Biomarker Research in Parkinson's Disease Using Metabolite Profiling

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.

1H NMR-Based Metabolomic Signatures in Rodent Models of Sporadic Alzheimer's Disease and Metabolic Disorders

Alzheimer's disease (AD) is a chronic neurological disorder that impacts the elderly population all over the globe. Evidence suggests association between AD and metabolic disorders such as diabetes mellitus (DM) and obesity (OB). The present study is an attempt to evaluate metabolic alterations in the serum and brain through NMR spectroscopy with the aim to identify shared metabolic signatures. AD was induced in rats by stereotactic intracerebroventricular injection of oligomerized Aβ-42 peptide into the brain. DM and OB were induced by intraperitoneal injection of streptozotocin and feeding rats on a high-fat diet, respectively. The metabolic alterations obtained through 1H NMR spectroscopy were further subjected to multivariate analysis by principal component analysis and partial least-squares discrimination for identification of metabolic signatures. In the serum, the levels of lactate and betaine were increased in AD, DM, and OB rats. On the other hand, the metabolite profile of brain indicated increase in the levels of lactate, N-acetylaspartate, and creatinine in AD, DM, and OB rats. Additionally, the concentration of neurochemicals such as glutamate, GABA, N-acetylglutamate, and myo-inositol were also elevated. The alterations in neurotransmitters and cerebral energy metabolism were accompanied by deficits in cognition assessed by Morris water maze in AD, DM, and OB rats. The perturbed metabolic profiles were accompanied by the presence of pathogenic amyloid deposits visualized by Congo red stain in the brains of AD, DM, and OB rats. Overall, the study identifies common metabolic signatures in AD, DM, and OB that may be involved in etiopathogenesis and also suggests linkages between these three conditions.

α-synuclein overexpression and the microbiome shape the gut and brain metabolome in mice

Pathological forms of α-synuclein contribute to synucleinopathies, including Parkinson's disease (PD). Most cases of PD arise from gene-environment interactions. Microbiome composition is altered in PD, and gut bacteria are causal to symptoms in animal models. We quantitatively profiled nearly 630 metabolites in the gut, plasma, and brain of α-synuclein-overexpressing (ASO) mice, compared to wild-type (WT) animals, and comparing germ-free (GF) to specific pathogen-free (SPF) animals (n = 5 WT-SPF; n = 6 ASO-SPF; n = 6 WT-GF; n = 6 ASO-GF). Many differentially expressed metabolites in ASO mice are also dysregulated in human PD patients, including amine oxides, bile acids and indoles. The microbial metabolite trimethylamine N-oxide (TMAO) strongly correlates from the gut to the plasma to the brain in mice, notable since TMAO is elevated in the blood and cerebrospinal fluid of PD patients. These findings uncover broad metabolomic changes that are influenced by the intersection of host genetics and microbiome in a mouse model of PD.

Neuroactive Kynurenines as Pharmacological Targets: New Experimental Tools and Exciting Therapeutic Opportunities

Both preclinical and clinical studies implicate functional impairments of several neuroactive metabolites of the kynurenine pathway (KP), the major degradative cascade of the essential amino acid tryptophan in mammals, in the pathophysiology of neurologic and psychiatric diseases. A number of KP enzymes, such as tryptophan 2,3-dioxygenase (TDO2), indoleamine 2,3-dioxygenases (IDO1 and IDO2), kynurenine aminotransferases (KATs), kynurenine 3-monooxygenase (KMO), 3-hydroxyanthranilic acid oxygenase (3-HAO), and quinolinic acid phosphoribosyltransferase (QPRT), control brain KP metabolism in health and disease and are therefore increasingly considered to be promising targets for the treatment of disorders of the nervous system. Understanding the distribution, cellular expression, and regulation of KP enzymes and KP metabolites in the brain is therefore critical for the conceptualization and implementation of successful therapeutic strategies. SIGNIFICANCE STATEMENT: Studies have implicated the kynurenine pathway of tryptophan in the pathophysiology of neurologic and psychiatric diseases. Key enzymes of the kynurenine pathway regulate brain metabolism in both health and disease, making them promising targets for treating these disorders. Therefore, understanding the distribution, cellular expression, and regulation of these enzymes and metabolites in the brain is critical for developing effective therapeutic strategies. This review endeavors to describe these processes in detail.

Salidroside improves cognitive function in Parkinson's disease via Braf-mediated mitogen‑activated protein kinase signaling pathway

OBJECTIVE

To delve into the underlying mechanism of Salidroside (Sal) on the improvement of cognitive function in Parkinson's Disease (PD).

METHODS

The experimental mice were divided into Control group, Model group [injected with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)], and Model+Sal (low concentration, high concentration) group. Mouse hippocampal tissues were extracted for RNA sequencing to obtain the core pathway and core gene. Mouse plasma was prepared and analyzed by LC-MS to obtain differential metabolites. In vitro experiments were verified by immunofluorescence and lentiviral transduction.

RESULTS

ELISA signaled that Sal facilitated the reduction of neuronal damage and inflammatory reaction in mice. MPTP_Sal_Low and MPTP_Sal_High groups had high levels of glial cell derived neurotrophie factor (GDNF) expression. Differentially expressed genes (DEGs) in control group, MPTP group and MPTP_Sal_High group were identified by transcriptomic, which were classified to the mitogen-activated protein kinase (MAPK) signaling pathway, and the core gene Braf was obtained. Metabolomics manifested that the differential metabolites involved DL-tyrosine, adenosine, phosphoenolpyruvate, and L-tryptophan. In vitro experiments verified that Sal treatment inhibited the up-regulation of p-p38, p-c-Jun N-terminal kinase (JNK), and p-extracellular signal-regulated kinase (ERK) expression, and growth of neuronal protrusions. The OE-Braf group showed a significant up-regulation of the GDNF expression, a decrease in the expression of p-p38, p-JNK, and p-ERK, and a significant growth of neuronal protrusions.

CONCLUSION

Sal may exert its effects in PD through the Braf-mediated MAPK signaling pathway, which can increase GDNF expression and promote neuronal protrusion growth for the protection of neurological function and the improvement of cognitive function.

