Using 'omics' to define pathogenesis and biomarkers of Parkinson's disease

Combined Metabolic Activators with Different NAD+ Precursors Improve Metabolic Functions in the Animal Models of Neurodegenerative Diseases

BACKGROUND

Mitochondrial dysfunction and metabolic abnormalities are acknowledged as significant factors in the onset of neurodegenerative disorders such as Parkinson's disease (PD) and Alzheimer's disease (AD). Our research has demonstrated that the use of combined metabolic activators (CMA) may alleviate metabolic dysfunctions and stimulate mitochondrial metabolism. Therefore, the use of CMA could potentially be an effective therapeutic strategy to slow down or halt the progression of PD and AD. CMAs include substances such as the glutathione precursors (L-serine and N-acetyl cysteine), the NAD+ precursor (nicotinamide riboside), and L-carnitine tartrate.

METHODS

Here, we tested the effect of two different formulations, including CMA1 (nicotinamide riboside, L-serine, N-acetyl cysteine, L-carnitine tartrate), and CMA2 (nicotinamide, L-serine, N-acetyl cysteine, L-carnitine tartrate), as well as their individual components, on the animal models of AD and PD. We assessed the brain and liver tissues for pathological changes and immunohistochemical markers. Additionally, in the case of PD, we performed behavioral tests and measured responses to apomorphine-induced rotations.

FINDINGS

Histological analysis showed that the administration of both CMA1 and CMA2 formulations led to improvements in hyperemia, degeneration, and necrosis in neurons for both AD and PD models. Moreover, the administration of CMA2 showed a superior effect compared to CMA1. This was further corroborated by immunohistochemical data, which indicated a reduction in immunoreactivity in the neurons. Additionally, notable metabolic enhancements in liver tissues were observed using both formulations. In PD rat models, the administration of both formulations positively influenced the behavioral functions of the animals.

INTERPRETATION

Our findings suggest that the administration of both CMA1 and CMA2 markedly enhanced metabolic and behavioral outcomes, aligning with neuro-histological observations. These findings underscore the promise of CMA2 administration as an effective therapeutic strategy for enhancing metabolic parameters and cognitive function in AD and PD patients.

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.

Combined metabolic activators improve metabolic functions in the animal models of neurodegenerative diseases

BACKGROUND

Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are associated with metabolic abnormalities. Integrative analysis of human clinical data and animal studies have contributed to a better understanding of the molecular and cellular pathways involved in the progression of NDDs. Previously, we have reported that the combined metabolic activators (CMA), which include the precursors of nicotinamide adenine dinucleotide and glutathione can be utilized to alleviate metabolic disorders by activating mitochondrial metabolism.

METHODS

We first analysed the brain transcriptomics data from AD patients and controls using a brain-specific genome-scale metabolic model (GEM). Then, we investigated the effect of CMA administration in animal models of AD and PD. We evaluated pathological and immunohistochemical findings of brain and liver tissues. Moreover, PD rats were tested for locomotor activity and apomorphine-induced rotation.

FINDINGS

Analysis of transcriptomics data with GEM revealed that mitochondrial dysfunction is involved in the underlying molecular pathways of AD. In animal models of AD and PD, we showed significant damage in the high-fat diet groups' brain and liver tissues compared to the chow diet. The histological analyses revealed that hyperemia, degeneration and necrosis in neurons were improved by CMA administration in both AD and PD animal models. These findings were supported by immunohistochemical evidence of decreased immunoreactivity in neurons. In parallel to the improvement in the brain, we also observed dramatic metabolic improvement in the liver tissue. CMA administration also showed a beneficial effect on behavioural functions in PD rats.

INTERPRETATION

Overall, we showed that CMA administration significantly improved behavioural scores in parallel with the neurohistological outcomes in the AD and PD animal models and is a promising treatment for improving the metabolic parameters and brain functions in NDDs.

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

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

Contribution of Human Pluripotent Stem Cell-Based Models to Drug Discovery for Neurological Disorders

One of the major obstacles to the identification of therapeutic interventions for central nervous system disorders has been the difficulty in studying the step-by-step progression of diseases in neuronal networks that are amenable to drug screening. Recent advances in the field of human pluripotent stem cell (PSC) biology offers the capability to create patient-specific human neurons with defined clinical profiles using reprogramming technology, which provides unprecedented opportunities for both the investigation of pathogenic mechanisms of brain disorders and the discovery of novel therapeutic strategies via drug screening. Many examples not only of the creation of human pluripotent stem cells as models of monogenic neurological disorders, but also of more challenging cases of complex multifactorial disorders now exist. Here, we review the state-of-the art brain cell types obtainable from PSCs and amenable to compound-screening formats. We then provide examples illustrating how these models contribute to the definition of new molecular or functional targets for drug discovery and to the design of novel pharmacological approaches for rare genetic disorders, as well as frequent neurodegenerative diseases and psychiatric disorders.

Untargeted metabolomics for uncovering plasma biological markers of wet age-related macular degeneration

Wet age-related macular degeneration (wAMD) causes central vision loss and represents a major health problem in elderly people. Here we have used untargeted metabolomics using UHPLC-MS to profile plasma from 127 patients with wAMD (67 choroidal neovascularization (CNV) and 60 polypoidal choroidal vasculopathy (PCV)) and 50 controls. A total of 545 biochemicals were detected. Among them, 17 metabolites presented difference between patients with wAMD and controls. Most of them were oxidized lipids (N=6, 35.29%). Comparing to controls, 28 and 18 differential metabolites were identified in patients with CNV and PCV, respectively. Two metabolites, hyodeoxycholic acid and L-tryptophanamide, were differently distributed between PCV and CNV. We first investigated the genetic association with metabolites in wet AMD (CFH rs800292 and HTRA1 rs10490924). We identified six differential metabolites between the GG and AA genotypes of CFH rs800292, five differential metabolites between the GG and AA genotypes of HTRA1 rs10490924, and four differential metabolites between the GG and GA genotypes of rs10490924. We selected four metabolites (cyclamic acid, hyodeoxycholic acid, L-tryptophanamide and O-phosphorylethanolamine) for in vitro experiments. Among them, cyclamic acid reduced the activity, inhibited the proliferation, increased the apoptosis and necrosis in human retinal pigment epithelial cells (HRPECs). L-tryptophanamide affected the proliferation, apoptosis and necrosis in HRPECs, and promoted the tube formation and migration in primary human retinal endothelial cells (HRECs). Hyodeoxycholic acid and O-phosphorylethanolamine inhibited the tube formation and migration in HRECs. The results suggested that differential metabolites have certain effects on wAMD pathogenesis-related HRPECs and HRECs.

