Can Biomarkers Help the Early Diagnosis of Parkinson's Disease?

Plasma extracellular vesicle pathognomonic proteins as the biomarkers of the progression of Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disorder for which reliable blood biomarkers to predict disease progression remain elusive. Plasma extracellular vesicles (EVs) have gained attention as a promising biomarker platform due to their stability and ability to cross the blood-brain barrier. This study explored the potential of EV-cargo proteins, specifically α-synuclein, tau, and β-amyloid, as biomarkers of PD progression. A cohort of 55 people with PD (PwP) and 58 healthy controls (HCs) underwent annual assessments of plasma EV proteins, cognition, and motor symptoms. EVs were isolated and validated using standardized methods, with pathognomonic proteins quantified via immunomagnetic reduction assays. Associations between biomarker changes and clinical symptom progression were analyzed. Over an average of 3.96 visits for PwP and 2.25 visits for HCs, PwP exhibited a distinct pattern of plasma EV protein changes linked to motor symptom progression, particularly in the Unified PD Rating Scale (UPDRS) part II score. Notably, changes in plasma EV α-synuclein levels were significantly correlated with changes in motor and cognitive symptoms, suggesting its central role in disease progression. These findings highlight the potential of plasma EV biomarkers, especially α-synuclein, as indicators of ongoing pathogenesis and as candidates for evaluating α-synuclein-targeted therapies in PD.

Parkinson biomarker determination with an Au microflower-enhanced electrochemical immunosensor using non-Faradaic capacitance measurements

This work comprehends the development and characterization of a carbon black-based electrode modified with Au microflowers to increase its effect as a capacitance biosensor for the determination of PARK7/DJ-1. Due to its high surface-to-volume ratio and biocompatibility, Au particles are suitable for antibody binding, and by monitoring surface capacitance, it is possible to identify the immune-pair interaction. Au microflowers allowed the adequate immobilization of Parkinsonian-related proteins: PARK7/DJ-1 and its antibody. The protein is associated with several antioxidant mechanisms, but its abnormal concentrations or mutations can be the cause of the loss of dopaminergic neurons, leading to Parkinson's disease. The device was characterized by scanning electron microscopy and cyclic voltammetry, revealing the flower-like structures and the electrochemically-interest enhancements they provide, such as increased heterogeneous electron transfer rate coefficient and electroactive area. The self-assembled monolayers of different molecules were optimized with the aid of 22 central composite experiments and a linear calibration curve was obtained between 0.700 and 120 ng mL-1 of PARK7/DJ-1, with a limit of detection of 0.207 ng mL-1. The data confirms that the addition of Au microflowers enhanced the electrochemical signal of the device, as well as allowed for the determination of an early stage Parkinson's disease biomarker with appreciable analytical performance.

From small to tall: breed-varied household pet dogs can be trained to detect Parkinson's Disease

Parkinson's Disease (PD) is a clinically diagnosed disease that carries a reported misdiagnosis rate of 10-20%. Recent scientific discoveries have provided evidence of volatile organic compounds in sebum that are unique to patients with PD. The primary objective of this study was to determine if companion dogs could be trained to distinguish between sebum samples provided by PD-positive patients and PD-negative human controls. This was a randomized, handler-blind, controlled study. Twenty-three canines of varying breeds, ages, and environmental backgrounds were included. The study period encompassed 200 total working days from 2021 to 2022. Factors investigated included donor gender and levodopa drug affectivity, as well as canine breed, age, and duration of training time. The findings in this study were compiled from data collected during the final two years of a seven-year research program. For this two-year reporting period, when averaged as a group, the 23 dogs were 89% sensitive and 87% specific to olfactory distinction between PD-positive and PD-negative human donor samples. Ten of the twenty-three dogs averaged 90% or higher in both sensitivity and specificity. In 161 separate trials, a dog was presented with both novel PD-positive and PD-negative samples. For these novel exposures, the dogs collectively averaged 86% sensitivity and 89% specificity. PD medication was also investigated and was found to have no discernible impact on canine sensitivity or specificity results. Study findings support the application of companion dogs, trained with force-free, reward-based methodologies, for the detection of PD-positive and PD-negative samples under controlled conditions.

Transcriptional pathobiology and multi-omics predictors for Parkinson's disease

Early diagnosis and biomarker discovery to bolster the therapeutic pipeline for Parkinson's disease (PD) are urgently needed. In this study, we leverage the large-scale whole-blood total RNA-seq dataset from the Accelerating Medicine Partnership in Parkinson's Disease (AMP PD) program to identify PD-associated RNAs, including both known genes and novel circular RNAs (circRNA) and enhancer RNAs (eRNAs). There were 1,111 significant marker RNAs, including 491 genes, 599 eRNAs, and 21 circRNAs, that were first discovered in the PPMI cohort (FDR < 0.05) and confirmed in the PDBP/BioFIND cohorts (nominal p < 0.05). Functional enrichment analysis showed that the PD-associated genes are involved in neutrophil activation and degranulation, as well as the TNF-alpha signaling pathway. We further compare the PD-associated genes in blood with those in post-mortem brain dopamine neurons in our BRAINcode cohort. 44 genes show significant changes with the same direction in both PD brain neurons and PD blood, including neuroinflammation-associated genes IKBIP, CXCR2, and NFKBIB. Finally, we built a novel multi-omics machine learning model to predict PD diagnosis with high performance (AUC = 0.89), which was superior to previous studies and might aid the decision-making for PD diagnosis in clinical practice. In summary, this study delineates a wide spectrum of the known and novel RNAs linked to PD and are detectable in circulating blood cells in a harmonized, large-scale dataset. It provides a generally useful computational framework for further biomarker development and early disease prediction.