Metabolic profiling reveals circulating biomarkers associated with incident and prevalent Parkinson's disease

The metabolic profile predating the onset of Parkinson's disease (PD) remains unclear. We aim to investigate the metabolites associated with incident and prevalent PD and their predictive values in the UK Biobank participants with metabolomics and genetic data at the baseline. A panel of 249 metabolites was quantified using a nuclear magnetic resonance analytical platform. PD was ascertained by self-reported history, hospital admission records and death registers. Cox proportional hazard models and logistic regression models were used to investigate the associations between metabolites and incident and prevalent PD, respectively. Area under receiver operating characteristics curves (AUC) were used to estimate the predictive values of models for future PD. Among 109,790 participants without PD at the baseline, 639 (0.58%) individuals developed PD after one year from the baseline during a median follow-up period of 12.2 years. Sixty-eight metabolites were associated with incident PD at nominal significance (P < 0.05), spanning lipids, lipid constituent of lipoprotein subclasses and ratios of lipid constituents. After multiple testing corrections (P < 9 × 10-4), polyunsaturated fatty acids (PUFA) and omega-6 fatty acids remained significantly associated with incident PD, and PUFA was shared by incident and prevalent PD. Additionally, 14 metabolites were exclusively associated with prevalent PD, including amino acids, fatty acids, several lipoprotein subclasses and ratios of lipids. Adding these metabolites to the conventional risk factors yielded a comparable predictive performance to the risk-factor-based model (AUC = 0.766 vs AUC = 0.768, P = 0.145). Our findings suggested metabolic profiles provided additional knowledge to understand different pathways related to PD before and after its onset.

α-Synuclein Overexpression and the Microbiome Shape the Gut and Brain Metabolome in Mice

Pathological forms of the protein α-synuclein contribute to a family of disorders termed synucleinopathies, which includes Parkinson's disease (PD). Most cases of PD are believed to arise from gene-environment interactions. Microbiome composition is altered in PD, and gut bacteria are causal to symptoms and pathology in animal models. To explore how the microbiome may impact PD-associated genetic risks, we quantitatively profiled nearly 630 metabolites from 26 biochemical classes in the gut, plasma, and brain of α-synuclein-overexpressing (ASO) mice with or without microbiota. We observe tissue-specific changes driven by genotype, microbiome, and their interaction. Many differentially expressed metabolites in ASO mice are also dysregulated in human PD patients, including amine oxides, bile acids and indoles. Notably, levels of the microbial metabolite trimethylamine N-oxide (TMAO) strongly correlate from the gut to the plasma to the brain, identifying a product of gene-environment interactions that may influence PD-like outcomes in mice. TMAO is elevated in the blood and cerebral spinal fluid of PD patients. These findings uncover broad metabolomic changes that are influenced by the intersection of host genetics and the microbiome in a mouse model of PD.

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.

NMR Precision Metabolomics: Dynamic Peak Sum Thresholding and Navigators for Highly Standardized and Reproducible Metabolite Profiling of Clinical Urine Samples

Metabolomics, especially urine-based studies, offers incredible promise for the discovery and development of clinically impactful biomarkers. However, due to the unique challenges of urine, a highly precise and reproducible workflow for NMR-based urine metabolomics is lacking. Using 1D and 2D non-uniform sampled (NUS) 1H-13C NMR spectroscopy, we systematically explored how changes in hydration or specific gravity (SG) and pH can impact biomarker discovery. Further, we examined additional sources of error in metabolomics studies and identified Navigator molecules that could monitor for those biases. Adjustment of SG to 1.002-1.02 coupled with a dynamic sum-based peak thresholding eliminates false positives associated with urine hydration and reduces variation in chemical shift. We identified Navigator molecules that can effectively monitor for inconsistencies in sample processing, SG, protein contamination, and pH. The workflow described provides quality assurance and quality control tools to generate high-quality urine metabolomics data, which is the first step in biomarker discovery.

Untargeted serum metabolic profiling of diabetes mellitus among Parkinson's disease patients

Type 2 diabetes mellitus (T2DM) is a common comorbidity among Parkinson's disease (PD) patients. Yet, little is known about dysregulated pathways that are unique in PD patients with T2DM. We applied high-resolution metabolomic profiling in serum samples of 636 PD and 253 non-PD participants recruited from Central California. We conducted an initial discovery metabolome-wide association and pathway enrichment analysis. After adjusting for multiple testing, in positive (or negative) ion mode, 30 (25) metabolic features were associated with T2DM in both PD and non-PD participants, 162 (108) only in PD participants, and 32 (7) only in non-PD participants. Pathway enrichment analysis identified 17 enriched pathways associated with T2DM in both the PD and non-PD participants, 26 pathways only in PD participants, and 5 pathways only in non-PD participants. Several amino acid, nucleic acids, and fatty acid metabolisms were associated with T2DM only in the PD patient group suggesting a possible link between PD and T2DM.

Global biomarker trends in Parkinson's disease research: A bibliometric analysis

As the second most common neurodegenerative disease globally, Parkinson's disease (PD) affects millions of people worldwide. In recent years, the scientific publications related to PD biomarker research have exploded, reflecting the growing interest in unraveling the complex pathophysiology of PD. In this study, we aim to use various bibliometric tools to identify key scientific concepts, detect emerging trends, and analyze the global trends and development of PD biomarker research.The research encompasses various stages of biomarker development, including exploration, identification, and multi-modal research. MOVEMENT DISORDERS emerged as the leading journal in terms of publications and citations. Key authors such as Mollenhauer and Salem were identified, while the University of Pennsylvania and USA stood out in collaboration and research output. NEUROSCIENCES emerged as the most important research direction. Key biomarker categories include α-synuclein-related markers, neurotransmitter-related markers, inflammation and immune system-related markers, oxidative stress and mitochondrial function-related markers, and brain imaging-related markers. Furthermore, future trends in PD biomarker research focus on exosomes and plasma biomarkers, miRNA, cerebrospinal fluid biomarkers, machine learning applications, and animal models of PD. These trends contribute to early diagnosis, disease progression monitoring, and understanding the pathological mechanisms of PD.

Global biomarker trends in Parkinson's disease research: A bibliometric analysis

As the second most common neurodegenerative disease globally, Parkinson's disease (PD) affects millions of people worldwide. In recent years, the scientific publications related to PD biomarker research have exploded, reflecting the growing interest in unraveling the complex pathophysiology of PD. In this study, we aim to use various bibliometric tools to identify key scientific concepts, detect emerging trends, and analyze the global trends and development of PD biomarker research.The research encompasses various stages of biomarker development, including exploration, identification, and multi-modal research. MOVEMENT DISORDERS emerged as the leading journal in terms of publications and citations. Key authors such as Mollenhauer and Salem were identified, while the University of Pennsylvania and USA stood out in collaboration and research output. NEUROSCIENCES emerged as the most important research direction. Key biomarker categories include α-synuclein-related markers, neurotransmitter-related markers, inflammation and immune system-related markers, oxidative stress and mitochondrial function-related markers, and brain imaging-related markers. Furthermore, future trends in PD biomarker research focus on exosomes and plasma biomarkers, miRNA, cerebrospinal fluid biomarkers, machine learning applications, and animal models of PD. These trends contribute to early diagnosis, disease progression monitoring, and understanding the pathological mechanisms of PD.

