Potential biomarkers of Parkinson's disease revealed by plasma metabolic profiling

Lipid and Transcriptional Regulation in a Parkinson's Disease Mouse Model by Intranasal Vesicular and Hexosomal Plasmalogen-Based Nanomedicines

Plasmalogens (vinyl-ether phospholipids) are an emergent class of lipid drugs against various diseases involving neuro-inflammation, oxidative stress, mitochondrial dysfunction, and altered lipid metabolism. They can activate neurotrophic and neuroprotective signaling pathways but low bioavailabilities limit their efficiency in curing neurodegeneration. Here, liquid crystalline lipid nanoparticles (LNPs) are created for the protection and non-invasive intranasal delivery of purified scallop-derived plasmalogens. The in vivo results with a transgenic mouse Parkinson's disease (PD) model (characterized by motor impairments and α-synuclein deposition) demonstrate the crucial importance of LNP composition, which determines the self-assembled nanostructure type. Vesicle and hexosome nanostructures (characterized by small-angle X-ray scattering) display different efficacy of the nanomedicine-mediated recovery of motor function, lipid balance, and transcriptional regulation (e.g., reduced neuro-inflammation and PD pathogenic gene expression). Intranasal vesicular and hexosomal plasmalogen-based LNP treatment leads to improvement of the behavioral PD symptoms and downregulation of the Il6, Il33, and Tnfa genes. Moreover, RNA-sequencing and lipidomic analyses establish a dramatic effect of hexosomal nanomedicines on PD amelioration, lipid metabolism, and the type and number of responsive transcripts that may be implicated in neuroregeneration.

Plasma oxylipin profiles reflect Parkinson's disease stage

Derivatives of polyunsaturated fatty acids (PUFAs), also known as oxylipins, are key participants in regulating inflammation. Neuroinflammation is involved in many neurodegenerative diseases, including Parkinson's disease. The development of ultra-high-performance liquid chromatography-mass spectrometry (UPLC-MS/MS) facilitated the study of oxylipins on a system level, i.e., the analysis of oxylipin profiles. We analyzed oxylipin profiles in the blood plasma of 36 healthy volunteers (HC) and 73 patients with Parkinson's disease (PD), divided into early (L\M, 29 patients) or advanced (H, 44 patients) stages based on the Hoehn and Yahr scale. Among the 40 oxylipins detected, we observed a decrease in the concentration of arachidonic acid (AA) and AA derivatives, including anandamide (AEA) and Leukotriene E4 (LTE4), and an increase in the concentration of hydroxyeicosatetraenoic acids 19-HETE and 12-HETE (PD vs HC). Correlation analysis of gender, age of PD onset, and disease stages revealed 20 compounds the concentration of which changed depending on disease stage. Comparison of the acquired oxylipin profiles to openly available PD patient brain transcriptome datasets showed that plasma oxylipins do not appear to directly reflect changes in brain metabolism at different disease stages. However, both the L\M and H stages are characterized by their own oxylipin profiles - in patients with the H stage oxylipin synthesis is increased, while in patients with L\M stages oxylipin synthesis decreases compared to HC. This suggests that different therapeutic approaches may be more effective for patients at early versus late stages of PD.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Mass Spectrometric Imaging of Anionic Phospholipids Desorbed from Human Hippocampal Sections: Discrimination between Temporal and Nontemporal Lobe Epilepsies

Temporal lobe epilepsy (TLE) is one of the most common neurological disorders, often accompanied by hippocampal sclerosis. The molecular processes underlying this epileptogenesis are poorly understood. To examine the lipid profile, 39 fresh frozen sections of the human hippocampus obtained from epilepsy surgery for TLE (n = 14) and non-TLE (control group; n = 25) patients were subjected to desorption electrospray ionization mass spectrometry imaging in the negative ion mode. In contrast to our earlier report that showed striking downregulation of positively charged phospholipids (e.g., phosphatidylcholine and phosphatidylethanolamine, etc.) in the TLE hippocampus, this study finds complementary upregulation of negatively charged phospholipids, notably, phosphatidylserine and phosphatidylglycerol. This result may point to an active metabolic pool in the TLE hippocampus that produces these anionic phospholipids at the expense of the cationic phospholipids. This metabolic shift could be due to the dysregulation of the Kennedy and CDP-DG pathways responsible for biosynthesizing these lipids. Thus, this study further opens up opportunities to investigate the molecular hallmarks and potential therapeutic targets for TLE.