A review on the new age methodologies for early detection of Alzheimer's and Parkinson's disease

BACKGROUNDS

Neurodegenerative diseases (NDDs) such as Alzheimer's (AD) and Parkinson's (PD) are often diagnosed late, impeding effective treatment; therefore, early detection is imperative. Modern methodologies can serve a pivotal role in fulfilling the crucial need for timely detection and intervention in this context.

OBJECTIVES

Evaluate early detection's significance and summarize key technologies (biomarkers, neuroimaging, AI/ML, genetics, digital health) for enhanced diagnostic strategies in AD and PD.

METHODS

This study employs a focused descriptive review approach, encompassing analysis of peer-reviewed articles and clinical trials from existing literature, to provide a nuanced exploration of the subject matter.

FINDINGS

This review underscores the efficacy of non-invasive biomarkers, biosensors and emerging promising technologies for advancing early diagnosis of AD and PD.

CONCLUSION

The landscape of early NDD detection has been reshaped by technology, yet challenges persist, encompassing the domains of validation and ethics. A collaborative effort between medical professionals, researchers and technologists is imperative to effectively address and combat NDDs.

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.

An innovative transportable immune device for the recognition of α-synuclein using KCC-1-nPr-CS2 modified silver nano-ink: integration of pen-on-paper technology with biosensing toward early-stage diagnosis of Parkinson's disease

Parkinson's disease (PD), the second most frequent neurodegenerative illness, is a neurological ailment that produces unintentional or uncontrolled body movements, which should be diagnosed in its early stages to hinder the progression. Monitoring the concentration of α-synuclein (α-Syn) in body fluids can be one of the most efficient ways for PD early detection. In this work, a paper-based electrochemical immunosensor was designed for α-Syn bio-assay in human plasma samples based on encapsulation of the biotinylated antibody on novel dendritic fibrous nanosilica ((KCC-1-nPr-CS2)-Ab). For this purpose, a three-electrode system was prepared using stabilization of silver nano-ink on photographic paper. Then, the (KCC-1-NH-CS2)-Ab was immobilized on its surface and used to detect the target antigen (α-Syn). After characterization of the prepared substrate by FE-SEM and EDS, the redox behavior of the biosensor was evaluated using chronoamperometry techniques. Under optimal experimental conditions and using a label-free strategy, the engineered immunosensor showed a linear relationship between peak current and antigen concentration in the linear range from 0.002 to 128 ng mL-1 with the lower limit of quantification of 0.002 ng mL-1. Moreover, this work involves unprecedented use of conductive nano-inks for the manufacture of α-Syn immunosensor, which is aided by the use of a mesoporous silicate dendrimer in encapsulating the α-Syn antibody, thus offering a robust and simple point-of-care device for early PD diagnosis. The ability of the proposed platform to detect small amounts of α-Syn offers a promising approach to developing low-cost, sensitive, and transportable biosensors for Parkinson's disease screening in its early stages.

A Comprehensive Review of the Role of Biomarkers in Early Diagnosis of Parkinson's Disease

Parkinson's disease (PD) is a complex neurological, degenerative clinical condition depicted by the advancing loss of dopaminergic neurons in the substantia nigra pars compacta, which manifests itself as a myriad of sensorimotor and non-motor signs in patients. The disease occurs due to the reduced levels of the neurotransmitter dopamine in the brain, which is primarily associated with functional characteristics regarding mobility and cognition. The basal ganglion is mainly involved in the generation of cognitive functions and therefore is the most significantly associated area in PD. Since the classical diagnosis and assessment of PD depends majorly on the appearance of motor characteristics, which only arise when ~60-80% of the dopamine neuronal cell death has already occurred, it is imperative we focus on identifying biomarkers that can help us assess and diagnose PD in the earlier stages of disease progression, thus providing a better prognosis for the patients. This review article will focus on the different biomarkers that are currently available and in use, divided under the headings of clinical, biological, imaging, and genetic biomarkers, and assess their specificity and sensitivity toward providing an early assessment of Parkinson's for the patients and the future of preclinical diagnostics using molecular biomarkers. PD affects over 1% of the population worldwide and only ranks second to Alzheimer's disease in the context of its incidence and consequent socioeconomic burden. While recent breakthroughs in biomarkers have dramatically improved patients' odds of survival and prognosis, it still remains primarily a symptomatic diagnostic tool. It is an area of research that requires to focus on creating more advanced approaches toward diagnosing PD early, involving clinical diagnostics, neuroimaging technology, and molecular biology collaborations to provide the highest degree of care and quality of life that a Parkinson's patient deserves.