Non-Coding RNAs in the Brain-Heart Axis: The Case of Parkinson's Disease

Parkinson's disease (PD) is a complex and heterogeneous disorder involving multiple genetic and environmental influences. Although a wide range of PD risk factors and clinical markers for the symptomatic motor stage of the disease have been identified, there are still no reliable biomarkers available for the early pre-motor phase of PD and for predicting disease progression. High-throughput RNA-based biomarker profiling and modeling may provide a means to exploit the joint information content from a multitude of markers to derive diagnostic and prognostic signatures. In the field of PD biomarker research, currently, no clinically validated RNA-based biomarker models are available, but previous studies reported several significantly disease-associated changes in RNA abundances and activities in multiple human tissues and body fluids. Here, we review the current knowledge of the regulation and function of non-coding RNAs in PD, focusing on microRNAs, long non-coding RNAs, and circular RNAs. Since there is growing evidence for functional interactions between the heart and the brain, we discuss the benefits of studying the role of non-coding RNAs in organ interactions when deciphering the complex regulatory networks involved in PD progression. We finally review important concepts of harmonization and curation of high throughput datasets, and we discuss the potential of systems biomedicine to derive and evaluate RNA biomarker signatures from high-throughput expression data.

Treatment of Parkinson's Disease by MAO-B Inhibitors, New Therapies and Future Challenges - A Mini-Review

BACKGROUND

One of the most prevalent neurodegenerative diseases with increasing age is Parkinson's disease (PD). Its pathogenesis is unclear and mainly confined to glutamate toxicity and oxidative stress. The dyskinesia and motor fluctuations and neuroprotective potential are the major concerns which are still unmet in PD therapy.

OBJECTIVE

This article is a capsulization of the role of MAO-B in the treatment of PD, pharmacological properties, safety and efficiency, clinical evidence through random trials, future therapies and challenges.

CONCLUSION

MAO-B inhibitors are well tolerated for the treatment of PD because of their pharmacokinetic properties and neuroprotective action. Rasagiline and selegiline were recommended molecules for early PD and proven safe and provide a modest to significant rise in motor function, delay the use of levodopa and used in early PD. Moreover, safinamide is antiglutamatergic in action. When added to Levodopa, these molecules significantly reduce the offtime with a considerable improvement of non-motor symptoms. This review also discusses the new approaches in therapy like the use of biomarkers, neurorestorative growth factors, gene therapy, neuroimaging, neural transplantation, and nanotechnology. Clinical evidence illustrated that MAOB inhibitors are recommended as monotherapy and added on therapy to levodopa. A large study and further evidence are required in the field of future therapies to unwind the complexity of the disease.

Pathogenic Pathways in Early-Onset Autosomal Recessive Parkinson's Disease Discovered Using Isogenic Human Dopaminergic Neurons

Parkinson's disease (PD) is a complex and highly variable neurodegenerative disease. Familial PD is caused by mutations in several genes with diverse and mostly unknown functions. It is unclear how dysregulation of these genes results in the relatively selective death of nigral dopaminergic neurons (DNs). To address this question, we modeled PD by knocking out the PD genes PARKIN (PRKN), DJ-1 (PARK7), and ATP13A2 (PARK9) in independent isogenic human pluripotent stem cell (hPSC) lines. We found increased levels of oxidative stress in all PD lines. Increased death of DNs upon differentiation was found only in the PARKIN knockout line. Using quantitative proteomics, we observed dysregulation of mitochondrial and lysosomal function in all of the lines, as well as common and distinct molecular defects caused by the different PD genes. Our results suggest that precise delineation of PD subtypes will require evaluation of molecular and clinical data.

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CRISPR knockin of reporter in TH locus allows live tracking and isolation of DNs

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Large-scale 3D midbrain DN differentiation using spinner flask culture

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Phenotypic comparison of isogenic DNs harboring knockouts of PARKIN, DJ-1, or ATP13A2

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Transcriptomics and quantitative proteomics studies determine common and distinct PD pathways

The Development of a Personalised Training Framework: Implementation of Emerging Technologies for Performance

Over the last decade, there has been considerable interest in the individualisation of athlete training, including the use of genetic information, alongside more advanced data capture and analysis techniques. Here, we explore the evidence for, and practical use of, a number of these emerging technologies, including the measurement and quantification of epigenetic changes, microbiome analysis and the use of cell-free DNA, along with data mining and machine learning. In doing so, we develop a theoretical model for the use of these technologies in an elite sport setting, allowing the coach to better answer six key questions: (1) To what training will my athlete best respond? (2) How well is my athlete adapting to training? (3) When should I change the training stimulus (i.e., has the athlete reached their adaptive ceiling for this training modality)? (4) How long will it take for a certain adaptation to occur? (5) How well is my athlete tolerating the current training load? (6) What load can my athlete handle today? Special consideration is given to whether such an individualised training framework will outperform current methods as well as the challenges in implementing this approach.

Identification of the iduronate-2-sulfatase proteome in wild-type mouse brain

Iduronate-2-sulfatase (IDS) is a lysosomal enzyme involved in the metabolism of the glycosaminoglycans heparan (HS) and dermatan (DS) sulfate. Mutations on IDS gene produce mucopolysaccharidosis II (MPS II), characterized by the lysosomal accumulation of HS and DS, leading to severe damage of the central nervous system (CNS) and other tissues. In this study, we used a neurochemistry and proteomic approaches to identify the brain distribution of IDS and its interacting proteins on wild-type mouse brain. IDS immunoreactivity showed a robust staining throughout the entire brain, suggesting an intracellular reactivity in nerve cells and astrocytes. By using affinity purification and mass spectrometry we identified 187 putative IDS partners-proteins, mainly hydrolases, cytoskeletal proteins, transporters, transferases, oxidoreductases, nucleic acid binding proteins, membrane traffic proteins, chaperons and enzyme modulators, among others. The interactions with some of these proteins were predicted by using bioinformatics tools and confirmed by co-immunoprecipitation analysis and Blue Native PAGE. In addition, we identified cytosolic IDS-complexes containing proteins from predicted highly connected nodes (hubs), with molecular functions including catalytic activity, redox balance, binding, transport, receptor activity and structural molecule activity. The proteins identified in this study would provide new insights about IDS physiological role into the CNS and its potential role in the brain-specific protein networks.

