Biomarker For Parkinson's Disease Research Articles

Detecting Misfolded α-Synuclein in Blood Years before the Diagnosis of Parkinson's Disease.

Identifying individuals with Parkinson's disease (PD) already in the prodromal phase of the disease has become a priority objective for opening a window for early disease-modifying therapies. The aim was to evaluate a blood-based α-synuclein seed amplification assay (α-syn SAA) as a novel biomarker for diagnosing PD in the prodromal phase. In the TREND study (University of Tuebingen) biennial blood samples of n = 1201 individuals with/without increased risk for PD were taken prospectively over 4 to 10 years. We retrospectively analyzed blood samples of 12 participants later diagnosed with PD during the study to detect and amplify pathological α-syn conformers derived from neuronal extracellular vesicles using (1) immunoblot analyses with an antibody against these conformers and (2) an α-syn-SAA. Additionally, blood samples of n = 13 healthy individuals from the TREND cohort and n = 20 individuals with isolated rapid eye movement sleep behavior disorder (iRBD) from the University Hospital Cologne were analyzed. All individuals with PD showed positive immunoblots and a positive α-syn SAA at the time of diagnosis. Moreover, all PD patients showed a positive α-syn SAA 1 to 10 years before clinical diagnosis. In the iRBD cohort, 30% showed a positive α-syn SAA. All healthy controls had a negative SAA. We here demonstrate the possibility to detect and amplify pathological α-syn conformers in peripheral blood up to 10 years before the clinical diagnosis of PD in individuals with and without iRBD. The findings of this study indicate that this blood-based α-syn SAA assay has the potential to serve as a diagnostic biomarker for prodromal PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Diagnosing Parkinson’s disease and monitoring its progression: Biomarkers from combined GC-TOF MS and LC-MS/MS untargeted metabolomics

Parkinson's disease (PD) is a prevalent neurodegenerative disorder with a poorly understood etiology. An accurate diagnosis of idiopathic PD remains challenging as misdiagnosis is common in routine clinical practice. Moreover, current therapeutics focus on symptomatic management rather than curing or slowing down disease progression. Therefore, identification of potential PD biomarkers and providing a better understanding of the underlying disease pathophysiology are urgent. Herein, hydrophilic interaction liquid chromatography–mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-TOF MS) based metabolomics approaches were used to profile the serum metabolome of 50 patients with different stages of idiopathic PD (early, mid and advanced) and 45 age-matched controls. Levels of 57 metabolites including cysteine-S-sulfate and N-acetyl tryptophan were significantly higher in patients with PD compared to controls, with lower amounts of additional 51 metabolites including vanillic acid, and N-acetylaspartic acid. Xanthines, including caffeine and its downstream metabolites, were lowered in patients with PD relative to controls indicating a potential role caffeine and its metabolites against neuronal damage. Seven metabolites, namely cysteine-S-sulfate, 1-methylxanthine, vanillic acid, N-acetylaspartic acid, 3-N-acetyl tryptophan, 5-methoxytryptophol, and 13-HODE yielded a ROC curve with a high classification accuracy (AUC 0.977). Comparison between different PD stages showed that cysteine-S-sulfate levels were significantly increasing with the advancement of PD stages while LPI 20:4 was significantly decreasing with disease progression. Our findings provide new biomarker candidates to assist in the diagnosis of PD and monitor its progression. Unusual metabolites like cysteine-S-sulfate might point to therapeutic targets that could enhance the development of novel PD treatments, such as NMDA antagonists.

Microglial Exosomes in Paraquat-Induced Parkinson’s Disease: Neuroprotection and Biomarker Clues

The exact mechanisms underlying the initiation and exacerbation of Parkinson's disease (PD) by paraquat remain unclear. We have revealed that exosomes mediate neurotoxicity induced by low dose paraquat exposure by transmitting intercellular signaling. Exposure to 40 μM paraquat promoted exosome release from mouse microglia cells (BV2) in vitro. Paraquat exposure at 100 μM caused degeneration of mouse dopaminergic MN9D cells and inhibited microglia exosome uptake by fluorescently labeling exosomes. We established an incubation model for exosomes and dopaminergic neuron cells under PQ treatment. The results indicated that microglial exosomes alleviated degeneration, increasing proliferation and PD-related protein expression of dopaminergic neurons; however, paraquat reversed this effect. Then, through exosome high-throughput sequencing and qRT-PCR experiments, miR-92a-3p and miR-24-3p were observed to transfer from exosomes to dopaminergic neurons, inhibited by paraquat. The specificity of miR-92a-3p and miR-24-3p was verified in PD patients exosomes, indicating the potential diagnostic value of the exosomal miRNAs in paraquat-induced PD. These results suggest glia-neuron communication in paraquat-induced neurodegeneration and may identify stable paraquat-mediated PD biomarkers, offering clues for early recognition and prevention of pesticide-induced degenerative diseases.