Water-Soluble Triazolium Covalent Cages for ATP Sensing

Water-soluble organic cages are attractive targets for their molecular recognition and sensing features of biologically relevant molecules. Here, we have successfully designed and synthesized a pair of water-soluble cationic cages employing click reaction as the fundamental step followed by the N-methylation of the triazole rings. The rigid and shape-persistent 3D hydrophobic cavity, positively charged surface, H-bonding triazolium rings, and excellent water solubility empower both cages to exhibit a superior affinity and selectivity for binding with adenosine-5'-triphosphate (ATP) compared to cyclophanes and other macrocyclic receptors. Both cage molecules (PCC⋅Cl and BCC⋅Cl) can bind a highly emissive dye HPTS (8-hydroxypyrene-1,3,6-trisulfonic acid trisodium salt) to form non-fluorescent complexes. The addition of ATP resulted in the stronger cage⊂ATP complexes with the retention of HPTS emission upon its displacement. The resultant indicator-displacement assay system can efficiently sense and quantify ATP in nanomolar detection limits in buffer solutions and human serum matrix. Spectroscopic and theoretical studies revealed the synergistic effect of π⋅⋅⋅π stacking interaction between the aromatic moiety of the cationic cages and the adenine moiety of ATP, as well as the electrostatic and hydrogen bonding interaction between the phosphate anion of ATP and triazole protons of cages, played the pivotal roles in the sensing process.

The potential role of glucose metabolism, lipid metabolism, and amino acid metabolism in the treatment of Parkinson's disease

PURPOSE OF REVIEW

Parkinson's disease (PD) is a common neurodegenerative disease, which can cause progressive deterioration of motor function causing muscle stiffness, tremor, and bradykinesia. In this review, we hope to describe approaches that can improve the life of PD patients through modifications of energy metabolism.

RECENT FINDINGS

The main pathological features of PD are the progressive loss of nigrostriatal dopaminergic neurons and the production of Lewy bodies. Abnormal aggregation of α-synuclein (α-Syn) leading to the formation of Lewy bodies is closely associated with neuronal dysfunction and degeneration. The main causes of PD are said to be mitochondrial damage, oxidative stress, inflammation, and abnormal protein aggregation. Presence of abnormal energy metabolism is another cause of PD. Many studies have found significant differences between neurodegenerative diseases and metabolic decompensation, which has become a biological hallmark of neurodegenerative diseases.

SUMMARY

In this review, we highlight the relationship between abnormal energy metabolism (Glucose metabolism, lipid metabolism, and amino acid metabolism) and PD. Improvement of key molecules in glucose metabolism, fat metabolism, and amino acid metabolism (e.g., glucose-6-phosphate dehydrogenase, triglycerides, and levodopa) might be potentially beneficial in PD. Some of these metabolic indicators may serve well during the diagnosis of PD. In addition, modulation of these metabolic pathways may be a potential target for the treatment and prevention of PD.

Early-stage idiopathic Parkinson's disease is associated with reduced circular RNA expression

Neurodegeneration in Parkinson's disease (PD) precedes diagnosis by years. Early neurodegeneration may be reflected in RNA levels and measurable as a biomarker. Here, we present the largest quantification of whole blood linear and circular RNAs (circRNA) in early-stage idiopathic PD, using RNA sequencing data from two cohorts (PPMI = 259 PD, 161 Controls; ICICLE-PD = 48 PD, 48 Controls). We identified a replicable increase in TMEM252 and LMNB1 gene expression in PD. We identified novel differences in the expression of circRNAs from ESYT2, BMS1P1 and CCDC9, and replicated trends of previously reported circRNAs. Overall, using circRNA as a diagnostic biomarker in PD did not show any clear improvement over linear RNA, minimising its potential clinical utility. More interestingly, we observed a general reduction in circRNA expression in both PD cohorts, accompanied by an increase in RNASEL expression. This imbalance implicates the activation of an innate antiviral immune response and suggests a previously unknown aspect of circRNA regulation in PD.

Transcriptome-based biomarker prediction for Parkinson's disease using genome-scale metabolic modeling

Parkinson's disease (PD) is the second most common neurodegenerative disease in the world. Identification of PD biomarkers is crucial for early diagnosis and to develop target-based therapeutic agents. Integrative analysis of genome-scale metabolic models (GEMs) and omics data provides a computational approach for the prediction of metabolite biomarkers. Here, we applied the TIMBR (Transcriptionally Inferred Metabolic Biomarker Response) algorithm and two modified versions of TIMBR to investigate potential metabolite biomarkers for PD. To this end, we mapped thirteen post-mortem PD transcriptome datasets from the substantia nigra region onto Human-GEM. We considered a metabolite as a candidate biomarker if its production was predicted to be more efficient by a TIMBR-family algorithm in control or PD case for the majority of the datasets. Different metrics based on well-known PD-related metabolite alterations, PD-associated pathways, and a list of 25 high-confidence PD metabolite biomarkers compiled from the literature were used to compare the prediction performance of the three algorithms tested. The modified algorithm with the highest prediction power based on the metrics was called TAMBOOR, TrAnscriptome-based Metabolite Biomarkers by On-Off Reactions, which was introduced for the first time in this study. TAMBOOR performed better in terms of capturing well-known pathway alterations and metabolite secretion changes in PD. Therefore, our tool has a strong potential to be used for the prediction of novel diagnostic biomarkers for human diseases.