Broad spectrum metabolomics for detection of abnormal metabolic pathways in a mouse model for retinitis pigmentosa

Retinitis pigmentosa (RP) is a degenerative disease of the retina that affects approximately 1 million people worldwide. There are multiple genetic causes of this disease, for which, at present, there are no effective therapeutic strategies. In the present report, we utilized broad spectrum metabolomics to identify perturbations in the metabolism of the rd10 mouse, a genetic model for RP that contains a mutation in Pde6β. These data provide novel insights into mechanisms that are potentially critical for retinal degeneration. C57BL/6J and rd10 mice were raised in cyclic light followed by either light or dark adaptation at postnatal day (P) 18, an early stage in the degeneration process. Mice raised entirely in the dark until P18 were also evaluated. After euthanasia, retinas were removed and extracted for analysis by ultra-performance liquid chromatography-time of flight-mass spectrometry (UPLC-QTOF-MS). Compared to wild type mice, rd10 mice raised in cyclic light or in complete darkness demonstrate significant alterations in retinal pyrimidine and purine nucleotide metabolism, potentially disrupting deoxynucleotide pools necessary for mitochondrial DNA replication. Other metabolites that demonstrate significant increases are the Coenzyme A intermediate, 4'-phosphopantothenate, and acylcarnitines. The changes in these metabolites, identified for the first time in a model of RP, are highly likely to disrupt normal energy metabolism. High levels of nitrosoproline were also detected in rd10 retinas relative to those from wild type mice. These results suggest that nitrosative stress may be involved in retinal degeneration in this mouse model.

Recent Advances in Biomarkers for Parkinson's Disease

Parkinson's disease (PD) is one of the common progressive neurodegenerative disorders with several motor and non-motor symptoms. Most of the motor symptoms may appear at a late stage where most of the dopaminergic neurons have been already damaged. In order to provide better clinical intervention and treatment at the onset of disease, it is imperative to find accurate biomarkers for early diagnosis, including prodromal diagnosis and preclinical diagnosis. At the same time, these reliable biomarkers can also be utilized to monitor the progress of the disease. In this review article, we will discuss recent advances in the development of PD biomarkers from different aspects, including clinical, biochemical, neuroimaging and genetic aspects. Although various biomarkers for PD have been developed so far, their specificity and sensitivity are not ideal when applied individually. So, the combination of multimodal biomarkers will greatly improve the diagnostic accuracy and facilitate the implementation of personalized medicine.

Convergent pathways in Parkinson's disease

Preferential degeneration of dopamine neurons (DAn) in the midbrain represents the principal hallmark of Parkinson's disease (PD). It has been hypothesized that major contributors to DAn vulnerability lie in their unique cellular physiology and architecture, which make them particularly susceptible to stress factors. Here, we report a concise overview of some of the cell mechanisms that may exacerbate DAn sensitivity and loss in PD. In particular, we highlight how defective protein sorting and clearance, endoplasmic reticulum stress, calcium dyshomeostasis and intracellular trafficking converge to contribute synergistically to neuronal dysfunction in PD pathogenesis.

From Genomics to Omics Landscapes of Parkinson's Disease: Revealing the Molecular Mechanisms

Molecular mechanisms of Parkinson's disease (PD) have already been investigated in various different omics landscapes. We reviewed the literature about different omics approaches between November 2005 and November 2017 to depict the main pathological pathways for PD development. In total, 107 articles exploring different layers of omics data associated with PD were retrieved. The studies were grouped into 13 omics layers: genomics-DNA level, transcriptomics, epigenomics, proteomics, ncRNomics, interactomics, metabolomics, glycomics, lipidomics, phenomics, environmental omics, pharmacogenomics, and integromics. We discussed characteristics of studies from different landscapes, such as main findings, number of participants, sample type, methodology, and outcome. We also performed curation and preliminary synthesis of multiple omics data, and identified overlapping results, which could lead toward selection of biomarkers for further validation of PD risk loci. Biomarkers could support the development of targeted prognostic/diagnostic panels as a tool for early diagnosis and prediction of progression rate and prognosis. This review presents an example of a comprehensive approach to revealing the underlying processes and risk factors of a complex disease. It urges scientists to structure the already known data and integrate it into a meaningful context.

Metabolomic biomarkers as strong correlates of Parkinson disease progression

OBJECTIVE

To determine whether a Parkinson disease (PD)-specific biochemical signature might be found in the total body metabolic milieu or in the CSF compartment, especially since this disorder has systemic manifestations beyond the progressive loss of dopaminergic nigrostriatal neurons.

METHODS

Our goal was to discover biomarkers of PD progression. Using ultra-high-performance liquid chromatography linked to gas chromatography and tandem mass spectrometry, we measured concentrations of small-molecule (≤1.5 kDa) constituents of plasma and CSF from 49 unmedicated, mildly affected patients with PD (mean age 61.4 years; mean duration of PD 11.4 months). Specimens were collected twice (baseline and final) at intervals up to 24 months. During this time, mean Unified Parkinson's Disease Rating Scale (UPDRS) parts 2 + 3 scores increased 47% (from 28.8 to 42.2). Measured compounds underwent unbiased univariate and multivariate analyses, including fitting data into multiple linear regression with variable selection using least absolute shrinkage and selection operator (LASSO).

RESULTS

Of 575 identified plasma and 383 CSF biochemicals, LASSO led to selection of 15 baseline plasma constituents with high positive correlation (0.87, p = 2.2e^-16) to baseline-to-final change in UPDRS parts 2 + 3 scores. Three of the compounds had xanthine structures, and 4 were either medium- or long-chain fatty acids. For the 15 LASSO-selected biomarkers, pathway enrichment software found no overrepresentation among metabolic pathways. CSF concentrations of the dopamine metabolite homovanillate showed little change between baseline and final collections and minimal correlation with worsening UPDRS parts 2 + 3 scores (0.29, p = 0.041).