Surface Modification of Ultrasonic Cavitation by Surfactants Improves Detection Sensitivity of α-Synuclein Amyloid Seeds.

The rapid amplification and sensitive detection of α-synuclein (αSyn) seeds is an efficient approach for the early diagnosis of Parkinson's disease. Ultrasonication stands out as a promising method for the rapid amplification of αSyn seeds because of its robust fibril fragmentation capability. However, ultrasonication also induces the primary nucleation of αSyn monomers, deteriorating the seed detection sensitivity by generating seed-independent fibrils. In this study, we show that an addition of surfactants to the αSyn monomer solution during αSyn seed detection under ultrasonication remarkably improves the detection sensitivity of the αSyn seeds by a factor of 100-1000. Chemical kinetic analysis reveals that these surfactants reduce the rate of primary nucleation while promoting the fragmentation of the αSyn fibrils under ultrasonication. These effects are attributed to the modification of the ultrasonic cavitation surface by the surfactants. Our study enhances the utility of ultrasonication in clinical assays targeting αSyn seeds as the Parkinson's disease biomarker.

Plasma extracellular vesicle synaptic proteins as biomarkers of clinical progression in patients with Parkinson's disease.

Synaptic dysfunction plays a key role in Parkinson's disease (PD), and plasma extracellular vesicle (EV) synaptic proteins are emerging as biomarkers for neurodegenerative diseases. Assessment of plasma EV synaptic proteins for their efficacy as biomarkers in PD and their relationship with disease progression was conducted. In total, 144 participants were enrolled, including 101 people with PD (PwP) and 43 healthy controls (HCs). The changes in plasma EV synaptic protein levels between baseline and 1-year follow-up did not differ significantly in both PwP and HCs. In PwP, the changes in plasma EV synaptic protein levels were significantly associated with the changes in Unified Parkinson's Disease Rating Scale (UPDRS)-II and III scores. Moreover, PwP with elevated levels (first quartile) of any one plasma EV synaptic proteins (synaptosome-associated protein 25, growth-associated protein 43 or synaptotagmin-1) had significantly greater disease progression in UPDRS-II score and the postural instability and gait disturbance subscore in UPDRS-III than did the other PwP after adjustment for age, sex, and disease duration. The promising potential of plasma EV synaptic proteins as clinical biomarkers of disease progression in PD was suggested. However, a longer follow-up period is warranted to confirm their role as prognostic biomarkers.

A systematic review of salivary biomarkers in Parkinson's disease.

The search for reliable and easily accessible biomarkers in Parkinson's disease is receiving a growing emphasis, to detect neurodegeneration from the prodromal phase and to enforce disease-modifying therapies. Despite the need for non-invasively accessible biomarkers, the majority of the studies have pointed to cerebrospinal fluid or peripheral biopsies biomarkers, which require invasive collection procedures. Saliva represents an easily accessible biofluid and an incredibly wide source of molecular biomarkers. In the present study, after presenting the morphological and biological bases for looking at saliva in the search of biomarkers for Parkinson's disease, we systematically reviewed the results achieved so far in the saliva of different cohorts of Parkinson's disease patients. A comprehensive literature search on PubMed and SCOPUS led to the discovery of 289 articles. After screening and exclusion, 34 relevant articles were derived for systematic review. Alpha-synuclein, the histopathological hallmark of Parkinson's disease, has been the most investigated Parkinson's disease biomarker in saliva, with oligomeric alpha-synuclein consistently found increased in Parkinson's disease patients in comparison to healthy controls, while conflicting results have been reported regarding the levels of total alpha-synuclein and phosphorylated alpha-synuclein, and few studies described an increased oligomeric alpha-synuclein/total alpha-synuclein ratio in Parkinson's disease. Beyond alpha-synuclein, other biomarkers targeting different molecular pathways have been explored in the saliva of Parkinson's disease patients: total tau, phosphorylated tau, amyloid-β1-42 (pathological protein aggregation biomarkers); DJ-1, heme-oxygenase-1, metabolites (altered energy homeostasis biomarkers); MAPLC-3beta (aberrant proteostasis biomarker); cortisol, tumor necrosis factor-alpha (inflammation biomarkers); DNA methylation, miRNA (DNA/RNA defects biomarkers); acetylcholinesterase activity (synaptic and neuronal network dysfunction biomarkers); Raman spectra, proteome, and caffeine. Despite a few studies investigating biomarkers targeting molecular pathways different from alpha-synuclein in Parkinson's disease, these results should be replicated and observed in studies on larger cohorts, considering the potential role of these biomarkers in determining the molecular variance among Parkinson's disease subtypes. Although the need for standardization in sample collection and processing, salivary-based biomarkers studies have reported encouraging results, calling for large-scale longitudinal studies and multicentric assessments, given the great molecular potentials and the non-invasive accessibility of saliva.

