Evaluation of cerebrospinal fluid proteins as potential biomarkers for early stage Parkinson's disease diagnosis

From the Gut to the Brain: Is Microbiota a New Paradigm in Parkinson's Disease Treatment?

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiota in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiota axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiota. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiota on PD and whether this may be a new paradigm for treating this devastating disease.

Cerebrospinal fluid protein biomarkers in Parkinson's disease

Proteomic profiling is an effective way to identify biomarkers for Parkinson's disease (PD). Cerebrospinal fluid (CSF) has direct connectivity with the brain and could be a source of finding biomarkers and their clinical implications. Comparative proteomic profiling has shown that a group of differentially displayed proteins exist. The studies performed using conventional and classical tools also supported the occurrence of these proteins. Many studies have highlighted the potential of CSF proteomic profiling for biomarker identification and their clinical applications. Some of these proteins are useful for disease diagnosis and prediction. Proteomic profiling of CSF also has immense potential to distinguish PD from similar neurodegenerative disorders. A few protein biomarkers help in fundamental knowledge generation and clinical interpretation. However, the specific biomarker of PD is not yet known. The use of proteomic approaches in clinical settings is also rare. A large-scale, multi-centric, multi-population and multi-continental study using multiple proteomic tools is warranted. Such a study can provide valuable, comprehensive and reliable information for a better understanding of PD and the development of specific biomarkers. The current article sheds light on the role of CSF proteomic profiling in identifying biomarkers of PD and their clinical implications. The article also explains the achievements, obstacles and hopes for future directions of this approach.

Neuronal dysfunction and gene modulation by non-coding RNA in Parkinson's disease and synucleinopathies

Over the last few decades, emerging evidence suggests that non-coding RNAs (ncRNAs) including long-non-coding RNA (lncRNA), microRNA (miRNA) and circular-RNA (circRNA) contribute to the molecular events underlying progressive neuronal degeneration, and a plethora of ncRNAs have been identified significantly misregulated in many neurodegenerative diseases, including Parkinson's disease and synucleinopathy. Although a direct link between neuropathology and causative candidates has not been clearly established in many cases, the contribution of ncRNAs to the molecular processes leading to cellular dysfunction observed in neurodegenerative diseases has been addressed, suggesting that they may play a role in the pathophysiology of these diseases. Aim of the present Review is to overview and discuss recent literature focused on the role of RNA-based mechanisms involved in different aspects of neuronal pathology in Parkinson's disease and synucleinopathy models.

The role of exosomes in the diagnosis of Parkinson's disease

Parkinson's disease is a common neurodegenerative disease characterized by intracellular aggregation of misfolded α-synuclein as a major pathological hallmark. Exosomes are cell-derived lipid bilayer membrane vesicles with various components, including proteins, RNA, and lipids, that mediate intercellular communication. Currently, exosomes are found to be responsible for transporting misfolded proteins from unhealthy neurons to nearby cells, spreading the disease from cell to cell. Such exosomes can also be found in the cerebrospinal fluid and blood. Thus, exosomes may serve as a potential tool to detect the pathology of Parkinson's disease for clinical diagnosis. In this article, the role and challenges of exosomes in the diagnosis of Parkinson's disease are outlined.

New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson's disease

Parkinson's disease (PD) is characterized by the loss of neuronal cells, which leads to synaptic dysfunction and cognitive defects. Despite the advancements in treatment strategies, the management of PD is still a challenging event. Early prediction and diagnosis of PD are of utmost importance for effective management of PD. In addition, the classification of patients with PD as compared to normal healthy individuals also imposes drawbacks in the early diagnosis of PD. To address these challenges, artificial intelligence (AI) and machine learning (ML) models have been implicated in the diagnosis, prediction, and treatment of PD. Recent times have also demonstrated the implication of AI and ML models in the classification of PD based on neuroimaging methods, speech recording, gait abnormalities, and others. Herein, we have briefly discussed the role of AI and ML in the diagnosis, treatment, and identification of novel biomarkers in the progression of PD. We have also highlighted the role of AI and ML in PD management through altered lipidomics and gut-brain axis. We briefly explain the role of early PD detection through AI and ML algorithms based on speech recordings, handwriting patterns, gait abnormalities, and neuroimaging techniques. Further, the review discuss the potential role of the metaverse, the Internet of Things, and electronic health records in the effective management of PD to improve the quality of life. Lastly, we also focused on the implementation of AI and ML-algorithms in neurosurgical process and drug discovery.