CONCLUSIONS

Metabolomic profiling of plasma yielded strong prediction of PD progression and offered biomarkers that may provide new insights into PD pathogenesis.

Transcriptomics, proteomics and metabolomics driven biomarker discovery in COPD: an update

INTRODUCTION

Diagnosis of chronic obstructive pulmonary disease (COPD), characterized by progressive irreversible airflow limitation, remains a challenge. Lack of sensitive diagnostic markers and alternative treatments have limited patients' survival rate. Herein, we provide for clinicians and scientists a comprehensive review on the various omics platforms used to investigate COPD.

AREAS COVERED

This review consists of articles from PubMed (2009-2016) as well as views of the contributing authors. The review highlights the need for COPD biomarker identification and also provides an update on promising candidate markers identified in various biological fluids using omics technologies. Expert commentary: The multi-omics approach holds promise for the development of robust early stage COPD diagnostic markers, screening of high-risk population, and also improved prognosis which could lead to personalized medicine in future. Various factors regulating an omics study including sample size, control selection, disease phenotyping, usage of complementary techniques and result replication in omics-based research are outlined.

Neuroprotective and Therapeutic Strategies against Parkinson's Disease: Recent Perspectives

Parkinsonism is a progressive motor disease that affects 1.5 million Americans and is the second most common neurodegenerative disease after Alzheimer’s. Typical neuropathological features of Parkinson’s disease (PD) include degeneration of dopaminergic neurons located in the pars compacta of the substantia nigra that project to the striatum (nigro-striatal pathway) and depositions of cytoplasmic fibrillary inclusions (Lewy bodies) which contain ubiquitin and α-synuclein. The cardinal motor signs of PD are tremors, rigidity, slow movement (bradykinesia), poor balance, and difficulty in walking (Parkinsonian gait). In addition to motor symptoms, non-motor symptoms that include autonomic and psychiatric as well as cognitive impairments are pressing issues that need to be addressed. Several different mechanisms play an important role in generation of Lewy bodies; endoplasmic reticulum (ER) stress induced unfolded proteins, neuroinflammation and eventual loss of dopaminergic neurons in the substantia nigra of mid brain in PD. Moreover, these diverse processes that result in PD make modeling of the disease and evaluation of therapeutics against this devastating disease difficult. Here, we will discuss diverse mechanisms that are involved in PD, neuroprotective and therapeutic strategies currently in clinical trial or in preclinical stages, and impart views about strategies that are promising to mitigate PD pathology.

Deep brain stimulation-associated brain tissue imprints: a new in vivo approach to biological research in human Parkinson's disease

BACKGROUND

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or the internal segment of the globus pallidus (GPi) has been established as a highly effective symptomatic therapy for Parkinson's disease (PD). An intriguing biological aspect related to the DBS procedure is that a temporary contact establishes between surgical instruments and the surrounding brain tissue. In this exploratory study, we took advantage of this unique context to harvest brain material adhering to the stylet routinely used during surgery, and to examine the biological value of these samples, here referred to as "brain tissue imprints" (BTIs).

RESULTS

Nineteen BTIs from 12 STN- or GPi-electrode implanted patients were obtained in vivo during DBS surgery, without any modification of the surgical procedure. Immunofluorescence analyses confirmed that our approach allowed the harvesting of many neural cells including neurons harboring distinct neurotransmitter markers. Shotgun proteomic and transcriptomic analyses provided for the first time molecular information from DBS-associated brain samples, and confirmed the compatibility of this new type of sample with poly-omic approaches. The method appears to be safe and results consistent.

CONCLUSIONS

We here propose BTIs as original and highly valuable brain samples, and DBS-related brain imprinting as a new conceptual approach to biological research in living patients with PD.

Differential proteomics analysis of mononuclear cells in cerebrospinal fluid of Parkinson's disease

Parkinson's disease (PD) is one common neurodegenerative disease featured with degeneration of dopaminergic neurons in substantia nigra. Multiple factors participate in the pathogenesis and progression of PD. In this study, we investigated the proteomics profiles of mononuclear cells in cerebrospinal fluids from both PD patients and normal people, in order to explore the correlation between disease factors and PD. Cerebrospinal fluid samples were collected from both PD and normal people and were separated for mononuclear cells in vitro. Proteins were then extracted and separated by 2-dimensional gel electrophoresis. Proteins with differential expressions were identified by comparison to standard proteome expression profile map, followed by software and database analysis. In PD patients, there were 8 proteins with consistent expression profile and 16 proteins with differential expressions. Those differential proteins identified include cytoskeleton proteins (actin, myosin), signal transduction proteins (adenosine cyclase binding protein 1, calcium binding protein, talin) and anti-oxidation factor (thioredoxin peroxide reductase). PD patients had differential protein expressional profiles in the mononuclear cells of cerebrospinal fluids compared to normal people, suggesting the potential involvement of cytoskeleton and signal transduction proteins in apoptosis of neuronal apoptosis and PD pathogenesis.

Biomarkers in Parkinson's disease: Advances and strategies

Parkinson's disease (PD) is a neurodegenerative disorder characterized by progressive motor disturbances and affects more than 1% of the worldwide population. Despite considerable progress in understanding PD pathophysiology, including genetic and biochemical causes, diagnostic approaches lack accuracy and interventions are restricted to symptomatic treatments. PD is a complex syndrome with different clinical subtypes and a wide variability in disorder course. In order to deliver better clinical management of PD patients and discovery of novel therapies, there is an urgent need to find sensitive, specific, and reliable biomarkers. The development of biomarkers will not only help the scientific community to identify populations at risk, but also facilitate clinical diagnosis. Furthermore, these tools could monitor progression, which could ultimately deliver personalized therapeutic strategies. The field of biomarker discovery in PD has attracted significant attention and there have been numerous contributions in recent years. Although none of the parameters have been validated for clinical practice, some candidates hold promise. This review summarizes recent advances in the development of PD biomarkers and discusses new strategies for their utilization.

Metabolome-Wide Association Study of Primary Open Angle Glaucoma

PURPOSE

To determine if primary open-angle glaucoma (POAG) patients can be differentiated from controls based on metabolic characteristics.