Metal-enhanced fluorescence biosensor integrated in capillary flow-driven microfluidic cartridge for highly sensitive immunoassays

Point-of-care testing (POCT) for low-concentration protein biomarkers remains challenging due to limitations in biosensor sensitivity and platform integration. This study addresses this gap by presenting a novel approach that integrates a metal-enhanced fluorescence (MEF) biosensor within a capillary flow-driven microfluidic cartridge (CFMC) for the ultrasensitive detection of the Parkinson's disease biomarker, aminoacyl-tRNA synthetase complex interacting multi-functional protein 2 (AIMP-2). Crucial point to this approach is the orientation-controlled immobilization of capture antibody on a nanodimple-structured MEF substrate within the CFMC. This strategy significantly enhances fluorescence signals without quenching, enabling accurate quantification of low-concentration AIMP-2 using a simple digital fluorescence microscope with a light-emitting diode excitation source and a digital camera. The resulting platform exhibits exceptional sensitivity, achieving a limit of detection in the pg/mL range for AIMP-2 in human serum. Additionally, the CFMC design incorporates a capillary-driven passive sample transport mechanism, eliminating the need for external pumps and further simplifying the detection process. Overall, this work demonstrates the successful integration of MEF biosensing with capillary microfluidics for point-of-care applications.

Neuroimaging of Parkinson's disease by quantitative susceptibility mapping

Parkinson's disease (PD) is a common neurodegenerative disease, and apart from a few rare genetic causes, its pathogenesis remains largely unclear. Recent scientific interest has been captured by the involvement of iron biochemistry and the disruption of iron homeostasis, particularly within the brain regions specifically affected in PD. The advent of Quantitative Susceptibility Mapping (QSM) has enabled non-invasive quantification of brain iron in vivo by MRI, which has contributed to the understanding of iron-associated pathogenesis and has the potential for the development of iron-based biomarkers in PD. This review elucidates the biochemical underpinnings of brain iron accumulation, details advancements in iron-sensitive MRI technologies, and discusses the role of QSM as a biomarker of iron deposition in PD. Despite considerable progress, several challenges impede its clinical application after a decade of QSM studies. The initiation of multi-site research is warranted for developing robust, interpretable, and disease-specific biomarkers for monitoring PD disease progression.

Pathogenesis of DJ-1/PARK7-Mediated Parkinson's Disease.

Parkinson's disease (PD) is a common movement disorder associated with the degeneration of dopaminergic neurons in the substantia nigra pars compacta. Mutations in the PD-associated gene PARK7 alter the structure and function of the encoded protein DJ-1, and the resulting autosomal recessively inherited disease increases the risk of developing PD. DJ-1 was first discovered in 1997 as an oncogene and was associated with early-onset PD in 2003. Mutations in DJ-1 account for approximately 1% of all recessively inherited early-onset PD occurrences, and the functions of the protein have been studied extensively. In healthy subjects, DJ-1 acts as an antioxidant and oxidative stress sensor in several neuroprotective mechanisms. It is also involved in mitochondrial homeostasis, regulation of apoptosis, chaperone-mediated autophagy (CMA), and dopamine homeostasis by regulating various signaling pathways, transcription factors, and molecular chaperone functions. While DJ-1 protects neurons against damaging reactive oxygen species, neurotoxins, and mutant α-synuclein, mutations in the protein may lead to inefficient neuroprotection and the progression of PD. As current therapies treat only the symptoms of PD, the development of therapies that directly inhibit oxidative stress-induced neuronal cell death is critical. DJ-1 has been proposed as a potential therapeutic target, while oxidized DJ-1 could operate as a biomarker for PD. In this paper, we review the role of DJ-1 in the pathogenesis of PD by highlighting some of its key neuroprotective functions and the consequences of its dysfunction.