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.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Oxylipin transport by lipoprotein particles and its functional implications for cardiometabolic and neurological disorders

Lipoprotein metabolism is critical to inflammation. While the periphery and central nervous system (CNS) have separate yet connected lipoprotein systems, impaired lipoprotein metabolism is implicated in both cardiometabolic and neurological disorders. Despite the substantial investigation into the composition, structure and function of lipoproteins, the lipoprotein oxylipin profiles, their influence on lipoprotein functions, and their potential biological implications are unclear. Lipoproteins carry most of the circulating oxylipins. Importantly, lipoprotein-mediated oxylipin transport allows for endocrine signaling by these lipid mediators, long considered to have only autocrine and paracrine functions. Alterations in plasma lipoprotein oxylipin composition can directly impact inflammatory responses of lipoprotein metabolizing cells. Similar investigations of CNS lipoprotein oxylipins are non-existent to date. However, as APOE4 is associated with Alzheimer's disease-related microglia dysfunction and oxylipin dysregulation, ApoE4-dependent lipoprotein oxylipin modulation in neurological pathologies is suggested. Such investigations are crucial to bridge knowledge gaps linking oxylipin- and lipoprotein-related disorders in both periphery and CNS. Here, after providing a summary of existent literatures on lipoprotein oxylipin analysis methods, we emphasize the importance of lipoproteins in oxylipin transport and argue that understanding the compartmentalization and distribution of lipoprotein oxylipins may fundamentally alter our consideration of the roles of lipoprotein in cardiometabolic and neurological disorders.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Detection of tuberculosis-associated compounds from human skin by GCxGC-TOFMS

Tuberculosis (TB) remains a global health concern. This study aimed to investigate the potential of human skin volatile organic compounds (VOCs) as prospective biomarkers for TB diagnosis. It employed a non-invasive approach using a wearable silicone rubber band for VOC sampling, comprehensive gas chromatography - time of flight mass spectrometry (GCxGC-TOFMS), and chemometric techniques. Both targeted and untargeted biochemical screening was utilized to explore biochemical differences between healthy individuals and those with TB infection. Results confirmed a correlation between compounds found in this study, and those reported for TB from other biofluids. In a comparison to known TB-associated compounds from other biofluids our analysis established the presence of 27 of these compounds emanating from human skin. Additionally, 16 previously unreported compounds were found as potential biomarkers. The diagnostic ability of the VOCs selected by statistical methods was investigated using predictive modelling techniques. Artificial neural network multi-layered perceptron (ANN) yielded two compounds, 1H-indene, 2,3 dihydro-1,1,3-trimethyl-3-phenyl; and heptane-3-ethyl-2-methyl, as the most discriminatory, and could differentiate between TB-positive (n = 15) and TB-negative (n = 23) individuals with an area under the receiver operating characteristic curve (AUROC) of 92 %, a sensitivity of 100 % and a specificity of 94 % for six targeted features. For untargeted analysis, ANN assigned 3-methylhexane as the most discriminatory between TB-positive and TB- negative individuals. An AUROC of 98.5 %, a sensitivity of 83 %, and a specificity of 88 % were obtained for 16 untargeted features as chosen by high performance variable selection. The obtained values compare highly favourable to alternative diagnostic methods such as breath analysis and GeneXpert. Consequently, human skin VOCs hold considerable potential as a TB diagnostic screening test.

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

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

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.

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

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

The acute effect of different NAD+ precursors included in the combined metabolic activators

NAD+ and glutathione precursors are currently used as metabolic modulators for improving the metabolic conditions associated with various human diseases, including non-alcoholic fatty liver disease, neurodegenerative diseases, mitochondrial myopathy, and age-induced diabetes. Here, we performed a one-day double blinded, placebo-controlled human clinical study to assess the safety and acute effects of six different Combined Metabolic Activators (CMAs) with 1 g of different NAD+ precursors based on global metabolomics analysis. Our integrative analysis showed that the NAD+ salvage pathway is the main source for boosting the NAD+ levels with the administration of CMAs without NAD+ precursors. We observed that incorporation of nicotinamide (Nam) in the CMAs can boost the NAD+ products, followed by niacin (NA), nicotinamide riboside (NR) and nicotinamide mononucleotide (NMN), but not flush free niacin (FFN). In addition, the NA administration led to a flushing reaction, accompanied by decreased phospholipids and increased bilirubin and bilirubin derivatives, which could be potentially risky. In conclusion, this study provided a plasma metabolomic landscape of different CMA formulations, and proposed that CMAs with Nam, NMN as well as NR can be administered for boosting NAD+ levels to improve altered metabolic conditions.

Dyrk1a Phosphorylation of α-Synuclein Mediating Apoptosis of Dopaminergic Neurons in Parkinson's Disease

Objective

To investigate the role of aberrant Dyrk1a expression in phosphorylation modification at the α-synuclein serine 129 (Ser129) site to analyze its molecular mechanism in mediating apoptosis of PD.