PARK7/DJ-1 in microglia: implications in Parkinson's disease and relevance as a therapeutic target

Microglia are the immune effector cells of the brain playing critical roles in immune surveillance and neuroprotection in healthy conditions, while they can sustain neuroinflammatory and neurotoxic processes in neurodegenerative diseases, including Parkinson's disease (PD). Although the precise triggers of PD remain obscure, causative genetic mutations, which aid in the identification of molecular pathways underlying the pathogenesis of idiopathic forms, represent 10% of the patients. Among the inherited forms, loss of function of PARK7, which encodes the protein DJ-1, results in autosomal recessive early-onset PD. Yet, although protection against oxidative stress is the most prominent task ascribed to DJ-1, the underlying mechanisms linking DJ-1 deficiency to the onset of PD are a current matter of investigation. This review provides an overview of the role of DJ-1 in neuroinflammation, with a special focus on its functions in microglia genetic programs and immunological traits. Furthermore, it discusses the relevance of targeting dysregulated pathways in microglia under DJ-1 deficiency and their importance as therapeutic targets in PD. Lastly, it addresses the prospect to consider DJ-1, detected in its oxidized form in idiopathic PD, as a biomarker and to take into account DJ-1-enhancing compounds as therapeutics dampening oxidative stress and neuroinflammation.

Parkinson's disease-associated 18 bp promoter variant of DJ-1 alters REST binding and regulates its expression

Parkinson's disease (PD) is a progressive neurodegenerative disorder with a complex etiology. Presence of autosomal mutations in PARK7/DJ-1 gene has been associated with early-onset PD. Growing evidence has suggested that DJ-1 acts as a putative sensor of oxidative stress. Reduced levels of DJ-1 protein have been reported in the cerebrospinal fluid of sporadic PD patients. Several case-control association studies have identified DJ-1 g.168_185del (rs200968609) variants conferring susceptibility towards PD pathogenesis. Similarly, among the PD patients in eastern India, the deletion allele (g.168_185) of this DJ-1 promoter polymorphism was found to be associated with PD. Hence, we aimed to find out the functional contribution of this promoter variant of DJ-1 in PD pathogenesis. The expression of DJ-1 was observed to be significantly reduced in the presence of both deletion and duplication sequences as identified from the luciferase promoter activity assay. The transcription factor binding prediction tool identified DJ-1 promoter 18 bp insertion polymorphism as the only binding partner of REST (RE1 Silencing Transcription Factor). Transient Chromatin Immuno-precipitation (ChIP) assay further confirmed this prediction. Previous reports have highlighted the role of REST in regulating the expression of stress-responsive genes. Our study has identified the functional involvement of DJ-1 promoter variants and REST-mediated regulation of DJ-1 expression in PD pathogenesis.

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

Background

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

Methods

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

Results

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

Conclusion

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

Alterations in the Proteome and Phosphoproteome Profiles of Rat Hippocampus after Six Months of Morphine Withdrawal: Comparison with the Forebrain Cortex

The knowledge about proteome changes proceeding during protracted opioid withdrawal is lacking. Therefore, the aim of this work was to analyze the spectrum of altered proteins in the rat hippocampus in comparison with the forebrain cortex after 6-month morphine withdrawal. We utilized 2D electrophoretic workflow (Pro-Q® Diamond staining and Colloidal Coomassie Blue staining) which was preceded by label-free quantification (MaxLFQ). The phosphoproteomic analysis revealed six significantly altered hippocampal (Calm1, Ywhaz, Tuba1b, Stip1, Pgk1, and Aldoa) and three cortical proteins (Tubb2a, Tuba1a, and Actb). The impact of 6-month morphine withdrawal on the changes in the proteomic profiles was higher in the hippocampus—14 proteins, only three proteins were detected in the forebrain cortex. Gene Ontology (GO) enrichment analysis of differentially expressed hippocampal proteins revealed the most enriched terms related to metabolic changes, cytoskeleton organization and response to oxidative stress. There is increasing evidence that energy metabolism plays an important role in opioid addiction. However, the way how morphine treatment and withdrawal alter energy metabolism is not fully understood. Our results indicate that the rat hippocampus is more susceptible to changes in proteome and phosphoproteome profiles induced by 6-month morphine withdrawal than is the forebrain cortex.