Longitudinal brain structure changes in Parkinson's disease: A replication study.

An existing major challenge in Parkinson's disease (PD) research is the identification of biomarkers of disease progression. While magnetic resonance imaging is a potential source of PD biomarkers, none of the magnetic resonance imaging measures of PD are robust enough to warrant their adoption in clinical research. This study is part of a project that aims to replicate 11 PD studies reviewed in a recent survey (JAMA neurology, 78(10) 2021) to investigate the robustness of PD neuroimaging findings to data and analytical variations. This study attempts to replicate the results in Hanganu et al. (Brain, 137(4) 2014) using data from the Parkinson's Progression Markers Initiative (PPMI). Using 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between structural changes and cognitive decline. We compared our findings to the results in the original study. (1) Similarly to the original study, PD patients with mild cognitive impairment (MCI) exhibited increased cortical thinning over time compared to patients without MCI in the right middle temporal gyrus, insula, and precuneus. (2) The rate of cortical thinning in the left inferior temporal and precentral gyri in PD patients correlated with the change in cognitive performance. (3) There were no group differences in the change of subcortical volumes. (4) We did not find a relationship between the change in subcortical volumes and the change in cognitive performance. Despite important differences in the dataset used in this replication study, and despite differences in sample size, we were able to partially replicate the original results. We produced a publicly available reproducible notebook allowing researchers to further investigate the reproducibility of the results in Hanganu et al. (2014) when more data is added to PPMI.

Integrative analysis of gene expression profiles of substantia nigra identifies potential diagnosis biomarkers in Parkinson's disease

Parkinson's disease (PD) is a progressive neurodegenerative disease whose etiology is attributed to development of Lewy bodies and degeneration of dopaminergic neurons in the substantia nigra (SN). Currently, there are no definitive diagnostic indicators for PD. In this study, we aimed to identify potential diagnostic biomarkers for PD and analyzed the impact of immune cell infiltrations on disease pathogenesis. The PD expression profile data for human SN tissue, GSE7621, GSE20141, GSE20159, GSE20163 and GSE20164 were downloaded from the Gene Expression Omnibus (GEO) database for use in the training model. After normalization and merging, we identified differentially expressed genes (DEGs) using the Robust rank aggregation (RRA) analysis. Simultaneously, DEGs after batch correction were identified. Gene interactions were determined through venn Diagram analysis. Functional analyses and protein–protein interaction (PPI) networks were used to the identify hub genes, which were visualized through Cytoscape. A Lasso Cox regression model was employed to identify the potential diagnostic genes. The GSE20292 dataset was used for validation. The proportion of infiltrating immune cells in the samples were determined via the CIBERSORT method. Sixty-two DEGs were screened in this study. They were found to be enriched in nerve conduction, dopamine (DA) metabolism, and DA biosynthesis Gene Ontology (GO) terms. The PPI network and Lasso Cox regression analysis revealed seven potential diagnostic genes, namely SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1, were subsequently validated in peripheral blood samples obtained from healthy control (HC) and PD patients, as well as in the GSE20292 dataset. The results revealed the exceptional sensitivity and specificity of these genes in PD diagnosis and monitoring. Moreover, PD patients exhibited a higher number of plasma cells, compared to HC individuals. The SLC18A2, TAC1, PCDH8, KIAA0319, PDE6H, AXIN1, and AGTR1 are potential diagnostic biomarkers for PD. Our findings also reveal the essential roles of immune cell infiltration in both disease onset and trajectory.

Altered Outer Retinal Structure, Electrophysiology and Visual Perception in Parkinson's Disease.