Methods

The protein level of P-α-synuclein (Ser129), α-synuclein, Bcl-2, Bax, active caspase 3, GSK3β, PI3K, AKT, and cyclinD1 were detected. The mRNA transcript levels of Dyrk1a and DAT and protein levels of IL-1β, IL-6, COX-2, and TNF-α were detected.

Results

P-α-synuclein (Ser129), α-synuclein, Bax, active caspase 3, GSK3β, and cyclinD1 expressions were decreased in Dyrk1a-AAV-ShRNA (P < 0.05), and Bcl-2, AKT, and PI3K expressions were increased (P < 0.05). Increased TH protein expression was shown in Dyrk1a-AAV-ShRNA (P < 0.05). Dyrk1a mRNA was decreased in the Dyrk1a-AAV-ShRNA group (P < 0.05), and DAT mRNA was increased (P < 0.05). IL-1β, IL-6, COX-2, and TNF-α protein levels were decreased in Dyrk1al-AAV-Sh-RNA (P < 0.05). Transcriptome sequencing showed that Fam220a, which was expected to activate STAT family protein binding activity and participate in the negative regulation of transcription through RNA polymerase II and protein dephosphorylation showed differentially upregulated expression. The untargeted metabolome showed that the major compounds in the Dyrk1a-AAV-ShRNA group were hormones and transmission mediators and the most metabolism-related pathways. Fam220a showed differentially upregulated expression, and differentially expressed genes were enriched for the neuroactive ligand-receptor interaction, vascular smooth muscle contraction, and melanogenesis-related pathways.

Conclusion

Abnormal Dyrk1a expression can affect α-synuclein phosphorylation modifications, and dyrk1a knockdown activates the PI3K/AKT pathway and reduces dopaminergic neuron apoptosis. It provides a theoretical basis for the group to further investigate the molecular mechanism.

Interpretable Machine Learning on Metabolomics Data Reveals Biomarkers for Parkinson's Disease

The use of machine learning (ML) with metabolomics provides opportunities for the early diagnosis of disease. However, the accuracy of ML and extent of information obtained from metabolomics can be limited owing to challenges associated with interpreting disease prediction models and analyzing many chemical features with abundances that are correlated and "noisy". Here, we report an interpretable neural network (NN) framework to accurately predict disease and identify significant biomarkers using whole metabolomics data sets without a priori feature selection. The performance of the NN approach for predicting Parkinson's disease (PD) from blood plasma metabolomics data is significantly higher than other ML methods with a mean area under the curve of >0.995. PD-specific markers that predate clinical PD diagnosis and contribute significantly to early disease prediction were identified including an exogenous polyfluoroalkyl substance. It is anticipated that this accurate and interpretable NN-based approach can improve diagnostic performance for many diseases using metabolomics and other untargeted 'omics methods.

Role of Microbiota-Modified Bile Acids in the Regulation of Intracellular Organelles and Neurodegenerative Diseases

Bile acids (BAs) are amphiphilic steroidal molecules generated from cholesterol in the liver and facilitate the digestion and absorption of fat-soluble substances in the gut. Some BAs in the intestine are modified by the gut microbiota. Because BAs are modified in a variety of ways by different types of bacteria present in the gut microbiota, changes in the gut microbiota can affect the metabolism of BAs in the host. Although most BAs absorbed from the gut are transferred to the liver, some are transferred to the systemic circulation. Furthermore, BAs have also been detected in the brain and are thought to migrate into the brain through the systemic circulation. Although BAs are known to affect a variety of physiological functions by acting as ligands for various nuclear and cell-surface receptors, BAs have also been found to act on mitochondria and autophagy in the cell. This review focuses on the BAs modified by the gut microbiota and their roles in intracellular organelles and neurodegenerative diseases.

The value of blood and urine metabolomics in differential diagnosis of cholestasis in infants

Background

Early detection of biliary atresia (BA) is a great challenge providing the main useful way to improve its clinical consequence. Promising metabolomics provides an effective method for determining innovative biomarkers and biochemical ways for improving early diagnosis. This study aimed to determine the benefit of serum and urinary potential bile acid metabolites in the differentiation of BA from non-biliary atresia (non-BA) cases using tandem mass spectrometry (MS/MS). Fourteen bile acids metabolites were measured quantitively by MS/MS in serum and urine samples from 102 cholestatic infants and 102 control infants, in addition to the assay of the total serum bile acid enzymatically.