Analysis of ADORA2A, MTA1, PTGDS, PTGS2, NSF, and HNMT Gene Expression Levels in Peripheral Blood of Patients with Early Stages of Parkinson's Disease

Parkinson's disease (PD) is a common chronic, age-related neurodegenerative disease. This disease is characterized by a long prodromal period. In this context, it is important to search for the genes and mechanisms that are involved in the development of the pathological process in the earliest stages of the disease. Published data suggest that blood cells, particularly lymphocytes, may be a model for studying the processes that occur in the brain in PD. Thus, in the present work, we performed an analysis of changes in the expression of the genes ADORA2A, MTA1, PTGDS, PTGS2, NSF, and HNMT in the peripheral blood of patients with early stages of PD (stages 1 and 2 of the Hoehn-Yahr scale). We found significant and PD-specific expression changes of four genes, i.e., MTA1, PTGS2, NSF, and HNMT, in the peripheral blood of patients with early stages of PD. These genes may be associated with PD pathogenesis in the early clinical stages and can be considered as potential candidate genes for this disease. Altered expression of the ADORA2A gene in treated PD patients may indicate that this gene is involved in processes affected by antiparkinsonian therapy.

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

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

NLRP3 Inflammasome-Mediated Neuroinflammation and Related Mitochondrial Impairment in Parkinson's Disease

Parkinson's disease (PD) is a common neurodegenerative disorder caused by the loss of dopamine neurons in the substantia nigra and the formation of Lewy bodies, which are mainly composed of alpha-synuclein fibrils. Alpha-synuclein plays a vital role in the neuroinflammation mediated by the nucleotide-binding oligomerization domain-, leucine-rich repeat-, and pyrin domain-containing protein 3 (NLRP3) inflammasome in PD. A better understanding of the NLRP3 inflammasome-mediated neuroinflammation and the related mitochondrial impairment during PD progression may facilitate the development of promising therapies for PD. This review focuses on the molecular mechanisms underlying NLRP3 inflammasome activation, comprising priming and protein complex assembly, as well as the role of mitochondrial impairment and its subsequent inflammatory effects on the progression of neurodegeneration in PD. In addition, the therapeutic strategies targeting the NLRP3 inflammasome for PD treatment are discussed, including the inhibitors of NLRP3 inflammatory pathways, mitochondria-focused treatments, microRNAs, and other therapeutic compounds.

Biomarkers: Role and Scope in Neurological Disorders

Neurological disorders pose a great threat to social health and are a major cause for mortality and morbidity. Effective drug development complemented with the improved drug therapy has made considerable progress towards easing symptoms associated with neurological illnesses, yet poor diagnosis and imprecise understanding of these disorders has led to imperfect treatment options. The scenario is complicated by the inability to extrapolate results of cell culture studies and transgenic models to clinical applications which has stagnated the process of improving drug therapy. In this context, the development of biomarkers has been viewed as beneficial to easing various pathological complications. A biomarker is measured and evaluated in order to gauge the physiological process or a pathological progression of a disease and such a marker can also indicate the clinical or pharmacological response to a therapeutic intervention. The development and identification of biomarkers for neurological disorders involves several issues including the complexity of the brain, unresolved discrepant data from experimental and clinical studies, poor clinical diagnostics, lack of functional endpoints, and high cost and complexity of techniques yet research in the area of biomarkers is highly desired. The present work describes existing biomarkers for various neurological disorders, provides support for the idea that biomarker development may ease our understanding underlying pathophysiology of these disorders and help to design and explore therapeutic targets for effective intervention.

Searching for Biomarkers in the Blood of Patients at Risk of Developing Parkinson's Disease at the Prodromal Stage

Parkinson's disease (PD) is diagnosed many years after its onset, under a significant degradation of the nigrostriatal dopaminergic system, responsible for the regulation of motor function. This explains the low effectiveness of the treatment of patients. Therefore, one of the highest priorities in neurology is the development of the early (preclinical) diagnosis of PD. The aim of this study was to search for changes in the blood of patients at risk of developing PD, which are considered potential diagnostic biomarkers. Out of 1835 patients, 26 patients were included in the risk group and 20 patients in the control group. The primary criteria for inclusion in a risk group were the impairment of sleep behavior disorder and sense of smell, and the secondary criteria were neurological and mental disorders. In patients at risk and in controls, the composition of plasma and the expression of genes of interest in lymphocytes were assessed by 27 indicators. The main changes that we found in plasma include a decrease in the concentrations of l-3,4-dihydroxyphenylalanine (L-DOPA) and urates, as well as the expressions of some types of microRNA, and an increase in the total oxidative status. In turn, in the lymphocytes of patients at risk, an increase in the expression of the DA D3 receptor gene and the lymphocyte activation gene 3 (LAG3), as well as a decrease in the expression of the Protein deglycase DJ-1 gene (PARK7), were observed. The blood changes we found in patients at risk are considered candidates for diagnostic biomarkers at the prodromal stage of PD.