Visual biomarkers of Parkinson's disease (PD) are attractive as the retina is an outpouching of the brain. Although inner retinal neurodegeneration in PD is well-established this has overlap with other neurodegenerative diseases and thus outer retinal (photoreceptor) measures warrant further investigation. To examine in a cross-sectional study whether clinically implementable measures targeting outer retinal function and structure can differentiate PD from healthy ageing and whether these are sensitive to intraday levodopa (L-DOPA) dosing. Centre-surround perceptual contrast suppression, macular visual field sensitivity, colour discrimination, light-adapted electroretinography and optical coherence tomography (OCT) were tested in PD participants (n = 16) and controls (n = 21). Electroretinography and OCT were conducted before and after midday L-DOPA in PD participants, or repeated after ∼2 hours in controls. PD participants had decreased center-surround contrast suppression (p < 0.01), reduced macular visual field sensitivity (p < 0.05), color vision impairment (p < 0.01) photoreceptor dysfunction (a-wave, p < 0.01) and photoreceptor neurodegeneration (outer nuclear layer thinning, p < 0.05), relative to controls. Effect size comparison between inner and outer retinal parameters showed that photoreceptor metrics were similarly robust in differentiating the PD group from age-matched controls as inner retinal changes. Electroretinography and OCT were unaffected by L-DOPA treatment or time. We show that outer retinal outcomes of photoreceptoral dysfunction (decreased cone function and impaired color vision) and degeneration (i.e., outer nuclear layer thinning) were equivalent to inner retinal metrics at differentiating PD from healthy age-matched adults. These findings suggest outer retinal metrics may serve as useful biomarkers for PD.

Abnormally low sensorimotor α band nonlinearity serves as an effective EEG biomarker of Parkinson's disease.

Biomarkers obtained from the neurophysiological signals of patients with Parkinson's disease (PD) have objective value in assessing their motor condition for effective diagnosis, monitoring, and clinical intervention. Prominent cortical biomarkers of PD have typically been derived from various β band wave features. This study approached the topic from an alternative perspective and attempted to estimate a recently suggested measure representing α band nonlinear autocorrelative memory from a publicly available EEG dataset that involves 15 patients with earlier-stage PD (dopaminergic medication OFF and ON states) and 16 age-matched healthy controls. The cortical nonlinearity was elevated for the PD ON state compared with the OFF state for bilateral sensorimotor channels C3 and C4 (n = 26; P = 0.003). A similar statistical difference was also identified between PD OFF state and healthy subjects (n = 26; P = 0.049). Analysis over all channels revealed that the α band nonlinearity induced upon medication was constrained to sensorimotor regions. The α nonlinearity measure was compared with a well-accepted cortical biomarker of β-γ phase-amplitude coupling (PAC). They were in moderate negative correlation (r = -0.412; P = 0.036) for only healthy subjects, but not for the patients. The nonlinearity measure was found to be insusceptible to the nonstationary variations within the particular data. Our study provides further evidence that the α band nonlinearity measure can serve as a promising cortical biomarker of PD. The suggested measure can be estimated from a noninvasive low-resolution single scalp EEG channel of patients with relatively early-stage PD, who did not yet need to undergo deep brain stimulation operation.NEW & NOTEWORTHY This study suggests a nonlinearity measure that differentiates Parkinson's disease (PD) dopamine OFF-state scalp EEG data from those of dopamine ON-state patients and healthy subjects. Unlike typical PD cortical biomarkers based on β band activity, this metric shows elevation upon dopaminergic medication in the α band. We provide evidence supporting its potential as an early-stage promising PD biomarker that can be estimated from noninvasive EEG recordings with low resolution and SNR.

Post-translational modification and mitochondrial function in Parkinson's disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease with currently no cure. Most PD cases are sporadic, and about 5-10% of PD cases present a monogenic inheritance pattern. Mutations in more than 20 genes are associated with genetic forms of PD. Mitochondrial dysfunction is considered a prominent player in PD pathogenesis. Post-translational modifications (PTMs) allow rapid switching of protein functions and therefore impact various cellular functions including those related to mitochondria. Among the PD-associated genes, Parkin, PINK1, and LRRK2 encode enzymes that directly involved in catalyzing PTM modifications of target proteins, while others like α-synuclein, FBXO7, HTRA2, VPS35, CHCHD2, and DJ-1, undergo substantial PTM modification, subsequently altering mitochondrial functions. Here, we summarize recent findings on major PTMs associated with PD-related proteins, as enzymes or substrates, that are shown to regulate important mitochondrial functions and discuss their involvement in PD pathogenesis. We will further highlight the significance of PTM-regulated mitochondrial functions in understanding PD etiology. Furthermore, we emphasize the potential for developing important biomarkers for PD through extensive research into PTMs.