Results

After the diagnostic clinical and laboratory workflow, cholestatic infants were divided into BA (37 infants) and non-BA (65 infants) subgroups. Remarkably on analysis of serum individual bile acid concentrations, there were significant differences between cholestatic BA and non-BA regarding serum (glycocenodeoxycholic acid (GCDCA), taurochenodeoxycholic acid (TCDCA), taurocholic acid (TCA), and GCDCA/chenodeoxycholic acid (CDCA) ratio) (p < 0.001, for all), while there was no significant difference between the two groups regarding serum level of (cholic acid (CA), glycocholic (GCA), or TCDCA/CDCA ratio). There were no significant differences in either the urinary individual bile acids or urinary primary bile acids (conjugated or unconjugated) between BA and non-BA. Further principal component analysis (PCA) analysis was done and receiver operating characteristic (ROC) analysis was performed using score plots of the positive factors in the first two principal components PC1 (CA, GCA, GCDCA, TCA, TCDCA) and PC2 (CA, CDCA, lithocholic (LCA), ursodeoxycholic acid (UDCA)) for establishing the differences between the two diseased groups and revealed that the area under the curve (AUC) for PC1 was (0.770) higher than AUC for PC2 (0.583) indicating that the positive components of PC1 may be potential biomarkers for differentiation between the two cholestatic groups.

Conclusions

Metabolomics of serum bile acid levels using tandem mass spectrometry might change the paradigm differentiating BA from non-BA saving patients from unnecessary invasive procedures.

Improvement of Spatial Memory and Cognitive Function in Mice via the Intervention of Milk Fat Globule Membrane

With the improvement of living standards, dietary interventions have become an appropriate approach to enhance memory and cognitive performance. The present study investigated the potential mechanisms of spatial memory and cognitive function improvement with the milk fat globule membrane (MFGM) intervention in mice. The Morris water maze experiment revealed that the trajectories of mice in group M were more disordered. Also, the immunohistochemical results demonstrated a significantly higher number of neurons in group M compared with group C, especially in the hippocampal dentate gyrus (DG) area. It is suggested that MFGM enhanced mice's spatial memory and cognition from macroscopic behavior and microscopic cytology, respectively. Meanwhile, 47 differentially expressed proteins (DEPs) were identified, including 20 upregulated and 27 downregulated proteins. Upregulated (Sorbs 2, Rab 39, and Cacna 1e) and downregulated (Hp and Lrg 1) DEPs may improve spatial memory and cognition in mice by promoting synapse formation and increasing neurotransmitter receptors. KEGG enrichment analysis of the DEPs identified seven signaling pathways that were significantly enriched (p < 0.05). One of these pathways was neuroactive ligand-receptor interactions, which are strongly associated with improved spatial memory and cognitive performance. These findings give some new insights and references to the potential mechanisms of spatial memory and cognitive enhancement by MFGM.

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

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

Natural product-based pharmacological studies for neurological disorders

Central nervous system (CNS) disorders and diseases are expected to rise sharply in the coming years, partly because of the world's aging population. Medicines for the treatment of the CNS have not been successfully made. Inadequate knowledge about the brain, pharmacokinetic and dynamic errors in preclinical studies, challenges with clinical trial design, complexity and variety of human brain illnesses, and variations in species are some potential scenarios. Neurodegenerative diseases (NDDs) are multifaceted and lack identifiable etiological components, and the drugs developed to treat them did not meet the requirements of those who anticipated treatments. Therefore, there is a great demand for safe and effective natural therapeutic adjuvants. For the treatment of NDDs and other memory-related problems, many herbal and natural items have been used in the Ayurvedic medical system. Anxiety, depression, Parkinson's, and Alzheimer's diseases (AD), as well as a plethora of other neuropsychiatric disorders, may benefit from the use of plant and food-derived chemicals that have antidepressant or antiepileptic properties. We have summarized the present level of knowledge about natural products based on topological evidence, bioinformatics analysis, and translational research in this review. We have also highlighted some clinical research or investigation that will help us select natural products for the treatment of neurological conditions. In the present review, we have explored the potential efficacy of phytoconstituents against neurological diseases. Various evidence-based studies and extensive recent investigations have been included, which will help pharmacologists reduce the progression of neuronal disease.

A new perspective on endocrine disrupting effects of triphenyltin on marine medaka: From brain transcriptome, gut content metabolome and behavior

Triphenyltin (TPT) is an endocrine contaminant that is often detected in the environment. However, the mechanism of the effects of TPT on biological systems is not fully understood. Here we exposed marine medaka (Oryzias melastigma) to TPT for 21 days. Brain transcriptome, intestinal content metabolism group, and behavior analysis were carried out. Through the comprehensive analysis of multiomics for the in-depth understanding of the ways related to health improvement, we determined that the glycine-serine-threonine metabolic axis was most perturbed by TPT. Through behavioral analysis, it was found that there was behavioral hyperactivity in the exposed group; behavioral hyperactivity may be caused by the interference of TPT with the neuroendocrine system. In order to gain a full understanding of the impacts of TPT on human health, transcriptomic screening of differential genes and an impartial attitude based on bioinformatics were used. Gene-disease interaction analysis using the Comparative Toxicogenomics Database (CTD) revealed the possible effects of TPT on human health. Finally, based on these findings, the relevant adverse outcome pathway (AOP), which is the "epigenetic modification of PPARG leading to adipogenesis," was identified from AOP Wiki. Further research is required to validate the potential AOP of TPT.