Modulation of the Interactions Between α-Synuclein and Lipid Membranes by Post-translational Modifications

Parkinson's disease is characterised by the presence in brain tissue of aberrant inclusions known as Lewy bodies and Lewy neurites, which are deposits composed by α-synuclein and a variety of other cellular components, including in particular lipid membranes. The dysregulation of the balance between lipid homeostasis and α-synuclein homeostasis is therefore likely to be closely involved in the onset and progression of Parkinson's disease and related synucleinopathies. As our understanding of this balance is increasing, we describe recent advances in the characterisation of the role of post-translational modifications in modulating the interactions of α-synuclein with lipid membranes. We then discuss the impact of these advances on the development of novel diagnostic and therapeutic tools for synucleinopathies.

DJ-1 in neurodegenerative diseases: Pathogenesis and clinical application

Neurodegenerative diseases (NDs) are one of the major health threats to human characterized by selective and progressive neuronal loss. The mechanisms of NDs are still not fully understood. The study of genetic defects and disease-related proteins offers us a window into the mystery of it, and the extension of knowledge indicates that different NDs share similar features, mechanisms, and even genetic or protein abnormalities. Among these findings, PARK7 and its production DJ-1 protein, which was initially found implicated in PD, have also been found altered in other NDs. PARK7 mutations, altered expression and posttranslational modification (PTM) cause DJ-1 abnormalities, which in turn lead to downstream mechanisms shared by most NDs, such as mitochondrial dysfunction, oxidative stress, protein aggregation, autophagy defects, and so on. The knowledge of DJ-1 derived from PD researches might apply to other NDs in both basic research and clinical application, and might yield novel insights into and alternative approaches for dealing with NDs.

Emerging targets for the diagnosis of Parkinson's disease: examination of systemic biomarkers

Parkinson's disease (PD) is a highly prevalent and irreversible neurodegenerative disorder that is typically diagnosed in an advanced stage. Currently, there are no approved biomarkers that reliably identify PD patients before they have undergone extensive neuronal damage, eliminating the opportunity for future disease-modifying therapies to intervene in disease progression. This unmet need for diagnostic and therapeutic biomarkers has fueled PD research for decades, but these efforts have not yet yielded actionable results. Recently, studies exploring mechanisms underlying PD progression have offered insights into multisystemic contributions to pathology, challenging the classic perspective of PD as a disease isolated to the brain. This shift in understanding has opened the door to potential new biomarkers from multiple sites in the body. This review focuses on emerging candidates for PD biomarkers in the context of current diagnostic approaches and multiple organ systems that contribute to disease.

Machine Learning for the Diagnosis of Parkinson's Disease: A Review of Literature

Diagnosis of Parkinson's disease (PD) is commonly based on medical observations and assessment of clinical signs, including the characterization of a variety of motor symptoms. However, traditional diagnostic approaches may suffer from subjectivity as they rely on the evaluation of movements that are sometimes subtle to human eyes and therefore difficult to classify, leading to possible misclassification. In the meantime, early non-motor symptoms of PD may be mild and can be caused by many other conditions. Therefore, these symptoms are often overlooked, making diagnosis of PD at an early stage challenging. To address these difficulties and to refine the diagnosis and assessment procedures of PD, machine learning methods have been implemented for the classification of PD and healthy controls or patients with similar clinical presentations (e.g., movement disorders or other Parkinsonian syndromes). To provide a comprehensive overview of data modalities and machine learning methods that have been used in the diagnosis and differential diagnosis of PD, in this study, we conducted a literature review of studies published until February 14, 2020, using the PubMed and IEEE Xplore databases. A total of 209 studies were included, extracted for relevant information and presented in this review, with an investigation of their aims, sources of data, types of data, machine learning methods and associated outcomes. These studies demonstrate a high potential for adaptation of machine learning methods and novel biomarkers in clinical decision making, leading to increasingly systematic, informed diagnosis of PD.

