from multiple dimensions and summarize the alterations of SCFAs in PD patients as well as their correlation with motor and non-motor symptoms. Future research should focus on further elucidating the role of SCFAs in neuroinflammation, as well as developing novel strategies employing SCFAs and their derivatives to treat 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.

Metabolic Disturbances in the Gut-brain Axis of a Mouse Model of MPTP-induced Parkinsonism Evaluated by Nuclear Magnetic Resonance

Parkinson's Disease is a synucleinopathy that primarily affects the dopaminergic cells of the central nervous system, leading to motor and gastrointestinal disturbances. However, intestinal peripheral neurons undergo a similar neurodegeneration process, marked by α-synuclein (αSyn) accumulation and loss of mitochondrial homeostasis. We investigated the metabolic alterations in different biometrics that compose the gut-brain axis (blood, brain, large intestine, and feces) in an MPTP-induced mouse model of sporadic Parkinson's Disease. Animals received escalating administration of MPTP. Tissues and fecal pellets were collected, and the metabolites were identified through the untargeted Nuclear Magnetic Resonance spectroscopic (1H NMR) technique. We found differences in many metabolites from all the tissues evaluated. The differential expression of metabolites in these samples mainly reflects inflammatory aspects, cytotoxicity, and mitochondrial impairment (oxidative stress and energy metabolism) in the animal model used. The direct evaluation of fecal metabolites revealed changes in several classes of metabolites. This data reinforces previous studies showing that Parkinson's disease is associated with metabolic perturbation not only in brain-related tissues, but also in periphery structures such as the gut. In addition, the evaluation of the microbiome and metabolites from gut and feces emerge as promising sources of information for understanding the evolution and progression of sporadic Parkinson's Disease.

Parkinson's Disease and the Heart: Studying Cardiac Metabolism in the 6-Hydroxydopamine Model

Parkinson's-disease (PD) is an incurable, age-related neurodegenerative disease, and its global prevalence of disability and death has increased exponentially. Although motor symptoms are the characteristic manifestations of PD, the clinical spectrum also contains a wide variety of non-motor symptoms, which are the main cause of disability and determinants of the decrease in a patient's quality of life. Noteworthy in this regard is the stress on the cardiac system that is often observed in the course of PD; however, its effects have not yet been adequately researched. Here, an untargeted metabolomics approach was used to assess changes in cardiac metabolism in the 6-hydroxydopamine model of PD. Beta-sitosterol, campesterol, cholesterol, monoacylglycerol, α-tocopherol, stearic acid, beta-glycerophosphoric acid, o-phosphoethanolamine, myo-inositol-1-phosphate, alanine, valine and allothreonine are the metabolites that significantly discriminate parkinsonian rats from sham counterparts. Upon analysis of the metabolic pathways with the aim of uncovering the main biological pathways involved in concentration patterns of cardiac metabolites, the biosynthesis of both phosphatidylethanolamine and phosphatidylcholine, the glucose-alanine cycle, glutathione metabolism and plasmalogen synthesis most adequately differentiated sham and parkinsonian rats. Our results reveal that both lipid and energy metabolism are particularly involved in changes in cardiac metabolism in PD. These results provide insight into cardiac metabolic signatures in PD and indicate potential targets for further investigation.

Multi-regional alterations in glucose and purine metabolic pathways in the Parkinson's disease dementia brain

Parkinson's disease (PD) is one of the most common neurodegenerative diseases, most commonly characterised by motor dysfunction, but also with a high prevalence of cognitive decline in the decades following diagnosis-a condition known as Parkinson's disease dementia (PDD). Although several metabolic disruptions have been identified in PD, there has yet to be a multi-regional analysis of multiple metabolites conducted in PDD brains. This discovery study attempts to address this gap in knowledge. A semi-targeted liquid chromatography-mass spectrometry analysis of nine neuropathologically-confirmed PDD cases vs nine controls was performed, looking at nine different brain regions, including the cingulate gyrus, cerebellum, hippocampus, motor cortex, medulla, middle temporal gyrus, pons, substantia nigra and primary visual cortex. Case-control differences were determined by multiple t-tests followed by 10% FDR correction. Of 64 identified analytes, 49 were found to be altered in at least one region of the PDD brain. These included metabolites from several pathways, including glucose and purine metabolism and the TCA cycle, with widespread increases in fructose, inosine and ribose-5-phosphate, as well as decreases in proline, serine and deoxyguanosine. Higher numbers of alterations were observed in PDD brain regions that are affected during earlier α-synuclein Braak stages-with the exception of the cerebellum, which showed an unexpectedly high number of metabolic changes. PDD brains show multi-regional alterations in glucose and purine metabolic pathways that reflect the progression of α-synuclein Braak staging. Unexpectedly, the cerebellum also shows a high number of metabolic changes.