Linking Nonalcoholic Fatty Liver Disease and Brain Disease: Focusing on Bile Acid Signaling

A metabolic illness known as non-alcoholic fatty liver disease (NAFLD), affects more than one-quarter of the world's population. Bile acids (BAs), as detergents involved in lipid digestion, show an abnormal metabolism in patients with NAFLD. However, BAs can affect other organs as well, such as the brain, where it has a neuroprotective effect. According to a series of studies, brain disorders may be extrahepatic manifestations of NAFLD, such as depression, changes to the cerebrovascular system, and worsening cognitive ability. Consequently, we propose that NAFLD affects the development of brain disease, through the bile acid signaling pathway. Through direct or indirect channels, BAs can send messages to the brain. Some BAs may operate directly on the central Farnesoid X receptor (FXR) and the G protein bile acid-activated receptor 1 (GPBAR1) by overcoming the blood-brain barrier (BBB). Furthermore, glucagon-like peptide-1 (GLP-1) and the fibroblast growth factor (FGF) 19 are released from the intestine FXR and GPBAR1 receptors, upon activation, both of which send signals to the brain. Inflammatory, systemic metabolic disorders in the liver and brain are regulated by the bile acid-activated receptors FXR and GPBAR1, which are potential therapeutic targets. From a bile acid viewpoint, we examine the bile acid signaling changes in NAFLD and brain disease. We also recommend the development of dual GPBAR1/FXR ligands to reduce side effects and manage NAFLD and brain disease efficiently.

Paper Spray Ionization Ion Mobility Mass Spectrometry of Sebum Classifies Biomarker Classes for the Diagnosis of Parkinson's Disease

Parkinson's disease (PD) is the second most common neurodegenerative disorder, and identification of robust biomarkers to complement clinical diagnosis will accelerate treatment options. Here, we demonstrate the use of direct infusion of sebum from skin swabs using paper spray ionization coupled with ion mobility mass spectrometry (PS-IM-MS) to determine the regulation of molecular classes of lipids in sebum that are diagnostic of PD. A PS-IM-MS method for sebum samples that takes 3 min per swab was developed and optimized. The method was applied to skin swabs collected from 150 people and elucidates ∼4200 features from each subject, which were independently analyzed. The data included high molecular weight lipids (>600 Da) that differ significantly in the sebum of people with PD. Putative metabolite annotations of several lipid classes, predominantly triglycerides and larger acyl glycerides, were obtained using accurate mass, tandem mass spectrometry, and collision cross section measurements.

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.

Studying the Parkinson's disease metabolome and exposome in biological samples through different analytical and cheminformatics approaches: a pilot study

Parkinson’s disease (PD) is the second most prevalent neurodegenerative disease, with an increasing incidence in recent years due to the aging population. Genetic mutations alone only explain <10% of PD cases, while environmental factors, including small molecules, may play a significant role in PD. In the present work, 22 plasma (11 PD, 11 control) and 19 feces samples (10 PD, 9 control) were analyzed by non-target high-resolution mass spectrometry (NT-HRMS) coupled to two liquid chromatography (LC) methods (reversed-phase (RP) and hydrophilic interaction liquid chromatography (HILIC)). A cheminformatics workflow was optimized using open software (MS-DIAL and patRoon) and open databases (all public MSP-formatted spectral libraries for MS-DIAL, PubChemLite for Exposomics, and the LITMINEDNEURO list for patRoon). Furthermore, five disease-specific databases and three suspect lists (on PD and related disorders) were developed, using PubChem functionality to identifying relevant unknown chemicals. The results showed that non-target screening with the larger databases generally provided better results compared with smaller suspect lists. However, two suspect screening approaches with patRoon were also good options to study specific chemicals in PD. The combination of chromatographic methods (RP and HILIC) as well as two ionization modes (positive and negative) enhanced the coverage of chemicals in the biological samples. While most metabolomics studies in PD have focused on blood and cerebrospinal fluid, we found a higher number of relevant features in feces, such as alanine betaine or nicotinamide, which can be directly metabolized by gut microbiota. This highlights the potential role of gut dysbiosis in PD development.

Lipidomics of Bioactive Lipids in Alzheimer's and Parkinson's Diseases: Where Are We?