Modulation of Small RNA Signatures by Astrocytes on Early Neurodegeneration Stages; Implications for Biomarker Discovery

Diagnosis of neurodegenerative disease (NDD) is complex, therefore simpler, less invasive, more accurate biomarkers are needed. small non-coding RNA (sncRNA) dysregulates in NDDs and sncRNA signatures have been explored for the diagnosis of NDDs, however, the performance of previous biomarkers is still better. Astrocyte dysfunction promotes neurodegeneration and thus derived scnRNA signatures could provide a more precise way to identify of changes related to NDD course and pathogenesis, and it could be useful for the dissection of mechanistic insights operating in NDD. Often sncRNA are transported outside the cell by the action of secreted particles such as extracellular vesicles (EV), which protect sncRNA from degradation. Furthermore, EV associated sncRNA can cross the BBB to be found in easier to obtain peripheral samples, EVs also inherit cell-specific surface markers that can be used for the identification of Astrocyte Derived Extracellular Vesicles (ADEVs) in a peripheral sample. By the study of the sncRNA transported in ADEVs it is possible to identify astrocyte specific sncRNA signatures that could show astrocyte dysfunction in a more simpler manner than previous methods. However, sncRNA signatures in ADEV are not a copy of intracellular transcriptome and methodological aspects such as the yield of sncRNA produced in ADEV or the variable amount of ADEV captured after separation protocols must be considered. Here we review the role as signaling molecules of ADEV derived sncRNA dysregulated in conditions associated with risk of neurodegeneration, providing an explanation of why to choose ADEV for the identification of astrocyte-specific transcriptome. Finally, we discuss possible limitations of this approach and the need to improve the detection limits of sncRNA for the use of ADEV derived sncRNA signatures.

Stacked Model-Based Classification of Parkinson’s Disease Patients Using Imaging Biomarker Data

Parkinson’s disease (PSD) is a neurological disorder of the brain where nigrostriatal integrity functions lead to motor and non-motor-based symptoms. Doctors can assess the patient based on the patient’s history and symptoms; however, the symptoms are similar in various neurodegenerative diseases, such as progressive supranuclear palsy (PSP), multiple system atrophy—parkinsonian type (MSA), essential tremor, and Parkinson’s tremor. Thus, sometimes it is difficult to identify a patient’s disease based on his or her symptoms. To address the issue, we have used neuroimaging biomarkers to analyze dopamine deficiency in the brains of subjects. We generated the different patterns of dopamine levels inside the brain, which identified the severity of the disease and helped us to measure the disease progression of the patients. For the classification of the subjects, we used machine learning (ML) algorithms for a multivariate classification of the subjects using neuroimaging biomarkers data. In this paper, we propose a stacked machine learning (ML)-based classification model to identify the HC and PSD subjects. In this stacked model, meta learners can learn and combine the predictions from various ML algorithms, such as K-nearest neighbor (KNN), random forest algorithm (RFA), and Gaussian naive Bayes (GANB) to achieve a high performance model. The proposed model showed 92.5% accuracy, outperforming traditional schemes.

Biosensor approaches on the diagnosis of neurodegenerative diseases: Sensing the past to the future

Early diagnosis of neurodegeneration-oriented diseases that develop with the aging world is essential for improving the patient's living conditions as well as the treatment of the disease. Alzheimer's and Parkinson's diseases are prominent examples of neurodegeneration characterized by dementia leading to the death of nerve cells. The clinical diagnosis of these diseases only after the symptoms appear, delays the treatment process. Detection of biomarkers, which are distinctive molecules in biological fluids, involved in neurodegeneration processes, has the potential to allow early diagnosis of neurodegenerative diseases. Studies on biosensors, whose main responsibility is to detect the target analyte with high specificity, has gained momentum in recent years with the aim of high detection of potential biomarkers of neurodegeneration process. This study aims to provide an overview of neuro-biosensors developed on the basis of biomarkers identified in biological fluids for the diagnosis of neurodegenerative diseases such as Alzheimer's disease (AD), and Parkinson's disease (PD), and to provide an overview of the urgent needs in this field, emphasizing the importance of early diagnosis in the general lines of the neurodegeneration pathway. In this review, biosensor systems developed for the detection of biomarkers of neurodegenerative diseases, especially in the last 5 years, are discussed.

Proton Magnetic Resonance Spectroscopy for Diagnosis of Non-Motor Symptoms in Parkinson's Disease

BACKGROUND

The current diagnosis of Parkinson's disease (PD) is mainly based on the typical clinical manifestations. However, 60% dopaminergic neurons have died when the typical clinical manifestations occur. Predictive neurobiomarkers may help identify those PD patients having non-motor disorders or in different stage and achieving the aim of early diagnosis. Up to date, few if any neuroimaging techniques have been described useful for non-movement disorders diagnosis in PD patients. Here, we investigated the alteration of metabolites in PD patients in different stage of PD and non-motor symptoms including sleep, gastrointestinal and cognitive dysfunction, by using the 1H-MRS.

METHODS

A total of 48 subjects were included between 2017 and 2019: 37 PD (15 men, age 47-82 years) and 11 healthy people (8 men, age 49-74 years). All participants underwent MRI and multi-voxel ¹H-MRS examination within 3 days in admission. Six kinds of metabolites, such as creatine (Cr), N-acetyl aspartate/creatine (NAA/Cr), N-acetyl aspartate/choline (NAA/Cho), choline/creatine (Cho/Cr), lipid/creatine (LL/Cr), and myo-Inositol/creatine ratio (mI/Cr) were tested among the PD group and the control groups. Statistical analyses and correlation analyses were performed by using SPSS. The p < 0.05 was considered statistically significant.

RESULTS

Compared late PD group with a control group or early group, higher Cr ratio and lower NAA/Cr ratio were observed in the late PD group (p < 0.05). The mI/Cr in the late PD group was also lower than that in the early PD group (p < 0.05). Regarding the relationship between metabolites and NMS, Cho/Cr was higher in the sleep disorder group, whereas mI/Cr was lower in the gastrointestinal dysfunction group in comparison with the non-symptom groups. Moreover, Cr, Cho/Cr, mI/Cr, and LL/Cr were identified to have higher concentrations in the cognitive group in thalamus.