METHODS

We used ultra-high resolution mass spectrometry with C18 liquid chromatography for metabolomic analysis on frozen plasma samples from 72 POAG patients and 72 controls. Metabolome-wide Spearman correlation was performed to select differentially expressed metabolites (DEM) correlated with POAG. We corrected P values for multiple testing using Benjamini and Hochberg false discovery rate (FDR). Hierarchical cluster analysis (HCA) was used to depict the relationship between participants and DEM. Differentially expressed metabolites were matched to the METLIN metabolomics database; both DEM and metabolites significantly correlating with DEM were analyzed using MetaboAnalyst to identify metabolic pathways altered in POAG.

RESULTS

Of the 2440 m/z (mass/charge) features recovered after filtering, 41 differed between POAG cases and controls at FDR = 0.05. Hierarchical cluster analysis revealed these DEM to associate into eight clusters; three of these clusters contained the majority of the DEM and included palmitoylcarnitine, hydroxyergocalciferol, and high-resolution METLIN matches to sphingolipids, other vitamin D-related metabolites, and terpenes. MetaboAnalyst also indicated likely alteration in steroid biosynthesis pathways.

CONCLUSIONS

Global ultrahigh resolution metabolomics emphasized the importance of altered lipid metabolism in POAG. The results suggest specific metabolic processes, such as those involving palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors, may contribute to POAG status and merit more detailed study with targeted methods.

Laser capture microdissection: Big data from small samples

Any tissue is made up of a heterogeneous mix of spatially distributed cell types. In response to any (patho) physiological cue, responses of each cell type in any given tissue may be unique and cannot be homogenized across cell-types and spatial co-ordinates. For example, in response to myocardial infarction, on one hand myocytes and fibroblasts of the heart tissue respond differently. On the other hand, myocytes in the infarct core respond differently compared to those in the peri-infarct zone. Therefore, isolation of pure targeted cells is an important and essential step for the molecular analysis of cells involved in the progression of disease. Laser capture microdissection (LCM) is powerful to obtain a pure targeted cell subgroup, or even a single cell, quickly and precisely under the microscope, successfully tackling the problem of tissue heterogeneity in molecular analysis. This review presents an overview of LCM technology, the principles, advantages and limitations and its down-stream applications in the fields of proteomics, genomics and transcriptomics. With powerful technologies and appropriate applications, this technique provides unprecedented insights into cell biology from cells grown in their natural tissue habitat as opposed to those cultured in artificial petri dish conditions.

A weighted relative difference accumulation algorithm for dynamic metabolomics data: long-term elevated bile acids are risk factors for hepatocellular carcinoma

Dynamic metabolomics studies can provide a systematic view of the metabolic trajectory during disease development and drug treatment and reveal the nature of biological processes at metabolic level. To extract important information in a systematic time dimension rather than at isolated time points, a weighted method based on the means and variations along the time points was proposed and first applied to previously published rat model data. The method was subsequently extended and applied to prospective metabolomics data analysis of hepatocellular carcinoma (HCC). Permutation was employed for noise filtering and false discovery rate (FDR) was used for parameter optimization during the feature selection. Long-term elevated serum bile acids were identified as risk factors for HCC development.

Proteomic profiling in MPTP monkey model for early Parkinson disease biomarker discovery

Identification of reliable and robust biomarkers is crucial to enable early diagnosis of Parkinson disease (PD) and monitoring disease progression. While imperfect, the slow, chronic 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced non-human primate animal model system of parkinsonism is an abundant source of pre-motor or early stage PD biomarker discovery. Here, we present a study of a MPTP rhesus monkey model of PD that utilizes complementary quantitative iTRAQ-based proteomic, glycoproteomics and phosphoproteomics approaches. We compared the glycoprotein, non-glycoprotein, and phosphoprotein profiles in the putamen of asymptomatic and symptomatic MPTP-treated monkeys as well as saline injected controls. We identified 86 glycoproteins, 163 non-glycoproteins, and 71 phosphoproteins differentially expressed in the MPTP-treated groups. Functional analysis of the data sets inferred the biological processes and pathways that link to neurodegeneration in PD and related disorders. Several potential biomarkers identified in this study have already been translated for their usefulness in PD diagnosis in human subjects and further validation investigations are currently under way. In addition to providing potential early PD biomarkers, this comprehensive quantitative proteomic study may also shed insights regarding the mechanisms underlying early PD development. This article is part of a Special Issue entitled: Neuroproteomics: Applications in neuroscience and neurology.

Metabolomic Analysis Provides Insights on Paraquat-Induced Parkinson-Like Symptoms in Drosophila melanogaster

Paraquat (PQ) exposure causes degeneration of the dopaminergic neurons in an exposed organism while altered metabolism has a role in various neurodegenerative disorders. Therefore, the study presented here was conceived to depict the role of altered metabolism in PQ-induced Parkinson-like symptoms and to explore Drosophila as a potential model organism for such studies. Metabolic profile was generated in control and in flies that were fed PQ (5, 10, and 20 mM) in the diet for 12 and 24 h concurrent with assessment of indices of oxidative stress, dopaminergic neurodegeneration, and behavioral alteration. PQ was found to significantly alter 24 metabolites belonging to different biological pathways along with significant alterations in the above indices. In addition, PQ attenuated brain dopamine content in the exposed organism. The study demonstrates that PQ-induced alteration in the metabolites leads to oxidative stress and neurodegeneration in the exposed organism along with movement disorder, a phenotype typical of Parkinson-like symptoms. The study is relevant in the context of Drosophila and humans because similar alteration in the metabolic pathways has been observed in both PQ-exposed Drosophila and in postmortem samples of patients with Parkinsonism. Furthermore, this study provides advocacy towards the applicability of Drosophila as an alternate model organism for pre-screening of environmental chemicals for their neurodegenerative potential with altered metabolism.

Cerebrospinal fluid biomarkers in parkinsonian conditions: an update and future directions

Parkinsonian diseases comprise a heterogeneous group of neurodegenerative disorders, which show significant clinical and pathological overlap. Accurate diagnosis still largely relies on clinical acumen; pathological diagnosis remains the gold standard. There is an urgent need for biomarkers to diagnose parkinsonian disorders, particularly in the early stages when diagnosis is most difficult. In this review, several of the most promising cerebrospinal fluid candidate markers will be discussed. Their strengths and limitations will be considered together with future developments in the field.