Biomarkers and the Role of α-Synuclein in Parkinson's Disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by the presence of α-synuclein (α-Syn)-rich Lewy bodies (LBs) and the preferential loss of dopaminergic (DA) neurons in the substantia nigra (SN) pars compacta (SNpc). However, the widespread involvement of other central nervous systems (CNS) structures and peripheral tissues is now widely documented. The onset of the molecular and cellular neuropathology of PD likely occurs decades before the onset of the motor symptoms characteristic of PD, so early diagnosis of PD and adequate tracking of disease progression could significantly improve outcomes for patients. Because the clinical diagnosis of PD is challenging, misdiagnosis is common, which highlights the need for disease-specific and early-stage biomarkers. This review article aims to summarize useful biomarkers for the diagnosis of PD, as well as the biomarkers used to monitor disease progression. This review article describes the role of α-Syn in PD and how it could potentially be used as a biomarker for PD. Also, preclinical and clinical investigations encompassing genetics, immunology, fluid and tissue, imaging, as well as neurophysiology biomarkers are discussed. Knowledge of the novel biomarkers for preclinical detection and clinical evaluation will contribute to a deeper understanding of the disease mechanism, which should more effectively guide clinical applications.

Plant Polyphenols as Neuroprotective Agents in Parkinson's Disease Targeting Oxidative Stress

Parkinson's disease (PD) is the second most prevalent progressive neurodegenerative disorder characterized by the degeneration of dopaminergic neurons in the human midbrain. Various ongoing research studies are competing to understand the pathology of PD and elucidate the mechanisms underlying neurodegeneration. Current pharmacological treatments primarily focused on improving dopamine metabolism in PD patients, despite the side effects of long-term usage. In recent years, it is recognized that oxidative stress-mediated pathways lead to neurodegeneration in the brain, which is associated with the pathophysiology of PD. The importance of oxidative stress is often less emphasized when developing potential therapeutic approaches. Natural plant antioxidants have been shown to mediate the oxidative stress-induced effects in PD, which has gained considerable attention in both in vitro and in vivo studies. Yet, clinical trials on natural polyphenol compounds are limited, restricting the potential use of these compounds as an alternative treatment for PD. Therefore, this review provides an understanding of the oxidative stress-induced effects in PD by elucidating the underlying events contributing to oxidative stress and explore the potential use of polyphenols in improving the oxidative status in PD. Preclinical findings have supported the potential of polyphenols in providing neuroprotection against oxidative stress-induced toxicity in PD. However, limiting factors, such as safety and bioavailability of polyphenols, warrant further investigations so as to make them the potential target for clinical applications in the treatment and management of PD.

Emerging role of S100B protein implication in Parkinson's disease pathogenesis

The exact etiology of Parkinson's disease (PD) remains obscure, lacking effective diagnostic and prognostic biomarkers. In search of novel molecular factors that may contribute to PD pathogenesis, emerging evidence highlights the multifunctional role of the calcium-binding protein S100B that is widely expressed in the brain and predominantly in astrocytes. Preclinical evidence points towards the possible time-specific contributing role of S100B in the pathogenesis of neurodegenerative disorders including PD, mainly by regulating neuroinflammation and dopamine metabolism. Although existing clinical evidence presents some contradictions, estimation of S100B in the serum and cerebrospinal fluid seems to hold a great promise as a potential PD biomarker, particularly regarding the severity of motor and non-motor PD symptoms. Furthermore, given the recent development of S100B inhibitors that are able to cross the blood brain barrier, novel opportunities are arising in the research field of PD therapeutics. In this review, we provide an update on recent advances in the implication of S100B protein in the pathogenesis of PD and discuss relevant studies investigating the biomarker potential of S100B in PD, aiming to shed more light on clinical targeting approaches related to this incurable disorder.