CONCLUSIONS

Proton magnetic resonance spectroscopy is an advanced tool to quantify the metabolic changes in PD. Three biomarkers (Cr, NAA/Cr, and mI/Cr) were detected in the late stage of PD, suggesting that these markers might be potential to imply the progression of PD. In addition, subgroups analysis showed that MRS of thalamus is a sensitive region for the detection of cognitive decline in PD, and the alteration of neurochemicals (involving Cr, Cho, mI, and LL) may be promising biomarkers to predict cognitive decline in PD.

Mitochondrial Defects in Fibroblasts of Pathogenic MAPT Patients

Mutations in MAPT gene cause multiple neurological disorders, including frontal temporal lobar degeneration and parkinsonism. Increasing evidence indicates impaired mitochondrial homeostasis and mitophagy in patients and disease models of pathogenic MAPT. Here, using MAPT patients' fibroblasts as a model, we report that disease-causing MAPT mutations compromise early events of mitophagy. By employing biochemical and mitochondrial assays we discover that upon mitochondrial depolarization, the recruitment of LRRK2 and Parkin to mitochondria and degradation of the outer mitochondrial membrane protein Miro1 are disrupted. Using high resolution electron microscopy, we reveal that the contact of mitochondrial membranes with ER and cytoskeleton tracks is dissociated following mitochondrial damage. This membrane dissociation is blocked by a pathogenic MAPT mutation. Furthermore, we provide evidence showing that tau protein, which is encoded by MAPT gene, interacts with Miro1 protein, and this interaction is abolished by pathogenic MAPT mutations. Lastly, treating fibroblasts of a MAPT patient with a small molecule promotes Miro1 degradation following depolarization. Altogether, our results show molecular defects in a peripheral tissue of patients and suggest that targeting mitochondrial quality control may have a broad application for future therapeutic intervention.

Early disease biomarkers can be found using animal models urine proteomics

INTRODUCTION

Early disease detection is a prerequisite for early intervention. Urine is not subjected to homeostatic control, and therefore, it accumulates very early changes associated with disease processes, some of which may be used as biomarkers. Animal models must be used to identify urinary changes associated with very early stages of diseases to avoid potential interfering factors and obtain urine samples at a sufficiently early time point before pathological or clinical manifestations occur.

AREAS COVERED

We reviewed recent (from 2009-2020) urine proteome studies using animal models of many diseases. We focused on early changes in urine proteome of animal models, particularly changes occurring prior to alterations in blood tests, light microscopy observations and clinical manifestations. Additional studies relevant to the topic were also extracted from the references of the cited papers. Changes in the urine proteome at different disease stages and the ability of the urine proteome to differentiate among different animal models are also discussed in this review.

EXPERT COMMENTARY

Urine proteomes of animal models may reflect early changes that occur even before changes in blood parameters, light microscopy observations and clinical manifestations, suggesting the potential use of urinary biomarkers for the very early detection of human diseases.

Connectivity and Functionality of the Globus Pallidus Externa Under Normal Conditions and Parkinson's Disease

The globus pallidus externa (GPe) functions as a central hub in the basal ganglia for processing motor and non-motor information through the creation of complex connections with the other basal ganglia nuclei and brain regions. Recently, with the adoption of sophisticated genetic tools, substantial advances have been made in understanding the distinct molecular, anatomical, electrophysiological, and functional properties of GPe neurons and non-neuronal cells. Impairments in dopamine transmission in the basal ganglia contribute to Parkinson's disease (PD), the most common movement disorder that severely affects the patients' life quality. Altered GPe neuron activity and synaptic connections have also been found in both PD patients and pre-clinical models. In this review, we will summarize the main findings on the composition, connectivity and functionality of different GPe cell populations and the potential GPe-related mechanisms of PD symptoms to better understand the cell type and circuit-specific roles of GPe in both normal and PD conditions.

[Development of early diagnosis of Parkinson's disease based on the search for biomarkers such as premotor symptoms and changes in blood]

OBJECTIVE

To determine changes in the chemical composition of blood plasma in subjects at risk of Parkinson's disease (PD) at the prodromal stage compared with age control.

MATERIAL AND METHODS

Subjects at risk were selected for the presence of characteristic premotor symptoms, including impairments of sleep, olfaction and constipation.The risk group included 12 people, the control group - 8 people.

RESULTS

Among seven catecholamines and their metabolites detected in the blood, only the concentration of L-dioxiphenylalanine (L-DOPA) changed (decreased) in subjects at risk compared with the control. A decrease in the concentration of L-DOPA is considered as a manifestation (marker) of selective degeneration of central and peripheral catecholaminergic neurons in PD. In contrast to L-DOPA, the concentration of seven of the twelve detected sphingomyelins in the blood of the subjects at risk increased. Given that a change in the metabolism of sphingomyelins is associated with processes such as apoptosis, autophagy, and synucleinopathy, an increase in their concentration in the blood of patients at risk is considered as a manifestation of systemic general degeneration of central and peripheral neurons. Finally, in the blood of subjects at risk, we found a trend towards a decrease in the concentration of urates, which are endogenous neuroprotectors.

CONCLUSION

The changes in the level of L-DOPA, sphingmyelins and urates in the blood of subjects at risk may serve as diagnostic markers of PD at the prodromal stage.