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.

Analysis of Y chromosome haplogroups in Parkinson's disease

Parkinson's disease is a complex neurodegenerative disorder that is about 1.5 times more prevalent in males than females. Extensive work has been done to identify the genetic risk factors behind Parkinson's disease on autosomes and more recently on Chromosome X, but work remains to be done on the male-specific Y chromosome. In an effort to explore the role of the Y chromosome in Parkinson's disease, we analysed whole-genome sequencing data from the Accelerating Medicines Partnership-Parkinson's disease initiative (1466 cases and 1664 controls), genotype data from NeuroX (3491 cases and 3232 controls) and genotype data from UKBiobank (182 517 controls, 1892 cases and 3783 proxy cases), all consisting of male European ancestry samples. We classified sample Y chromosomes by haplogroup using three different tools for comparison (Snappy, Yhaplo and Y-LineageTracker) and meta-analysed this data to identify haplogroups associated with Parkinson's disease. This was followed up with a Y-chromosome association study to identify specific variants associated with disease. We also analysed blood-based RNASeq data obtained from the Accelerating Medicines Partnership-Parkinson's disease initiative (1020 samples) and RNASeq data obtained from the North American Brain Expression Consortium (171 samples) to identify Y-chromosome genes differentially expressed in cases, controls, specific haplogroups and specific tissues. RNASeq analyses suggest Y-chromosome gene expression differs between brain and blood tissues but does not differ significantly in cases, controls or specific haplogroups. Overall, we did not find any strong associations between Y-chromosome genetics and Parkinson's disease, suggesting the explanation for the increased prevalence in males may lie elsewhere.

Altered prefrontal neurochemistry in the DJ-1 knockout mouse model of Parkinson's disease: complementary semi-quantitative analyses with in vivo magnetic resonance spectroscopy and MALDI-MSI

In vivo proton magnetic resonance spectroscopy (¹H-MRS) and matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) are two semi-quantitative analytical methods commonly used in neurochemical research. In this study, the two methods were used complementarily, in parallel, to investigate neurochemical perturbations in the medial prefrontal cortex (mPFC) of 9-month-old DJ-1 knockout mice, a well-established transgenic model for Parkinson's diseases. Convergingly, the results obtained with the two methods demonstrated that, compared with the wild-type (WT) mice, the DJ-1 knockout mice had significantly increased glutathione (GSH) level and GSH/glutamate (Glu) ratio in the mPFC, which likely presented an astrocytic compensatory mechanism in response to elevated regional oxidative stress induced by the loss of DJ-1 function. The results from this study also highlighted (1) the need to be cautious when interpreting the in vivo ¹H-MRS results obtained from aged transgenic animals, in which the concentration of internal reference, being whether water or total creatine, could no longer be assumed to be the same as that in the age-matched WT animals, and (2) the necessity and importance of complementary analyses with more than one method under such circumstances.

Triticonazole enantiomers induced enantioselective metabolic phenotypes in Fusarium graminearum and HepG2 cells

The management of Fusarium head blight relies heavily on triazole fungicides. Most of triazole fungicides are chiral, and their enantioselective effects on metabolic phenotypes are poorly understood. Herein, we analyzed the bioactivity of triticonazole against Fusarium graminearum, and ¹H-nuclear magnetic resonance-based metabolomics was used to assess the metabolic disturbances of triticonazole enantiomers in Fusarium graminearum and human hepatocarcinoma cells. Results indicated that the bioactivity of R-triticonazole was 4.28-fold higher than its antipode since it bound stronger with fungal CYP51B and induced more abnormal metabolic processes of Fusarium graminearum, including lipid metabolism, glycolysis, and amino acid metabolism. In human hepatocarcinoma cells, pathways of "alanine, aspartic acid and glutamate metabolism" and "pyruvate metabolism" were disturbed significantly by R-triticonazole; "phenylalanine metabolism" and "taurine-hypotaurine metabolism" were abnormal in the exposure of S-triticonazole. These results suggested that R- and S-triticonazole could affect different metabolic pathways of human hepatocarcinoma cells, and the massively use of inefficient S-triticonazole should be avoided. Our data will help to better understand the enantioselectivity of chiral pesticides and provide a reference for the development of green pesticides.

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.