An Integrative Nomogram for Identifying Early-Stage Parkinson's Disease Using Non-motor Symptoms and White Matter-Based Radiomics Biomarkers From Whole-Brain MRI

Purpose: To develop and validate an integrative nomogram based on white matter (WM) radiomics biomarkers and nonmotor symptoms for the identification of early-stage Parkinson's disease (PD).

Methods: The brain magnetic resonance imaging (MRI) and clinical characteristics of 336 subjects, including 168 patients with PD, were collected from the Parkinson's Progress Markers Initiative (PPMI) database. All subjects were randomly divided into training and test sets. According to the baseline MRI scans of patients in the training set, the WM was segmented to extract the radiomic features of each patient and develop radiomics biomarkers, which were then combined with nonmotor symptoms to build an integrative nomogram using machine learning. Finally, the diagnostic accuracy and reliability of the nomogram were evaluated using a receiver operating characteristic curve and test data, respectively. In addition, we investigated 58 patients with atypical PD who had imaging scans without evidence of dopaminergic deficit (SWEDD) to verify whether the nomogram was able to distinguish patients with typical PD from patients with SWEDD. A decision curve analysis was also performed to validate the clinical practicality of the nomogram.

Results: The area under the curve values of the integrative nomogram for the training, testing and verification sets were 0.937, 0.922, and 0.836, respectively; the specificity values were 83.8, 88.2, and 91.38%, respectively; and the sensitivity values were 84.6, 82.4, and 70.69%, respectively. A significant difference in the number of patients with PD was observed between the high-risk group and the low-risk group based on the nomogram (P < 0.05).

Conclusion: This integrative nomogram is a new potential method to identify patients with early-stage PD.

Intranigral Administration of β-Sitosterol-β-D-Glucoside Elicits Neurotoxic A1 Astrocyte Reactivity and Chronic Neuroinflammation in the Rat Substantia Nigra

Chronic consumption of β-sitosterol-β-D-glucoside (BSSG), a neurotoxin contained in cycad seeds, leads to Parkinson's disease in humans and rodents. Here, we explored whether a single intranigral administration of BSSG triggers neuroinflammation and neurotoxic A1 reactive astrocytes besides dopaminergic neurodegeneration. We injected 6 μg BSSG/1 μL DMSO or vehicle into the left substantia nigra and immunostained with antibodies against tyrosine hydroxylase (TH) together with markers of microglia (OX42), astrocytes (GFAP, S100β, C3), and leukocytes (CD45). We also measured nitric oxide (NO), lipid peroxidation (LPX), and proinflammatory cytokines (TNF-α, IL-1β, IL-6). The Evans blue assay was used to explore the blood-brain barrier (BBB) permeability. We found that BSSG activates NO production on days 15 and 30 and LPX on day 120. Throughout the study, high levels of TNF-α were present in BSSG-treated animals, whereas IL-1β was induced until day 60 and IL-6 until day 30. Immunoreactivity of activated microglia (899.0 ± 80.20%) and reactive astrocytes (651.50 ± 11.28%) progressively increased until day 30 and then decreased to remain 251.2 ± 48.8% (microglia) and 91.02 ± 39.8 (astrocytes) higher over controls on day 120. C3(+) cells were also GFAP and S100β immunoreactive, showing they were neurotoxic A1 reactive astrocytes. BBB remained permeable until day 15 when immune cell infiltration was maximum. TH immunoreactivity progressively declined, reaching 83.6 ± 1.8% reduction on day 120. Our data show that BSSG acute administration causes chronic neuroinflammation mediated by activated microglia, neurotoxic A1 reactive astrocytes, and infiltrated immune cells. The severe neuroinflammation might trigger Parkinson's disease in BSSG intoxication.

GBA1-associated parkinsonism: new insights and therapeutic opportunities

PURPOSE OF REVIEW

GBA1 mutations, which result in the lysosomal disorder Gaucher disease, are the most common known genetic risk factor for Parkinson disease and Dementia with Lewy Bodies (DLB). The pathogenesis of this association is not fully understood, but further elucidation of this link could lead to new therapeutic options.