Lipids are not only constituents of cellular membranes, but they are also key signaling mediators, thus acting as “bioactive lipids”. Among the prominent roles exerted by bioactive lipids are immune regulation, inflammation, and maintenance of homeostasis. Accumulated evidence indicates the existence of a bidirectional relationship between the immune and nervous systems, and lipids can interact particularly with the aggregation and propagation of many pathogenic proteins that are well-renowned hallmarks of several neurodegenerative disorders, including Alzheimer’s (AD) and Parkinson’s (PD) diseases. In this review, we summarize the current knowledge about the presence and quantification of the main classes of endogenous bioactive lipids, namely glycerophospholipids/sphingolipids, classical eicosanoids, pro-resolving lipid mediators, and endocannabinoids, in AD and PD patients, as well as their most-used animal models, by means of lipidomic analyses, advocating for these lipid mediators as powerful biomarkers of pathology, diagnosis, and progression, as well as predictors of response or activity to different current therapies for these neurodegenerative diseases.

Multiomics implicate gut microbiota in altered lipid and energy metabolism in Parkinson's disease

We aimed to investigate the link between serum metabolites, gut bacterial community composition, and clinical variables in Parkinson’s disease (PD) and healthy control subjects (HC). A total of 124 subjects were part of the study (63 PD patients and 61 HC subjects). 139 metabolite features were found to be predictive between the PD and Control groups. No associations were found between metabolite features and within-PD clinical variables. The results suggest alterations in serum metabolite profiles in PD, and the results of correlation analysis between metabolite features and microbiota suggest that several bacterial taxa are associated with altered lipid and energy metabolism in PD.

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.

Fat and Protein Combat Triggers Immunological Weapons of Innate and Adaptive Immune Systems to Launch Neuroinflammation in Parkinson's Disease

Parkinson's disease (PD) is the second-most common neurodegenerative disease in the world, affecting up to 10 million people. This disease mainly happens due to the loss of dopaminergic neurons accountable for memory and motor function. Partial glucocerebrosidase enzyme deficiency and the resultant excess accumulation of glycosphingolipids and alpha-synuclein (α-syn) aggregation have been linked to predominant risk factors that lead to neurodegeneration and memory and motor defects in PD, with known and unknown causes. An increasing body of evidence uncovers the role of several other lipids and their association with α-syn aggregation, which activates the innate and adaptive immune system and sparks brain inflammation in PD. Here, we review the emerging role of a number of lipids, i.e., triglyceride (TG), diglycerides (DG), glycerophosphoethanolamines (GPE), polyunsaturated fatty acids (PUFA), sphingolipids, gangliosides, glycerophospholipids (GPL), and cholesterols, and their connection with α-syn aggregation as well as the induction of innate and adaptive immune reactions that trigger neuroinflammation in PD.

Plasma Metabolite Markers of Parkinson's Disease and Atypical Parkinsonism

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

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.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

The Metabolomic Approach Reveals the Alteration in Human Serum and Cerebrospinal Fluid Composition in Parkinson's Disease Patients

Parkinson’s disease (PD) is a major public health problem. Since currently there are no reliable diagnostic tools to reveal the early steps of PD, new methods should be developed, including those searching the variations in human metabolome. Alterations in human metabolites could help to establish an earlier and more accurate diagnosis. The presented research shows a targeted metabolomics study of both of the serum and CSF from PD patients, atypical parkinsonian disorders (APDs) patients, and the control. The use of the LC-MS/MS system enabled to quantitate 144 analytes in the serum and 51 in the CSF. This information about the concentration enabled for selection of the metabolites useful for differentiation between the studied group of patients, which should be further evaluated as candidates for markers of screening and differential diagnosis of PD and APDs. Among them, the four compounds observed to be altered in both the serum and CSF seem to be the most important: tyrosine, putrescine, trans-4-hydroxyproline, and total dimethylarginine. Furthermore, we indicated the metabolic pathways potentially related to neurodegeneration processes. Our studies present evidence that the proline metabolism might be related to neurodegeneration processes underlying PD and APDs. Further studies on the proposed metabolites and founded metabolic pathways may significantly contribute to understanding the molecular background of PD and improving the diagnostics and treatment in the future.

Metabolomics in Parkinson's disease

Parkinson's disease (PD) is a multifactorial neurodegenerative disorder in which environmental (lifestyle, dietary, infectious disease) factors as well as genetic make-up play a role. Metabolomics, an evolving research field combining biomarker discovery and pathogenetics, is particularly useful in studying complex pathophysiology in general and Parkinson's disease (PD) specifically. PD, the second most frequent neurodegenerative disorder, is characterized by the loss of dopaminergic neurons in the substantia nigra and the presence of intraneural inclusions of α-synuclein aggregates. Although considered a predominantly movement disorder, PD is also associated with number of non-motor features. Metabolomics has provided useful information regarding this neurodegenerative process with the aim of identifying a disease-specific fingerprint. Unfortunately, many disease variables such as clinical presentation, motor system involvement, disease stage and duration substantially affect biomarker relevance. As such, metabolomics provides a unique approach to studying this multifactorial neurodegenerative disorder.