Systems-based analyses of brain regions functionally impacted in Parkinson's disease reveals underlying causal mechanisms

Detailed analysis of disease-affected tissue provides insight into molecular mechanisms contributing to pathogenesis. Substantia nigra, striatum, and cortex are functionally connected with increasing degrees of alpha-synuclein pathology in Parkinson's disease. We undertook functional and causal pathway analysis of gene expression and proteomic alterations in these three regions, and the data revealed pathways that correlated with disease progression. In addition, microarray and RNAseq experiments revealed previously unidentified causal changes related to oligodendrocyte function and synaptic vesicle release, and these and other changes were reflected across all brain regions. Importantly, subsets of these changes were replicated in Parkinson's disease blood; suggesting peripheral tissue may provide important avenues for understanding and measuring disease status and progression. Proteomic assessment revealed alterations in mitochondria and vesicular transport proteins that preceded gene expression changes indicating defects in translation and/or protein turnover. Our combined approach of proteomics, RNAseq and microarray analyses provides a comprehensive view of the molecular changes that accompany functional loss and alpha-synuclein pathology in Parkinson's disease, and may be instrumental to understand, diagnose and follow Parkinson's disease progression.

Metabolic analysis of striatal tissues from Parkinson's disease-like rats by electrospray ionization ion mobility mass spectrometry

Electrospray ionization ion mobility mass spectrometry (ESI-IMMS) was used to study the striatal metabolomes in a Parkinson's like disease (PD-like) rat model. Striatal tissue samples from Berlin Druckrey IV (BD-IV) with PD-like disease 20 dpn-affected and 15 dpn-affected rats (dpn: days postnatal) were investigated and compared with age-matched controls. An ion mobility mass spectrometer (IMMS) produced multidimensional spectra with mass to charge ratio (m/z), ion mobility drift time, and intensity information for each individual metabolite. Principle component analysis (PCA) was applied in this study for pattern recognition and significant metabolites selection (68% data was modeled in PCA). Both IMMS spectra and PCA results showed that there were clear global metabolic differences between PD-like samples and healthy controls. Nine metabolites were selected by PCA and identified as potential biomarkers using the Human Metabolome Database (HMDB). One targeted metabolite in this study was dopamine. Selected-mass mobility analysis indicated the absence of dopamine in PD-like striatal metabolomes. A major discovery of this work, however, was the existence of an isomer of dopamine. By using ion mobility spectrometry, the dopamine isomer, which has not previously been reported, was separated from dopamine.

Emerging candidate biomarkers for Parkinson's disease: a review

Parkinson's disease is a chronic neurodegenerative disorder leading to progressive motor impairment affecting more than 1% of the over-65 population. In spite of considerable progress in identifying the genetic and biochemical basis of PD, to date the diagnosis remains clinical and disease-modifying therapies continue to be elusive. A cornerstone in recent PD research is the investigation of biological markers that could help in identifying at-risk population or to track disease progression and response to therapies. Although none of these parameters has been validated for routine clinical practice yet, however some biochemical candidates hold great promise for application in PD patients, especially in the early stages of disease, and it is likely that in the future the diagnosis of PD will require a combination of genetic, imaging and laboratory data. In this review we discuss the most interesting biochemical markers for PD (including the "-omics" techniques), focusing on the methodological challenges in using ex vivo blood/CSF/tissue-based biomarkers and suggesting alternative strategies to overcome the difficulties that still prevent their actual use.

Metabolome-wide association study of neovascular age-related macular degeneration

PURPOSE

To determine if plasma metabolic profiles can detect differences between patients with neovascular age-related macular degeneration (NVAMD) and similarly-aged controls.

METHODS

Metabolomic analysis using liquid chromatography with Fourier-transform mass spectrometry (LC-FTMS) was performed on plasma samples from 26 NVAMD patients and 19 controls. Data were collected from mass/charge ratio (m/z) 85 to 850 on a Thermo LTQ-FT mass spectrometer, and metabolic features were extracted using an adaptive processing software package. Both non-transformed and log2 transformed data were corrected using Benjamini and Hochberg False Discovery Rate (FDR) to account for multiple testing. Orthogonal Partial Least Squares-Discriminant Analysis was performed to determine metabolic features that distinguished NVAMD patients from controls. Individual m/z features were matched to the Kyoto Encyclopedia of Genes and Genomes database and the Metlin metabolomics database, and metabolic pathways associated with NVAMD were identified using MetScape.

RESULTS

Of the 1680 total m/z features detected by LC-FTMS, 94 unique m/z features were significantly different between NVAMD patients and controls using FDR (q = 0.05). A comparison of these features to those found with log2 transformed data (n = 132, q = 0.2) revealed 40 features in common, reaffirming the involvement of certain metabolites. Such metabolites included di- and tripeptides, covalently modified amino acids, bile acids, and vitamin D-related metabolites. Correlation analysis revealed associations among certain significant features, and pathway analysis demonstrated broader changes in tyrosine metabolism, sulfur amino acid metabolism, and amino acids related to urea metabolism.

CONCLUSIONS

These data suggest that metabolomic analysis can identify a panel of individual metabolites that differ between NVAMD cases and controls. Pathway analysis can assess the involvement of certain metabolic pathways, such as tyrosine and urea metabolism, and can provide further insight into the pathophysiology of AMD.

3-hydroxykynurenine and other Parkinson's disease biomarkers discovered by metabolomic analysis

Parkinson's disease (PD) biomarkers are needed to enhance therapeutics research and to understand PD pathogenesis. Methods that simultaneously measure hundreds of small molecular-weight compounds-metabolomic analysis-"fingerprint" disease-specific alterations in individual compounds or metabolic pathways. Beyond a nontargeted search for PD biomarkers, we hypothesized that PD cerebrospinal fluid would show increased formation of the excitotoxin 3-hydroxykynurenine and diminished concentration of the antioxidant glutathione. Cerebrospinal fluid was collected at <4 hours postmortem from 48 pathologically-verified PD subjects and 57 comparably-aged controls. Assays involved ultra-high-performance liquid and gas chromatography linked to mass spectrometry. We used univariate techniques to determine fold-changes in concentrations of biochemicals; false-discovery rates were calculated to exclude spurious findings. Data was modeled using a Support Vector Machine for analyzing compounds selected by Welch's t test. Classification accuracy was determined by cross-validation. Of 243 structurally-identified biochemicals,19 compounds differentiated PD from controls at a 20% false-discovery level. In PD, mean 3-hydroxykynurenine concentration was increased by one-third, and mean oxidized glutathione was decreased by 40% (for each, P < .01). Four of the 19 compounds differentiating PD from controls were N-acetylated amino acids, suggesting a generalized alteration in N-acetylation activity. The Support Vector Machine classification model distinguished between groups at 83% sensitivity and 91% specificity for the learning data, and at 65% and 79% from cross-validation. In this study, the first for metabolomic profiling of PD cerebrospinal fluid, we found several novel biomarkers and offer new directions for recognizing disease-specific biochemical indicators. The findings support involvement of excitotoxicity and oxidative stress in the pathogenesis of PD.