Rapid Metabolic Profiling of 1 μL Crude Cerebrospinal Fluid by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging Can Differentiate De Novo Parkinson's Disease

Parkinson's disease (PD) is a highly prevalent neurodegenerative disorder affecting the motor system. However, the correct diagnosis of PD and atypical parkinsonism may be difficult with high clinical uncertainty. There is an urgent need to identify reliable biomarkers using high-throughput, molecular-specific methods to improve current diagnostics. Here, we present a matrix-assisted laser desorption/ionization mass spectrometry imaging method that requires minimal sample preparation and only 1 μL of crude cerebrospinal fluid (CSF). The method enables analysis of hundreds of samples in a single experiment while simultaneously detecting numerous metabolites with subppm mass accuracy. To test the method, we analyzed CSF samples from 12 de novo PD patients (that is, newly diagnosed and previously untreated) and 12 age-matched controls. Within the identified molecules, we found neurotransmitters and their metabolites such as γ-aminobutyric acid, 3-methoxytyramine, homovanillic acid, serotonin, histamine, amino acids, and metabolic intermediates. Limits of detection were estimated for multiple neurotransmitters with high linearity (R2 > 0.99) and sensitivity (as low as 16 pg/μL). Application of multivariate classification led to a highly significant (P < 0.001) model of PD prediction with a 100% classification rate, which was further thoroughly validated with a permutation test and univariate analysis. Molecules related to the neuromelanin pathway were found to be significantly increased in the PD group, indicated by their elevated relative intensities compared to the control group. Our method enables rapid detection of PD-related biomarkers in low sample volumes and could serve as a valuable tool in the development of robust PD diagnostics.

Chemical catalysis by biological amyloids

Toxic aggregation of proteins and peptides into amyloid fibers is the basis of several human diseases. In each disease, a particular peptide noncovalently assembles into long thin structures with an overall cross-β fold. Amyloids are not only related to disease: functional amyloids are found in many biological systems and artificial peptide amyloids are developed into novel nanomaterials. Amyloid fibers can act as template for the generation of more amyloids but are considered nonreactive in chemical catalysis. The perception of amyloids as chemically inert species was recently challenged by in vitro work on three human amyloid systems. With the use of model substrates, amyloid-β, α-synuclein and glucagon amyloids were found to catalyze biologically relevant chemical reactions. The detected catalytic activity was much less than that of 'real' enzymes, but like that of designed (synthetic) catalytic amyloids. I here describe the current knowledge around this new activity of natural amyloids and the putative connection to metabolic changes in amyloid diseases. These pioneering studies imply that catalytic activity is an unexplored gain-of-function activity of disease amyloids. In fact, all biological amyloids may harbor intrinsic catalytic activity, tuned by each amyloid's particular fold, that await discovery.

Effects of dopamine D2 receptor antagonists on retinal pigment epithelial/choroid complex metabolism in form-deprived myopic guinea pigs

The retinal pigment epithelial (RPE)/choroid complex regulates myopia development, but the precise pathogenesis of myopia remains unclear. We aimed to investigate the changes in RPE/choroid complex metabolism in a form deprivation myopia model after dopamine D2 receptor (D2R) modulation. Guinea pigs were randomly divided into normal (NC), form deprivation myopia (FDM), and FDM treated with dopamine D2R antagonist groups. Differential metabolites were screened using SIMCA-P software and MetaboAnalyst metabolomics analysis tool. Functions of differential metabolites were analyzed using KEGG enrichment pathways. Relative to the NC group, 38 differential metabolites were identified, comprising 29 increased metabolites (including nicotinic acid, cytosine, and glutamate) and 9 decreased metabolites, of which proline exhibited the largest decrease. Pathway analysis revealed regulation of arginine/proline and aspartate/glutamate metabolism. Intravitreal D2R antagonist injection increased proline concentrations and activated arginine/proline and purine metabolism pathways. In sum, D2R antagonists alleviated the myopia trend of refractive biological parameters in form deprivation myopic guinea pigs, suggesting the involvement of dopamine D2R signaling in myopia pathogenesis. The RPE/choroid may provide glutamate to the retina by activating proline metabolism via metabolic coupling with the retina. Dopamine D2R antagonism may modulate proline/arginine metabolic pathways in the RPE/choroid and regulate metabolism, information presentation, and myopia.

Amyloids of α-Synuclein Promote Chemical Transformations of Neuronal Cell Metabolites

The assembly of α-synuclein into cross-β structured amyloid fibers results in Lewy body deposits and neuronal degeneration in Parkinson's disease patients. As the cell environment is highly crowded, interactions between the formed amyloid fibers and a range of biomolecules can occur in cells. Although amyloid fibers are considered chemically inert species, recent in vitro work using model substrates has shown α-synuclein amyloids, but not monomers, to catalyze the hydrolysis of ester and phosphoester bonds. To search for putative catalytic activity of α-synuclein amyloids on biologically relevant metabolites, we here incubated α-synuclein amyloids with neuronal SH-SY5Y cell lysates devoid of proteins. LC-MS-based metabolomic (principal component and univariate) analysis unraveled distinct changes in several metabolite levels upon amyloid (but not monomer) incubation. Of 63 metabolites identified, the amounts of four increased (3-hydroxycapric acid, 2-pyrocatechuic acid, adenosine, and NAD), and the amounts of seventeen decreased (including aromatic and apolar amino acids, metabolites in the TCA cycle, keto acids) in the presence of α-synuclein amyloids. Many of these metabolite changes match what has been reported previously in Parkinson's disease patients and animal-model metabolomics studies. Chemical reactivity of α-synuclein amyloids may be a new gain-of-function that alters the metabolite composition in cells and, thereby, modulates disease progression.

Regulation of LRRK2 mRNA stability by ATIC and its substrate AICAR through ARE-mediated mRNA decay in Parkinson's disease

Mutations in LRRK2 are the most common genetic causes of Parkinson's disease (PD). While the enzymatic activity of LRRK2 has been linked to PD, previous work has also provided support for an important role of elevated LRRK2 protein levels, independent of enzymatic activity, in PD pathogenesis. However, the mechanisms underlying the regulation of LRRK2 protein levels remain unclear. Here, we identify a role for the purine biosynthesis pathway enzyme ATIC in the regulation of LRRK2 levels and toxicity. AICAr, the precursor of ATIC substrate, regulates LRRK2 levels in a cell-type-specific manner in vitro and in mouse tissue. AICAr regulates LRRK2 levels through AUF1-mediated mRNA decay. Upon AICAr treatment, the RNA binding protein AUF1 is recruited to the AU-rich elements (ARE) of LRRK2 mRNA leading to the recruitment of the decapping enzyme complex DCP1/2 and decay of LRRK2 mRNA. AICAr suppresses LRRK2 expression and rescues LRRK2-induced dopaminergic neurodegeneration and neuroinflammation in PD Drosophila and mouse models. Together, this study provides insight into a novel regulatory mechanism of LRRK2 protein levels and function via LRRK2 mRNA decay that is distinct from LRRK2 enzymatic functions.