Genomic, transcriptomic, and metabolomic profiles of hiPSC-derived dopamine neurons from clinically discordant brothers with identical PRKN deletions

We previously reported on two brothers who carry identical compound heterozygous PRKN mutations yet present with significantly different Parkinson's Disease (PD) clinical phenotypes. Juvenile cases demonstrate that PD is not necessarily an aging-associated disease. Indeed, evidence for a developmental component to PD pathogenesis is accumulating. Thus, we hypothesized that the presence of additional genetic modifiers, including genetic loci relevant to mesencephalic dopamine neuron development, could potentially contribute to the different clinical manifestations of the two brothers. We differentiated human-induced pluripotent stem cells (hiPSCs) derived from the two brothers into mesencephalic neural precursor cells and early postmitotic dopaminergic neurons and performed wholeexome sequencing and transcriptomic and metabolomic analyses. No significant differences in the expression of canonical dopamine neuron differentiation markers were observed. Yet our transcriptomic analysis revealed a significant downregulation of the expression of three neurodevelopmentally relevant cell adhesion molecules, CNTN6, CNTN4 and CHL1, in the cultures of the more severely affected brother. In addition, several HLA genes, known to play a role in neurodevelopment, were differentially regulated. The expression of EN2, a transcription factor crucial for mesencephalic dopamine neuron development, was also differentially regulated. We further identified differences in cellular processes relevant to dopamine metabolism. Lastly, wholeexome sequencing, transcriptomics and metabolomics data all revealed differences in glutathione (GSH) homeostasis, the dysregulation of which has been previously associated with PD. In summary, we identified genetic differences which could potentially, at least partially, contribute to the discordant clinical PD presentation of the two brothers.

NMR-Based Metabolomics of Rat Hippocampus, Serum, and Urine in Two Models of Autism

Autism spectrum disorders (ASDs) are increasingly diagnosed as developmental disabilities of unclear etiology related to genetic, epigenetic, or environmental factors. The diagnosis of ASD in children is based on the recognition of typical behavioral symptoms, while no reliable biomarkers are available. Rats in whom ASD-like symptoms are due to maternal administration of the teratogenic drugs valproate or thalidomide on critical day 11 of pregnancy are widely used models in autism research. The present studies, aimed at detecting changes in the levels of hydrophilic and hydrophobic metabolites, were carried out on 1-month-old rats belonging to the abovementioned two ASD models and on a control group. Analysis of both hydrophilic and hydrophobic metabolite levels gives a broader view of possible mechanisms involved in the pathogenesis of autism. Hippocampal proton magnetic resonance (MRS) spectroscopy and ex vivo nuclear magnetic resonance (NMR) analysis of serum and urine samples were used. The results were analyzed using advanced statistical tests. Both the results of our present MRS studies of the hippocampus and of the NMR studies of body fluids in both ASD models, particularly from the THAL model, appeared to be consistent with previously published NMR results of hippocampal homogenates and data from the literature on autistic children. We detected symptoms of disturbances in neurotransmitter metabolism, energy deficit, and oxidative stress, as well as intestinal malfunction, which shed light on the pathogenesis of ASD and could be used for diagnostic purposes. These results confirm the usefulness of the noninvasive techniques used in ASD studies.

Metabolic Profile in Plasma AND CSF of LEVODOPA-induced Dyskinesia in Parkinson's Disease: Focus on Neuroinflammation

The existence of few biomarkers and the lack of a better understanding of the pathophysiology of levodopa-induced dyskinesia (LID) in Parkinson's disease (PD) require new approaches, as the metabolomic analysis, for discoveries. We aimed to identify a metabolic profile associated with LID in patients with PD in an original cohort and to confirm the results in an external cohort (BioFIND). In the original cohort, plasma and CSF were collected from 20 healthy controls, 23 patients with PD without LID, and 24 patients with PD with LID. LC-MS/MS and metabolomics data analysis were used to perform untargeted metabolomics. Untargeted metabolomics data from the BioFIND cohort were analyzed. We identified a metabolic profile associated with LID in PD, composed of multiple metabolic pathways. In particular, the dysregulation of the glycosphingolipid metabolic pathway was more related to LID and was strongly associated with the severity of dyskinetic movements. Furthermore, bile acid biosynthesis metabolites simultaneously found in plasma and CSF have distinguished patients with LID from other participants. Data from the BioFIND cohort confirmed dysregulation in plasma metabolites from the bile acid biosynthesis pathway. There is a distinct metabolic profile associated with LID in PD, both in plasma and CSF, which may be associated with the dysregulation of lipid metabolism and neuroinflammation.