Biomarkers in Parkinson's disease (recent update)

Parkinson's disease (PD) is the second most common neurodegenerative disorder mostly affecting the aging population over sixty. Cardinal symptoms including, tremors, muscle rigidity, drooping posture, drooling, walking difficulty, and autonomic symptoms appear when a significant number of nigrostriatal dopaminergic neurons are already destroyed. Hence we need early, sensitive, specific, and economical peripheral and/or central biomarker(s) for the differential diagnosis, prognosis, and treatment of PD. These can be classified as clinical, biochemical, genetic, proteomic, and neuroimaging biomarkers. Novel discoveries of genetic as well as nongenetic biomarkers may be utilized for the personalized treatment of PD during preclinical (premotor) and clinical (motor) stages. Premotor biomarkers including hyper-echogenicity of substantia nigra, olfactory and autonomic dysfunction, depression, hyposmia, deafness, REM sleep disorder, and impulsive behavior may be noticed during preclinical stage. Neuroimaging biomarkers (PET, SPECT, MRI), and neuropsychological deficits can facilitate differential diagnosis. Single-cell profiling of dopaminergic neurons has identified pyridoxal kinase and lysosomal ATPase as biomarker genes for PD prognosis. Promising biomarkers include: fluid biomarkers, neuromelanin antibodies, pathological forms of α-Syn, DJ-1, amyloid β and tau in the CSF, patterns of gene expression, metabolomics, urate, as well as protein profiling in the blood and CSF samples. Reduced brain regional N-acetyl-aspartate is a biomarker for the in vivo assessment of neuronal loss using magnetic resonance spectroscopy and T2 relaxation time with MRI. To confirm PD diagnosis, the PET biomarkers include [(18)F]-DOPA for estimating dopaminergic neurotransmission, [(18)F]dG for mitochondrial bioenergetics, [(18)F]BMS for mitochondrial complex-1, [(11)C](R)-PK11195 for microglial activation, SPECT imaging with (123)Iflupane and βCIT for dopamine transporter, and urinary salsolinol and 8-hydroxy, 2-deoxyguanosine for neuronal loss. This brief review describes the merits and limitations of recently discovered biomarkers and proposes coenzyme Q10, mitochondrial ubiquinone-NADH oxidoreductase, melatonin, α-synculein index, Charnoly body, and metallothioneins as novel biomarkers to confirm PD diagnosis for early and effective treatment of PD.

A micro-silicon chip for in vivo cerebral imprint in monkey

Access to cerebral tissue is essential to better understand the molecular mechanisms associated with neurodegenerative diseases. In this study, we present, for the first time, a new tool designed to obtain molecular and cellular cerebral imprints in the striatum of anesthetized monkeys. The imprint is obtained during a spatially controlled interaction of a chemically modified micro-silicon chip with the brain tissue. Scanning electron and immunofluorescence microscopies showed homogeneous capture of cerebral tissue. Nano-liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) analysis of proteins harvested on the chip allowed the identification of 1158 different species of proteins. The gene expression profiles of mRNA extracted from the imprint tool showed great similarity to those obtained via the gold standard approach, which is based on post-mortem sections of the same nucleus. Functional analysis of the harvested molecules confirmed the spatially controlled capture of striatal proteins implicated in dopaminergic regulation. Finally, the behavioral monitoring and histological results establish the safety of obtaining repeated cerebral imprints in striatal regions. These results demonstrate the ability of our imprint tool to explore the molecular content of deep brain regions in vivo. They open the way to the molecular exploration of brain in animal models of neurological diseases and will provide complementary information to current data mainly restricted to post-mortem samples.

Cerebrospinal fluid biomarker candidates for parkinsonian disorders

The Parkinsonian disorders are a large group of neurodegenerative diseases including idiopathic Parkinson’s disease (PD) and atypical Parkinsonian disorders (APD), such as multiple system atrophy, progressive supranuclear palsy, corticobasal degeneration, and dementia with Lewy bodies. The etiology of these disorders is not known although it is considered to be a combination of genetic and environmental factors. One of the greatest obstacles for developing efficacious disease-modifying treatment strategies is the lack of biomarkers. Reliable biomarkers are needed for early and accurate diagnosis, to measure disease progression, and response to therapy. In this review several of the most promising cerebrospinal biomarker candidates are discussed. Alpha-synuclein seems to be intimately involved in the pathogenesis of synucleinopathies and its levels can be measured in the cerebrospinal fluid and in plasma. In a similar way, tau protein accumulation seems to be involved in the pathogenesis of tauopathies. Urate, a potent antioxidant, seems to be associated to the risk of developing PD and with its progression. Neurofilament light chain levels are increased in APD compared with PD and healthy controls. The new “omics” techniques are potent tools offering new insights in the patho-etiology of these disorders. Some of the difficulties encountered in developing biomarkers are discussed together with future perspectives.

NMR Metabolomics Analysis of Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disease, which is characterized by progressive death of dopaminergic neurons in the substantia nigra pars compacta. Although mitochondrial dysfunction and oxidative stress are linked to PD pathogenesis, its etiology and pathology remain to be elucidated. Metabolomics investigates metabolite changes in biofluids, cell lysates, tissues and tumors in order to correlate these metabolomic changes to a disease state. Thus, the application of metabolomics to investigate PD provides a systematic approach to understand the pathology of PD, to identify disease biomarkers, and to complement genomics, transcriptomics and proteomics studies. This review will examine current research into PD mechanisms with a focus on mitochondrial dysfunction and oxidative stress. Neurotoxin-based PD animal models and the rationale for metabolomics studies in PD will also be discussed. The review will also explore the potential of NMR metabolomics to address important issues related to PD treatment and diagnosis.