Candidate biomarkers of EV-microRNA in detecting REM sleep behavior disorder and Parkinson’s disease

Parkinson’s disease (PD) lacks reliable, non-invasive biomarker tests for early intervention and management. Thus, a minimally invasive test for the early detection and monitoring of PD and REM sleep behavior disorder (iRBD) is a highly unmet need for developing drugs and planning patient care. Extracellular vehicles (EVs) are found in a wide variety of biofluids, including plasma. EV-mediated functional transfer of microRNAs (miRNAs) may be viable candidates as biomarkers for PD and iRBD. Next-generation sequencing (NGS) of EV-derived small RNAs was performed in 60 normal controls, 56 iRBD patients and 53 PD patients to profile small non-coding RNAs (sncRNAs). Moreover, prospective follow-up was performed for these 56 iRBD patients for an average of 3.3 years. Full-scale miRNA profiles of plasma EVs were evaluated by machine-learning methods. After optimizing the library construction method for low RNA inputs (named EVsmall-seq), we built a machine learning algorithm that identified diagnostic miRNA signatures for distinguishing iRBD patients (AUC 0.969) and PD patients (AUC 0.916) from healthy individuals; and PD patients (AUC 0.929) from iRBD patients. We illustrated all the possible expression patterns across healthy-iRBD-PD hierarchy. We also showed 20 examples of miRNAs with consistently increasing or decreasing expression levels from controls to iRBD to PD. In addition, four miRNAs were found to be correlated with iRBD conversion. Distinct characteristics of the miRNA profiles among normal, iRBD and PD samples were discovered, which provides a panel of promising biomarkers for the identification of PD patients and those in the prodromal stage iRBD.

A potential patient stratification biomarker for Parkinson´s disease based on LRRK2 kinase-mediated centrosomal alterations in peripheral blood-derived cells

Parkinson´s disease (PD) is a common neurodegenerative movement disorder and leucine-rich repeat kinase 2 (LRRK2) is a promising therapeutic target for disease intervention. However, the ability to stratify patients who will benefit from such treatment modalities based on shared etiology is critical for the success of disease-modifying therapies. Ciliary and centrosomal alterations are commonly associated with pathogenic LRRK2 kinase activity and can be detected in many cell types. We previously found centrosomal deficits in immortalized lymphocytes from G2019S-LRRK2 PD patients. Here, to investigate whether such deficits may serve as a potential blood biomarker for PD which is susceptible to LRKK2 inhibitor treatment, we characterized patient-derived cells from distinct PD cohorts. We report centrosomal alterations in peripheral cells from a subset of early-stage idiopathic PD patients which is mitigated by LRRK2 kinase inhibition, supporting a role for aberrant LRRK2 activity in idiopathic PD. Centrosomal defects are detected in R1441G-LRRK2 and G2019S-LRRK2 PD patients and in non-manifesting LRRK2 mutation carriers, indicating that they accumulate prior to a clinical PD diagnosis. They are present in immortalized cells as well as in primary lymphocytes from peripheral blood. These findings indicate that analysis of centrosomal defects as a blood-based patient stratification biomarker may help nominate idiopathic PD patients who will benefit from LRRK2-related therapeutics.

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

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

Meta-analysis of the serum/plasma proteome identifies significant associations between COVID-19 with Alzheimer's/Parkinson's diseases.

In recent years, we have seen the widespread devastations and serious health complications manifested by COVID-19 globally. Although we have effectively controlled the pandemic, uncertainties persist regarding its potential long-term effects, including prolonged neurological issues. To gain comprehensive insights, we conducted a meta-analysis of mass spectrometry-based proteomics data retrieved from different studies with a total of 538 COVID-19 patients and 523 healthy controls. The meta-analysis revealed that top-enriched pathways were associated with neurological disorders, including Alzheimer's (AD) and Parkinson's disease (PD). Further analysis confirmed a direct correlation in the expression patterns of 24 proteins involved in Alzheimer's and 23 proteins in Parkinson's disease with COVID-19. Protein-protein interaction network and cluster analysis identified SNCA as a hub protein, a known biomarker for Parkinson's disease, in both AD and PD. To the best of our knowledge, this is the first meta-analysis study providing proteomic profiling evidence linking COVID-19 to neurological complications.