Salivary Biomarkers: Noninvasive Ways for Diagnosis of Parkinson's Disease

Finding reliable biomarkers has a crucial role in Parkinson's disease (PD) assessments. Saliva is a bodily fluid, which might be used as a source of biomarkers for PD. Our article has reviewed several publications on salivary proteins in PD patients and their potential as biomarkers. We find out that α-Syn's proportion in oligomeric form is higher in PD patients' saliva, which is potent to use as a biomarker for PD. The salivary concentration of DJ-1 and alpha-amylase is lower in PD patients. Also, substance P level is more moderate in PD patients. Although salivary flow rate is decreased in PD patients, high levels of heme oxygenase and acetylcholinesterase might be used as noninvasive biomarkers. Salivary miRNAs (miR-153, miR-223, miR-874, and miR-145-3p) are novel diagnostic biomarkers that should be given more attention.

Brain-Biomarker Changes in Body Fluids of Patients with Parkinson's Disease

Parkinson's disease (PD) is an incurable neurodegenerative disease that is rarely diagnosed at an early stage. Although the understanding of PD-related mechanisms has greatly improved over the last decade, the diagnosis of PD is still based on neurological examination through the identification of motor symptoms, including bradykinesia, rigidity, postural instability, and resting tremor. The early phase of PD is characterized by subtle symptoms with a misdiagnosis rate of approximately 16-20%. The difficulty in recognizing early PD has implications for the potential use of novel therapeutic approaches. For this reason, it is important to discover PD brain biomarkers that can indicate early dopaminergic dysfunction through their changes in body fluids, such as saliva, urine, blood, or cerebrospinal fluid (CSF). For the CFS-based test, the invasiveness of sampling is a major limitation, whereas the other body fluids are easier to obtain and could also allow population screening. Following the identification of the crucial role of alpha-synuclein (α-syn) in the pathology of PD, a very large number of studies have summarized its changes in body fluids. However, methodological problems have led to the poor diagnostic/prognostic value of this protein and alternative biomarkers are currently being investigated. The aim of this paper is therefore to summarize studies on protein biomarkers that are alternatives to α-syn, particularly those that change in nigrostriatal areas and in biofluids, with a focus on blood, and, eventually, saliva and urine.

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.

Impaired Extracellular Proteostasis in Patients with Heart Failure

BACKGROUND

Proteostasis impairment and the consequent increase of amyloid burden in the myocardium have been associated with heart failure (HF) development and poor prognosis. A better knowledge of the protein aggregation process in biofluids could assist the development and monitoring of tailored interventions.

AIM

To compare the proteostasis status and protein's secondary structures in plasma samples of patients with HF with preserved ejection fraction (HFpEF), patients with HF with reduced ejection fraction (HFrEF), and age-matched individuals.

METHODS

A total of 42 participants were enrolled in 3 groups: 14 patients with HFpEF, 14 patients with HFrEF, and 14 age-matched individuals. Proteostasis-related markers were analyzed by immunoblotting techniques. Fourier Transform Infrared (FTIR) Spectroscopy in Attenuated Total Reflectance (ATR) was applied to assess changes in the protein's conformational profile.

RESULTS

Patients with HFrEF showed an elevated concentration of oligomeric proteic species and reduced clusterin levels. ATR-FTIR spectroscopy coupled with multivariate analysis allowed the discrimination of HF patients from age-matched individuals in the protein amide I absorption region (1700-1600 cm^-1), reflecting changes in protein conformation, with a sensitivity of 73 and a specificity of 81%. Further analysis of FTIR spectra showed significantly reduced random coils levels in both HF phenotypes. Also, compared to the age-matched group, the levels of structures related to fibril formation were significantly increased in patients with HFrEF, whereas the β-turns were significantly increased in patients with HFpEF.

CONCLUSION

Both HF phenotypes showed a compromised extracellular proteostasis and different protein conformational changes, suggesting a less efficient protein quality control system.

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.

Systemic Metabolic Alteration Dependent on the Thyroid-Liver Axis in Early PD

OBJECTIVE

Parkinson's disease (PD) is a common neurodegenerative disease characterized by initial involvement of the olfactory bulb/amygdala or autonomic nerves followed by nigral degeneration. Although autonomic innervation strictly regulates multiorgan systems, including endocrine functions, circulation, and digestion, how dysautonomia in PD affects systemic metabolism has not been identified. In this study, we tried to estimate the pathogenic linkage of PD by nuclear medicine techniques, trans-omic analysis of blood samples, and cultured cell experiments.

METHODS

Thyroid mediastinum ratio of ¹²³ I-metaiodobenzylguanidine (MIBG) scintigraphy was measured in 1,158 patients with PD. Furthermore, serum exosome miRNA transcriptome analysis and plasma metabolome analysis followed by trans-omic analysis were performed in patients with de novo PD and age-matched healthy control persons. Additionally, thyroid hormone was administered to skeletal muscle and liver derived cells to evaluate the effect of hypothyroidism for these organs.

RESULTS

Sympathetic denervation of thyroid correlating with its cardiac denervation was confirmed in 1,158 patients with PD by MIBG scintigraphy. Among patients with drug-naïve PD, comprehensive metabolome analysis revealed decreased levels of thyroxine and insufficient fatty acid β-oxidation, which positively correlate with one another. Likewise, both plasma metabolome data and transcriptome data of circulating exosomal miRNAs, revealed specific enrichment of the peroxisome proliferator-activated receptor (PPARα) axis. Finally, association of thyroid hormone with PPARα-dependent β-oxidation regulation was confirmed by in vitro experiments.

INTERPRETATION

Our findings suggest that interorgan communications between the thyroid and liver are disorganized in the early stage of PD, which would be a sensitive diagnostic biomarker for PD. ANN NEUROL 2023;93:303-316.

Lipid profiles in the cerebrospinal fluid of rats with 6-hydroxydopamine-induced lesions as a model of Parkinson's disease

Background

Parkinson's disease (PD) is a progressive neurodegenerative disease with characteristic pathological abnormalities, including the loss of dopaminergic (DA) neurons, a dopamine-depleted striatum, and microglial activation. Lipid accumulation exhibits a close relationship with these pathologies in PD.

Methods

Here, 6-hydroxydopamine (6-OHDA) was used to construct a rat model of PD, and the lipid profile in cerebrospinal fluid (CSF) obtained from model rats was analyzed using lipidomic approaches.