The neuromicrobiology of Parkinson's disease: A unifying theory

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

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

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

Recent progress in plasmonic nanoparticle-based biomarker detection and cytometry for the study of central nervous system disorders

Neurological disorders affect hundreds of millions of people around the world, are often life-threatening, untreatable, and can result in debilitating symptoms. The high prevalence of these disorders, which feature biochemical or structural abnormalities in neuronal systems, has spurned innovations in both rapid and early detection to assist in the selection of appropriate treatment strategies to improve the patients' quality of life. Plasmonic nanoparticles (PNPs), a versatile and promising class of nanomaterials, are widely utilized in numerous imaging techniques, drug delivery systems, and biomarker detection methods. Recently, PNP-based nanoprobes have attracted considerable attention for the early diagnosis of neurological disorders. Gold nanoparticles (AuNPs), with high local surface plasmon resonance (LSPR) signals, have been particularly well exploited as probes for dynamic biomarker detection, with quantification sensitivity demonstrated down to the single-molecule level. In this review, we will discuss the possibilities of PNPs in the methodological development for rapid neurological disease identification. In addition, we will also describe a new digital cytometry method that combines dark-field imaging and machine learning for precise biomarker enumeration on single cells. The aim of this review is to attract researchers working on the future development of new plasmonic nanoprobe-based strategies for the diagnosis of neurological disorders.

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

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

Gut Microbial Metabolites in Parkinson's Disease: Implications of Mitochondrial Dysfunction in the Pathogenesis and Treatment

The search for therapeutic targets for Parkinson's disease (PD) is hindered by the incomplete understanding of the pathophysiology of the disease. Mitochondrial dysfunction is an area with high potential. The neurobiological signaling connections between the gut microbiome and the central nervous system are incompletely understood. Multiple lines of evidence suggest that the gut microbiota participates in the pathogenesis of PD. Gut microbial dysbiosis may contribute to the loss of dopaminergic neurons through mitochondrial dysfunction. The intervention of gut microbial metabolites via the microbiota-gut-brain axis may serve as a promising therapeutic strategy for PD. In this narrative review, we summarize the potential roles of gut microbial dysbiosis in PD, with emphasis on microbial metabolites and mitochondrial function. We then review the possible ways in which microbial metabolites affect the central nervous system, as well as the impact of microbial metabolites on mitochondrial dysfunction. We finally discuss the possibility of gut microbiota as a therapeutic target for PD.

Distinguishing normal and aggregated alpha-synuclein interaction on gold nanorod incorporated zinc oxide nanocomposite by electrochemical technique

Misfolding and accumulation of the protein alpha synuclein in the brain cells characterize Parkinson's disease (PD). Electrochemical based aluminum interdigitated electrodes (ALIDEs) was fabricated by using conventional photolithography method and modified the surfaces with zinc oxide and gold nanorod by using spin coating method for the analysis of PD protein biomarker. The device surface modified with gold nanorod of 25 nm diameter was used. The bare devices and the surface modified devices were characterized by Scanning Electron Microscope, 3D-Profilometer, Atomic Force Microscope and high-power microscope. The above measurement was also performed to measure the interaction of antibody with aggregated alpha-synuclein for normal, aggregated and aggregated alpha synuclein in human serum and distinguished against 3 control proteins (PARK1, DJ-1 and Factor IX). The detection limit for normal alpha synuclein was 1 f. with the sensitivity of 1 f. on a linear regression (R² = 0.9759). The detection limit for aggregated alpha synuclein was 10 aM with the sensitivity of 1 aM on a linear regression (R² = 0.9797). Also, the detection limit of aggregated alpha synuclein in serum was 10 aM with the sensitivity of 1 aM on a linear regression (R² = 0.9739). These results however indicate that, serum has only minimal amount of alpha synuclein.