Neurochemistry and the non-motor aspects of PD

Parkinson disease (PD) is a systemic disease with variegated non-motor deficits and neurological symptoms, including impaired olfaction, autonomic failure, cognitive impairment and psychiatric symptoms, in addition to the classical motor symptoms. Many non-motor symptoms appear before or in parallel with motor deficits and then worsen with disease progression. Although there is a relationship, albeit not causal, between motor symptoms and the presence of Lewy bodies (LBs) and neurites filled with abnormal α-synuclein, other neurological alterations are independent of the amount of α-synuclein inclusions in neurons and neurites, thereby indicating that different mechanisms probably converge in the degenerative process. This may apply to complex alterations interfering with olfactory and autonomic nervous systemfunctions, emotions, sleep regulation, and behavioral, cognitive and mental performance. Involvement of the cerebral cortex leading to impaired behavior and cognition is related to several convergent altered factors including: a. dopaminergic, noradrenergic, serotoninergic and cholinergic cortical innervation; b. synapses; c. cortical metabolism; d. mitochondrial function and energy production; e. oxidative damage; f. transcription; g. protein expression; h. lipid composition; and i. ubiquitin–proteasome system and autophagy, among others. This complex situation indicates that multiple subcellular failure in selected cell populations is difficult to reconcilewith a reductionistic scenario of a single causative cascade of events leading to non-motor symptoms in PD. Furthermore, these alterationsmay appear at early stages of the disease and may precede the appearance of substantial irreversible cell loss by years. These observations have important implications in the design of therapeutic approaches geared to prevention and treatment of PD.

Single cell genomics of the brain: focus on neuronal diversity and neuropsychiatric diseases

Single cell genomics has made increasingly significant contributions to our understanding of the role that somatic genome variations play in human neuronal diversity and brain diseases. Studying intercellular genome and epigenome variations has provided new clues to the delineation of molecular mechanisms that regulate development, function and plasticity of the human central nervous system (CNS). It has been shown that changes of genomic content and epigenetic profiling at single cell level are involved in the pathogenesis of neuropsychiatric diseases (schizophrenia, mental retardation (intellectual/leaning disability), autism, Alzheimer's disease etc.). Additionally, several brain diseases were found to be associated with genome and chromosome instability (copy number variations, aneuploidy) variably affecting cell populations of the human CNS. The present review focuses on the latest advances of single cell genomics, which have led to a better understanding of molecular mechanisms of neuronal diversity and neuropsychiatric diseases, in the light of dynamically developing fields of systems biology and "omics".

Biochemical premotor biomarkers for Parkinson's disease

A biomarker is a biological characteristic that is objectively measured and evaluated as an indicator of normal biological or pathologic processes or of pharmacologic responses to a therapeutic intervention. We reviewed the current status of target protein biomarkers (eg, total/oligomeric α-synuclein and DJ-1) in cerebrospinal fluid, as well as on unbiased processes that can be used to discover novel biomarkers. We have also provide details about strategies toward potential populations/models and technologies, including the need for standardized sampling techniques, to pursue the identification of new biochemical markers in the premotor stage of Parkinson's disease in the future.

Dopaminergic therapies modulate the T-CELL proteome of patients with Parkinson's disease

Dopamine receptor agonists and L-dihydroxyphenylalanine (L-DOPA) counteract dopamine loss in the striatum and are therefore used in the treatment of Parkinson's disease (PD). T-Lymphocytes express some features of the dopaminergic system, and their function or activation might be regulated by dopaminergic treatments. Two-dimensional electrophoresis of total protein extract from T-lymphocytes was performed to identify therapy-induced proteome changes in T-cells of 17 patients with PD. Specific protein level alterations were further validated by Western blotting. Of 17 enrolled patients, 11 were treated with different doses of L-DOPA; in this group, we found that the levels of two spots, corresponding to ATP synthase subunit β and proteasome subunit β type-2, correlated linearly with the L-DOPA daily dose. Moreover, we identified seven proteins (prolidase, actin-related protein 2, F-actin-capping protein subunit β, tropomyosin α-3 chain, proteasome activator complex subunit 1, peroxiredoxin 6, and a glyceraldehyde-3-phosphate dehydrogenase isoform) whose levels were significantly different in patients treated with dopamine agonists. These findings demonstrate that dopaminergic stimulation has important effects on T-cell proteome in patients under long-term treatment. Therefore, therapies acting on the dopaminergic system may have additional effects on the immune system.

Genomics and bioinformatics of Parkinson's disease

Within the last two decades, genomics and bioinformatics have profoundly impacted our understanding of the molecular mechanisms of Parkinson's disease (PD). From the description of the first PD gene in 1997 until today, we have witnessed the emergence of new technologies that have revolutionized our concepts to identify genetic mechanisms implicated in human health and disease. Driven by the publication of the human genome sequence and followed by the description of detailed maps for common genetic variability, novel applications to rapidly scrutinize the entire genome in a systematic, cost-effective manner have become a reality. As a consequence, about 30 genetic loci have been unequivocally linked to the pathogenesis of PD highlighting essential molecular pathways underlying this common disorder. Herein we discuss how neurogenomics and bioinformatics are applied to dissect the nature of this complex disease with the overall aim of developing rational therapeutic interventions.

Premotor biomarkers for Parkinson's disease - a promising direction of research

The second most serious neurodegenerative disease is Parkinson’s disease (PD). Over the past several decades, a strong body of evidence suggests that PD can begin years before the hallmark clinical motor symptoms appear. Biomarkers for PD are urgently needed to differentiate between neurodegenerative disorders, screen novel therapeutics, and predict eventual clinical PD before the onset of symptoms. Some clinical evaluations and neuroimaging techniques have been developed in the last several years with some success in this area. Moreover, other strategies have been utilized to identify biochemical and genetic markers associated with PD leading to the examination of PD progression and pathogenesis in cerebrospinal fluid, blood, or saliva. Finally, interesting results are surfacing from preliminary studies using known PD-associated genetic mutations to assess potential premotor PD biomarkers. The current review highlights recent advances and underscores areas of potential advancement.