Increased iron in the substantia nigra pars compacta identifies patients with early Parkinson’s disease: A 3T and 7T MRI study

Degeneration in the substantia nigra (SN) pars compacta (SNc) underlies motor symptoms in Parkinson’s disease (PD). Currently, there are no neuroimaging biomarkers that are sufficiently sensitive, specific, reproducible, and accessible for routine diagnosis or staging of PD. Although iron is essential for cellular processes, it also mediates neurodegeneration. MRI can localize and quantify brain iron using magnetic susceptibility, which could potentially provide biomarkers of PD.We measured iron in the SNc, SN pars reticulata (SNr), total SN, and ventral tegmental area (VTA), using quantitative susceptibility mapping (QSM) and R2* relaxometry, in PD patients and age-matched healthy controls (HCs). PD patients, diagnosed within five years of participation and HCs were scanned at 3T (22 PD and 23 HCs) and 7T (17 PD and 21 HCs) MRI. Midbrain nuclei were segmented using a probabilistic subcortical atlas. QSM and R2* values were measured in midbrain subregions. For each measure, groups were contrasted, with Age and Sex as covariates, and receiver operating characteristic (ROC) curve analyses were performed with repeated k-fold cross-validation to test the potential of our measures to classify PD patients and HCs. Statistical differences of area under the curves (AUCs) were compared using the Hanley-MacNeil method (QSM versus R2*; 3T versus 7T MRI).PD patients had higher QSM values in the SNc at both 3T (padj = 0.001) and 7T (padj = 0.01), but not in SNr, total SN, or VTA, at either field strength. No significant group differences were revealed using R2* in any midbrain region at 3T, though increased R2* values in SNc at 7T MRI were marginally significant in PDs compared to HCs (padj = 0.052). ROC curve analyses showed that SNc iron measured with QSM, distinguished early PD patients from HCs at the single-subject level with good diagnostic accuracy, using 3T (mean AUC = 0.83, 95 % CI = 0.82–0.84) and 7T (mean AUC = 0.80, 95 % CI = 0.79–0.81) MRI. Mean AUCs reported here are from averages of tests in the hold-out fold of cross-validated samples. The Hanley-MacNeil method demonstrated that QSM outperforms R2* in discriminating PD patients from HCs at 3T, but not 7T. There were no significant differences between 3T and 7T in diagnostic accuracy of QSM values in SNc.This study highlights the importance of segmenting midbrain subregions, performed here using a standardized atlas, and demonstrates high accuracy of SNc iron measured with QSM at 3T MRI in identifying early PD patients. QSM measures of SNc show potential for inclusion in neuroimaging diagnostic biomarkers of early PD. An MRI diagnostic biomarker of PD would represent a significant clinical advance.

Lab-made disposable screen-printed electrochemical sensors and immunosensors modified with Pd nanoparticles for Parkinson's disease diagnostics.

Anew conductive ink based on the addition of carbon black to a poly(vinyl alcohol) matrix is developed and investigated for electrochemical sensing and biosensing applications. The produced devices were characterized using morphological and electrochemical techniques and modified with Pd nanoparticles to enhance electrical conductivity and reaction kinetics. With the aid of chemometrics, the parameters for metal deposition were investigated and the sensor was applied tothe determination of Parkinson's disease biomarkers, specifically epinephrine and α-synuclein. A linear behavior was obtained in the range 0.75 to 100μmol L-1 of the neurotransmitter, and the device displayed a limit of detection (LOD) of 0.051μmol L-1. The three-electrode system was then tested using samples of synthetic cerebrospinal fluid. Afterward, the device was modified with specific antibodies to quantify α-synuclein using electrochemical impedance spectroscopy. In phosphate buffer, a linear range was obtained for α-synuclein concentrations from 1.5 to 15μgmL-1, with a calculated LOD of 0.13μgmL-1. The proposed immunosensor was also applied to blood serum samples, and, in this case, the linear range was observed from 6.0 to 100.5μgmL-1 of α-synuclein, with a LOD = 1.3µgmL-1. Both linear curves attend the range for the real diagnosis, demonstrating its potential application to complex matrices.