RECENT FINDINGS

The characteristic clinical phenotype of GBA1-PD resembles sporadic Parkinson disease, but with an earlier onset and more severe course. Many different GBA1 mutations increase the risk of Parkinson disease, some primarily detected in specific populations. Glucocerebrosidase deficiency appears to be associated with increased α-synuclein aggregation and accumulation, mitochondrial dysfunction because of impaired autophagy, and increased endoplasmic reticulum stress.

SUMMARY

As our understanding of GBA1-associated Parkinson disease increases, new treatment opportunities emerge. MicroRNA profiles are providing examples of both up-regulated and down-regulated proteins related to GBA1 and may provide new therapeutic targets. Chaperone therapy, directed at either misfolded glucocerebrosidase or α-synuclein aggregation, is currently under development and there are several early clinical trials ongoing. Substrate reduction therapy, aimed at lowering the accumulation of metabolic by-products, especially glucosylsphingosine, is also being explored. Basic science insights from the rare disorder Gaucher disease are serving to catapult drug discovery for parkinsonism.

Targeted Multiple Reaction Monitoring Analysis of CSF Identifies UCHL1 and GPNMB as Candidate Biomarkers for ALS

The neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD) share some common molecular deficits including disruption of protein homeostasis leading to disease-specific protein aggregation. While insoluble protein aggregates are the defining pathological confirmation of diagnosis, patient stratification based on early molecular etiologies may identify distinct subgroups within a clinical diagnosis that would respond differently in therapeutic development programs. We are developing targeted multiple reaction monitoring (MRM) mass spectrometry methods to rigorously quantify CSF proteins from known disease genes involved in lysosomal, ubiquitin-proteasomal, and autophagy pathways. Analysis of CSF from 21 PD, 21 ALS, and 25 control patients, rigorously matched for gender, age, and age of sample, revealed significant changes in peptide levels between PD, ALS, and control. In patients with PD, levels of two peptides for chromogranin B (CHGB, secretogranin 1) were significantly reduced. In CSF of patients with ALS, levels of two peptides from ubiquitin carboxy-terminal hydrolase like protein 1 (UCHL1) and one peptide each for glycoprotein non-metastatic melanoma protein B (GPNMB) and cathepsin D (CTSD) were all increased. Analysis of patients with ALS separated into two groups based on length of survival after CSF sampling revealed that the increases in GPNMB and UCHL1 were specific for short-lived ALS patients. While analysis of additional cohorts is required to validate these candidate biomarkers, this study suggests methods for stratification of ALS patients for clinical trials and identifies targets for drug efficacy measurements during therapeutic development.

Electrochemical biosensors for the detection and study of α-synuclein related to Parkinson's disease - A review

Parkinson's disease (PD) is a long-term degenerative disorder that affects predominately dopaminergic neurons in the substantia nigra, which mainly control movement. Alpha-synuclein (α-syn) is a major constituent of Lewy bodies that are reported to be the most important toxic species in the brain of PD patients. In this critical review, we highlight novel electrochemical biosensors that have been recently developed utilizing aptamers and antibodies in connection with various nanomaterials to study biomarkers related to PD such as α-syn. We also review several research articles that have utilized electrochemical biosensors to study the interaction of α-syn with biometals as well as small molecules such as clioquinol, (-)-epigallocatechin-3-gallate (EGCG) and baicalein. Due to the significant advances in nanomaterials in the past decade, electrochemical biosensors capable of detecting multiple biomarkers in clinically relevant samples in real-time have been achieved. This may facilitate the path towards commercialization of electrochemical biosensors for clinical applications and high-throughput screening of small molecules for structure-activity relationship (SAR) studies.

DJ-1 in Parkinson's Disease: Clinical Insights and Therapeutic Perspectives

Mutations in the protein DJ-1 cause autosomal recessive forms of Parkinson’s disease (PD) and oxidized DJ-1 is found in the brains of idiopathic PD individuals. While several functions have been ascribed to DJ-1 (most notably protection from oxidative stress), its contribution to PD pathogenesis is not yet clear. Here we provide an overview of the clinical research to date on DJ-1 and the current state of knowledge regarding DJ-1 characterization in the human brain. The relevance of DJ-1 as a PD biomarker is also discussed, as are studies exploring DJ-1 as a possible therapeutic target for PD and neurodegeneration.