Results

Establishment of this PD model was confirmed by apomorphine-induced rotation behaviors, loss of DA neurons, depletion of dopamine in the striatum, and microglial activation after 6-OHDA-induced lesion generation. Unsupervised and supervised methods were employed for lipid analysis. A total of 172 lipid species were identified in CSF and subsequently classified into 18 lipid families. Lipid families, including eicosanoids, triglyceride (TG), cholesterol ester (CE), and free fatty acid (FFA), and 11 lipid species exhibited significantly altered profiles 2 weeks after 6-OHDA administration, and significant changes in eicosanoids, TG, CE, CAR, and three lipid species were noted 5 weeks after 6-OHDA administration. During the period of 6-OHDA-induced lesion formation, the lipid families and species showed concentration fluctuations related to the recovery of behavior and nigrostriatal abnormalities. Correlation analysis showed that the levels of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) exhibited positive relationships with apomorphine-induced rotation behaviors and negative relationships with tyrosine hydroxylase (TH) expression in the midbrain.

Conclusion

These results revealed that non-progressive nigrostriatal degeneration induced by 6-OHDA promotes the expression of an impairment-related lipidomic signature in CSF, and the level of eicosanoids, CE, TG families, and TG (16:0_20:0_18:1) in CSF may reveal pathological changes in the midbrain after 6-OHDA insult.

Metabolites as extracellular vesicle cargo in health, cancer, pleural effusion, and cardiovascular diseases: An emerging field of study to diagnostic and therapeutic purposes

Extracellular vesicles (EVs) are highly diverse nanoscale membrane-bound structures released from different cell types into the extracellular environment. They play essential functions in cell signaling by transporting their cargo, such as proteins, RNA, DNA, lipids, metabolites, and small molecules, to recipient cells. It has recently been shown that EVs might modulate carcinogenesis by delivering cargo to recipient cells. Furthermore, recent discoveries revealed that changes in plasma-derived EV levels and cargo in subjects with metabolic diseases were documented by many researchers, suggesting that EVs might be a promising source of disease biomarkers. One of the cargos of EVs that has recently attracted the most attention is metabolites. The metabolome of these vesicles introduces a plethora of disease indicators; hence, examining the metabolomics of EVs detected in human biofluids would be an effective approach. On the other hand, metabolites have various roles in biological systems, including the production of energies, synthesizing macromolecules, and serving as signaling molecules and hormones. Metabolome rewiring in cancer and stromal cells is a characteristic of malignancy, but the current understanding of how this affects the metabolite composition and activity of tumor-derived EVs remains in its infancy. Since new findings and studies in the field of exosome biology and metabolism are constantly being published, it is likely that diagnostic and treatment techniques, including the use of exosome metabolites, will be launched in the coming years. Recent years have seen increased interest in the EV metabolome as a possible source for biomarker development. However, our understanding of the role of these molecules in health and disease is still immature. In this work, we have provided the latest findings regarding the role of metabolites as EV cargoes in the pathophysiology of diseases, including cancer, pleural effusion (PE), and cardiovascular disease (CVD). We also discussed the significance of metabolites as EV cargoes of microbiota and their role in host-microbe interaction. In addition, the latest findings on metabolites in the form of EV cargoes as biomarkers for disease diagnosis and treatment are presented in this study.

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.

Exposure to the environmentally toxic pesticide maneb induces Parkinson's disease-like neurotoxicity in mice: A combined proteomic and metabolomic analysis

Maneb is a typical dithiocarbamate fungicide that has been extensively used worldwide. Epidemiological evidence shows that exposure to maneb is an environmental risk factor for Parkinson's disease (PD). However, the mechanisms underlying maneb-induced neurotoxicity have yet to be elucidated. In this study, we exposed SH-SY5Y cells to maneb at environmentally relevant concentrations (0, 0.1, 5, 10 mg/L) and found that maneb dose-dependently decreased the cell viability. Furthermore, maneb (60 mg/kg) induced PD-like motor impairment in α-synuclein A53T transgenic mice. The results of tandem mass tag (TMT) proteomics and metabolomics studies of mouse brain and serum revealed significant changes in proteins and metabolites in the pathways involved in the neurotransmitter system. The omics results were verified by targeted metabolomics and Western blot analysis, which demonstrated that maneb induced disturbance of the PD-related pathways, including the phenylalanine and tryptophan metabolism pathways, dopaminergic synapse, synaptic vesicle cycle, mitochondrial dysfunction, and oxidative stress. In addition, the PD-like phenotype induced by maneb was attenuated by the asparagine endopeptidase (AEP) inhibitor compound #11 (CP11) (10 mg/kg), indicating that AEP may play a role in maneb-induced neurotoxicity. To the best of our knowledge, this is the first study to investigate the molecular mechanisms underlying maneb-induced PD-like phenotypes using multiomics analysis, which identified novel therapeutic targets for PD associated with pesticides and other environmental pollutants.

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.

Propolis induces cardiac metabolism changes in 6-hydroxydopamine animal model: A dietary intervention as a potential cardioprotective approach in Parkinson’s disease

While there is sustained growth of the older population worldwide, ageing is a consistent risk factor for neurodegenerative diseases, such as Parkinson’s-disease (PD). Considered an emblematic movement disorder, PD comprises a miscellany of non-motor symptoms, for which effective management remains an unfulfilled need in clinical practice. Highlighted are the cardiovascular abnormalities, that cause significant burden in PD patients. Evidence suggests that key biological processes underlying PD pathophysiology can be modulated by diet-derived bioactive compounds, such as green propolis, a natural functional food with biological and pharmacological properties. The effects of propolis on cardiac affection associated to PD have received little coverage. In this study, a metabolomics approach and Positron Emission Tomography (PET) imaging were used to assess the metabolic response to diet supplementation with green propolis on heart outcomes of rats with Parkinsonism induced by 6-hydroxydopamine (6-OHDA rats). Untargeted metabolomics approach revealed four cardiac metabolites (2-hydroxybutyric acid, 3-hydroxybutyric acid, monoacylglycerol and alanine) that were significantly modified between animal groups (6-OHDA, 6-OHDA + Propolis and sham). Propolis-induced changes in the level of these cardiac metabolites suggest beneficial effects of diet intervention. From the metabolites affected, functional analysis identified changes in propanoate metabolism (a key carbohydrate metabolism related metabolic pathway), glucose-alanine cycle, protein and fatty acid biosynthesis, energy metabolism, glutathione metabolism and urea cycle. PET imaging detected higher glucose metabolism in the 17 areas of the left ventricle of all rats treated with propolis, substantially contrasting from those rats that did not consume propolis. Our results bring new insights into cardiac metabolic substrates and pathways involved in the mechanisms of the effects of propolis in experimental PD and provide potential novel targets for research in the quest for future therapeutic strategies.