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

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

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

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

Sensitive ELISA-based detection method for the mitophagy marker p-S65-Ub in human cells, autopsy brain, and blood samples

Mitochondrial dysfunction is an early, imminent event in neurodegenerative disorders including Parkinson disease (PD) and Alzheimer disease (AD). The enzymatic pair PINK1 and PRKN/Parkin recognize and transiently label damaged mitochondria with ubiquitin (Ub) phosphorylated at Ser65 (p-S65-Ub) as a signal for degradation via the autophagy-lysosome system (mitophagy). Despite its discovery in cell culture several years ago, robust and quantitative detection of altered mitophagy in vivo has remained challenging. Here we developed a sandwich ELISA targeting p-S65-Ub with the goal to assess mitophagy levels in mouse brain and in human clinical and pathological samples. We characterized five total Ub and four p-S65-Ub antibodies by several techniques and found significant differences in their ability to recognize phosphorylated Ub. The most sensitive antibody pair detected recombinant p-S65-Ub chains in the femtomolar to low picomolar range depending on the poly-Ub chain linkage. Importantly, this ELISA was able to assess very low baseline mitophagy levels in unstressed human cells and in brains from wild-type and prkn knockout mice as well as elevated p-S65-Ub levels in autopsied frontal cortex from AD patients vs. control cases. Moreover, the assay allowed detection of p-S65-Ub in blood plasma and was able to discriminate between PINK1 mutation carriers and controls. In summary, we developed a robust and sensitive tool to measure mitophagy levels in cells, tissue, and body fluids. Our data strongly support the idea that the stress-activated PINK1-PRKN mitophagy pathway is constitutively active in mice and humans under unstimulated, physiological and elevated in diseased, pathological conditions.Abbreviations: Ab: antibody; AD: Alzheimer disease; AP: alkaline phosphatase; CV: coefficient of variation; ECL: electrochemiluminescence; KO: knockout; LoB: Limit of Blank; LoD: Limit of Detection; LoQ: Limit of Quantification; MSD: meso scale discovery; PD: Parkinson disease; p-S65-PRKN: phosphorylated PRKN at serine 65; p-S65-Ub: phosphorylated ubiquitin at serine 65; Std.Dev.: standard deviation; Ub: ubiquitin; WT: wild type.

Metabolic Alterations in FMR1 Premutation Carriers

FMR1 gene premutation carriers are at risk of developing Fragile X-associated tremor/ataxia syndrome (FXTAS) and Fragile X-associated primary ovarian insufficiency (FXPOI) in adulthood. Currently the development of biomarkers and effective treatments in FMR1 premutations is still in its infancy. Recent metabolic studies have shown novel findings in asymptomatic FMR1 premutation carriers and FXTAS, which provide promising insight through identification of potential biomarkers and therapeutic pathways. Here we review the latest advancements of the metabolic alterations found in asymptomatic FMR1 premutation carriers and FXTAS, along with our perspective for future studies in this emerging field.

Gut Microbiota and Metabolome Alterations Associated with Parkinson's Disease

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

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

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

Metabolic alterations in plasma from patients with familial and idiopathic Parkinson's disease

The research of new biomarkers for Parkinson's disease is essential for accurate and precocious diagnosis, as well as for the discovery of new potential disease mechanisms and drug targets. The main objective of this work was to identify metabolic changes that might serve as biomarkers for the diagnosis of this neurodegenerative disorder. For this, we profiled the plasma metabolome from mice with neurotoxin-induced Parkinson's disease as well as from patients with familial or sporadic Parkinson's disease. By using mass spectrometry technology, we analyzed the complete metabolome from healthy volunteers compared to patients with idiopathic or familial (carrying the G2019S or R1441G mutations in the LRRK2 gene) Parkinson's disease, as well as, from mice treated with 6-hydroxydopamine to induce Parkinson disease. Both human and murine Parkinson was accompanied by an increase in plasma levels of unconjugated bile acids (cholic acid, deoxycholic acid and lithocholic acid) and purine base intermediary metabolites, in particular hypoxanthine. The comprehensive metabolomic analysis of plasma from Parkinsonian patients underscores the importance of bile acids and purine metabolism in the pathophysiology of this disease. Therefore, plasma measurements of certain metabolites related to these pathways might contribute to the diagnosis of Parkinson's Disease.

Bacterial Metabolites Mirror Altered Gut Microbiota Composition in Patients with Parkinson's Disease

Increasing evidence is supporting the hypothesis of α-synuclein pathology spreading from the gut to the brain although the exact etiology of Parkinson’s disease (PD) is unknown. Furthermore, it has been proposed that inflammation, via the gastrointestinal tract, potentially through infections, may contribute to α-synuclein pathogenesis, and thus to the risk of developing PD. Recently, many studies have shown that PD patients have an altered microbiota composition compared to healthy controls. Inflammation in the gut might drive microbiota alterations or vice versa. Many studies focused on the detection of biomarkers of the etiology, onset, or progression of PD however also report metabolites from bacterial origin. These metabolites might reflect the bacterial composition and as well play an important role in immune homeostasis, ultimately affecting the progression of PD. Besides the bacterial metabolites, pharmacological treatment of PD might play a crucial role during the progression and thus treatment of the disease on the immune system. This review aims to establish a link between the microbial composition with the observed alterations of bacterial metabolites and their impact on the immune system, which could have influential effect in onset, progression and etiology of PD.