A nano-composite based regenerative neuro biosensor sensitive to Parkinsonism-associated protein DJ-1/Park7 in cerebrospinal fluid and saliva

In this study, we developed an electrochemical-based single-use neurobiosensor based on multiwalled carbon nanotube (MWCNT)-gold nanoparticle (AuNP) nanocomposite doped, 11-amino-1-undecanethiol (11-AUT)-modified polyethylene terephthalate coated indium tin oxide (ITO-PET) electrodes. This electrode was used for the sensitive determination of DJ-1, a protein responsible for mitochondrial dysfunction in Parkinson's disease (PD) with the task of eliminating oxidative stress. The design strategy and analytical studies for the neurobiosensor were monitored with electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and single frequency impedance (SFI) techniques. The selective determination range for DJ-1 of the developed neurobiosensor system is 4.7-4700 fg mL^-1 in accordance with the charge transfer resistance (Rct) associated with a limit of detection of 0.5 fg mL^-1. Since changes in the expression of DJ-1 protein is particularly important in cerebrospinal fluid (CSF) and saliva, the ability of the developed neurobiosensor system to detect the DJ-1 protein in these media was tested by the standard addition method. The statistical results show that the biosensor decorated with MWCNT-AuNP-AUT may be recommended for the selective determination of DJ-1 protein.

Cartesian genetic programming for diagnosis of Parkinson disease through handwriting analysis: Performance vs. interpretability issues

In the last decades, early disease identification through non-invasive and automatic methodologies has gathered increasing interest from the scientific community. Among others, Parkinson's disease (PD) has received special attention in that it is a severe and progressive neuro-degenerative disease. As a consequence, early diagnosis would provide more effective and prompt care strategies, that cloud successfully influence patients' life expectancy. However, the most performing systems implement the so called black-box approach, which do not provide explicit rules to reach a decision. This lack of interpretability, has hampered the acceptance of those systems by clinicians and their deployment on the field. In this context, we perform a thorough comparison of different machine learning (ML) techniques, whose classification results are characterized by different levels of interpretability. Such techniques were applied for automatically identify PD patients through the analysis of handwriting and drawing samples. Results analysis shows that white-box approaches, such as Cartesian Genetic Programming and Decision Tree, allow to reach a twofold goal: support the diagnosis of PD and obtain explicit classification models, on which only a subset of features (related to specific tasks) were identified and exploited for classification. Obtained classification models provide important insights for the design of non-invasive, inexpensive and easy to administer diagnostic protocols. Comparison of different ML approaches (in terms of both accuracy and interpretability) has been performed on the features extracted from the handwriting and drawing samples included in the publicly available PaHaW and NewHandPD datasets. The experimental findings show that the Cartesian Genetic Programming outperforms the white-box methods in accuracy and the black-box ones in interpretability.

Multimodal analysis of gene expression from postmortem brains and blood identifies synaptic vesicle trafficking genes to be associated with Parkinson's disease

OBJECTIVE

We aimed to identify key susceptibility gene targets in multiple datasets generated from postmortem brains and blood of Parkinson's disease (PD) patients and healthy controls (HC).

METHODS

We performed a multitiered analysis to integrate the gene expression data using multiple-gene chips from 244 human postmortem tissues. We identified hub node genes in the highly PD-related consensus module by constructing protein-protein interaction (PPI) networks. Next, we validated the top four interacting genes in 238 subjects (90 sporadic PD, 125 HC and 23 Parkinson's Plus Syndrome (PPS)). Utilizing multinomial logistic regression analysis (MLRA) and receiver operating characteristic (ROC), we analyzed the risk factors and diagnostic power for discriminating PD from HC and PPS.

RESULTS

We identified 1333 genes that were significantly different between PD and HCs based on seven microarray datasets. The identified MEturquoise module is related to synaptic vesicle trafficking (SVT) dysfunction in PD (P < 0.05), and PPI analysis revealed that SVT genes PPP2CA, SYNJ1, NSF and PPP3CB were the top four hub node genes in MEturquoise (P < 0.001). The levels of these four genes in PD postmortem brains were lower than those in HC brains. We found lower blood levels of PPP2CA, SYNJ1 and NSF in PD compared with HC, and lower SYNJ1 in PD compared with PPS (P < 0.05). SYNJ1, negatively correlated to PD severity, displayed an excellent power to discriminating PD from HC and PPS.

CONCLUSIONS

This study highlights that SVT genes, especially SYNJ1, may be promising markers in discriminating PD from HCs and PPS.

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.

Identification of biomarkers for early diagnosis of Parkinson's disease by multi-omics joint analysis

Objective

The purpose of this study is to identify the biomarkers for early diagnosis of Parkinson's disease (PD) by multi-omics joint analysis, so as to identify the biomarkers for early diagnosis of PD, and to help clinicians make early diagnosis and treatment.

Methods

In this study, mice are taken as the study subjects. The model of PD mice is established, and then lymphocyte, striatum, substantia nigra protein and proteolysis are extracted. After that, the experiments of protein imprinting and 4¹⁸O labeling are carried out. Mass Spectrometry (MS) analysis technology is mainly used to study proteomics and to analyze the quantitative and qualitative situation of differential proteins in striatum, substantia nigra protein and lymphocyte. By this method, biomarkers for early diagnosis of PD are analyzed and identified.