REM sleep behavior and olfactory dysfunction: improving the utility and translation of animal models in the search for neuroprotective therapies for Parkinson's disease

Parkinson's disease (PD) is a heterogeneous neurodegenerative disease that belongs to the family of synucleiopathies, varying in age, symptoms and progression. Hallmark of the disease is the accumulation of misfolded α-synuclein protein (α-Syn) in neuronal and non-neuronal brain cells. In past decades, diagnosis and treatment of PD has focused on motor deficits, which for the clinical endpoint, have contributed to the prevalence of deficits in the nigrostriatal dopaminergic system and animal models related to motor behavior to study disease. However, clinical trials have failed to translate results from animal models into effective treatments. PD as a multisystem disorder therefore requires additional assessment of motor and non-motor symptoms. Braak's staging revealed early α-Syn pathology in pontine brainstem and olfactory circuits controlling rapid eye movement sleep behavior disorder (RBD) and olfaction, respectively. Recent converging evidence from multicenter clinical studies supports that RBD is the most important risk factor for prodromal PD and the conduct of neuroprotective therapeutic trials in RBD-enriched cohorts has been recommended. Animal models of RBD and olfaction dysfunction can aid to fill the gap in translational research.

GPBAR1 preserves neurite and synapse of dopaminergic neurons via RAD21-OPCML signaling: Role in preventing Parkinson's disease in mouse model and human patients

Parkinson's disease (PD) exhibits systemic impacts on the metabolism, while metabolic alteration contributes to the risk and progression of PD. Bile acids (BA) metabolism disturbance has been linked to PD pathology. Membrane-bound G protein-coupled bile acid receptor 1 (GPBAR1) is expressed in the brain and thought to be neuroprotective; however, the role of GPBAR1 in PD remains unknown. The current study aimed to explore the effect of GPBAR1 in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mice with dopaminergic (DA) neuron-specific Gpbar1 knockdown or central GPBAR1 activation. The underlying mechanisms were investigated using mesencephalic primary neurons analyzed. Our study found that GPBAR1 was reduced in the substantia nigra of PD patients and MPTP-PD mice, and its expression was negatively correlated with the severity of PD-related features. Genetic downregulation of Gpbar1 in mouse mesencephalic DA neurons exacerbated MPTP-induced neurobehavioral and neuropathological deficits, whereas activation of central GPBAR1 with INT-777 (INT) relieved it. Moreover, in vivo and in vitro experiments showed the neurite- and synapse-protective effects of GPBAR1 activation in PD model. Mechanistically, by promoting the nuclear localization of cohesin subunit RAD21, GPBAR1 activation increased opioid-binding cell adhesion molecule (Opcml) expression, thereby inhibiting neurite and synapse degeneration of DA neurons in PD model. Collectively, our findings demonstrate that GPBAR1 is implicated in PD pathogenesis and activation of central GPBAR1 with INT antagonizes neurodegenerative pathology in PD model. This neuroprotection, at least in part, is attributed to the RAD21-OPCML signaling in neurons. Hence, GPBAR1 may serve as a promising candidate target for PD treatment.

Miltirone Attenuates Reactive Oxygen Species-Dependent Neuronal Apoptosis in MPP+-Induced Cell Model of Parkinson's Disease Through Regulating the PI3K/Akt Pathway

Miltirone is a phenanthrene-quinone derived from Salvia miltiorrhiza Bunge with anti-inflammatory and anti-oxidant effects. Our study aimed to explore the protective effect of miltirone on 1-methyl-4-phenylpyridinium (MPP⁺)-induced cell model of Parkinson's disease (PD). PharmMapper database was employed to predict the targets of miltirone. PD-related genes were identified using GeneCards database. The overlapping genes between miltirone and PD were screened out using Venn diagram. KEGG analysis was performed using DAVID and KOBAS databases. Cell viability, reactive oxygen species (ROS) generation, apoptosis, and caspase-3 activity were detected by CCK-8 assay, a ROS assay kit, TUNEL, and caspase-3 activity assay, respectively. Effect of miltirone on the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) pathway was explored by western blot analysis. A total of 214 targets of miltirone and 372 targets related to PD were attained, including 29 overlapping targets. KEGG analysis demonstrated that the 29 overlapping targets were both significantly enriched in the PI3K/Akt pathway. MPP⁺ stimulation reduced the cell viability in SH-SY5Y cells and neuronal primary cultures derived from human brain. Miltirone or N-acetylcysteine (NAC) attenuated MPP⁺-induced reduction in cell viability, ROS production, SOD activity reduction, apoptosis, and increase of caspase-3 activity. Additionally, miltirone recuperated MPP⁺-induced inactivation of the PI3K/Akt pathway. Moreover, treatment with LY294002, an inhibitor of the PI3K/Akt pathway, reversed the inhibitory effect of miltirone on MPP⁺-induced ROS generation and apoptosis in SH-SY5Y cells and neuronal primary cultures. In conclusion, miltirone attenuated ROS-dependent apoptosis in MPP⁺-induced cellular model of PD through activating the PI3K/Akt pathway.

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.

Integrative metabolomics-genomics approach reveals key metabolic pathways and regulators of Alzheimer's disease

Metabolites, the biochemical products of the cellular process, can be used to measure alterations in biochemical pathways related to the pathogenesis of Alzheimer's disease (AD). However, the relationships between systemic abnormalities in metabolism and the pathogenesis of AD are poorly understood. In this study, we aim to identify AD-specific metabolomic changes and their potential upstream genetic and transcriptional regulators through an integrative systems biology framework for analyzing genetic, transcriptomic, metabolomic, and proteomic data in AD. Metabolite co-expression network analysis of the blood metabolomic data in the Alzheimer's Disease Neuroimaging Initiative (ADNI) shows short-chain acylcarnitines/amino acids and medium/long-chain acylcarnitines are most associated with AD clinical outcomes, including episodic memory scores and disease severity. Integration of the gene expression data in both the blood from the ADNI and the brain from the Accelerating Medicines Partnership Alzheimer's Disease (AMP-AD) program reveals ABCA1 and CPT1A are involved in the regulation of acylcarnitines and amino acids in AD. Gene co-expression network analysis of the AMP-AD brain RNA-seq data suggests the CPT1A- and ABCA1-centered subnetworks are associated with neuronal system and immune response, respectively. Increased ABCA1 gene expression and adiponectin protein, a regulator of ABCA1, correspond to decreased short-chain acylcarnitines and amines in AD in the ADNI. In summary, our integrated analysis of large-scale multiomics data in AD systematically identifies novel metabolites and their potential regulators in AD and the findings pave a way for not only developing sensitive and specific diagnostic biomarkers for AD but also identifying novel molecular mechanisms of AD pathogenesis.