Results

The biomarkers of Parkinson's early onset are related to the same quantitative differential expression of lymphocyte, striatum, substantia nigra protein, lymphocyte and substantia nigra.

Conclusion

This experimental method can analyze and identify the biomarkers of early diagnosis of PD, help to explore the pathophysiology and pathogenesis of PD, effectively help clinicians make timely diagnosis in advance, and improve the prevention and treatment effect of the disease.

Parkinson's disease and the non-motor symptoms: hyposmia, weight loss, osteosarcopenia

Non-motor symptoms (NMSs) are common in Parkinson's disease (PD) and can precede, sometimes for several years. NMSs include, other than gastrointestinal symptoms like constipation and dysphagia, also hyposmia, weight loss and osteosarcopenia. These three NMSs seem to be inter-related and affect patients' health and quality of life. Unfortunately, patients with these symptoms usually are not initially seen by a neurologist, and by the time they are consulted, nearly ~ 80% of the dopaminergic neurons in the substantia nigra have died. To date, no guidelines exist for screening, assessment and management of NMSs in general. A better understanding of these specific NMSs, likely in the context of others, will make it possible to approach and optimise the treatment of the motor symptoms thereby enhancing the welfare of PD patients. Identifying the NMSs could be very helpful, and among them, hyposmia, weight loss and osteosarcopenia may play an important role in solving the limitations in the diagnosis of PD. A strict collaboration between general practitioners, clinicians, geriatricians and neurologists can be one approach towards the diagnosis of pre-PD. Waiting until the motor symptoms develop and the patient is finally visited by the neurologist could be too late, considering the catastrophic prognosis of the disease.

Development of early diagnosis of Parkinson's disease: Illusion or reality?

The fight against neurodegenerative diseases, Alzheimer disease and Parkinson's disease (PD), is a challenge of the 21st century. The low efficacy of treating patients is due to the late diagnosis and start of therapy, after the degeneration of most specific neurons and depletion of neuroplasticity. It is believed that the development of early diagnosis (ED) and preventive treatment will delay the onset of specific symptoms. This review evaluates methodologies for developing ED of PD. Since PD is a systemic disease, and the degeneration of certain neurons precedes that of nigrostriatal dopaminergic neurons that control motor function, the current methodology is based on searching biomarkers, such as premotor symptoms and changes in body fluids (BF) in patients. However, all attempts to develop ED were unsuccessful. Therefore, it is proposed to enhance the current methodology by (i) selecting among biomarkers found in BF in patients at the clinical stage those that are characteristics of animal models of the preclinical stage, (ii) searching biomarkers in BF in subjects at the prodromal stage, selected by detecting premotor symptoms and failure of the nigrostriatal dopaminergic system. Moreover, a new methodology was proposed for the development of ED of PD using a provocative test, which is successfully used in internal medicine.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest-based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Parkinson's Disease Exhibits Amplified Intermuscular Coherence During Dynamic Voluntary Action

Parkinson's disease (PD) is typically diagnosed and evaluated on the basis of overt motor dysfunction, however, subtle changes in the frequency spectrum of neural drive to muscles have been reported as well. During dynamic actions, coactive muscles of healthy adults often share a common source of 6-15 Hz (alpha-band) neural drive, creating synchronous alpha-band activity in their EMG signals. Individuals with PD commonly exhibit kinetic action tremor at similar frequencies, but the potential relationship between the intermuscular alpha-band neural drive seen in healthy adults and the action tremor associated with PD is not well-understood. A close relationship is most tenable during voluntary dynamic tasks where alpha-band neural drive is strongest in healthy adults, and where neural circuits affected by PD are most engaged. In this study, we characterized the frequency spectrum of EMG synchronization (intermuscular coherence) in 16 participants with PD and 15 age-matched controls during two dynamic motor tasks: (1) rotation of a dial between the thumb and index finger, and (2) dynamic scaling of isometric precision pinch force. These tasks produce different profiles of coherence between the first dorsal interosseous and abductor pollicis brevis muscles. We sought to determine if alpha-band intermuscular coherence would be amplified in participants with PD relative to controls, if such differences would be task-specific, and if they would correlate with symptom severity. We found that relative to controls, the PD group displayed amplified, but similarly task-dependent, coherence in the alpha-band. The magnitude of coherence during the rotation task correlated with overall symptom severity as per the UPDRS rating scale. Finally, we explored the potential for our coherence measures, with no additional information, to discriminate individuals with PD from controls. The area under the Receiver Operating Characteristic curve (AUC) indicated a clear separation between groups (AUC = 0.96), even though participants with PD were on their typical medication and displayed only mild-moderate symptoms. We conclude that a task-dependent, intermuscular neural drive within the alpha-band is amplified in PD. Its quantification via intermuscular coherence analysis may provide a useful tool for detecting the presence of PD, or assessing its progression.

Does retina play a role in Parkinson's Disease?

Visual disorder is one of the non-motor symptoms found in Parkinson's disease (PD). It can be easily identified in the early stages even before the spread of pathological conditions to the brain parts. Studies have revealed that loss of dopamine (DA) cells in retinal layers is a prime cause for both retinal disturbance and pathological conditions of PD. This reduction of DA in retina is due to the aggregation of phosphorylated α-synuclein (aSyn) in the intra-retinal region, which eventually results in visual impairment in PD. Until now, very limited studies have been focused on the mechanism of aSyn influence and DA depletion as a cause for both retinal layer dysfunction and PD. Thus, more research is warranted to provide the missing connection between the exact role of DA and aSyn as a risk factor for visual problems in PD. Hence, the current review's focus is on the function and effects of DA degeneration in retinal cells of PD. Further, we suggest that iron plays a major role in regulating the aggregation of aSyn in the DA cells of retina and brain in PD. The study finds that the unidentified pathophysiological role of retinal degeneration in PD is an essential biomarker that needs further investigation to use it as a novel therapy in treating retinal dysfunctions in PD.

Application of Lectin Microarrays for Biomarker Discovery

Many proteins in living organisms are glycosylated. As their glycan patterns exhibit protein-, cell-, and tissue-specific heterogeneity, changes in the glycosylation levels could serve as useful indicators of various pathological and physiological states. Thus, the identification of glycoprotein biomarkers from specific changes in the glycan profiles of glycoproteins is a trending field. Lectin microarrays provide a new glycan analysis platform, which enables rapid and sensitive analysis of complex glycans without requiring the release of glycans from the protein. Recent developments in lectin microarray technology enable high-throughput analysis of glycans in complex biological samples. In this review, we will discuss the basic concepts and recent progress in lectin microarray technology, the application of lectin microarrays in biomarker discovery, and the challenges and future development of this technology. Given the tremendous technical advancements that have been made, lectin microarrays will become an indispensable tool for the discovery of glycoprotein biomarkers.

Miro1 Marks Parkinson's Disease Subset and Miro1 Reducer Rescues Neuron Loss in Parkinson's Models

The identification of molecular targets and pharmacodynamic markers for Parkinson's disease (PD) will empower more effective clinical management and experimental therapies. Miro1 is localized on the mitochondrial surface and mediates mitochondrial motility. Miro1 is removed from depolarized mitochondria to facilitate their clearance via mitophagy. Here, we explore the clinical utility of Miro1 for detecting PD and for gauging potential treatments. We measure the Miro1 response to mitochondrial depolarization using biochemical assays in skin fibroblasts from a broad spectrum of PD patients and discover that more than 94% of the patients' fibroblast cell lines fail to remove Miro1 following depolarization. We identify a small molecule that can repair this defect of Miro1 in PD fibroblasts. Treating patient-derived neurons and fly models with this compound rescues the locomotor deficits and dopaminergic neurodegeneration. Our results indicate that tracking this Miro1 marker and engaging in Miro1-based therapies could open new avenues to personalized medicine.

Biomarkers for Parkinson's Disease: How Good Are They?

Parkinson's disease (PD) is a complex neurodegenerative disorder with no cure in sight. Clinical challenges of the disease include the inability to make a definitive diagnosis at the early stages and difficulties in predicting the disease progression. The unmet demand to identify reliable biomarkers for early diagnosis and management of the disease course of PD has attracted a lot of attention. However, only a few reported candidate biomarkers have been tried in clinical practice at the present time. Studies on PD biomarkers have often overemphasized the discovery of novel identity, whereas efforts to further evaluate such candidates are rare. Therefore, we update the new development of biomarker discovery in PD and discuss the standard process in the evaluation and assessment of the diagnostic or prognostic value of the identified potential PD biomarkers in this review article. Recent developments in combined biomarkers and the current status of clinical trials of biomarkers as outcome measures are also discussed. We believe that the combination of different biomarkers might enhance the specificity and sensitivity over a single measure that might not be sufficient for such a multiplex disease.

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.

Cerebrospinal fluid levels of alpha-synuclein measured using a poly-glutamic acid-modified gold nanoparticle-doped disposable neuro-biosensor system

A gold nanoparticle and polyglutamic acid-modified ITO-based biosensor system to detect alpha-synuclein, an important biomarker of Parkinson's disease.

Physiological clearance of tau in the periphery and its therapeutic potential for tauopathies

Accumulation of pathological tau is the hallmark of Alzheimer's disease and other tauopathies and is closely correlated with cognitive decline. Clearance of pathological tau from the brain is a major therapeutic strategy for tauopathies. The physiological capacity of the periphery to clear brain-derived tau and its therapeutic potential remain largely unknown. Here, we found that cisterna magna injected ¹³¹I-labelled synthetic tau dynamically effluxed from the brain and was mainly cleared from the kidney, blood, and liver in mice; we also found that plasma tau levels in inferior vena cava were lower than those in femoral artery in humans. These findings suggest that tau proteins can efflux out of the brain and be cleared in the periphery under physiological conditions. Next, we showed that lowering blood tau levels via peritoneal dialysis could reduce interstitial fluid (ISF) tau levels in the brain, and tau levels in the blood and ISF were dynamically correlated; furthermore, tau efflux from the brain was accelerated after the addition of another set of peripheral system in a parabiosis model. Finally, we established parabiosis mouse models using tau transgenic mice and their wild-type littermates and found that brain tau levels and related pathologies in parabiotic transgenic mice were significantly reduced after parabiosis, suggesting that chronic enhancement of peripheral tau clearance alleviates pathological tau accumulation and neurodegeneration in the brain. Our study provides the first evidence of physiological clearance of brain-derived pathological tau in the periphery, suggesting that enhancing peripheral tau clearance is a potential therapeutic strategy for tauopathies.