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.

Path analysis of biomarkers for cognitive decline in early Parkinson’s disease

Clinical and biochemical diversity of Parkinson’s disease (PD) and numerous demographic, clinical, and pathological measures influencing cognitive function and its decline in PD create problems with the determination of effects of individual measures on cognition in PD. This is particularly the case where these measures significantly interrelate with each other producing intricate networks of direct and indirect effects on cognition. Here, we use generalized structural equation modelling (GSEM) to identify and characterize significant paths for direct and indirect effects of 14 baseline measures on global cognition in PD at baseline and at 4 years later. We consider 269 drug-naïve participants from the Parkinson’s Progression Marker Initiative database, diagnosed with idiopathic PD and observed for at least 4 years after baseline. Two GSEM networks are derived, highlighting the possibility of at least two different molecular pathways or two different PD sub-types, with either CSF p-tau181 or amyloid beta (1–42) being the primary protein variables potentially driving progression of cognitive decline. The models provide insights into the interrelations between the 14 baseline variables, and determined their total effects on cognition in early PD. High CSF amyloid concentrations (> 500 pg/ml) are associated with nearly full protection against cognitive decline in early PD in the whole range of baseline age between 40 and 80 years, and irrespectively of whether p-tau181 or amyloid beta (1–42) are considered as the primary protein variables. The total effect of depression on cognition is shown to be strongly amplified by PD, but not at the time of diagnosis or at prodromal stages. CSF p-tau181 protein could not be a reliable indicator of cognitive decline because of its significantly heterogeneous effects on cognition. The outcomes will enable better understanding of the roles of the clinical and pathological measures and their mutual effects on cognition in early PD.

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

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

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.

Plasma Metabolite Signature Classifies Male LRRK2 Parkinson’s Disease Patients

Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.

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

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

Kynurenic acid in neurodegenerative disorders-unique neuroprotection or double-edged sword?

AIMS

The family of kynurenine pathway (KP) metabolites includes compounds produced along two arms of the path and acting in clearly opposite ways. The equilibrium between neurotoxic kynurenines, such as 3-hydroxykynurenine (3-HK) or quinolinic acid (QUIN), and neuroprotective kynurenic acid (KYNA) profoundly impacts the function and survival of neurons. This comprehensive review summarizes accumulated evidence on the role of KYNA in Alzheimer's, Parkinson's and Huntington's diseases, and discusses future directions of potential pharmacological manipulations aimed to modulate brain KYNA.

DISCUSSION

The synthesis of specific KP metabolites is tightly regulated and may considerably vary under physiological and pathological conditions. Experimental data consistently imply that shift of the KP to neurotoxic branch producing 3-HK and QUIN formation, with a relative or absolute deficiency of KYNA, is an important factor contributing to neurodegeneration. Targeting specific brain regions to maintain adequate KYNA levels seems vital; however, it requires the development of precise pharmacological tools, allowing to avoid the potential cognitive adverse effects.

CONCLUSIONS

Boosting KYNA levels, through interference with the KP enzymes or through application of prodrugs/analogs with high bioavailability and potency, is a promising clinical approach. The use of KYNA, alone or in combination with other compounds precisely influencing specific populations of neurons, is awaiting to become a significant therapy for neurodegenerative disorders.

Tryptophan Metabolism in Central Nervous System Diseases: Pathophysiology and Potential Therapeutic Strategies

The metabolism of L-tryptophan (TRP) regulates homeostasis, immunity, and neuronal function. Altered TRP metabolism has been implicated in the pathophysiology of various diseases of the central nervous system. TRP is metabolized through two main pathways, the kynurenine pathway and the methoxyindole pathway. First, TRP is metabolized to kynurenine, then kynurenic acid, quinolinic acid, anthranilic acid, 3-hydroxykynurenine, and finally 3-hydroxyanthranilic acid along the kynurenine pathway. Second, TRP is metabolized to serotonin and melatonin along the methoxyindole pathway. In this review, we summarize the biological properties of key metabolites and their pathogenic functions in 12 disorders of the central nervous system: schizophrenia, bipolar disorder, major depressive disorder, spinal cord injury, traumatic brain injury, ischemic stroke, intracerebral hemorrhage, multiple sclerosis, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease. Furthermore, we summarize preclinical and clinical studies, mainly since 2015, that investigated the metabolic pathway of TRP, focusing on changes in biomarkers of these neurologic disorders, their pathogenic implications, and potential therapeutic strategies targeting this metabolic pathway. This critical, comprehensive, and up-to-date review helps identify promising directions for future preclinical, clinical, and translational research on neuropsychiatric disorders.

Analysis of circulating metabolites to differentiate Parkinson's disease and essential tremor

Parkinson disease (PD) and essential tremor (ET) are two common adult-onset tremor disorders in which prevalence increases with age. PD is a neurodegenerative condition with progressive disability. In ET, neurodegeneration is not an established etiology. We sought to determine whether an underlying metabolic pattern may differentiate ET from PD. Circulating metabolites in plasma and cerebrospinal fluid were analyzed using gas chromatography-mass spectroscopy. There were several disrupted pathways in PD compared to ET plasma including glycolysis, tyrosine, phenylalanine, tyrosine biosynthesis, purine and glutathione metabolism. Elevated α-synuclein levels in plasma and CSF distinguished PD from ET. The perturbed metabolic state in PD was associated with imbalance in the pentose phosphate pathway, deficits in energy production, and change in NADPH, NADH and nicotinamide phosphoribosyltransferase levels. This work demonstrates significant metabolic differences in plasma and CSF of PD and ET patients.

Metabolomics in degenerative brain diseases

Among the most studied diseases that affect the central nervous system are Parkinson's, Alzheimer's, and Huntington's diseases, but the lack of effective biomarkers, accurate diagnosis, and precise treatment for each of them is currently an issue. Due to the contribution of biomarkers in supporting diagnosis, many recent efforts have focused on their identification and validation at the beginning or during the progression of the mental illness. Metabolome reveals the metabolic processes that result from protein activities under the guided gene expression and environmental factors, either in healthy or pathological conditions. In this context, metabolomics has proven to be a valuable approach. Currently, magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the most commonly used bioanalytical techniques for metabolomics. MS-assisted profiling is considered the most versatile technique, and the NMR is the most reproductive. However, each one of them has its drawbacks. In this review, we summarized several alterations in metabolites that have been reported for these three classic brain diseases using MS and NMR-based research, which might suggest some possible biomarkers to support the diagnosis and/or new targets for their treatment.

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

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